Cand. Merc. FIB Department of Economics and Business

September 2nd 2013

Master’s Thesis

Author: Rune Faaborg

Supervisor: Stefan Hirth  

       

           

Valuation  of  Veloxis  Pharmaceuticals  A/S    

 A  Biotech  Project  Valuation  Framework                              

Aarhus  School  of  Business,  Aarhus  University    

 

   

Executive Summary: The  purpose  of  this  thesis  is  twofold:  1)  Develop  a  practical  valuation  framework  comprising  

real  option  analysis   (ROA),   specifically  designed   to  value  biotech  R&D  projects.  2)  Use   this  

framework  to  value  the  Danish  biotechnological  company  Veloxis.    

Veloxis  has  a  history  of  operating  within  two  therapeutic  areas;  immunosuppressive  therapy  

and  cholesterol  lowering  medication.  However,  at  this  point  in  time  they  are  devoting  their  

full  attention  towards  completing  the  development  and  preparing  for  the  possible  commer-­‐

cialisation  of  their  main  product  candidate  Tacro.  Tacro  recently  completed  the  final  phase  of  

clinical  development  and   is   therefore  only  a  market   approval   away   from  getting   launched.  

This   forms  the  basis   for  another   interesting  question:   Is  ROA  even  necessary  when  valuing  

late-­‐stage  biotech  projects?  

Initially,  the  paper  presents  the  characteristics  of  the  biotech  industry  and  empirical  findings  

regarding  average  estimates  of  industry  specific  factors.    

Subsequently,  the  financial  theory  of  real  options  is  described  and  discussed  which  ultimate-­‐

ly  leads  to  the  presentation  of  a  6-­‐step  valuation  guide  for  valuing  biotech  R&D  projects.  

In   the   following   section   the   suggested   framework   is   applied   to   estimate   the   fair   value   of  

Tacro,  and  ultimately  the  value  of  Veloxis  estimated.  

As  of  August  1st   2013,   the   estimated  worth  of  Tacro   is  DKK  1787m.  Of   this   value   the  ROA  

accounts  for  DKK  108m.  That  ROA  provides  additional  value  is  not  surprising.  The  static  DCF  

model  has  an   inward  downward  bias,  as   it   fails   to   incorporate   the  value  of   flexibility   in  an  

uncertain  environment,  which  is  clearly  the  case  in  the  biotech  industry.  As  expected,  the  real  

option  values  do  not  contribute  with  an  extensive  amount,  nevertheless,  enough  to  justify  its  

application.  

The  estimated  value  of  Veloxis  translates  to  a  stock  price  of  DKK  1.15,  which  is  approx.  twice  

the  current  market  value  of  DKK  0.58.  The  estimated  value   is  also  significantly  higher  than  

Danske  Market’s   current   target   price   of   DKK   0.80.   The   rough   competitive   situation   in   the  

American  Market,  along  with  the  inexperience  of  Veloxis  when  it  comes  to  the  commerciali-­‐

sation  process,  is  considered  the  main  concerns  in  the  market.  

 

 

 

 

   

Table of Contents

1. Introduction  .....................................................................................................................  1  1.1 Motivation  ..............................................................................................................................  1  1.2 Problem statement  ................................................................................................................  2  1.3 Delimitations  ..........................................................................................................................  2  1.4 Structure  .................................................................................................................................  4  

2. Method  ..............................................................................................................................  4  2.1 Validity and Framework Development  ............................................................................  5  2.2 Strategic Theories  .................................................................................................................  5  

2.2.1 External Analysis  ..........................................................................................................................  5  2.2.2 Internal Analysis  ............................................................................................................................  5  

2.3 Financial Theories  ................................................................................................................  5  2.3.1 The Separation Principle  .............................................................................................................  6  2.3.2 Valuation Model  ............................................................................................................................  6  2.4.3 Discount Rate  .................................................................................................................................  7  2.3.4 WACC Components (Re and Rd)  ............................................................................................  7  

3. Characteristics of the Biotech Industry  ....................................................................  9  3.1 Definition of a Biotechnology Firm  ...................................................................................  9  3.2 The Regulation of Drugs  ..................................................................................................  10  

3.2.1 Drug Development Stages  .......................................................................................................  11  3.2.2 Pre-discovery:  ..............................................................................................................................  11  3.2.3 Target Identification and Validation:  ..................................................................................  11  3.2.4 Drug Discovery:  .........................................................................................................................  11  3.2.5 Early Safety Tests:  .....................................................................................................................  11  3.2.6 Lead Optimisation:  ....................................................................................................................  12  3.2.7 Preclinical Testing:  ....................................................................................................................  12  3.2.8 The development process:  .......................................................................................................  12  3.2.9 Phase I Clinical Trial:  ...............................................................................................................  12  3.2.10 Phase II Clinical Trial:  ...........................................................................................................  12  3.2.11 Phase III Clinical Trial:  .........................................................................................................  13  3.2.12 New Drug Application (NDA) filling and review:  .......................................................  13  3.2.13 Manufacturing:  .........................................................................................................................  13  3.2.14 On-going Studies and Phase IV Trials:  ............................................................................  13  

3.3 Risks  ......................................................................................................................................  14  3.3.1 Market Uncertainty  ....................................................................................................................  14  3.3.2 Technological Uncertainty  ......................................................................................................  14  

3.4 Empirical Studies  ...............................................................................................................  15  3.4.1 Probability of Success in the Clinical Trials  .....................................................................  15  3.4.2 Duration of the Clinical Trials  ...............................................................................................  15  3.4.3 Development Costs and Launch Associated Costs  .........................................................  16  3.4.4 Product Life Cycle (PLC)  ........................................................................................................  17  3.4.5 Patents  ............................................................................................................................................  17  

4. Real Options Theory  ...................................................................................................  18  4.1 Financial Options vs. Real Options  ................................................................................  19  4.2 Different Types of Real Options  .....................................................................................  20  

4.2.1 Simple Option: Option to defer  .............................................................................................  20  4.2.2 Simple Option: Abandonment option  ..................................................................................  21  

 

   

4.2.3 Simple Options: Option to expand or contract  .................................................................  21  4.2.4 Simple Option: Option to choose  ..........................................................................................  21  4.2.5 Simple Option: Switching option  .........................................................................................  21  4.2.6 Compound Option or Follow-on option  .............................................................................  21  4.2.7 Compound Option: Learning option  ....................................................................................  22  4.2.8 Compound Option: Rainbow option  ....................................................................................  22  

4.3 Real Options Valuation Methods  ...................................................................................  22  4.3.1 DTA  ................................................................................................................................................  22  4.3.2 Real Options Analysis (ROA)  ...............................................................................................  22  

4.4 Volatility Estimation  .........................................................................................................  26  4.4.2 Monte Carlo Simulation  ...........................................................................................................  26  4.4.3 Project Proxy Approach  ...........................................................................................................  28  4.4.4 Market Proxy Approach  ...........................................................................................................  28  4.4.5 Management Assumption Method  .......................................................................................  29  

5. Recommended Framework  .......................................................................................  29  5.2 Interaction between Market Risks and Private Risks  ...............................................  29  5.3 Preferred Method  ..............................................................................................................  30  5.4 Framework  ..........................................................................................................................  30  

5.4.1 Step 1: Strategic Analysis  ........................................................................................................  30  5.4.2 Step 2: Estimation of Input Variables for DCF  ................................................................  30  5.4.3 Step 3: Discount Rate  ...............................................................................................................  31  5.4.4 Step 4: Static DCF Model  .......................................................................................................  31  5.4.5 Step 5: Volatility Estimation  ..................................................................................................  32  5.4.6 Step 6: Real Option Valuation (ROV)  ................................................................................  32  

6. Valuation of Veloxis  ....................................................................................................  32  6.1 Step 1: Strategic Analysis of Veloxis  ..............................................................................  32  

6.1.1 Company Profile  .........................................................................................................................  33  6.1.2 Business Strategy  .......................................................................................................................  33  6.1.3 MeltDose technology  ................................................................................................................  34  6.1.4 Fenoglide  .......................................................................................................................................  34  6.1.5 External Analysis  .......................................................................................................................  35  6.1.6 Internal Analysis  .........................................................................................................................  47  6.1.7 SWOT  ............................................................................................................................................  50  

6.2 Step 2: Estimation of Input Variables for DCF (Tacro)  ...........................................  50  6.2.1 Market risks  ..................................................................................................................................  51  6.2.2 Technological risks  ....................................................................................................................  56  

6.3 Step 3: Veloxis’ Cost of Capital  ......................................................................................  57  6.4 Step 4: The Tacro DCF Models  ......................................................................................  59  6.5 Step 5: Volatility of Tacro  ................................................................................................  59  6.6 Step 6: Tacro ROA  ............................................................................................................  60  6.7 Valuation of Veloxis  ..........................................................................................................  61  6.7.1 Sensitivity Analysis  .........................................................................................................  62  

7. Discussion of Results  ...................................................................................................  63  8. Conclusion  ....................................................................................................................  65  References  ..........................................................................................................................  67  

 

       

1  

1. Introduction

The biotech industry is characterised by high R&D costs and long time horizons for product

development, which combined put significant pressure on the liquidity and long term financing.

To achieve the necessary financing, they are dependent on efficient markets where investors are

able to estimate the fair value of the stock prices. The above-mentioned characteristics of the

biotech industry lead to periods with negative cash flows and high uncertainty regarding future

cash flows. Hence, making these shares difficult to value with the traditional valuation methods, as

these do not account for the value of flexibility, and the possibilities spawned hereby.

Even so, many biotechnology firms, without any revenue, have significant market valuations. In

order to incorporate the value of flexibility in the valuation, real option theory might provide the

best alternative.

Real option valuation has been praised as superior to the traditional Discounted Cash Flow

Method (DCF), as it incorporates the value of managerial flexibility into future strategic opportu-

nities. Nevertheless, empirical studies show that practitioners seldom use real options, and many

who try to implement the ideas are leaving them shortly after. A 2007 study by Block investigated

the reasons behind the poor support through a survey. The top 3 reasons for not using real options

were #1 lack of support from top management, #2 DCF is considered a proven method, #3 ROA

requires too much sophistication. (Block 2007, p255).

Therefore one of the objectives of this paper is to develop a framework, that can capture the value

of flexibility in R&D project valuation for biotech firms, while simultaneously not being overly

sophisticated and thereby scaring off practitioners.

1.1 Motivation The main motivation behind choosing to create a framework for project valuation in the biotech

industry stems from a fundamental interest within the financial and strategic considerations

required when performing a comprehensive valuation. Past experiences with the most commonly

applied methods for valuation have taught the author that these hold some indisputable weakness-

es. Therefore it would be interesting to explore some alternative valuation approaches. Real

Options Analysis (ROA) is currently considered one of the most interesting alternatives, as it

holds the promise of fixing one of the main obstacles of the standard static models – the value of

flexibility. Further, the fact that practitioners deselect ROA as it is considered to burdensome

thrives as a motivation to create a relatively easy-to-apply framework. The biotech industry serves

 

       

2  

as a perfect match for ROA, as this industry holds several characteristics that enhance the value of

flexibility.

The Danish biotech company called Veloxis is considered a very interesting valuation target, as it

currently is on the verge of making or braking. The next 1-2 years will determine whether they

succeed or go out of business.

This rather short time horizon would indicate that the value contribution of ROA will be of a small

size, as the flexibility is shrinking for each completed phase in the development process. Thus, it

is interesting to see whether ROA is able to contribute with additional value in the late project

states of a biotech firm, or the standard valuation methods are sufficient.

1.2 Problem statement The purpose of this thesis is twofold, and the following issues will form the basis of the paper:

Is it, based on available theories and current empirical findings, possible to present a fairly straightforward, practicable and theoretically valid step-by-step valuation guide for biotech

drug development projects? And if so:

What is then the considered a fair value of the Danish company Veloxis Pharmaceuticals A/S

based on this framework?

In order to answer these questions, this thesis will seek to answer the following sub question:

• Which characteristics and regulations are applicable in the biotechnological indus-

try?

• What is the rationale behind real options theory, and is it relevant in late stage bio-tech projects?

• Which valuation methods can be used in order to achieve a theoretical valid valuation

of a biotech firm?

• How is the estimated value of Veloxis in comparison to the market value?

1.3 Delimitations

Real Options Theory The Black-Scholes real option valuation model will not be included in this paper, as the underly-

ing assumptions of the model are considered to make it inappropriate for the biotech industry. E.g.

the model assumes only one source of uncertainty, while the real options held by a project

 

       

3  

developing biotech firm are compounded options (explained in section 4.2.6), and thereby affected

by more than one source of uncertainty (Copeland et al. 2003, p106).

Further, partial differential equations are excluded, as they are considered too complex and

thereby also hard to communicate and not least inappropriate for practical application.

Biotech Market

This paper uses the American Food and Drug Administration (FDA) regulations of the biotech

industry. The reason for this is the fact, that Veloxis are planning to launch their main product

candidate in the U.S. while the rest of the world will be targeted through partner deals. Hence

U.S. is the market of highest interest for Veloxis. At the same time the regulations provided by

FDA are similar to those used in Europe by the European Medicines Agency (EMA), why it

seems plausible to select only one standard.

Financial Statement Analysis

A traditional financial statement analysis is considered irrelevant in relation to the valuation of a

biotech company like Veloxis. They have very unstable earnings, if any, making it difficult to use

historical data in sales forecast (Plenborg et al. 2005, p267).

Time Frame

The valuation of Veloxis is based on the information available prior to August 1st 2013. Subse-

quent events are thereby not considered in the valuation.

Taxes

The Danish corporate tax rate is used, as Veloxis is a Danish firm with headquarters located in

Denmark. The Danish corporate tax rate is currently in the process of being lowered. Appendix 1

provides an overview of this process.

Exchange Rates

Future fluctuations in exchange rates are not included in this paper. The observable exchange rates

at the valuation date are used as a proxy for future rates. In acknowledgement of the impact of

changing exchange rates, the valuation section will contain a sensitivity analysis of the impact of

fluctuations in exchange rates.

 

       

4  

1.4 Structure

The structure of the paper is presented in the illustration beneath.

2. Method

This chapter initially presents how the thesis will treat information in order to ensure validity,

followed by an overview and presentation of the strategic and financial theories implemented in

the thesis.

!"#$%&'(%&$)

!"*+$,-./"0%(%./.)%

!"1.-&/&%(%&$)2

!"3(-&4&%5"()4"6+(/.7$+8"1.'.-$9/.)%

!"0%+(%.:&;"<=.$+5

!"6&)();&(-"<=.$+5

!"1.>&)&%&$)"$>"("?&$%.;=)$-$:5"6&+/

!"<=."@.:A-(%&$)"$>"1+A:2

!"@&282

!"B/9&+&;(-"0%A4&.2

!"6&)();&(-"C9%&$)2"'2D"@.(-"C9%&$)2

!"1&>>.+.)%"<59.2"$>"@.(-"C9%&$)2

!"@.(-"C9%&$)2"3(-A(%&$)"#.%=$42

!"3$-(%&-&%5"B2%&/(%&$)

!"0%+(%.:&;"E)(-52&2

!"F);.+%(&)%&.2

!"3.-$G&2H"I$2%"$>"I(9&%(-

!"1I6

!"@CE

!"3(-A(%&$)

!"#$%&'()*

+"#,)*-.**)'/#'0#1%*.&2*

3"#4'/-&.*)'/

5"#6/27'8.-2)'/

9"#:%2;'8

<"#1%=&#>?2)'/*#@;%'7A

B"#4;=7=-2%7)*2)-*#'0#2;%#C)'2%-;#6/8.*27A

D"#E7=F%G'7H

 

       

5  

2.1 Validity and Framework Development

The in this paper suggested framework will be based solely on secondary data, consisting of

findings from empirical studies, existing theories, and recognised expert’s opinions. Thus, the

framework will be an utilisation of several existing theories and findings.

In the following corporate valuation case the emphasis will be on objectivity and ensuring validity

of data. Most of the information used comes from Veloxis’ annual reports and public presenta-

tions, websites, public available reports and papers, along with stock analyst’s estimates and

opinions. Some of these are obviously stakeholders, and could therefore hold an interest in

suppressing negative information or enhance and overestimate the value of positive information.

To address this problem, statements and evaluations from independent sources will be incorpo-

rated when possible, and information from stakeholders will be crosschecked if possible, and

otherwise interpreted with caution. The author does not have access to internal information from

Veloxis, and there is therefore no guarantee for complete validity.

2.2 Strategic Theories

The strategic analysis of Veloxis is build upon Richard Lynch’s approach to strategic analysis,

which constitutes environmental analysis from both a macro and micro perspective along with an

internal analysis (Schack, B., 2009).

2.2.1 External Analysis

The framework is build as an outside-in analysis, and initiates therefore from a macro perspective,

as illustrated in appendix 2. This PEST framework is chosen for this task, as it identifies relevant

external issues in the macro environment. For the micro perspective Porter’s Five Forces

framework is applied. The purpose of this analysis is to investigate the general attractiveness of

the industry and identify possible key industry characteristics, but mainly to identify factor factors

that will influence the future sale of the product.

2.2.2 Internal Analysis

For the internal analysis Porter’s Value Chain framework is applied. This analyse the internal

primary and secondary activities within the company in order to identify where the value creation

takes place and where there might be room for improvement. The value chain framework used in

this paper is adjusted so as to more appropriately fit biotech firms.

2.3 Financial Theories

 

       

6  

This section presents the fundamental financial theories and principles needed for understanding

and applying the real option valuation framework presented in chapter 5.

2.3.1 The Separation Principle The separation principle is a key assumption and a basic investment decision rule, as it allows the

decision maker to disregard complicated individual utility functions (Copeland et al. 2003, p63).

Instead it can be assumed, that each investor’s wealth is maximised when firms’ keep on investing

until the expected rate of return on the marginal investments is equal to the company’s cost of

capital. Hence, it is called the separation principle as the wealth maximizing investment decision

rule does not take individual utility functions into account, and is thereby separated from these.

2.3.2 Valuation Model There are generally several categories of valuation models, but the enterprise discounted cash flow

model (DCF) remains the favourite among practitioners and academics (Koller et al. 2010, p103).

The DCF model discounts the forecasted FCF to present value terms using a risk-adjusted

discount rate, i.e. the weighted cost of capital (WACC), which is presented in the next section. The

estimated future cash flows are divided into an explicit forecasted period and a continuing value.

This is done because the long term projections becomes more and more unreliable, and therefore it

is considered meaningless to continue to forecast on a year-to-year basis. The explicit forecast

period is typically a period with either a high or low growth rate, whereas the growth rate is

expected to stabilise with time, why a perpetuity formula can calculate the continuing value

(Koller et al. 2010, p112). It is important to ensure, that the continuing value is calculated based

on normalised cash flows, as it commonly constitutes a substantial part of the total value. This

needs to be taken into consideration when choosing the length of the explicit forecasting period.

The present value of the FCF’s in the explicit budgeted period can be calculated through the net

present value (NPV) formula presented below. The NPV is the foundation on which DCF is build.

The continuing value is calculated as a growing perpetuity based on the stabilised FCF at the end

of the explicit forecasted period. This FCF is expected to grow at a constant growth rate, and the

total value is discounted back with WACC.

!"#$%&'()* +,-(.#,/,0-(1'&%,

!"# !$%&"'$($)%&#*+,$-. -*(/&.+01' 23(40,)%&5*%$

!"#$%&'()&$*(+(,&-.$/"(01223(456

!"# ! !"!!! ! ! !!

!

!!!!"!!"#$#!!

 

       

7  

2.4.3 Discount Rate To correctly value the forecasted FCF’s from the DCF model they have to be discounted by the

WACC. The most important principle in order to successfully implement the cost of capital is to

ensure consistency between the components of the WACC and the FCF’s. Thus, the WACC has to

include the required return for each investor type, as the FCF is the cash flow available to all

investors (Koller et al. 2010, p235).

The WACC formula in its simplest form is presented in formula 3 below. If there are other

investors than shareholders and lenders these should be included in the weighted average as well.

WACC includes the value of the tax shield, which is thereby incorporated when discounting the

FCF’s.

2.3.4 WACC Components (Re and Rd) Since none of the WACC components are directly observable, these have to be estimated through

different models.

The cost of debt (Rd) is the rate required by the investors in the company’s debt, and therefore

indicates the rate at which the company can borrow money. Biotech firms are regularly operating

with none or negligible interest bearing debt, because of the very uncertain environment. Thus,

biotech firms are usually financed through stocks and venture capital. As a result, the cost of debt

estimation is considered redundant. Methods for calculating the cost of debt can be found in KGW

on p261 (KGW: Koller, Goedhart, and Wessels, 2010).

!"#$%&'()* +",-.,%'-.",(/'&%0

!"! !#$$%"&'(%!)*+, -#*+.(%/&.$# 01'2*34.%/&.$

!"#$%&'()&$*(+(,&-.$/"(01223(4256

!"#$%#&'$%"#!!"#$% ! !"!! ! !!! !!!! ! !! !

!"#$%&'()* +,-./0,1(23,#'.,(4"50("6(4'7-0'&

! "#$%&'()#*+&(,-(!.+/'01 "#$%&'()#*+&(,-(1&2'$! 3,4'(,-(!.+/'0$1 3,4'(,-(1&2''#5 "#$6/7#*(3,$8,$#'&(9#5(:#'&

!"#$%&'()&$*(+(,&-.$/"(01223(4567

!"## ! !! ! ! ! !! !

!! ! ! ! !!!!! !"#!!

 

       

8  

The cost of equity (Re) is the required return of the company’s equity holders. As this is non-

observable, a model capable of transforming risk into return is needed. Several models exist

including the Fama-French three-factor model, the arbitrage pricing theory model (APT) and the

more commonly used capital asset pricing model (CAPM) (Koller et al. 2010, p238). The formula

for CAPM is presented below.

The risk-free rate (rf) is estimated through default-free government bonds. When valuating

European companies, Koller suggests using 10-year German Eurobond, as these have higher

liquidity and lower credit risk than bonds from other European countries (Koller et al. 2010,

p241). Ideally, each cash flow should be discounted with the interest from the zero-coupon bond

with matching maturity. But in reality few practitioners discount each cash flow using matched

maturities (Koller et al. 2010, p241). Taking the uncertainty regarding the size and not least timing

of forecasted biotech cash flows into account, discounting each cash flow with matching maturity

does not seem worth the trouble.

The market risk premium (MRP) is considered one of the most debated issues in finance (Koller et

al. 2010, p242). It is defined as the difference between the market’s expected return and the risk-

free rate, hence, it is the additional required return investors demand to invest their money in

stocks rather than bonds. During the current stressed market conditions investors have become

increasingly risk averse resulting in significant capital inflow to countries like Denmark and

Germany, as these are considered ‘safe havens’ by many investors. Up till this point no single

model for estimating the MRP has gained universal acceptance (Koller et al. 2010, p242). Koller

presents three methods for estimating the MRP:

• Through the use of historical returns

• Using regression analysis to link current market variables to project the expected market

risk premium

• Using DCF valuation, along with estimates of return on investment and growth, to reverse

engineer the market’s cost of capital

!"#$%&'()* +',-.'&(/001.(2#-3-45(6"71&(8+/269

!" #$%&'$('")*+&,!( -+%.'/!00'-1&020&1 20&1'$3'&40'5&$6.-7.& "89'-0&*!3'$3'71!.0&':/

!"#$%&'()&$*(+(,&-.$/"(01223(4502

!! ! !! ! ! ! !! !!"! ! !! !

 

       

9  

Only the beta varies across companies, as both the risk-free rate and the market risk premium are

mutual for all companies. According to CAPM, a stock’s expected return is driven by its beta.

Beta measures to what extent the individual stock and the entire market move together. The most

common regression used to estimate the raw beta is the market model (Koller et al. 2010, p249).

The next chapter discusses some of the various characteristics of the biotech drug developing

industry, and ultimately present some relevant empirical findings regarding average estimates for

the industry.

3. Characteristics of the Biotech Industry

3.1 Definition of a Biotechnology Firm The biotech industry includes firms that perform R&D activities within several different indus-

tries, e.g. food and nutrition, environmental or medicine. The framework created in this thesis is

targeting biotech firms that use their time and resources on drug development. Hence, a definition

that separates this group of biotech firms from the rest is necessary.

The OECD suggest the following definition of a biotech firm:

“A biotechnology firm can be defined as a firm that is engaged in biotechnology by using at

least on biotechnology technique to produce goods or services and/or to perform biotechnology

R&D” (OECD Biotechnology Statistics 2009, p10).

As this definition is rather broad and includes firms that just use biotechnology to some extent,

OECD suggest a more narrow definition for what they call Dedicated Biotechnology Firms:

Defined as “A biotechnology firm whose predominant activity involves the application of

biotechnology techniques to produce goods or services and/or to perform biotechnology R&D”

(OECD Biotechnology Statistics 2009, p10).

The definition is still considered too broad for the purpose of this paper, as the area of interest is

firms involved in pharmaceutical R&D. Valentin, Dahlgren & Jensen suggest a more specific

definition of a biotech firm that is better suited for the purpose of this thesis:

“A biotechnology firm is defined as a firm whose predominant activities involves R&D within

pharmaceutical drugs” (Valentin et al. 2006, p7).

!"#$%&'()* +'#,-.(+"/-&

!" #$%&'()*+,"&!%(-./!0+( #$%&01.+%(,"&!%(-./

!"#$%&'()"**&$(&+(,*-(./0/1(2.34

!! ! ! ! !!!"# ! !!

 

       

10  

Another relevant distinction is the difference between a biotechnology firm and a pharmaceutical

company. A biotech firm is typically a small research and development unit, with the primary

objective of developing a range of product candidates. When a product is taken successfully

through all the clinical trials and is ready for market launch, the biotech firm typically needs the

larger and financially stronger pharmaceutical companies to market the product. Hence, they

might cooperate through strategic alliances or the pharmaceutical company can buy the rights to

market the product with milestone payments and/or royalties. They might also cooperate in the

development process, where the pharmaceutical firm typically help finance the process. The

pharmaceutical company can thus be defined as a larger and financially stronger player which is

active in within all the parts of the value chain making them a perfect partner for the biotech firm

and vice versa.

3.2 The Regulation of Drugs This paper, as mentioned, follows the American regulations by the FDA. Explanations are that the

US pharmaceutical market accounts for approx. 50% of the global market (Prweb.com, 28th May

2013), it is by far the most important market for Veloxis, and finally the regulation of EMA is

very similar.

Biotechnology drugs are reviewed by either FDA’s Center for Drug Evaluation (CDER) or under

the Center for Biologics Evaluation and Research (CBER) (FDA Basics, p5).

These centers operate with three categories of drugs: New Drugs, Generic Drugs, and Over-The-

Counter Drugs (OTC). As the name indicates, OTC drugs are available directly to the consumers

without prescription. These drugs can be marketed without FDA approval as long as they comply

FDA’s procedure regarding permitted ingredients, formulations, doses etc. If the drug does not fit

into these standards it has to be taken through the new drug approval (NDA) system (FDA Basics

p5). The NDA system is the most demanding of the three and the one that is relevant to most

biotech firms. Product approval applications require, among other things: product description; pre-

clinical data; clinical data demonstrating safety and effectiveness; description of product manufac-

ture, processing and packaging; stability data; proposed labelling; and patent exclusivity infor-

mation (FDA Basics p5). As should be clear from the listed requirements, new drug development

is a long and demanding process with very high statutory demands. As the development of new

drugs is the process of attention regarding the framework, a detailed description of the stages in

new drug development will be presented in the next section.

The final category of drugs, Generic Drugs, is typically cheaper exact versions of already

marketed drugs with expired patent protection. When taking generic drugs to market, FDA does

 

       

11  

not demand clinical test results, but require clear evidence that the generic version is an exact copy

of the original drug.

3.2.1 Drug Development Stages It can take up to 15 years to develop one new drug from the early discovery phase to the time it

becomes available for patients (Drug Discovery and Development 2007(DDD), p2). During this

time the compound is developed and taken through a variety of clinical phases and tests. The steps

included in the drug development process are:

3.2.2 Pre-discovery: Before any new medication can be discovered, the scientists have to get an in-depth understanding

of the disease, and understand the underlying cause of the condition. This research process takes

many years of work, and often leads to a frustrating dead end (DDD 2007, p2)

3.2.3 Target Identification and Validation: Once the researchers have acquired enough knowledge about the decease and the underlying

cause, they select a “target” for a potential medicine. A target is normally a single molecule. Next

step is to show that the chosen target is actually involved in the disease and can be affected by a

drug. In this stage the researchers are performing complicated experiments in both living cells and

in animal models of disease. (DDD 2007, p3)

3.2.4 Drug Discovery:

Now the scientists are ready to start looking for a drug. They search for a “lead compound” or a

molecule, which might act on their target to alter the disease course.

3.2.5 Early Safety Tests: The “lead compound” then has to go through a series of tests in order to provide an early

assessment of the safety of the compound. Normally this assessment includes absorption,

distribution, metabolism, excretion and toxicology (ADME/Tox). In order for a drug to be a

potential success it has to be: Absorbed into the bloodstream, Distributed to the proper site of

action in the body, Metabolised efficiently and effectively, successfully Excreted from the body,

and demonstrated not to be Toxic (DDD 2007, p4).

These tests help researchers to prioritise and compare lead compounds early in the discovery

process.

 

       

12  

3.2.6 Lead Optimisation:

The compounds that make it through the early safety tests are then optimised or altered to make

them safer and more effective. Normally hundreds of different variation are made and tested,

ultimately resulting in one preferred compound - the candidate drug compound (DDD 2007, p4).

3.2.7 Preclinical Testing:

In the preclinical stage, the researchers test the optimised compound extensively in lab experi-

ments (in vitro) and in living cell cultures and animal models (in vivo). This is done to figure out

how the drug is working and not least what its safety profile looks like. This is the last step before

human testing and the FDA requires extremely thorough testing before the drug candidate can be

studied in humans.

3.2.8 The development process: Before the clinical trial development can begin, the developing company must file an Investiga-

tional New Drug (IND) application with the FDA. This application must include the results from

the preclinical work, a description of the chemical structure, how it is thought to work in the

human body, a list of potential side effects, and manufacturing information. The high requirements

from the FDA are to make sure, that the people participating in the clinical trials are not exposed

to unreasonable amounts of risks.

3.2.9 Phase I Clinical Trial: Here the drug candidate is tested in people for the first time. The tested people are a small group

of healthy volunteers - usually in the lower range of 20-100 persons. The main purpose of these

tests is to prove that the drug is safe in humans. Other than that the researchers investigate how the

drug is absorbed and ultimately eliminated from the body. They look for side effects and obvious-

ly whether the drug has the desired effect.

3.2.10 Phase II Clinical Trial: The next step is testing the drug on the targeted patients. In phase II the drug is tested and

evaluated on between 100 and 500 patients with the disease in question. Possible short-term side

effects are examined and the researchers investigate whether the drug improves the condition of

the patients, and what dosage shows the most promising improvements. If the phase II studies are

successful, the preparations for the much larger phase III trials can begin.

 

       

13  

3.2.11 Phase III Clinical Trial:

Phase III is the final step before the researching firm can apply the NDA to the FDA. This phase is

larger in all aspects. The patient population tested is normally between 1000-5000 patients in

multiple locations around the world, it is the longest trial regarding the timeframe, and thereby of

course also the most expensive of the three phases. This phase of research is the key in determin-

ing whether the drug proves to be both safe and effective.

During the trial the firm will be planning the necessary requirements for a possible market launch

and preparing for the complex application required for the FDA approval process (DDD 2007,

p7).

3.2.12 New Drug Application (NDA) filling and review:

After completion of the three phases, the firm will analyse all data. If the data shows, that the drug

is both effective and safe, they will file a NDA. This application is a complicated and extensive

matter and can comprise more than 100.000 pages (DDD 2007, p8).

FDA experts on the subject will then review all the information included, and determine whether

the benefits of the drug outweigh the risks. They will also assess what information the package

insert should contain in order to help guide the physicians in the use of the drug, and finally they

will examine whether the methods suggested for manufacture ensure a high quality product.

3.2.13 Manufacturing: Going from the small-scale needed in the clinical trials to large-scale manufacturing is a major

task. New manufacturing facility is needed in many cases or a restructuring of an old one, as the

manufacturing process is very different from drug to drug, and the facility has to satisfy strict

FDA guidelines for Good Manufacturing Practices (GMP).

Making high-quality drug compounds on a large scale takes a great deal of care. There are few, if

any, other industries that require the level of skill in manufacturing as necessary in drug produc-

tion (DDD 2007, p9)

3.2.14 On-going Studies and Phase IV Trials: The research period is not ended with the phase III clinical trials, but continues even after approval

of the drug. A much larger number of patients begin to use the drug, and the company must

therefore continue to monitor the drug and is obliged to submit periodic reports of adverse events

to the FDA. FDA can also require, that the firm conduct additional studies after approval, so called

phase IV studies, e.g. to evaluate long-term safety or how the drug affects specific groups of

patients (DDD p9).

 

       

14  

The phases from phase I clinical trials to NDA and review are the relevant ones regarding the

valuation of the projects. Prior to phase I it is impossible to value the compound, as the level of

information is deficient. And further it is only approximately 1 out of 50 preclinical tested drug

compounds that reach the clinical trials. This clearly indicates, that drug development is associated

with a significant amount of risk. The following section will elaborate on these risks.

3.3 Risks As indicated in the above review of the drug development process, creating new drugs are

associated with significant risks. When valuing R&D projects the understanding of the uncertain-

ties affecting the projects is of crucial importance. In the literature on the subject, the researchers1

agree that the biotechnology industry is affected by two sources of uncertainty. But they are not in

agreement on how the two uncertainties should be treated when valuing R&D projects. The two

sources are market uncertainty and technological uncertainty.

3.3.1 Market Uncertainty The market uncertainty comprises all the market-related uncertainties regarding the targeted

market of the drug, e.g. uncertainty of price per unit, the costs associated with production and

launch, quantity of sales when the drug has been granted NDA approval, and the competitive

situation in the market (Copeland et al. 2003, p325). The market uncertainties are systematic2, and

cannot be eliminated through diversification.

3.3.2 Technological Uncertainty The technological uncertainty is the uncertainties associated with, in this case, the development of

a drug. This uncertainty resolves with the information from every clinical trial leading to either

clinical success or failure. If successful, the technological risk decreases. If a product candidate

passes the final FDA approval the technological risk is resolved. Hence it is only present in the

development process. This type of risk is also called idiosyncratic risk, specific risk, unsystematic

risk, and diversifiable risk. This type of risk can in theory, as the latter name indicates, be

eliminated through diversification (Shockley 2007, p47-51)

                                                                                                               1 Copeland p276, Shockley p342, Kodukula p174 2  Systematic risk is also called market risk, aggregate risk, and undiversifiable risk.  

 

       

15  

How to handle these uncertainties, and whether they interact or not, are treated in the development

of the valuation framework in section 5.2. The following section presents empirical studies on the

technological uncertainties

3.4 Empirical Studies This section will present a series of empirical findings concerning the technological uncertainties

affecting the biotech drug development process. These findings will include estimates of the

duration of the clinical trials, statistics on the probability of success in each phase, the average

development cost for each phase and a study on the product life cycle of new drugs.

3.4.1 Probability of Success in the Clinical Trials

The likelihood of clinical success is an important estimate when valuing biotech R&D projects, as

it is an important input in the calculation, holding the potential to significantly affect the value of

the project.

DiMasi & Gabowski in 2007 conducted a study, where they reached the following estimates for

the probability of success in each of the clinical phases.

Their study did not include an estimate of the probability of FDA approval after submitting the

final NDA following successful phase III results. The average FDA approval rate from fiscal

years 2002-2009 has been 71% (US GAO, 2010 p14). 71% therefore seems as a reasonable proxy

for the probability of FDA approval when filling a NDA.

3.4.2 Duration of the Clinical Trials

Also in the study from 2007 by DiMasi & Grabowski, the researchers examined the time duration

of the different clinical trials. Below, in figure 2, their estimates for the average duration of the

clinical trials are presented in months.

!"#$%&'( )%*+,+"-"./'0*%'1-"2"1,-'3$11&33

)4,3&'5 )4,3&'55 )4,3&'555 677%*8,- !

9"*.&14 :;<=> ?@<;> @A<B> =(<C>

D$E$-,.&F'7%*+,+"-"./' B(<?>

!"#$%&'()*+,-*(.(/$,0"1-2*3(4556(7869:(;!(/,"3(45<5(7<8

 

       

16  

As can be seen in the figure, the overall development duration from the beginning of the clinical

phase I trial to the FDA approval is estimated to almost 98 months, or 8 years and 2 months. This

is in line with the findings in the report “Drug Discovery and Development (DDD)” from 2007,

where the overall development process from clinical phase I to FDA review is estimated to last

between 6,5 and 9 years (DDD 2007, p2).

DiMasi & Grabowski estimate the FDA review process to take an average of 16 months. The

DDD report states that the FDA review process can vary between 6 months and 2 years. These

findings are significantly higher/longer than the FDA’s objective of completing 90% of the NDA’s

within 10 months.

3.4.3 Development Costs and Launch Associated Costs In table 1 below, DiMasi & Grabowski’s findings regarding the average development costs for

each phase is presented.

These costs are average estimates, and should therefore be adjusted for firm specific technological

uncertainty if applied in a valuation.

The papers by DiMasi & Grabowski are still considered the most detailed on the subject.

However, they have been subject to considerable criticism, most recently in a paper by Light &

Warburton, for overestimating the cost of drug development (sciencebasedmedicine.org). Hence, a

!"#$%&'() *$%+,"-.'-/'01"."2+1'3%"+14

!"#$%&' !"#$%&'' !"#$%&''' ()*&+%,-%. /01#23041"$ 5678 967: :976 5; 6<7<!"#$%&'()*+,-*(.(/$,0"1-2*(34456(7859

!" #!" $!" %!" &!" '!!" '#!"

()*+,"

-./"012314"

56+71"888"

56+71"88"

56+71"8"

()*+," -./"012314" 56+71"888" 56+71"88" 56+71"8"9):*67" ;<=<" '%" >#=;" #;=>" ';=?"

!"#$%&'( )%*%$+,-%./&0+1/1&234+/%056

!""#$%&'()*$+,-./0&)1(2'3'(42$5&'42* #6788$90:4*)$; <!7!8$90:4*)$;; <=7>6$90:4*)$;;; 6>7"6$9

!"#$%&'()*+,-*(.(/$,0"1-2*(34456(7853

 

       

17  

practitioner should be careful when using the estimates in a valuation, and it is advised to adjust

them subjectively based on firm and project specific knowledge gained in the strategic analysis.

After completing all clinical phases, the next cost endured is the cost associated with the NDA

filing (provided the compound is to be launched in the US). The fee that is to be paid to the FDA

is USD 1.841.500 (Wapner 2012). However, the filing process is a complicated process, as

described above, and requires substantial preparation. Shockley estimates the total cost of the

NDA process to amount to USD 15 m (2007 prices) (Shockley 2007, p349).

Launching a drug compound includes the creation of samples, advertising to physicians, a build-

up of inventory, and a marketing campaign targeted at both prescribing physicians as well as the

general public (Shockley 2007, p328). Shockely provide an estimate of USD 50 m for launching a

drug compound in the US.

3.4.4 Product Life Cycle (PLC) The below presented figure illustrates how the sale of a newly launched drug develops over the

course of its life cycle. The sales volume on the y-axis is in itself not interesting, but the develop-

ment of the sales curve considered in relation to the point of patent expiration in year 12 is

interesting. This information is useful when forecasting the possible future sales of a drug

candidate.

As can be seen on the graph, the sales volume is significantly higher before the point of patents

expiration. Hence, it is interesting to explore how the patent regulations are constructed.

3.4.5 Patents

A patent is an exclusive right (similar to a monopoly) granted by a state to the patentee for a fixed

period of time (Norman, 2007 p35). The biotech R&D projects are, as illustrated above, very

expensive and time consuming. Hence, the industry is very dependent on the patent protection

regulations. Without this system it is safe to say, that the industry would not exist. As illustrated in

!"#$%&'() *%+,$-.'/"0&'12-3&'4'5%$#

!"#$%&'()$*+",-./0(1&$2"2(3(4/5*-/0(6776(89:

 

       

18  

figure 3 above, the average sales during and after patent protection are significantly different. The

explanation is obvious. During patent protection the company holds exclusive rights to market and

sell the product, but as the patent expires competitors have the opportunity to launch generic

versions of the medication. And as they have not invested in the expensive development of the

drug, they are able to offer the product at a significantly cheaper price. This leads to the sharp

decline in sales following patent expirations.

In the table beneath, the patent regulations in the three largest pharmaceutical markets are shown.

This chapter provided the reader with the necessary basic knowledge of the industry specific

characteristics of the biotech industry. The next chapter will turn the focus to the financial theory

of real options.

4. Real Options Theory

According to Shockley the market value of a corporate project can be decomposed into two

pieces: The incremental value of the CF’s from the investment, and the value of the flexibility that

results from the investment.

The standard DCF method is a deterministic model, and cannot handle future decisions. Hence, it

assumes that any future flexibility and decisions are given up at the time of investment (Shockley

2007, p17). This means, that when applying the static NPV rule the user implicitly applies an all-

or-nothing rule. The model would be the perfect choice for valuing a project without flexibility

(e.g. an irreversible investment decision) in a world without uncertainty. But this is rarely the case

in the real world. To incorporate uncertainty, the DCF model discounts the CF’s with a risk-

adjusted discount rate. Hence, risky projects are discounted with a higher risk premium. In doing

so, DCF only acknowledges the downside of risk, and the greater upside potential that follows

risky investments is thereby not incorporated. Thus, the static DCF method has a downward

negative bias incorporated, which leads to rejection of promising investment opportunities simply

!"#$%&'( )*+,&-".%/.0 123 4+*5-% 6"-"/

7"089&!%*: !"#$%&'( !"#$%&'( !"#$%&'()'*+#,-#)./.01 )'*+#2'.*'.3$#)./.01 )'*+#2'.*'.3$#)./.01

!%*:&4;.%/085/0 "#3*#4#$%&'( "#3*#4#$%&'( "#3*#4#$%&'(5)*'#'%16/&3*'$#7%/&$(8 *0/$#&22/.9&:/% &22/.9&:/%#3* &22/.9&:/%#3*

3*#*0%#2&3%03 +6/3.2/%#2&3%30( +6/3.2/%#2&3%30(

<%=8".*89&4;.%/085/ ;#+*03<( ;#+*03<(#52'*2*(%78 =*3#&>&./&:/%

>8/8:+0&<".%/.&!%*: !"#$%&'( !"#$%&'( !"#$%&'(

>";8:+:&4;9$+08?8.@&<%*85= !;#$%&'( !4#$%&'( !4#$%&'(5)'*+#2'.*'.3$#)./.01#7&3%8 ;#+*03<( ;#+*03<(!"#$%&'()"$*+,-(.//0(123

 

       

19  

because of a high risk profile (Kodukula et al. 2006, p47). Copeland goes as far as to say that the

DCF method systematically undervalues every project (Copeland et al. 2003, p5).

Based on the above argumentation, it is clear that there are cases in which the traditional DCF

method is not sufficient. And this is where ROA comes in. This being said, it is important to note,

that ROA can never replace the traditional DCF method, because ROA depends on knowing the

value of the underlying assets (The DCF estimated value) (Koller 2010, p680). Hence, ROA is to

be considered a supplement to handle and incorporate the value of flexibility.

Real options theory is based on the theory of financial options. The next section begins with a

presentation of financial options.

4.1 Financial Options vs. Real Options “A financial option contract gives its owner the right (but not the obligation) to purchase or sell

an asset at a fixed price at some future date” (Berk & DeMarzo 2011, p673).

There are two distinct kinds of financial options; call options and put options. The call option

gives the owner the right to buy the asset, whereas the put option provides the owner with the right

to sell the asset. Options are further divided into two types – American and European options. A

European option can only be exercised on a the expiration date (a final date), while the American

option, which is the most common kind, can be exercised on any date up to, and including, the

expiration date (Berk & DeMarzo 2011, p673). Options offer an asymmetric payoff. When

holding an option the downside is limited to the price paid to acquire the option, whereas the

upside is unlimited for call options and limited to the difference between the exercise price and the

value of the asset for put options. Being short on a call-option means being on the other side of the

trade. Hence, you have sold the right to purchase the asset. This person (the one holding a shot

position) therefore holds the opposite risk profile of an unlimited downside and a maximum

upside of the selling price. Options are said to be in-the-money (call options) when the value of

the underlying asset exceeds the value of the exercise price. When this is not the case the option is

said to be out-of-the-money.

“A real option is the right, but not the obligation, to take an action (e.g., deferring, expanding,

contracting, or abandoning) at a predetermined cost called the exercise price, for a predeter-

mined period of time – the life of the option” (Copeland et al. 2003, p5).

The clear distinction between financial options and real options is, that real options are non-traded

assets and thereby illiquid assets. And the so-called exercise price is the costs associated with

acquiring the possibility of waiting. A final distinction is the fact, that the holder of a real option,

opposite to holders of financial options, influences the value of the option (Kodukula et al. 2006,

 

       

20  

p6). This is the case, as the value of the option is dependent on the owner making qualified

decisions. A competent management is therefore crucial for the value of a real option.

The value of real options is dependent on the same 5 variables as financial options plus an

important additional 6th variable (Copeland et al. 2003, p5). These 6 variables are presented in

figure 4:

An increase in the PV of the CF’s will increase the value of NPV and thereby also increase the

real option value (ROV). Higher investment costs will reduce the NPV and thereby also ROV.

More time to expiration allows the holder of the option to learn more about the uncertainties and

therefor increase the ROV. An increase in volatility (uncertainty) will lead to an increase in ROV.

The effect of an increase in the risk free rate is twofold; it will increase the time value of deferring

the investment cost, but simultaneously decrease the value of the CF’s as these are thereby

discounted with a higher discount rate. And the effect of the final variable is obvious; losing CF’s

to competitors due to deferral of the investment clearly lowers the value of the real option

(Copeland et al. 2003, p7). The following section will present different types of real options.

4.2 Different Types of Real Options There are generally two types of real options; simple options and compound options.

4.2.1 Simple Option: Option to defer

The option to defer is the possibility to postpone an investment, rather than investing immediately

and killing the option to “wait and see”. Thus, the firm can wait and see how market uncertainties

evolve before investing. In the case of biotech firms this option is not considered interesting, as

new drugs are patent protected, hence, waiting means the company will forego early operating

cash inflows (S.I. p110). An option to defer is equivalent to a call option on a stock (Koller et al.

2010, p687).

!"#$%&'() *+&',-%"-./&0'*+-1'2%"3&'1+&',-/$&'45'6&-/'781"490

!"#$%&'()"*&+,-.(&/(,+0(12234(*5

!"#$%&'()*+%,#$-"%

./'"0("1%23"4"+(%,#$-"%

*5%6784%

9+:"4(;"+(%6*4(4%

<);"%(*%./')3"%=+0"3(#)+(>%?,*$#()$)(>@%#A*-(%(B"%2,%

!)4C%73""%9+("3"4(%!#("%

6784%D*4(%E-"%(*%6*;'"()(*34%

FB*%G#:"%7-$$>%6*;;)(("1%

 

       

21  

4.2.2 Simple Option: Abandonment option

If a project shows disappointing results, the decision maker can abandon the project and collect

the liquidation value. The expected liquidation value is equivalent to the exercise price. The option

to abandon is equivalent to a put option on a stock, as the opportunity to abandon sets a lower

boundary on the value of the project (Koller et al. 2010, p688).

4.2.3 Simple Options: Option to expand or contract An option to expand gives the management the ability to expand the project if circumstances turn

out favourable. The option to contract is the ability to outsource the project or parts of it. Hence,

decrease future investment expenses.

The option to expand is equivalent to a call option on a stock, while the option to contract is

similar to a put option (Koller et al. 2010, p688).

4.2.4 Simple Option: Option to choose

The chooser option is a combination of some of the above-presented options. Having more than

one option obviously increase the value of the project, but the option value is not the sum of the

options combined, as they are likely to be mutually exclusive (Mun 2006, p174). E.g. it is not

possible to abandon and expand a project at the same time.

4.2.5 Simple Option: Switching option The switching option is the flexibility of being able to switch on and off the operations of a

project. Restarting a project after being shut down is equivalent to a call option, while shutting

down a project is equivalent to a put option on a stock. The option to be able to switch between

production facilities or change inputs in the production is a portfolio of call and put options

(Koller et al. 2010, p688).

4.2.6 Compound Option or Follow-on option

Follow-on options are options on options (Also called compound options). A parallel compound

option is when two options are active simultaneously, and is equivalent to a call option (Kodukula

et al. 2006, p63). A sequential compound option is present when a project is completed in phases

where each phase is dependent on success in the prior phase (Koller et al. 2010, p688). Hence,

sequential compound options are relevant in the drug development process in the biotech industry.

 

       

22  

4.2.7 Compound Option: Learning option

A learning option is present in a sequential compound option where the company learns more

about the uncertainty as time goes by. In parallel compound options there are no learning options

(Kodukula et al. 2006, p64).

4.2.8 Compound Option: Rainbow option

Rainbow options are options that are exposed to multiple sources of uncertainty and can be both

simple and compound options (Kodukula et al. 2006, p 64).

4.3 Real Options Valuation Methods This section will present methods, for calculation the value of real options, from two contingent

valuation approaches; the decision tree analysis (DTA), and real option analysis (ROA)

4.3.1 DTA DTA is a long-standing method for attempting to capture the value of flexibility. It allows the

decision maker to wait and see until the end of the period before having to decide whether to

invest or not (Copeland et al. 2003, p90).

Koller argues, that when no reliable estimates for the value and variance of the future CF’s are

available, there is little justification for applying more sophisticated ROA techniques. Further, the

DTA approach holds the advantage of being more transparent to managers than ROA (Koller et al.

2010, p680). This being said, DTA is widely criticised for a range drawbacks:

The probabilities for the future up and down state are subjective assessments. Thus, the manage-

ment’s opinions highly influence the value of the project’s flexibility (Kodukula et al. 2006, p49).

There is disagreement regarding which discount rate to apply. It is incorrect to apply the discount

rate from the DCF model, as the risk profile of the project changes when including flexibility.

Using the DCF discount rate will therefore overestimate the value of the project. Actually, in

theory, it is necessary to adjust the discount rate at each node of the decision tree, because the risk

profile of the project changes with each note. Thus, using a constant discount rate violates the law

of one price (Copeland et al. 2001, p112).

4.3.2 Real Options Analysis (ROA) ROA corrects the flaws of DTA by forming replicating portfolios based on the law of one price,

and thereby correctly prices the flexibility of the project (Copeland et al. 2001, p112). In 1973

Myron Scholes and Fischer Black presented their now famous Black-Scholes model in their paper;

The Pricing of Options and Corporate Liabilities. This laid the foundation for the financial

 

       

23  

options and thereby also real options. Since then a variety of valuation approaches have been

developed. Table 3 presents an overview of some of the methods applicable for ROV:

The partial differentiation models are, as mentioned, not considered in this paper, as their

mathematical complexity makes them difficult to apply in practice. This paper’s focus will be on

the lattice models, as these are the preferred choice by theoreticians in cases of R&D-stage

projects.

ROA have two methods for handling the value of flexibility: A replicating portfolio approach, as

mentioned above, and through risk-neutral probabilities. Because the replicating portfolio

approach is considered the most complicated approach of the two, the risk-neutral probabilities are

considered best suited for practical application. Thus, this method will receive the most attention

in this paper.

Binomial lattice Before being able to calculate the value op the option, the binomial lattice has to be constructed.

This approach uses the static NPV from DCF as the starting point in the tree. The NPV is then

multiplied by an up and down factor in order to reach the next node in the tree. The calculations of

the up and down factors are presented on the next page.

As visible in the above formula, in order to calculate these movement factors, the volatility of the

project needs to be estimated. Section 4.4 presents various methods for estimating the volatility.

One complication when working with the binomial model is that it uses continues compounding.

Hence, the below equation is used to adjust the discount rate for the tree.

!"#$%&'( )*+&",,-."/0%1&"23&1,%/454/&6%70.31

8"-74"$&9455%-%274"$&:;<"74.21 !"#$%&'"(")&*+$,-"%./"-010$%2"&$+-,/"3+21"-+$450+.-!"6.%$750&%$"6882+9:!";411,20&%$"<,5*+/-

="774/%1 !"#0.+10%$"$%550&,!"=20.+10%$"$%550&,!">4%/2%.+10%$"$%550&,!<4$50.+10%$"$%550&,

!"#$%&'()"*#+#,-(&.(-,/(01123(422

!"#$%&'()* +,('-.(/"0-(!'12"#

! "#$%&'()*+ ,)-.$%&'()*/ 0&(!*&1$2)3&*4(567( 846/$9.(/*:&1;< =)1&(414(>$)?$@*)A/'(

!"#$%&'(!)"%*+&,(-../0(122/

! ! !! !! !

! ! !!!

 

       

24  

Once the up and down factors have been calculated the binomial tree can be constructed. The net

present value is multiplied with the up factor to reach the up state and vice versa. Below a 4 period

tree is illustrated.

The 5 nodes to the right represent the range of values of the underlying asset at the time of option

expiration. Further it is worth noticing, that the tree is recombining – meaning an up movement

followed by a down movement equals the value of the reverse order. Hence, two periods leads to

only 3 possible outcomes.

Before it possible to value the option the risk-neutral probabilities needs to be calculated. When

doing so, the risk element is incorporated into the probabilities via the up and down factors.

Hence, it justifies discounting with the risk free rate. The formula for calculating the risk-neutral

probabilities is presented underneath.

Once the risk-neutral probabilities have been calculated it is possible to calculate the value of the

option. The value in each node is calculated via formula 9. The calculation takes it starting point at

end of the tree, and through backward induction the values are calculated all the way back to t=0

(Kodukula et al. 2006, p78).

!"#$%&'()* +,-."%/0,/1(2(3"/0,/%"%-(3"$4"%/5,/1

! "#$%&#'()*+#&,$-." "%./!&(*0(1*.2*%345(& 6,57(8&!!(6#$!

!"#$%&'(!)"%*+&,(-../0(1-2.

!! ! ! ! !!!"# ! !! !"#!!!

!! !!

!! !! !

!"#$%&'() *"+,-"./'0.11"2&'34'5&%",678

9:;$49:;$<

9:;$= 9:;$<69:;$ 9:;$=6

>9',?'@!A7'39:8 9:;$6 9:;$=6=9:;6 9:;$6=

9:;6= 9:;$6<9:;6<

9:;64

1"-& ! " # $ %

!"#$%&'()*+(%"+,$-.#,-"+

!"#$%&'()* +,-.(/0%1#'&(2#"3'3,&,1,0-

! "#$%&'()*+,-./+01,1#-#*2( ',*)+,-.304,+#*56+ "#$%.7+((.",*() 89.7,:*0+; <0=>.7,:*0+?* @#6(.A>*(+B,-$

!"#$%&'(!)"%*+&,(-../0(1223

! ! !!!!! ! !! ! ! !

 

       

25  

If the value in a node is negative, not exercising the option will always be the best choice; hence,

the value of the node in question is 0.

Once the backward induction is completed, the value of the option is found by subtracting the

static NPV from the value in t=0.

To summarise the calculation process:

• Estimate the volatility of the project (and the risk free rate)

• Estimate the up and down factor, and the risk neutral probabilities

• Construct the binomial lattice

• Calculate the option value

Trinomial Lattice:

This approach is similar to the binomial approach. The one big difference is that it offers 3

different outcomes at each point in time. Hence, creating a significant wider tree. This

obvious complicate the practical application, why it is not considered further in this paper.

Quadranomial lattice The qaudranomial approach is an extension of the binomial approach, where two sources

uncertainty are integrated in the tree instead of one. Kodukula is of the opinion that when two

sources of uncertainty affects the value of the project, are nearly uncorrelated, and evolve

differently through time, the qudranomial method is appropriate (Kodukula et al. 2006, p167). The

method is identical to the binomial method, except of the fact, that it models two independent

uncertainties simultaneously. Thus, two sets of up and down factors needs to be calculated. As the

figure below illustrates, the model is quite similar to a 2 period binomial lattice for each period.

The method recommendation is presented within the following framework.

!"#$%&'()* +,-."/(0'&%1('-(1'23(4"51

!" !#$%&'()'(*"+(,'#"'"- .+/012&%"3#$'43(5#5+$+"6!%*7!8(9, :*"+(,'!#$%&'+,'";&',(8&<" =+>&'?,"&3@#$/3 .+/0'A3&&'.#"&

!"#$%&'(!)"%*+&,(-../0(1-/2

!! !! ! !!"!!"!!!!! ! !!! !! ! !!"#$!!"!!!!!

!!!!! !

 

       

26  

4.4 Volatility Estimation Estimating the volatility represents the hardest theoretical problem for practitioners when applying

ROA (Copeland 2003, p42 & Kodukula 2006, p86). Copeland therefore advise the use of different

methodologies. Many consultants suggest, that the firm should use the volatility of their stock

returns as their volatility input for their real options. This is not feasible, as the volatility of a stock

will be significantly lower than the volatility of an individual project (Shockley 2007, p301).

Another common mistake is the use of the volatility of input variables such as the volatility of the

price or the quantity (Copeland 2003, p244).

In acknowledgement of the challenges associated with estimating volatility, this section is

dedicated to present a variety of methods for estimating volatility.

Kodukula presents various methods for estimation a project specific volatility (Kodukula et al.

2006, p88). The methods are:

• Monte Carlo Simulation

• Project Proxy Approach

• Market Proxy Approach

• Management Assumption Approach

4.4.2 Monte Carlo Simulation The Monte Carlo simulation method takes multiple uncertainties (E.g., price, quantity, and

variable costs) and combines them into one by running them through a spreadsheet using a

program like Crystal Ball or At Risk (Copeland et al. 2003, p244-245). This is done by simulating

different CF’s in the excel model, which ultimately presents a distribution of the present value of

the project. The standard deviation of this value is the estimated volatility of the project.

One of the simplest assumptions regarding the uncertainty of the variables (e.g. prices) is that they

follow a geometric Brownian motion, where the value next period equals the current value

!"#$%&'() *$+,%+-./"+0'1+22"3&'45'6&%".,78

9:;$5<59:;$5<

9:;$< 9:;$=,9:;$ 9:;$<,

>9'.?'@!A7'49:8 9:;$B 9:;$5B59:;, 9:;$B,

9:;,B 9:;,<,B9:;,B,

9:;,5B5

2"/& ! " #

!"#$%&'()*+(%"+,$-.#,-"+

 

       

27  

multiplied by a constant growth factor (Copeland et al. 2003, p260). The tricky part is, while the

value of an asset follows a geometric Brownian motion, the rate of return of the same asset

follows an arithmetic Brownian motion. The explanation is intuitive; prices never go negative and

therefore follow a lognormal distribution and are modelled in a geometric Brownian motion. The

rates of return can be negative, and therefor follow an arithmetic Brownian motion (Copeland et

al. 2003, p250+283).

Before running the simulation a range of input estimates must be identified and incorporated into

the spreadsheet. These estimates are the variables considered to have the greatest impact on the

value of the project, e.g. price, quantity, and variable costs. Those variables are to be defined as

assumption-cells in the simulation spreadsheet. For each of these an expected value, a standard

deviation, possible autocorrelation or/and correlations amongst each other have to be forecasted.

The expected values are the CF’s from the standard DCF model. How to estimate the standard

deviations is more tricky. Copeland suggests two alternative ways – using historical data, or

subjective data provided by management (Copeland et al. 2003, p257).

If it seems reasonable that the future will be like the past, then it is sufficient to construct

confidence bands around the expected value based on history. For biotech companies this is

unlikely the case, as their main objective is to develop new products.

Therefore the focus will be on the subjective approach. In the subjective approach one is to

quantify the uncertainties regarding the input estimates, by the use of management estimates

(Copeland 2001, p259). Copeland suggests the following approach, where the manager is to

identify a range of outcomes – with at least either the upper or lower boundary. Thus an example

of this is; what is, with 95% confidence, the highest and/or lowest price each year (Copeland 2001,

p260)

Once the upper or lower value of the variable is estimated for each year, the standard deviation of

the variables can be estimated by using one of the following two formulas:

This standard deviation is applied for the variable in all the forecasted years. Once the expected

return and standard deviation of the variables are estimated, the next step is to identify possible

!"#$%&'()*+ ,-./$'.0(1"&'./&/.2("3(456%.(1'#/'7&0-

!"#$%%&'( )*+&,"-!./$&-01-!.'*.2/&-#345-67*7(!"#/08&'( 908&,"-!./$&-01-!.'*.2/&-#345-67*7('#*( :&.'/;-<'08"=-01-"=&-!.'*.2/&> 9&?+"=-01-@$A+&"&A-B&'*0A

!"#$%&'()"*&+,-.(&/(,+0(12234(*151

!! !!!!

!!! ! !" !!!"#$%!!

! ! !!!

! !!" !!!""#$

!! ! !!!!!!

! ! !

 

       

28  

correlations among the variables and autocorrelations (Copeland 2001, p249). Autocorrelation is

relevant when the value of the variable is expected to be dependent on the values in prior years.

An example of this is the price. The price next year is likely to be highly dependent on the price in

the current. For an example of correlations and autocorrelation see section 6.5.

Now the assumption cells are in place. But before the simulations can begin, the forecasting

variable must be identified. The present value from the static DCF in year 0 is held constant in a

cell. The value connected to the Crystal Ball sheet is compounded 1 year into the future (using

WACC), and serves therefore a proxy for the value of the project in t=1. The final step before

running the simulations is to create a forecasting-cell, z, where the difference between the value in

t=0 (static DCF) and the value in t=1 (simulated value) is transformed into logarithmic returns.

After running the simulation, the estimated standard deviation of the distribution of the logarith-

mic returns are the forecasted volatility of the project, and serves as input in ROA.

4.4.3 Project Proxy Approach The project proxy approach is a simple method, where the volatility from a prior project, with

similar CF’s and risks, are used as proxy for the present project (Kodukula et al. 2006, p91).

Hence, it is an indirect method that requires a historical project with similar CF’s and risks.

According to Copeland, this is mostly only the case when the project in question is a replacement

investment, or when the option is a switching option (Copeland et al. 2003, p257).

4.4.4 Market Proxy Approach

This method is similar to the project proxy approach. Instead of using the volatility of a prior

project, the volatility of the stock return of a publicly traded company, with similar CF’s and risks

as the project in question, is used. The method is simple, provided access to a company with the

mentioned characteristics. The approach is not without drawbacks: Usually numerous products

and product candidates affect the market value of a company, thus, firms are rarely representative

for a project (Kodukula et al. 2006, p91).

!"#$%&'())* +,-.$'-/(0"&'-.&.-1("2(345%-(0'#.'6&/,

! "#$#%&'()&*+,-.#'&/-+,-'0%123+45+67 2%-8-1'+3#.0-+45+6#8(+7.49

!"#$%&'()#*(+,,-.(/01-

! ! !"!!"!!"!!!!!

!"!!"!!"!!!!!

!

 

       

29  

4.4.5 Management Assumption Method

The management assumption method is rather straightforward (Kodukula et al. 2006, p92). The

idea is, that in many situations with a new project, the only certainty is that the future will not be

like the past. Hence, assuming management to be competent and experienced, management’s

estimates about the future might prove to be the best ones (Copeland et al. 2003, p259).

Kodukula advices, that the management estimate a most likely, an optimistic, and pessimistic

forecast of the project’s expected return (Kodukula et al. 2006, p91-92).

5. Recommended Framework

This chapter initiates with a theoretical discussion of the uncertainties affecting real options in the

biotech industry. Subsequently, the author will evaluate the current valuation methods capable of

handling the uncertainties, and ultimately suggest the preferred approach for valuing biotech real

options.

Theoreticians disagree widely, upon which method is the preferred choice when it comes to value

real options in the biotech industry. The main point of discussion is how the two main uncertain-

ties (market risk and private risk) should be treated and whether or not they interact.

5.2 Interaction between Market Risks and Private Risks Koller argues, that the value of biotech projects is primarily driven by technological risk, and

therefore the DTA is the preferred approach (Koller et al. 2010, p695). DTA is chosen over ROA,

as it is unlikely that reliable values and standard deviations can be estimated, and therefore there is

little justification for applying the more sophisticated ROA (as mentioned) (Koller et al. 2010,

p680).

In line with Kodukula, Copeland and Shockley, the author does not believe that the values of

biotech projects are predominantly driven by technological risk. Further, as stated by Kodukula,

the DTA approach becomes less useful when projects are subject to large amounts of uncertainty

(which is clearly the case for biotech projects) (Kodukula et al. 2006, p53). Hence, the DTA

approach is not considered suited for the purpose.

Kellogg and Charnes suggest a model where the technological risk is modelled through DTA, and

the market risk is subsequently modelled via a binomial lattice (Kellogg et al. 2000 p8). The

author does not believe it is correct to keep the uncertainties separate in the calculation. The

 

       

30  

explanation is intuitive: A lower technological risk in later stages will increase the number of go

decisions in lower economic states, which thereby increase the value of the option. Thus, in a

multistage option problem it is simply not appropriate to treat the uncertainties separate, as they

work jointly to affect the optimal exercise and discontinue decisions (Shockley 2007, p353).

5.3 Preferred Method Kodukula and Copeland both suggest the use of the quadranomial approach for R&D drug

projects, as this method, as mentioned, is capable of handling two uncertainties (Copeland et al.

2001, p279; Kodukula et al. 2006, p167). Shockley on the other hand argues, that the binomial

lattice is perfectly capable of handling both uncertainties (Shockley 2007, p348). Lander &

Pinches questions that the use of the quadranomial approach will provide better results than

simply increasing the number of steps in the binomial lattice (Lander and Pinches 1998, p546).

Based on the above argumentation, and the fact that the quadranomial approach complicates the

calculations and thereby toughens the practical application, the binomial method is the preferred

choice for valuing the real option value of biotech R&D projects.

5.4 Framework On the back of chapter 3 and 4 the following 6 step approach for valuing biotech projects is

recommended.

5.4.1 Step 1: Strategic Analysis The first point of action is to perform a thorough strategic analysis. The analysis should include an

examination of the environment in which the product candidate is to be launched, the industry, and

the company itself. The purpose of the analysis is to acquire sufficient knowledge before the

construction of the DCF model. Estimates of future market share, growth rates, prices, number of

customers etc. (market risks) are all based on the findings in the strategic analysis.

5.4.2 Step 2: Estimation of Input Variables for DCF In this step all the critical input variables for the DCF model needs to be estimated. The market

risk variables are, as mentioned above, estimated based on the knowledge acquired in step 1.,

whereas the technological risks, such as the duration of the drug development phases, costs

associated with the different phases, and the likelihood of clinical success in different phases, are

estimated by the use of empirical data. These historical estimates are to be considered the starting

 

       

31  

point. The information gathered in the strategic analysis is used to modify these historical

estimates, so as to customise them to project. Examples of this modification process can be found

in the valuation of Veloxis in section 6.2.2.

5.4.3 Step 3: Discount Rate The third step is to calculate the project specific discount rate for the DCF model. Upcoming

biotech firms are in many cases exclusively (or approx. exclusively) financed by equity. If this is

the case, the required return from of equity holders (e.g. estimated from CAPM) is used as the

discount rate. Otherwise a weighted average of the required returns from the different investor

types is applied (WACC). It is important to note, that these discount rates are company-wide

discount rates. Thus, for project valuation these discount rates have to be adjusted so as to match

the risk of the project.

The following estimations have to be done in this step:

• Risk free rate

• Company wide beta

• Market risk premium

• (Cost of debt)

• Cost of equity

• Project risk adjustment

5.4.4 Step 4: Static DCF Model Now everything is set for construction of the standard DCF model, for the purpose of calculating

the static NPV of the project. There are two approaches to build the revenue forecast: One can use

a top-down forecast, where the total market value, market growth and market shares are the main

determinants. The other approach is a bottom-up approach, where the emphasis is on customers,

demand, potential for new customers and prices are the basis of the forecast (Koller et al. 2010,

193). This paper’s revenue forecasts are built in the latter approach.

Based on the information obtained in step 1 and 2, future CF’s for the development process and

the phase following market launch are forecasted.

Once the static PV of the commercialisation phase is estimated, a risk adjusted NPV is calculated

by subtracting the PV of development costs (+NDA application costs +launch associated costs),

and finally multiplying the cumulative probability of market launch (See appendix 3 for an

example of how to risk adjust the PV of CF’s).

 

       

32  

5.4.5 Step 5: Volatility Estimation

This step is considered the most challenging of the 6. In order to calculate the real option value,

the standard deviation of the underlying project has to be estimated (volatility). Hence, it is the

standard deviation of the CF’s from the commercialisation period. The author recommends the use

of Monte Carlo simulation. Before it is possible to run the simulation, the DCF excel sheets

require a number of adjustments and additional calculations. Section 4.4.2 presented a detailed

description of the required adjustments. Appendix 4 provides an example of how the sheet could

look like before running the simulation. Appendix 5 presents output from Crystal Ball.

5.4.6 Step 6: Real Option Valuation (ROV) The sixth and final step is to calculate the option value, and thereby the value of the project

including flexibility. As explained in section 5.3, the author, in line with Shockley, advise the use

of the binomial lattice. The step-by-step overview of this method was provided in section 4.3.2.

Appendix 6 provides an illustrative example of how to calculate the ROV through the binomial

approach.

6. Valuation of Veloxis

The above presented valuation framework is in this chapter applied to value Veloxis’ only active

product candidate Tacro. Following the valuation of Tacro, the total value of Veloxis Pharmaceu-

ticals A/S is estimated.

6.1 Step 1: Strategic Analysis of Veloxis The strategic analysis of Veloxis, is, as mentioned in the beginning, based on the available

information as of August 1st 2013. The purpose of the strategic analysis is to identify Veloxis’ key

risk and success factors along with potential competitive advantageous held by the company.

These form the foundation for the future earnings potential for the firm and will be used when

forecasting future performance scenarios.

The strategic chapter initiates with a company profile of Veloxis, after which the strategic analysis

begins. The analysis is built on Richard Lynch’s strategic framework, which comprises an internal

and external analysis (Schack, B., 2009). This framework is visualised in appendix 2.

 

       

33  

6.1.1 Company Profile

Veloxis Pharmaceuticals A/S is a Danish biotech company with headquarters located in Ho-

ersholm Denmark. It was founded in 2002 under the name LifeCycle Pharma as a spin-off from H.

Lundbeck A/S. The name was changed to Veloxis Phamaceuticals A/S in July 2011.

The initial purpose of the company was to address a critical roadblock experienced by many

pharmaceutical firms relating poor oral absorption of otherwise high potential drugs (Ve-

loxis.com/history.cfm). This led to the development of a unique technology called MeltDose.

MeltDose increases the bioavailability of low water-soluble and insoluble drug substances, so that

they can be taken orally (Veloxis.com/history.cfm).

After developing the MeltDose Technology, the company have been focusing on two therapeutic

areas; organ transplants and cardiovascular deceases. Recently the cardiovascular area has been

put on stand by, in order to fully focus on their strongest and most developed product candidate

within the organ transplant area.

Veloxis went public ultimo 2006 and have ever since experienced a rather turbulent stock price

valuation in the market. The stock price development since listing is illustrated in appendix 7. As

of August 1st Veloxis was valued at DKK 962m. On December 31st 2012 there were a total of

4,275 registered shareholders, but the main share is divided between the two largest shareholders.

Lundbeckfonden Invest A/S and Novo A/S each held 42,7% of the shares ultimo 2012 (A.R 2013

p24).

6.1.2 Business Strategy Veloxis’ approach to drug development differentiates them from other biotechnology and

pharmaceutical firms. They do not develop new drugs. Instead they use their patented MeltDose

technology to modify already developed medicines in order to improve their effect. Hence,

Veloxis is exposed to a lower technological risk than the average firm in the drug developing

industry, as they are only modifying what the FDA and EMA have already accepted.

In 2009 Veloxis chose to focus all resources on taking their strongest product candidate, LCP-

Tacro, to market. This meant, that their primary cardiovascular product candidate, LCP-AtorFen,

was put on standby after phase II completion. Since then they have been open for partnership

agreements, but they have not been able to make such a deal, even though they, allegedly, have

received continues interest from potential partners within the cardiovascular field (Company

announcement no. 15, 2009). Thus, the current goal of Veloxis is to obtain regulatory approval in

the US and the European Union, and thereafter commercialise Tacro (A.R. 2012 p6).

 

       

34  

A Marketing Authorisation Application (MAA) was filed for the European market on May 21st

2013, and the answer from the EMA regarding the European Union is expected in 2014 (Veloxis

statement, May 21st 2013).

The company is planning to submit a New Drug Application (NDA) for the American market in

the second half of 2013. Provided acceptance by the FDA the commercial launch will take place in

the second half of 2014. The strategy is to handle the commercialisation in the US on their own,

and through partnering arrangements in the rest of the world (veloxis.com/strategy.cfm).

The MeltDose technology is what makes the above described product development strategy

possible.

6.1.3 MeltDose technology

The company’s proprietary MeltDose technology is designed to enhance the bioavailability of

drug substances, which are poorly water-soluble and have suboptimal uptake and absorption in the

body - also mentioned as ‘the brick problem’. This is done through their patented Controlled

Agglomeration Process, in which a liquid vehicle system containing the drug is sprayed on an

inert carrier that can be transformed to tablets by way of direct compression (A.R. 2009 p11 &

veloxis.com/technology.cfm). The process makes it possible to create improved versions of

already marketed drugs, with a range of meaningful clinical benefits (A.R.2010 p11). Other than

the main objective of improved bioavailability, the technology furthermore offer a controlled- or

modified-release formulation, which might be able to reduce the daily dosing frequency. Addi-

tionally a reduction in adverse side effects, decrease in the variability in the absorption of the drug,

e.g., yielding a significant reduction in the interaction of food intake and degree of absorption, are

mentioned as some of the meaningful clinical benefits of the technology. The above listed benefits

would most likely improve patient compliance and convenience ultimately resulting in improved

safety (A.R.2009 p11).

The MeltDose technology is a fairly simple process to apply in practice, it can rather easily be

performed on a large scale, and is compatible with conventional process equipment (A.R.2009

p11). Thus, the technology is not expensive to apply to large-scale production.

6.1.4 Fenoglide Since founding, the company has had a range of product candidates in the clinical development

phases. One of these products, Fenoglide, was taken successfully through all development phases

and achieved regulatory approval in the US in 2007. In early 2008, Fenoglide was the first Danish

speciality pharma product to be launched in the primary care market in the US (A.R.2009 p3).

 

       

35  

Another important milestone for Veloxis was when they received their very first product patent,

also on Fenoglide. This was vital, as it proved that Veloxis were able to patent their adjusted

versions of already launched drugs. Fenoglide was launched through a partner, Sciele Pharma. The

commercial rights to sell Fenoglide are today held by Santarus, Inc. The annual sales of Fenoglide

have been rather steady around $4m. Thus, yielding rather insignificant royalties to Veloxis

(Santarus Inc. A.R. 2011, 2012). Fenoglide is therefore assumed not to hold any real value for

Veloxis

6.1.5 External Analysis

In accordance with the Lynch Framework, the external analysis is performed form a macro and

micro perspective respectively, The selected tools for the external strategic analysis are: PEST,

Porter’s Five Forces and a Competitor analysis.

The Basics

This section should be considered an introduction to the external analysis, in which the frame for

the following analysis is set. It includes a product description of LCP-Tacro followed by definition

and description of the market.

LCP-Tacro

LCP-Tacro is Veloxis’ most important product candidate, and currently the only candidate in

active development.

LCP-Tacro is a drug intended to reduce the function of the immune system when patients undergo

transplant surgery. When a vital organ fails, death is often inevitable. However, in patients with

end-stage kidney failure, a life extending treatment involving maintenance dialysis is an option.

Yet, dialysis is debilitating the patients and thereby significantly reduces their quality of life.

Therefore, organ transplantation can seem as the only real alternative (A.R. 2009 p7). After

transplantation, the patient needs to maintain a minimum level of tacrolimus in the blood, in order

to prevent the body from rejecting the implanted organ. If, on the other hand, the body receives

too much tacrolimus, there is an increased risk of severe side effects e.g. kidney damage,

nephrotoxicity, tremor, diabetes, high blood pressure, and opportunistic infections (A.R. 2011 p7

& I.R. March 2013 p6).

Ever since the first successful human kidney transplant was performed in 1954, the development

of effective immunosuppression drugs, coupled with advances in immunology, surgical tech-

niques, donor selection and postoperative care have all improved the outcomes for solid organ

 

       

36  

transplants (A.R. 2009 p6). Organ transplantation is now an established treatment for organ failure

of the kidney, pancreas, liver, heart and lung (A.R. 2009 p6).

Tacro was initially intended to target both kidney and liver transplants, but in 2011, Veloxis chose

to focus its development efforts on pursuing LCP-Tacro for treatment of only kidney transplant

patients, given a significantly larger potential patient population and demand (A.R. 2011 p5).

LCP-Tacro is being developed as a once-daily dosage tablet version of tacrolimus. The first

tacrolimus drug, Prograf, was introduced by Fujisawa3 in 1992, and was subsequently regarded as

the “gold standard” calcineurin inhibitor (Veloxis Presentation 14th February 2012 p8+p9). LCP-

Tacro is basically a generic version of Prograf. However, Veloxis’ proprietary MeltDose technol-

ogy is capable of adding a number of potentially relevant improvements to the drug;

• Once daily dosing;

• Improved systematic absorption;

• Improved bioavailability, and thereby a lower dose of tacrolimus;

• Limited variability in the concentration of the tacrolimus in the blood (“peak-to-through”

fluctuation)

Further, Veloxis is hoping that the lower dosage of tacrolimus in LCP-Tacro translates to fewer

side effects.

An overview of the completed LCP-Tacro clinical trials is presented below. In table 4 the findings

from the phase I+II are presented, and table 5 shows the results from the phase III trials.

                                                                                                               3 Today known as Astellas Pharma Inc.  

!"#$%&!'(! !!!)*+,"#-./!,!*%010-#%!+2#3&!4544!6&37%83

+2#3&!4!"#$%&'()*+",(-"./012"3+"4"51(6357"81*-+2-96&37%83(!!":1;+2-3*(31<".*1(31*"=/+(0(/6(=/6/37")+;8(*1<"3+"><0(.*(?!">88*+@9"ABC"5/.51*"=/+(0(/6(=/6/37D"(2<"-E81*/+*"1@312<1<"*161(-1"8*+?/61!"F5+,1<"2+"21,"-(?137")+2)1*2-

'GH":IJK"LF"F>MH"LN"GJO>NF

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

'GH":IJK"LF"UVIWLNKD">N:"FGVULNK"FLKNF"VM"LO%IVXHOHN'

!"#$%&'()*+(%"+,$-.#,-"+

 

       

37  

Phase I proved that the drug is safe in humans, but more interesting, it indicated a vast superiority

compared to Advagraf4. However, the test was performed on only 8 individuals and holds no real

power. In the phase II trials, Veloxis demonstrated what was expected – the drug is working and

showing signs of improvements compared to Prograf. Appendix 8 presents a more detailed

description of the findings in phase I and II.

In phase III Veloxis has completed three studies. The first, ‘Study 3001’, proved that Tacro holds,

at least, the same safety and tolerability profile as Prograf; patients can safely convert from

Prograf to LCP-Tacro; lower dosage of tacrolimus; and a trend towards lower rejection rates. In

their second phase III study, ‘Study 3002’, the results were less positive, as it showed that the

                                                                                                               4 Advagraf is a once-daily version of Prograf, launched by Astellas Pharma Inc. The compound recent-ly gained approval by FDA, under the brand Astagraf.

!"#$%&!'(! !!!)*+,"#-./!,!*%010-#%!+2#3&!444!5&36%73

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

899A!376;<!"&</+"+,-.8";'+"90)>*)?0."P1.0)"I90(/'6"%)*,*(*6"Q=)00?01,";/,<"C@Q"/1".0"1*A*"7/.108"""",)'1+96'1,"9',/01,+5&36%73!"&<0"9)/?')8"01.9*/1,+R"""K/*9+8"%)*A01"Q(-,0"N',0"SK%QNW"""O)'>,">'/6-)0"""#*++",*">*66*;B-9"""@0',<!"EA0)'66",<0"+,-.8">*-1."'",)0',?01,"./>>0)01(0"*>"BV:XH"/1">'A*-)"*>"#$%B&'()*"(*?9')0."""",*"9)*=)'>J"Y1"'"TZH"$Y",<0",)0',?01,"./>>0)01(0"/+";/,</1"SB[:TH:"\Z:2HW!"]/,</1",<0"+0(*1.')8"01.9*/1,+"#$%B&'()*"+6/=<,68"*-,90)>*)?0."%)*=)'>

8998!376;<!"&</+";'+"'"+,-.8"/1"7/.108",)'1+96'1,")0(/9/01,+"0^90)/01(/1=",)0?*)+"'+"'")0+-6,"*>",<0"""",'()*6/?-+"?0./(',/*1!"&<0"9-)9*+0";'+",*"0^96*)0";<0,<0)"(*1A0),/1="9',/01,+:";<*";0)0"0^90)/01(/1=""""+8?9,*?',/(",)0?*)">)*?"%)*=)'>:",*"#$%B&'()*",'560,:"60.",*"?0'+-)'560"/?9)*A0?01,"/1""",)0?*)5&36%73=>?&.7!-/@@&17(_*<1"$J"L*)='1:"LJ@J:"%<J@J:"Q++*(/',0"%)*>0++*)"/1",<0"L*A0?01,"@/+*).0)"%)*=)'?:"@09'),?01,"*>"`0-)*6*=8"',"L0./('6"$*660=0"*>"O0*)=/'R!"#7%&%)*'4&%#2<$'&087670(884&3$(676+9*8&73512:$3$6)&921&1$6(8&)1(6%58(6)&5()7$6)%&$=5$17$6076+&)1$321%>&"(012873*%/76'*0$'&)1$321&08$(184&735(0)%&?*(87)4&29&879$&(6'&)#7%&%)*'4&'$326%)1()$%&)#()&<#$6&5()7$6)%&<$1$&%<7)0#$'&)2&,-./"(012;&)#$4&$=5$17$60$'&%7+67970(6)&73512:$3$6)&76&)#$71&(@787)4&)2&5$19213&$:$14'(4&)(%A%&(6'&73512:$3$6)&26&)#$71&?*(87)4&29&879$!!"&</+"+,-.8"+<*;0."+/=1/>/('1,"*A0)'66"/?9)*A0?01,+">*66*;/1=",<0"+;/,(<",*"#$%B&'()*"""S9aG:GGVW!"&<0"*A0)'66"/?9)*A0?01,+";0)0")',0."-+/1=",<0"A'6/.',0."C&L"+('60J"&<0")0+-6,"+<*;0."""'1"'A0)'=0"VZH"/?9)*A0?01,

!"#$%&'()*+(%"+,$-.#,-"+

 

       

38  

amount of side effects from taking Tacro, are very similar to those of Prograf. The ‘Study 3003’

had focus on the important side effect Tremor. This study showed a significant advantage in

favour of LCP-Tacro. Overall the phase III studies have successfully demonstrated LCP-Tacro to

be a safe and effective tacrolimus version. The main findings throughout phase III is presented in

table 5 above. Appendix 9 presents the detailed results from the three phase III studies.

Market definition Veloxis are planning to launch LCP-Tacro in the American market through its own dedicated

sales, marketing and medical team, and through partners in the rest of the world. The transplant

marketplace in the US is ideally suited for a small and focused selling effort, as the transplants are

generally performed at a small number of specialized centres – approximately 250 centres. Hence,

a small number of sales representatives can cover the majority of the biggest market in the world.

As the American market is by far the most important market for Veloxis, the focus in the

following strategic analysis will be on this market. The valuation of Tacro will however be

divided into three parts - the US launch, the launch in Europe through their Italian partner Chiesi,

and the possibility of launching Tacro in Japan through a partner.

• Thus, the relevant market for Veloxis is the American post-kidney-transplant immunosuppres-

sion care market

Market description The overall immunosuppression market contains several different compound classes, including

Calcineurin Inhibitors (CNIs), Antoproliferative and Antimetabolic Drugs, S1p-R agonists,

Malononitrilamides and a series of antibodies (emedicine.medscape.com). Yet, over 90% of new

American kidney transplant patients are discharged on a CNI, and since 2001 the dominant CNI

compound has been tacrolimus (Company presentation Feb 14th 2012, p8). There is a general

perception that tacrolimus is superior in efficiency compared to cyclosporine (the second best

selling CNI) and at the same time easier to dose.

In 2010, the market value of the immunosuppression therapy market was USD 5.8b (isotechni-

ka.com). The three leading drugs were tacrolimus, mycophenolate mofetil, and ciclosporin, with

tacrolimus capturing the largest share of the market with over USD 2b in sales (dddmag.com).

PEST

 

       

39  

Lynch’s framework dictates that a macro perspective analysis of the environment, in which the

firm is to operate, is a necessary part of the strategic analysis. The PEST analysis, which identifies

the Political, Economical, Socio-Cultural and Technological factors, is chosen for this purpose,

and the main findings from the analysis are presented in table 6.

Political

Kidney transplant patients are dependent on the immunosuppression therapy from the moment

they receive the transplant, till the day they die. They will need to take the medicine every day for

the rest of their lives, which is a huge financial burden for many patients. Many patients are

therefore dependent on subsidies, making the public healthcare system and insurance companies

an important player and customer, for Veloxis.

For more than quarter of a century, reimbursement and insurance coverage for immunosuppressive

medicine have been serious issues for kidney transplant patients (Evans et al. 2010). Between

1986 and 2000, modest changes were made in Medicare coverage and reimbursement policies. At

that time, Medicare covered 80% of the medicine related costs following transplantation, but only

for a period of 3 years. In 1999 the congress extended the Medicare, to now cover the immuno-

suppressive drugs for the rest of the patient’s life. However, this was only eligible to a minority of

the transplant patients, as it was only valid for persons older than 65 years, and/or disabled

individuals (Evans et al. 2010).

Because the regulations still require patients to carry the full medical expenses 3 years after the

operation, some patients are unable to afford their immunosuppressive drugs, leading to premature

and avoidable graft failure.

According to a paper by Roger W. Evans et.al. (2010), the lack of national representative

contemporary data that characterise the prevalence of immunosuppressive medication-related

problems, has made all attempts to expand the Medicare coverage to lifelong coverage for all

transplant patients unsuccessful. The same paper presented the much-needed data.

Due to the history, and the current attention of expanding the Medicare coverage, it is expected,

that the current coverage will not be restricted. It is considered more likely that an additional

expansion of the coverage will be implemented.

Another highly relevant political aspect for Veloxis is whether they will be acknowledged as the

‘best-in-class’ medication. This will influence the degree of subsidies to patients on Tacro, and

thereby highly impact the sale of LCP-Tacro in the US. Based on the results presented in the

clinical trials, Veloxis is confident that Tacro will prove ‘best-in-class’ (Tables 4 and 5 provides

 

       

40  

resumes of the trial results, whereas appendix 8 and 9 describe the findings in more detail). This

view is supported by Dr. Suphamai Bunnapradist, M.D., Professor of Medicine and Director of

Kidney Transplant Reseach: “These data suggest that LCP-Tacro may potentially offer an

improvement in outcomes, as well as improve convenience for transplant patients due to the

once-a-day dosing” (Company announcement no. 9/2011).

Whether LCP-Tacro will be labelled ‘best-in-class’ is still an uncertainty, and is considered one of

the most significant risks, as it will drastically influence the US sale of LCP-Tacro.

Economical Sick people are dependent on getting their medicine, why economic conditions are generally of

less importance in the pharmaceutical industry, compared to other industries. This is especially

true for the immunosuppression market, as the patients are kept alive by their medication. Thus,

the sales volume of immunosuppression drugs can decline if the prevalence of kidney failures

drops, the number of organ donor’s decrease, or if new improved treatments are launched.

The three largest players on the American market are all competing with generic versions of their

branded product. Prograf, Tacro’s main competitor, faced generic competition from 2009 in the

US, and 2010 in Europe. Initially, the generic erosion was held back, as physicians were con-

cerned about the predictability of switching to generic formulations, as immunosuppression drugs

are considered narrow therapeutic window drugs5 (Company presentation 14th Feb 2012 p8).

Subsequently this attitude changed, and as of 12th of April 2012 the generic versions attained 64%

of the American tacrolimus market (A.R. 2012 p11).

This could cause problems for Veloxis, as their future consumers have become accustomed to the

lower prices offered by the generics. Veloxis are therefore dependent on their ability to convince

physicians, the healthcare system, and the health insurance companies that LCP-Tacro offer

significant improvements compared to the original tacrolimus version. Based on the clinical

results presented earlier, this is considered feasible.

Socio-Cultural

Naturally, key drivers for the market potential of immunosuppression drugs are the number of

transplants and patient survival rates. Figure 7 and 8 illustrate the historic development in these

key drivers.

                                                                                                               5 A narrow therapeutic window drug is a drug where the timing of absorption, and the dosage amount is of critical importance

 

       

41  

The steady development in the number of kidney transplants since 2006 is not a sign of decreasing

demand for organ transplants. As of July 19th 2013, there were 96.994 kidney transplant candi-

dates on the waiting list for receiving a transplant6. 70.500 of these have been waiting more than

one year. The problem has to be attributed the lack of kidney donors. Thus, the long-term market

potential for immunosuppressive drugs is dependent on the public awareness of organ donation,

and how the general public position on the issue evolves. It is regarded as an ethical issue, and is

consequently difficult to predict.

                                                                                                               6  http://optn.transplant.hrsa.gov/ -> Data -> Organ Datasource -> National Data -> Waiting list -> Overall by organ  

!"#$%&'() *+',"-.&/'0%1.231.42'1.-'566'*+',"-.&/'78.8%2

!"#$%&'()**+',,"+*-.*$/-0+1/-*.)$0/.2"3,(45(6/*/(45(7$2/-(6/*/0"#$%&(45((((((((((((((((8/*9"-/1(6/*/(45(6"-"$:,;$/-0+1/-*(45(<9=-&>(;$/-+1/-*0:,<9=-&>

!"#$$%

!&#$$%

!'#$$%

!##$$%

!(#$$%

!)#$$%

!*#$$%

!+#$$%

"$$"% "$$&% "$$'% "$$#% "$$(% "$$)% "$$*% "$$+% "$!$% "$!!% "$!"%

!"#$%&'()#*+,'-./,'0-#

,-./01%2345-1%6/.5780.567% 900%:;%4<5</7%

!"#$%&'() *$+,-.&/'0.-1#'02$3+'4"21&5'+%01/6301+'%&,"6"&1+/'"1'+7&'89

*$+,-.&/'0.-1#'02$3+'4"21&5'+%01/6301+'%&,"6"&1+/)'2&,&0/&2'2-1-%

*$+,-.&/'0.-1#'02$3+'4"21&5'+%01/6301+'%&,"6"&1+/)'3":"1#'2-1-%

!"#$%&'()*+,-!.+.(/011(233#45(.&6"$7(84749(6::

 

       

42  

Figure 8, above, shows a general trend towards increasing survival rates for kidney recipients in

the United States. This trend obviously affects the market value positively, as it results in a larger

pool of patients on immunosuppression medication.

However, this development cannot continue, as the post transplant survival rate is closing in on

100% for the 1 year. Beyond the 5-year point there are still opportunities for improvements. Yet,

the relative importance of this former key driver is declining.

Technological

One of the greatest threats in the pharmaceutical industry is the development of comparable, or

improved drugs, by competitors. Veloxis’ main competitors are all large and financially strong

established pharmaceutical companies, making them capable of investing significantly more in

R&D than Veloxis. But in order to develop a tacrolimus version better than LCP-Tacro, a

technology capable of increasing the bioavailability is needed. At the moment, the author is

familiar with only one technology capable to increase the bioavailability in compounds in line

with MeltDose – the NanoCrystal Technology (owned by Elan). This technology depletes

particles into smaller pieces and thereby increases the bioavailability. According to Veloxis, this

technology is considerably more complex and expensive to apply in the production process. One

immunosuppression drug based on this technology has been approved - Rapamune, Sirolimus, by

Wyeth (Gulsun et al. 2009, p62).

The technological threat from competitors is one of the more serious threats for Veloxis, but at the

moment they are considered holding a competitive advantage through their proprietary MeltDose

technology platform.

The main findings from the pest analysis are presented in table 6 beneath, along with their

potential impact from Veloxis’ point of view.

 

       

43  

The main determiner for the future sales volume in the industry is the development within organ

donors, while the most important event regarding pricing is the recent generic penetration. Thus,

in order to switch patients to higher priced new products, future drug compound launches are

required to offer significant benefits compared to the available generic products.

Porter’s Five Forces

Porter’s Five Forces is a micro perspective analytical framework used to investigate the external

environment in which the firm is operating. The analysis is used to assess the attractiveness of the

immunosuppression drug industry through an evaluation of five forces.

The Threat of Substitutes

The human body is equipped with two kidneys, but we only need one in order to survive. If both

kidneys fail, there are only two possible treatment forms that can keep the person alive; a kidney

transplantation or life-long dialysis therapy (bidmc.org).

Dialysis is thus the only substitute for transplantation. Dialysis is a lifesaving treatment, but it only

performs about 10% of the work a functioning kidney does, why being in dialysis treatment causes

other serious health problems, including anemia7, high blood pressure, heart decease, and nerve

damage (bidmc.org). Consequently, the average life expectancy for patients in dialysis treatment is

approx. 5 years. The life expectancy following a kidney transplant is, on average, 12-20 years for

a living donor kidney and 8-12 years for deceased donor kidneys (bidmc.org). Even though a

kidney transplants is a major surgery, and is followed by a tough recovery period, according to

patients who have been in dialysis therapy and subsequently had a kidney transplant, it offers the

patient a more satisfying life with a better quality of life, (bidmc.org).

                                                                                                               7  Anemia is a shortage of red blood cells. This diminishes oxygen and lowers energy and strength  

!"#$%&'(&)*+!&","$-./.&01%21/%3

4"5602 7..8% )20#"#/$/6- 79"56&0,&10$89% 79:"56&0,&:2/5%

!"#$%$&'# !"#$%&'"($%)*$)+,-&./0.121$. 3"%$&4,+1$)+.&#1--&0$&2$4$)2$)+&")&'$)$%15.

61'7$%&'"($%)*$)+,-&./0.121$. 3"%$&4,+1$)+.&#1--&0$&-18$-9&+"&/.$&!:;<=,5%"

(&")"*$&'# >$)$%15&4$)$+%,+1") ;,+1$)+.&'$++1)'&/.$2&+"&57$,4$%&2%/'.

+"&$",&-#%-.'# 3,%8$+&1)&)$$2&"?&2")"%. 6"-21)'&*,%8$+&4"+$)+1,-&0,58

;,+1$)+&./%(1(,-&%,+$.&1*4%"(1)' @)5%$,.1)'&+7$&5/.+"*$%&0,.$

;,+1$)+&./%(1(,-&%,+$.&-1*1+,+1"). A1--&.-"#&2"#)&'%"#+7&%,+$

/0&1)"#"&$'# B/0.+,)+1,-&1)($.+*$)+.&1)&CDE&%$F/1%$2

:").+,)+&1))"(,+1($&4%$../%$

+"-.&02345)3&")%.$6-%$")

7,;$8%,5%&

 

       

44  

Hence, Transplantation is considered the only long-term treatment, whereas dialysis therapy is

considered a necessary treatment that keeps patients alive while they wait for a suitable kidney.

The power of buyers The physicians are important players. Their opinions are important, as they basically choose which

drugs the patients receive. Apart from the physicians, the healthcare sector and the insurance

companies hold a significant purchasing power, as they choose which drugs to reimburse.

The power of suppliers

Veloxis are planning to outsource the pill production. As described in section 6.1.3, the MeltDose

technology is relatively simple to use in large-scale production, and can be applied in any pill

factory machinery. Thus, the suppliers are not considered to hold significant purchasing power.

Barriers to entry The barriers to enter the American immunosuppression market are considered reasonably low, as

the three top selling compounds in the US have all lost their patents exclusivity protection. Hence,

pharmaceutical companies can market generic versions of the top selling compounds at minimal

cost. This was exactly what happened to Prograf since loss of patent protection in 2008. In 2009

Sandoz, a global leader in generics, were the first to launch a generic version of tacrolimus. Since

then, three new versions were launched in 2010, one in 2011 and one in 2012 (drugs.com). Hence,

a total of 6 generic versions of with Astellas’ Prograf have become available on the American

market since 2009. But in order to compete on equal terms with Tacro, the new player has to

develop a technology similar to MeltDose.

Rivalry among existing competitors

Table 7 presents the worldwide sales of immunosuppression medicine in 2010. The compounds

highlighted in bold are the products that will compete with LCP-Tacro, according to Veloxis (A.R.

2012 p10). Hence, the main focus will be on these compounds.

 

       

45  

In 2010, the three largest players on the worldwide immunosuppression market were Astellas,

Roche and Novartis. The main focus of this paper is, as mentioned, on the American market. The

tacrolimus compound still holds approx. 90% of the US market, but since Prograf’s loss of

exclusivity in 2008 a lot have changed (Company presentation Feb 14th 2012 p8). As mentioned

previously, a total of 6 generic compounds have been brought to the American market since

Sandoz launched the first in 2009. According to Astellas, the generic versions had captured a 64%

share of the US tacrolimus market as of the April 12th 2012 (A.R. 2012 p11). Comparing this

percentage to the 2011 Prograf sale in America of USD 370m suggests a total US tacrolimus

market worth USD 1.030m8(assuming no price differences, hence the true value is slightly lower).

Initially, Astellas tried to fight off the generic competition by launching a new compound -

Advagraf. Advagraf is, like LCP-Tacro, a once-a-day dosage tacrolimus version. Hence, Veloxis

expected Advagraf to be their main competitor in the American market, why they organised

clinical trials with the purpose of demonstrating that LCP-Tacro is superior to Advagraf (Appen-

dix 8).

Advagraf was approved in Europe in 2007, but was later rejected by the FDA due to failure of a

clinical trial, and data suggesting poor bioavailability compared to Prograf. In September 2012

Astellas announced filing a new submission for market approval under the new brand Astagraf.

On July 19th 2013 the FDA approved Astagraf (Astellas.com). This means that Veloxis will have

to compete with a compound holding similar characteristics, which is launched by a very strong

and experienced pharmaceutical company (Astellas), and will not be the first once-a-day dosage

tacrolimus version on the US market.

                                                                                                               8 USD 1.030m=370/(64%-1)

!"#$%&'(&)*+*&,-.$/&,0/%&12234-5366.%5507%&8%/09":0-4&;"$%5&<,,=

>.-/39: ?-26"4@ A%4%.09&4"2% ;"$%5&<B;C2=&)*+* 8".D%:&5E".%

>.-F."G H5:%$$"5 !"9.-$0235 )*I* JKL!"##$"%& '($)" *+$(%)",(#-&"./(0"&1# 2345 336

M%-."$N?5H M-7".:05 ?@9$-56-.04% O'* +PL7)+/(8#(9:#1, ;-,8;&-& <,&1=&)+/($+&".8#(9:#1, .......>?&1/-&"@.A55 256

*+0(B&1$ C(D-&1? *+$(%)",(#1$ EE5 F6

'-%-/:," G01H"B ;1B(#1/:? I45 J6

<H-?-,KL/:B"# ;-#1M."&N-#N <H-&)1(%B1," .......................O.255 ................O.36

H/7"F."G H5:%$$"5 !"9.-$0235 &&&&&&&&&&&&&&&&&&&&&&&Q&+** &&&&&&&&&&&&&&&&Q&)L!"B&1$-, C(D-B&1? >D"B(#1/:? .......................O.255 ................O.36

;1/:#"$& C(D-B&1? P-?1#1M1/-9 .......................O.255 ................O.36

H5:"F."G H5:%$$"5 !"9.-$0235 &&&&&&&&&&&&&&&&&&&&&&&&&MNH &&&&&&&&&&&&&&&&&&&MNHM3$-R0S T.05:-$U8@%.5&;V30## T%$":%9%6: &&&&&&&&&&&&&&&&&&&&&&&&&MNH &&&&&&&&&&&&&&&&&&&MNH7(&-# QF55 2556

!"#$%&'()**+',,---./0"*&%)1/23.%"4,511,6$"5#%*0718&9&:"+4&1*,;"%:"0+"$/1,744#1"0#++$&00/"1<3$2&*.30+=

 

       

46  

Cyclosporine is the second best selling immunosuppressive compound in America, and was

initially launched by Novartis under the brand Neoral. In 2012 Neoral sales amounted to USD

64m in the US (A.R. Neoral 2012, p155). This clearly illustrates the strong market position held

by the tacrolimus compound.

To summarise, LCP-Tacro is going to have to compete with Prograf, 6 cheaper generic verison,

the soon-to-be launched Advagraf, which will be the first once-daily dosage tacrolimus compound

to hit the market; and the cyclosporine compounds. Hence, the rivalry among existing competitors

in the American immunosuppression is fierce.

Competitor Analysis

The final element of the external analysis framework suggested by Lynch is a characterisation of

the main competitors. Astellas, the market leader, and the companies behind the generic versions

are targeted in this section, as these are highlighted by Veloxis as their main competitors in the

American market.

Astellas Astellas Pharma Inc. is a Japanese pharmaceutical company founded in 1923 with headquarters

located in Tokyo. The company owns R&D performing subsidiaries all around the world, but their

business strategy is built around manufacturing, marketing and import/export of pharmaceutical

products (Astellas.com). It is the second-largest pharmaceutical company in Japan, and currently

ranks within the top-20 pharmaceuticals worldwide, earning USD 11,822m in net sales in 2012,

while spending USD 2,315m on R&D. (Astellas A.R 2012 p4)

Astellas mainly operate within five therapeutic areas where immunosuppressive drugs are part of

their immunology and factious diseases area. They are the recognized leader in the transplantation

therapy market, and have been committed in the industry for more than 20 years.

Before the American patent protection on Prograf expired in 2008, they served approx. 90% of the

American transplant patients with immunosuppressive drugs. As previously mentioned generic

erosion subsequently took place and altered their market position, but the recent NDA for Astagraf

is likely to turn this development around, and could give Astellas a comeback on the American

market.

Generic versions The companies behind the generic versions of tacrolimus are; Accord Healthcare, Dr. Reddy’s

Labs Ltd, Mylan, Sandoz, Panacea Biotec Ltd and Watson Labs (now called Actavis)

(drugs.com). Accord Healthcare is one of the fastest growing generic companies in the world and

 

       

47  

has launched in over 28 European markets (accord-healthcare.eu). Dr. Reddys Labs Ltd is India’s

second largest drug maker with revenues of more than USD 2 b in 2012 (Dr. Reddys A.R. 2012

p5). Mylan and Sandoz are considered among the world’s leading generic pharmaceutical

companies. Thus, all these companies are Veloxis financially superior. Further, they distribute a

large variety of compounds, and are thereby not dependent on how a single compound is selling.

6.1.6 Internal Analysis The main purpose of this section is to identify Veloxis’ internal strength and weaknesses. To do

so, Michael Porter’s Value Chain model is applied. The model is adjusted so as to better fit the

value chain of a biotech company.

Primary Activity: Inbound Logistics There is nothing indicating that Veloxis is neither better nor worse than competitors, when it

comes to handle the inputs needed for producing the drugs required for the clinical trials.

Primary Activity: R&D

Capabilities within R&D are a key factor for success in the biotech industry. As previously

mentioned, Veloxis differ from the normal biotech firm in that they do not develop new drugs, but

instead use their proprietary MeltDose technology to improve already marketed drugs. This

obviously reduces the technological risk associated with the clinical trials significantly. Neverthe-

less, the company has to prove that their technology can improve the compounds, which require a

strong R&D department. Veloxis have proven that they hold the competences to take a product

candidate through all development phases and achieve FDA approval through their marketed

Fenoglide. Further, they have proved capable of performing comprehensive phase III studies, i.e.

the recently completed 3002-study enrolled more than 540 de novo kidney patients from locations

in all parts of the world.

On a more negative note, Veloxis is currently 100% focused on Tacro, which already in 2010

resulted in the firing of 26 employees, when they re-focused their strategy towards the launch of

Tacro (A.R. 2010 p3). This might indicate that the R&D department have been neglected, which

could come beck to haunt the company in the future.

Primary Activity: Patent Protection

 

       

48  

In order to survive in the biotech industry it is very important to be capable of protecting technol-

ogies and product candidates through the patent protection system. Section 3.4.5 described the

patent system for the drug industry.

Veloxies have proved capable of handling this task. Their cornerstone MeltDose technology is

protected until 2022 (meltdose.com), and LCP-Tacro is patented in China, India, Europa, and the

US (A.R. 2009 p3 + presentation November 9th 2011). Thus, Veloxis have proven able of

protecting their most important assets.

Primary Activity: Production Up till this point, Veloxis has not been responsible for production in large scale, as their only

marketed product was launched through a partner. This will not change if LCP-Tacro is launched,

as the plan is to outsource the production. This is possible, as the MeltDose technology, as

mentioned, is a very simple technology to implement in a standard pill producing facility.

The simple technology is considered a strategic advantage, as competing compounds are,

according to Veloxis, based on far more complicated processes. On the downside, by outsourcing

the production Veloxis will give up the control, and thus becomes dependent on their partner’s

ability to handle the production satisfactory.

Primary Activity: Marketing & sale Veloxis holds no experience within marketing and sale, and plans to commercialize Tacro in the

US through its own sales, marketing and medical team (Investor presentation, Feb 14th 2012 p21).

According to Veloxis, the US transplant marketplace is ideally suited for a small and focused

selling effort, since the majority of transplants are performed at a small number of specialised

centres (Approx. 250) (A.R. 2012 p9). Thus, Veloxis believes it can cover the market with a sales

force of only 20 sales representatives, 2 regional managers and 1 head of sales. For a more

detailed overview of their commercialisation strategy see appendix 10.

Veloxis’ is, as described, restricted to very limited financial resources compared to their competi-

tors. Thus, the strength of the marketing and sales activity is considered uncertain, and could

likely prove a serious competitive weakness.

Secondary Activity: Human Resources

Human Resource Management is extremely important in the biotech industry, as it is the employ-

ees who identify possible product candidates, and subsequently develop the compounds. Thus,

 

       

49  

being capable of attracting and sustaining the best scientists and experts in the fields of interest is

crucial, and considered a key success factor. Veloxis knows that, and “attracting and retaining the

best talent (…) continues to be a company-wide focus” (A.R. 2009 p14).

As of December 31st 2012 79% of the 29 employees were working within R&D, while the

remaining 21% were in general and administrative positions. 48% have been employed in the

biotech or pharmaceutical industry for more than 15 years (A.R. 2012 p18).

There is nothing to indicate that Veloxis’ has problems attracting qualified personnel. The history

of Fenoglide taken successfully through all development stages, along with the more recently

presented Tacro results, demonstrate that Veloxis holds a competent team of R&D employees.

The strength of the sale and marketing personnel who are commercialising Tacro in the US is yet

to be proven.

Secondary Activity: Firm Structure

Ultimo 2008 Veloxis employed 106 people. The current CEO, Dr. William J. Polvino, then joined

Veloxis in 2009. Subsequently, Veloxis implemented steps to streamline and focus the organisa-

tion (A.R. 2009 p3). At the end of 2009 the number of employees was reduced to 65, and by

primo 2013 the number was down to 29 (A.R.2012 p18). These steps were taken in order to ensure

an innovative, dynamic, highly efficient and not least cost-effective organisation (A.R.2009 p3).

Another, and perhaps more reliable, explanation for this development is the changed business

strategy of now devoting the full focus of the organisation towards the commercialisation of

Tacro.

Secondary Activity: Investor Relations

For a biotech firm like Veloxis, who practically does not generate any revenue, it is very important

to maintain a good relationship to investors. These are virtually their only source of financing.

From having less than 57m shares outstanding in 2009, the company have carried out two share

issues, one in 2010 and one in 2012, which have led to a total of 1,659m outstanding shares as of

December 31st 2012. The net proceeds from the most recent issue amounted to DKK 409m. The

two largest investors are, as mentioned, Novo Nordisk and Lundbeck, who combined own 85,4%.

According to Veloxis the most recent rights issue will finance the company through the commer-

cialisation process of Tacro in both the US and EU (A.R.2012 p3). With the current financial

position and the strong backing from Novo Nordisk and Lundbeck, Veloxis is currently consid-

ered to be in a relatively safe financial situation.

 

       

50  

Secondary Activity: Technological Development Veloxis currently has two patented technology platforms; MeltDose and LLT (Liquid Loadable

Tablets). The potential of MeltDose has already been validated through one market launch and

promising late trial results from Tacro. LLT has yet to be proven. No product candidate based on

the LLT has been presented till this point. Nevertheless, Veloxis believes that LLT is a promising

technology and expect future product candidates based on LLT.

It is very important to constantly improve your technologies in the biotech sector. Otherwise it is

only a matter of time before competitors present similar, or eventually superior, technologies.

Veloxis has proven capable of developing technologies and is therefor considered suited for the

technological-battle.

6.1.7 SWOT The key findings in the external and internal analysis are summarised in the following

SWOT matrix.

6.2 Step 2: Estimation of Input Variables for DCF (Tacro) This step estimates the market and technological risk input variables for the Tacro DCF models

!"#$%&'(&)*+!&,-%$./012)34%5637 *%"85%11%1

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

!"L,)%(-%B"9'$$"4/")3/"B'-,)"*&./@1%'$5@1*,/".*:0*+&1"'&")3/"MG!"D/0/&1/&)"*&".*&)'&*+,$5"4/'&(".%0%4$/"*B"%))-%.)'&("%&1";//0'&("F+%$'B'/1"9*-;/-,

9+$%,&:";<'",+'(%54$(5+'

 

       

51  

6.2.1 Market risks

In this section the estimation of the market risk input variables for the standard DCF models for

LCP-Tacro is presented. These variables include the number of patients, dosages, prices, market

development, market shares, margins and royalties.

Patients

Table 9 presents the geographical populations of patients living with a transplanted kidney along

with the share of de novo patients (2011).

The data concerning the development of the number of yearly US kidney transplantations (Figure

7) corresponds to a CAGR of 1,1%9 in the period from 2002 to 2012. This number is not repre-

sentative for the yearly growth rate in the total pool of patients living with a kidney transplant.

Factors like the decreasing post operation death rates, improved therapeutic treatments etc.,

suggest the CAGR of the total pool of patients is higher. However, in the long run, the CAGR of

the number of yearly transplants is considered a good proxy for the growth rate of the pool of

patients.

In the absence of a better estimate, this paper will deploy a slightly upward adjusted version of the

1.1%: A conservative CAGR estimate of 1.5% for the total American pool of living transplanted

kidney patients. In recognition of the importance of this estimate, the valuation section includes a

sensitivity analysis on this input variable.

Dosage

The required daily dosage for immunosuppressive patients is individual and varies significantly

from patient to patient. Individual dosing is therefore based on clinical blood level monitoring and

adjustments until the correct blood levels are achieved. It is of great importance that the correct

dosage is found as fast as possible, as a too low dose makes the body reject the transplanted organ,

whereas too high doses completely shuts down the immune system.

                                                                                                               9 1,1% = (16,485/14,780)^(1/10)-1

!"#$%&!'(!)*&+#%%!,-./&0!"+#/12%#/3!4526%#3-5/!7899

4526%#3-5/ :&!/5*5!3+#/12%#/31

!" #$%&%#% #'&($)*+,-./ #($&%01 #(&10)234 #1%&$($ #$&)$)5-678 %('&'09 :9&0'$

!"#$%&'()**+',,---./0"*&%)1/23.%"4,511,6$"5#%*0718&9&:"+4&1*,((((((((((((((((;"%:"0+"$/1,744#1"0#++$&00/"1<3$2&*.30+=

 

       

52  

The average daily dosage of tacrolimus is between 0.075 mg/kg and 0,2 mg/kg (Appendix 11).

When looking at the table in Appendix 11, it can be seen, that the average daily dosage starts high

and declines rather quickly within the first year. This justifies an average daily dosage in the lower

end of the range, which is also consistent with the immense focus on lowest possible dose due to

avoidance of side effects. 0.1 mg/kg is set as the average daily dosage per patient. According to

the Centers for Disease Control and Prevention, the average American male and female weights

88.9 kg and 75.6 kg respectively (Appendix 12) (cdc.gov). Combined this gives the average

American person a weight of 82.3 kg. As a minority of children undergo the same surgery, the

average weight is reduced to 80 kg. The average daily dosage of tacrolimus for American

transplant patients is thereby calculated to approx. 8 mg (Appendix 13).

For the R.O.W. the average weights are significant lower (See Appendix 12 for the estimated avg.

weights in EU and Japan). The average daily doses for Europe and Japan are estimated to 6.9 mg

and 5.8 mg respectively. Appendix 13 provides the calculations.

Based on the results from the clinical trials, LCP-Tacro has proved capable of lowering the daily

dosage with between 20-50% due to increased bioavailability. A decrease of 20% is set for the

DCF model, as this was the finding in the most recent and extensive phase III trial.

Price

The Unites States’ position as the world leader in biopharmaceutical innovation is founded on the

basis that the US does not impose price controls on prescriptive drugs (medicalprogressto-

day.com). This means, that the American consumers basically have been funding most of the costs

of the innovative drug development. The rise of the Internet has given these consumers awareness

and access to drugs in price-controlled countries. This have led to increased demand for policy-

makers to legalize import or impose price controls, which experts argue will undermine medical

innovation. The Centre for Medical Parasitology (CMP) are working on shifting the focus of the

debate to how the entire world benefits from the premium American consumers pay for drug

research and development. Hence, policymakers should focus on encourage other rich nations to

help bear the full costs of innovative drug development (medicalprogresstoday.com). If the US

follows the rest of the world and force price controls over the market, the likely outcome is

pharmacies packed with cheap generics and not much else – all over the world. Based on the

above discussion, it is difficult to predict how the drug pricing will develop in the US.

Before the generic competition entered in 2009, the yearly cost for immunosuppressive therapy

amounted to approximately $12,000-15,000 (Abecassis et al. 2006, p1445 & Medscape.com). The

 

       

53  

generic competition has significantly lowered the yearly cost; an overview of the current prices in

America is presented in table 10.

The price of Astagraf is expected to be close to $4 per mg. When Tacro subsequently hits the

shelves it is most likely to priced very close to the price of Astagraf. Hence, the price of LCP-

Tacro is forecasted to be $3.75 per mg. In doing so, Veloxis will be able to position itself as a

cheaper compound then Astagraf, as the required daily dosage per patient (as mentioned) is likely

to be at least 20% lower with Tacro.

The $3.75 per mg corresponds to an average yearly price in the US of DKK 49.340, which is

actually slightly lower than the current price of Prograf. The average yearly prices in Europe and

Japan are considerably lower (EU DKK 39.431, JPN DKK 33.214). The reasons for these

differences are lower prices per mg, and lower dosage requirements per patient. See appendix 14

for an overview of the detailed assumptions concerning the price forecasts for Tacro in each

market (2013 prices).

Market development

The overall tacrolimus sales showed strong progress in the years leading up to patent expiration in

2009 (2006-2008). See appendix 15 for a graphical presentation.

• CAGR, United States=7,9%

• CAGR, Europe=14%

• CAGR, Asia/Australia=17,9%

This development consequently slowed as the cheaper generics entered the market in 2009 and

2010. As generics captured more and more market share the development turned slightly negative,

as more patients were switching to the cheaper products and thereby reducing the total pie. The

launch of the brand Astagraf, and possibly Tacro, is expected to turn the current development and

show a positive development in the total sale of tacrolimus.

!"#$%&'() &!"*+,$-./0&1+-*%&1%+&'.2&1-$$&3456&3708-."8%9&":2&;%"+$;&<+-*%0&"+%&-=&>('?&<+-*%06

!"#$"%& '()("*+, -./%$"%&012%)%.%3!4%"5%+6+4(+7("8+#5 9:8;;<=8>; 9?8>@<:8>= 9=8:A<@8;B 1?BB0C*DD,3(."E$,(%"+48+#5 9:8;F<=8>A 9?8F=<:8@G 1?BB0C*DD,3

-/$06(%"D60C"*+(0C("0C%H*()H0I*H40C"*+(09=8? !"#$"%& AB8;G@ !""-/$06(%"D60C"*+(0C("0C%H*()H0I*H40C"*+(09?8G '()("*+ :;8>B@ !""-/$06(%"D60C"*+(0C("0C%H*()H0I*H40C"*+(09@8B -./%$"%&012%)%.%3 >A8FGA !""

J,H*5%H(.0%/$806(%"D60C"*+(0C("0C%H*()H0I*H40C"*+(0#&09=8FA K2!<L%+"# @;8=@B !""

!"#$%&'()*+$,+%-%*&%.&$/%",(0(&1$#23&+$%*/%",

 

       

54  

The overall immunosuppression market showed a more controlled growth with a CAGR of 1,8%

from USD 5.3 b in 2005 till USD 5.8 b in 2010 (Appendix 24). The compound annual growth rate

is forecasted to around 2% during 2010 through 2020 (William J. Polvino, CEO of Veloxis

(dddmag.com)).

Market share

This paper takes the approach of only focusing on the market for tacrolimus. Hence, all attention

is on how much market share LCP-Tacro can conquer form Prograf, the generic versions and

Astagraf. Exactly how large a share of this market Tacro is capable of winning is very difficult to

forecast, and this estimate is therefore associate with a high degree of uncertainty, why it is also

treated in the sensitivity analysis. Veloxis estimate that Tacro will be able to peak at 20-25%

market share of the current pool of American tacrolimus patients, with further projections of an

ability to win 24-35% of de novo patients (Appendix 16).

If Tacro is able to achieve best-in-class status, these projections are by no means unrealistic, as

this status alone will yield significant market share. Further, the status is likely to ensure that the

healthcare sector and insurance companies will support the Tacro patients with considerable

subsidies, which is considered very significant for the future sale of Tacro. If they choose not to

do so, it is likely to have a devastating effect on the sale, why this is considered one of the most

important uncertainties.

The clinical results showing significantly higher bioavailability compared to the competing

products, is likely to turn many physicians in favour of Tacro, as a lower dose of tacrolimus would

be in everyone’s best interest. Further the lower daily dosage required would, if Tacro is priced in

the range of Prograf and Astagraf, mean a lower daily price for the patients (as illustrated earlier).

On the negative side; Veloxis is to compete with the world leader and the most experienced

company in the immunosuppressive industry, which, as illustrated in the competitor analysis

section, is financially in a completely different league than Veloxis; Astagraf will be the first-to-

market once-daily-dosage compound; since 2009 tacrolimus users have been switching to cheaper

generic compounds, hence getting used to cheaper prices; Veloxis has no experience when it

comes to commercialisation; They are planning to launch Tacro with a small sales force of 20

sales representatives (Appendix 10), which might not prove enough. That being said, it is worth

remembering that Novo Nordisk and Lundbeck hold more than 85% of the ownership of Veloxis –

thus, strong and experienced pharmaceutical companies ‘own’ Veloxis.

 

       

55  

The pros clearly indicate, that Tacro holds a potential, making it capable of winning significant

market shares. On the other hand, it is at the time obvious that Veloxis are facing a range of

challenges.

Based on the above discussion and the strategic analysis, the author believes, Veloxis’ projections

of acquiring 20-25% could prove an overly optimistic scenario. Especially the fact that the current

pool of patients is getting used to the cheaper generic prices is viewed as a huge threat for the sales

potential of Tacro. A more reasonable, and perhaps a bit conservative, base case estimate is that

Tacro’s market share potential lies in the range of 10-15%. Hence, the input for the standard DCF

model is 12.5% market share in the US.

The European market is a more complex market than the American. There are a variety of laws,

regulations and subsidy policies to take into consideration in the commercialisation process. As

Tacro is getting launched through their strong strategic partner, the Italian, Chiesi Farmaceutici

S.P.A., it expected they hold the financial power required to penetrate the European market.

Hence, 12.5% market share in the European market is considered a reasonable estimate. The

Japanese market is Astella’s home market, and thus considered a tough market to penetrate.

Provided Veloxis find a strong strategic partner to handle the launch, an estimated 10% market

share is forecasted.

In recognition of the market share’s immense impact on the total value, this variable is included in

the sensitivity analysis in the valuation section.

Margin

Tacro is believed to be a high-margin product, as Tacro, as mentioned, is going to be taken to

market by a small sales force of 20 representatives and is build on the simple MeltDose technolo-

gy, which means that the production of the pills is considered to be performed at a relatively low

cost. A conservative estimate of a 50% margin of is chosen for the DCF model. As this estimate

could prove to be overly conservative, it is also includet in the sensitivity analysis.

Royalties

As LCP-Tacro is going to be launched through partners in the R.O.W., it is relevant to investigate

likely royalty rates. The royalty rates for the valuation are based on the findings from the report

BioPharmaceutical Rayalty Rates & Deal Terms Report from 2008. As Tacro has completed all

clinical stages and the DCF forecasted revenues in Europe are in excess of USD 100 m, the

royalties are expected to be around 15%. The possible revenues in Japan are significantly lower

 

       

56  

why a royalty rate of 12.5% is chosen. Appendix 17 presents the empirical evidence the estima-

tions are based upon.

6.2.2 Technological risks As LCP-Tacro recently successfully completed the phase III trials, the technological risks have

almost cleared, The technological risk within each clinical trial is considered to have been lower

than what is normal for the industry, as Veloxis are using their proprietary MeltDose technology

to improve already approved drugs.

The most important technological risk facing Veloxis at this point is the FDA decision of whether

or not to approve Tacro for the American market. The average FDA approval rate is 71% (figure

1, p15). It is considered, that the likelihood of FDA approval is significantly higher for Tacro than

this average percentage. Tacro is, as mentioned, an improved version of the already FDA

approved tacrolimus compound. Further the results of the clinical trials proved that Tacro as a

minimum keeps the current standards regarding safety and efficiency (Tables 4 and 5). Further the

results, as mentioned, suggest some relevant improvements regarding bioavailability, dosage and

different side effects. Finally the fact that Astagraf was approved earlier this year, increase the

probability of Tacro approval, as Tacro outperformed Astagraf in a direct comparison study

(Appendix 8). The probability of FDA approval is therefore estimated to be 90% for LCP-Tacro.

The likely approval rates for the other markets are also set to 90%, as the requirements are very

similar.

As mentioned, it is very important that Tacro will be approved as a best-in-class compound, and

thereby accepted as a subsidies granted compound. Without this feature the majority of the

patients cannot afford to switch to Tacro, and there will be patients who will be reluctant to do so,

as they have become accustomed to the lower generic prices. Based on the clinical trial results,

presented in section 6.1.5, and a reasonable assumption that the best treatment option available,

despite costly, will be the preferred choice, it seems plausible that Tacro will be granted best in-

class under the current conditions. Thus, the likelihood of being granted best-in-class is estimated

to 75% in all markets.

The cumulative probabilities used to risk adjust the NPV for Tacro in the United States, Europe

and Japan respectively are 68%10, 68%11 and 22%12 respectively. The low percentage for Japan is

caused by the uncertainties associated with finding a strategic partner.

                                                                                                               10 Est NDA approval rate*Est. US subsidies probability: 90%*75%=68% 11 Est. MAA approval rate*Est. EU subsidies probability: 90%*75%=68% 12 Est. JPN approval rate*Est. JPN subsidies probability*Partner: 90%*75%*33,3%=22%  

 

       

57  

6.3 Step 3: Veloxis’ Cost of Capital For the purpose of estimating the risk free rate it is considered customary among Danish practi-

tioners to apply a 10-year Danish government bond as a proxy. Koller, as mentioned, suggests the

use of the 10-year German Eurobond for the purpose, as these bonds have higher liquidity and

lower credit risk than bonds of other European countries (Koller et al. 2010, p241). That being

said, it is the author’s opinion that the difference in liquidity and credit risks between the two is

insignificant, as the Danish government bond is exposed to a very low amount of both. By

selecting the Danish government bond inflation is treated consistently, as this achieves the same

denomination between the CF’s (DKK) and the discount rate. Thus, the Danish 10-year govern-

ment bond is chosen as proxy for the risk free rate. The risk free rate is estimated to 1,41%

(appendix 18).

When estimating beta, Koller recommends using monthly returns, as using daily or weekly returns

will lead to systematic biases. Further, the estimation should be based on at least 60 data points,

which is equivalent to 5 years of monthly returns. And finally, it is important that the company

stock return is regressed against a value-weighted and well-diversified portfolio (Koller p250).

Not all agree with this approach. E.g. the service provider Bloomberg uses 2 years of weekly when

estimating raw betas (Koller p251).

As Veloxis’ share is not traded on all trading days, Koller’s suggested approach of using monthly

data is considered best suited for estimating the beta of Veloxis.

The returns of Veloxis’ share and S&P 500 are used as inputs in the regression analysis. The

regression results can be found in appendix 19. The result of the 5 year monthly data regression is

a beta of 0.702, with an R-squared of 7.9%. Because of the relatively low coefficient of determina-

tion, the applied beta is a weighted average of other analyst’s estimates and own estimate. Table

11 below, presents the different estimates and the weighted average estimate.

The relatively low beta of 0.86 does not mean that Veloxis is a low-risk company. Investors are

not compensated for firm specific risks, as these are fully diversifiable in large portfolios. Hence,

!"#$%&''( )%$*+,-.&/%0"

!"#$%&'()*'%$+,-.%*/&$01$)0#'23.$4*'*5 6786920)&0#$:%;'%/& 67<= +>;?$@6A=5B*C/0*D(&$E#C 6788 +F;3$@6A=5G*)*40/*# A76H +F*#$@6A=5>I%/*?% 1234

!"#$%&'()$#*&$'+%",-),.%$"./0'+%",-)1.,.2"$.3)43503&

 

       

58  

the beta is a measure of the systematic risk, and thereby solely measures how sensitive Veloxis is

to fluctuations in the market.

Koller believes that the market risk premium (Rm-Rf) varies continuously between 4.5-5.5%

(Koller p242), and many practitioners use a constant historical market risk premium (Jyske bank

article, p13). But as the author, in line with Rune Møller, is of the opinion that the investors’ risk-

aversion changes over time, using a historical risk premium is not preferable under the current

market conditions (Møller, R. 2010: Estimation af danske aktiers risikopræmie). When the market

is performing well and has done so for a while investors are likely to forget about the risk. Thus,

when the market is performing well, no investor wants to be on the sideline, while they flee when

the market is under pressure (Jyske bank article, p13). A paper from Barberis et al. in 2001

supports the shifting risk-aversion theory: “After a run-up in stock prices, our agent is less risk

averse because those gains will cushion any subsequent less. After a fall in stock prices, he

becomes more wary of further losses and hence more risk averse” (Barberis et al. 2001, p3).

Under the current market conditions, it is the author’s opinion, that the market risk premium

deviates from the range suggested by Koller, as the investors are more risk-averse, and thereby

require a higher rate of return if they are to invest in stocks, which is also reflected in the

extremely low current yields on government bonds. Therefore, the market risk premium is in need

of an additional premium. This kind of upward adjustment is in line with current market practice,

according to PWC’s annual cost of capital survey among Danish companies (2011). In their

survey two thirds of the respondents add an additional premium to the cost of capital as a result of

the current financial situation (PWC 2011, p4). Unfortunately the survey does not offer any

consensus regarding the size of the additional premium.

In the paper Macroeconomic Crises Since 1870 by Barro and Ursua (2008), they investigate

historical equity risk premiums under financial crisis situations. An average equity risk premium

of 7% based on 15 OECD countries was estimated during crisis situations. Damadoran calculates

the European equity risk premium to be 7.89% as of Jan. 2013 (Damadoran Online). Based on the

above discussion an additional premium of 2% is added to the average of Koller’s historical

premium (5%). Thus, a market risk premium of 7% is applied for the calculation of Veloxis’ cost

of capital.

The above results lead to a cost of capital of 7.47%. The calculation is presented below.

!!!"#$%&'$%()!(*!+,-(.%#/!0(#$!(*!0'1$%'-

!"#$%&'()*+(%"+,$-.#,-"+

!!!"!! !!!"# ! !" ! !!!"#!

 

       

59  

As the cost of capital has a huge impact on the final value of the project, the sensitivity analysis

includes an analysis of the impact of alternative discount rates.

6.4 Step 4: The Tacro DCF Models The DCF models are built on the estimates and forecasts obtained in step 2 and 3. As the product

life cycle of drugs are very dependent on patent protection, it is chosen to model the entire life of

Tacro explicit. The wide-ranging budgeted period is naturally associated with a significant amount

of uncertainty. Even so, this is considered the preferred choice, as the sale is expected to decline

quickly after patent expiry (section 3.4.4), making the calculation of a continuing value inappro-

priate.

The development of the sales throughout the forecasting period is estimated based on the

empirical findings regarding the PLC of drug compounds presented in section 3.4.4.

The risk adjusted NPV for Tacro in the US market is calculated to DKK 1.384m. For the

European market the NPV of the royalty payments are estimated to DKK 315m, and for Japan the

NPV is DKK -19.5m.

The risk adjusted NPV is, as previously described, calculated as PV for the CF’s multiplied by the

cumulative probability of success, less the PV of the NDA filing and launch-associated costs.

Appendix 20 presents the DCF models for Tacro.

6.5 Step 5: Volatility of Tacro Before calculating the real option value of the projects, the standard deviation of the static NPV

needs to be estimated.

In order to estimate the different volatilities, the static DCF models needs a few adjustments. For a

view of the Crystal Ball sheets see appendix 4.

The input variables/uncertainties chosen for the simulation are patients, prices, and variable costs.

These are chosen as they represent the greatest uncertainties regarding the future performance of

the product (Copeland 2003, p244). For the European market and Japan, variable costs are

substituted with royalties, as Veloxis will not be launching Tacro in these markets. A distribution,

expected mean, and standard deviation is selected or estimated for each uncertainty.

Prices and patients are considered to follow a lognormal distribution, as these intuitively never go

negative. Royalties are estimated to follow a triangular distribution around the lower and upper

possible rate. The expected means are the CF’s from the static DCF, and the standard deviations of

the input variables are calculated from formula 10 on p29.

 

       

60  

The following assumptions were made: Prices are 90% autocorrelated, which is in line with

Copeland’s prediction (p248). The reasoning behind is that a very high price one year is unlikely

to be followed by a low price the next. The number of patients is assumed to be -0.1 negatively

correlated with price, as price increases is likely to encourage patients to switch to the cheaper

generic products. And finally variable costs are presumed to be 0.65 correlated with number of

patients, as more customers clearly increase variable costs. For the other markets; royalties are

assumed to be 0,75 correlated with the number of patients – more patients on Tacro will increase

the royalties. The outputs from the Monte Carlo Simulations are presented in Appendix 5. The

results are volatilities of 68.5% for the US, 67% for the European market, and 72.2% for Japan.

Karl Keegan finds that the volatility of biotech projects varies between 20 and 80%. Thus, the

estimates of Tacro are in line with his findings (Karl D. Keegan 2008, s. 135).

6.6 Step 6: Tacro ROA With the volatility estimates in place, the up and down factor for the binomial lattice can be

calculated through formula 6 on page 23. Starting with the static NPV of the projects, the

developments of the underlying asset values (the project) are calculated through the up and down

factors.

Next the risk neutral probabilities are calculated (via formula 8), and used for calculating the real

option values through backward induction. The binomial lattices and the option calculation are

presented in appendix 6.

The estimated option values are DKK 79.6m for the US, DKK 0 for Europe, and DKK 28.2m for

Japan.

That the US option value does not contribute a larger share is not surprising. The product is close

to point of launch, consequently, the timeframe of the option is short, and the remaining uncertain-

ty limited.

That there is no option value for the European project is also no surprise. All the costs associated

with the project, form the view point of Veloxis, have been paid and the MAA filing has been

handed to the EMA. Further, there are no macroeconomic states in which the value of the static

NPV is negative. Thus, there are no points in the model where it would be advisable not to

proceed.

The Japanese marked is an interesting case. The risk adjusted NPV is, as mentioned, DKK -19.5m.

The option value of DKK 28.2m changes the total value of the project to DKK 8.7m. The large

 

       

61  

uncertainty regarding the prospect of finding a partner contributes to the option value, as the

payment regarding a possible new drug application is dependent on finding a partner.

The values of these options are, as explained earlier, dependent on the management being capable

of making rational decisions. There is nothing in the strategic analysis suggesting the management

of Veloxis is incapable of doing so.

6.7 Valuation of Veloxis The value of Veloxis is calculated as the value of LCP-Tacro added the current amount of cash

and cash equivalents and the risk adjusted PV of their deferred tax asset, deducted the estimated

amount of future indirect costs and financial liabilities. Table 12 presents the calculations.

The future indirect costs are estimated via formula 12. The indirect costs of DKK 32.3m from

2012 are used as a proxy for future expenses.

In the 2012 annual report, Veloxis write off the value of their deferred tax asset (DKK 401.4 m).

This is common accounting practice in industries like the biotech industry, where future revenues

!"#$%&'()*+ ,-./$'./"0("1(!%.%#2(304/#25.(6"-.-

!"#$%&'()$*+,&-(&.(*,/(01123(4567

!"#!"#!!"#$%&'(!!"#$# ! !"#$%&'(!!"#$#!!! ! !!! !!!!"## ! !"#$%&!'"! ! !"!!"" ! !!! !!"!

!!!!"#! !!!"#! ! !"!!!"#!!

!"#$%&'()&&&*"$+",-./&.0&*%$.1-234.5+6, 7"48%, 39"2% :,",-6&;3* <=,-./&*"$+% !.,"$&*"$+% :,.68&34-6%

!"#$%&'() *+, -.,/012134 567689 9:8; 5<;686 =877

>?()@& A,,/012BC 65D8= =8= 65D8= =85:

E&@&3 -BBC/@&(F3B( $5:8D G78G 789 =8=5

HB3)421CB -I, -I, -I, -I,

%)F&2/J&2?B/)0/!"#$%&'() 5;9:8G 5=987 59798= 58=7

//$/K3C1(B'F/')LFL $<9685 $=8G:

>M?1FN/O&2?B '>'>?@ =89:

//P/H13&3'1&2/,LLBFL

"&LQ <G=8D =8GD

O&2?B/)0/%&R/,LLBF G9G8: =85;

//$/H13&3'1&2/!1&S121F1BL

!)34$FB(T/.BSF = =

+Q)(F$FB(T/.BSF $::8D $=8=;

A&(UBF/O&2?B/V.WWTX 585DY?FLF&3C134/LQ&(BL/VTX 5Z;D:!"#$%&'()*+(%"+,$-.#,-"+

 

       

62  

are associated with a significant amount of risk. However, it is the author’s opinion that this asset

should be including in a corporate valuation. The value of the tax asset is dependent on Tacro

succeed. Hence, it is adjusted with the cumulative probability of Tacro being launched in the

American market. See appendix 21 for the adjustment.

6.7.1 Sensitivity Analysis

In recognition of the significant amount of uncertainty regarding the forecasted estimates applied

in the valuation, this section serves to investigate the impact of alternative estimates.

The market share estimate is considered among the most important input estimates. Thus, the

above table presents a sensitivity analysis of the impact of changing Veloxis’ market share, along

with impact of different growth rates for the total pool of kidney transplant patient.

It is worth noticing, that with a market share of 5%, the valuation, DKK 0.57 corresponds to the

current market valuation (DKK 0.58). Further, if Veloxis’ manage to win their forecasted 20%

market share, this would suggest a stock price of DKK 1.74, or triple the current share price.

The estimate of a 50% margin for Tacro is, as described in the paper, considered a conservative

estimate. Table 14 suggests, that increasing the margin with 10% points would increase the value

!"#$%&'()&*"+,%-&./"+%0&1234&5"-6%7-8

91:&!";+<&=. >?@A 'B?>A B@?@A BC?>A (>?@A DB?>A@?>A !"# $"#% "$&$ '(!! '#$) !&#(

1234& '?>A !#! $!)'*' "!'+ '!(& !'%( +'+"5"-6%7-8 B?>A +)& $)!% "&'( '%$' !%#+ +#&%

(?>A )!% $%+' '(+% !")! +!&( ))&+D?>A &'% "(%$ '!"! !&)& )$(# &!+"

1<++%85<7E67F&./"+%&5+6;%>A 'B?>@A B@A BC?>@A (>A DB?>@A

@?>A (*+' $*(+ $*+% "*$ "*)' '*$+'?>A (*+& $*$+ $*&! "*'" "*#$ '*!#B?>A (*)$ $*") $*#$ "*+& '*"" '*%&(?>A (*)) $*'% "*$$ "*%! '*+) !*"#D?>A (*&$ $*+" "*'' '*$! '*#+ !*&)

*"+,%-&./"+%

!"#$%&'()&*+,-%./"+0,1

23*&!"-+4&56 789:; 78':; :; 7<':; 7<9:;(:; !!" #"#" ##$% #&'% #$%%=:; ##$% #$"# #('$)$ #'&* #+!+

/"+0,1 >:; #$%% #*%$ #+!+ #%!& &#+'?:; #'*! #!!* &### &$$! &*'*@:; #%#+ &#+' &($* &'%* &%*(

34++%AB41C,10&6D"+%&B+,-%789:; 78':; :; 7<':; 7<9:;

(:; ")! ")!! ")%* #)"$ #)##=:; ")%* #)"* #)#* #)&* #)$*>:; #)## #)&$ #)$* #)(' #)*!?:; #)&+ #)( #)*( #)'! #)!#@:; #)(& #)*! #)+( #)!% &)"*

*+,-%

 

       

63  

of Veloxis approx. DKK 0.20. The table also visualises the impact of changing different prices of

Tacro.

As the majority of Veloxis’ value comes from the standard DCF model, the discount rate is an

important factor. As can be seen in table 15, even with a discount rate of 15%, the stock price is

worth more than the current market price (DKK 0.66 > DKK 0.58).

The impact of changing the estimates of the technological risks is presented in table 16. By

changing these with -15% points to +10% points, a corresponding valuation range of DKK 0.86-

1.38 appears.

As mentioned in the thesis, the practitioners generally regard the estimation of the volatility

estimate as the most difficult task when valuing real options. Table 17 provides the information,

that in the US Tacro case, the volatility estimate contributes with an almost insignificant impact on

the value of the project.

7. Discussion of Results

Based solely on the results obtained in the DCF model, the Japanese market is not worthy of any

considerations (DKK -19.5 m). But when including ROA (DKK 28.2 m) the situation changes.

!"#$%&'()&*+,,-./01"23%&4"5%6,7&!"048&9:

!"#!$ %"#!$ &"#!$ '"#!$ ()"#!$ (("#!$ (*"))$#"!+ (,'' ((%! ()!* '!* &%* %'# *!!*"(+ (#*! (+,) (('% ()&! '&% &'% !#+

./01&4"5% *"!+ (!(# (#!+"+ (+,' (,)% ()'& ())) %,)!"(+ (%%( (!)% (#!) (+,& (,() ((), %'&!"!+ (',& (%*( (*', (#*) (+,( (,)* &%*

,844%;<82=>23&:1"4%&<4>0%!"#!$ %"#!$ &"#!$ '"#!$ ()"#!$ (("#!$ (*"))$

#"!+ (")* )"'& )"'( )"&* )"&) )"%* )"!(*"(+ ("(* (")! )"'' )"', )"&! )"&( )"!!*"!+ (",# ("(* (")% (")) )"'+ )"&% )"%!"(+ ("++ (",# ("(* (")% (")) )"'+ )"%*!"!+ ("#+ ("+, (",+ ("(# (")! )"'' )"&)

*+,,

!"#$%&'()&!%*+,-$-./*"$&0/1213%4*%,5".%&3-/,51 !"#$% !"#&% !"$% & !'$% !'#&%678&"994-:"$ !"# $%# $"# &%# &"# '%%#;<#1/=>&94-#? (%# ("# !%# !"# $%# $"#@"$<%&!"*4-&AB;C &!( '')! ')&% '*(+,+ '(*$ '$*+;5-*2&34/*% %,$( %,&" ',%" ','" ',)( ',+$

!"#$%&'()&*+$",-$-,./01&!"23+*+$",-$-,. '4 567894 :994*"$;% !"#$ !"#$%$ !&'$<,+2=&13-2% !%!& !%!& !%!(

 

       

64  

Adding the ROA turns the value from the Japanese market positive, and thereby justifies a

continuing effort regarding finding a strategic partner. This example illustrates the strength of

ROA, and shows that excluding the value of managerial flexibility might lead to the rejection of

valuable projects.

The sensitivity analysis demonstrates that valuation of Veloxis is very sensitive toward changes in

the input variables. But simultaneously it proves, that it takes a lot of change before the value gets

below the market valuation.

On August 1st 2013, the Veloxis’ share traded at DKK 0.58, which is significantly lower than the,

in this thesis, estimated value of DKK 1.15 per share. The current cash and cash equivalents

combined with the risk-adjusted value of the deferred tax asset amounts to a value of DKK 0.36

per share. Thus, investors implicitly assign Tacro a value of approx. DKK 0.16 per share13. When

considering this implicit market valuation of Tacro in relation to the results and calculations

presented in the thesis, it is the author’s opinion, that the market significantly undervalues the

market potential of the project.

Table 18 presents the result (in price per share) from the paper, the market value of the company,

and Danske Market’s target price as of Jun 28th 2013.

Danske Market maintains a hold rating on the stock, as they are concerned about the US market

potential. The author, as presented in the paper (e.g. in the SWOT analysis), identified a range of

obstacles regarding the prospect of penetrating the American market. These obstacles resulted in,

considered by the author, rather conservative estimates for a likely ‘best-in-class’ drug compound,

e.g. the market share estimations (12.5% in the US market).

Even with these moderate estimates a stock price of DKK 1.15 is projected, which is nearly twice

the current market value. In the opinion of the author also the target price of Danske Market

                                                                                                               13  DKK 0.58-0.36-0.06=DKK 0.16  

!"#$%&'() *+,-"./0+1&+2&3%04$50

6"5%78".%&9./:%& !"#$%&'(%)*&+, -..%*/01%

;<1&=05/,"5% !"#$%&'(%)*&+, -..%&/&0!".>%5&9./:%

6"10?%&@".?%50 !2#3%)1(4%)*&+, -..%*/1*

!"#$%&'()*+,)%",-$./#-.",0)1#$".,2'-"$345

 

       

65  

underestimates the value of Veloxis. Hence, the current fair value is considered to be closer to the

estimated value of DKK 1.01, and it is considered more likely to be higher than lower.

The fact that the two largest shareholders, the large pharmaceutical companies Novo Nordisk and

Luncbeck, in the recent share issue bought more than 95% of the shares, proves that they have

confidence in the market potential of Tacro (Company announcement Nov 2012).

This being said, one should not forget that investing in Veloxis is associated with a significant

amount of risk. In a going concern perspective the life of Veloxis is completely dependent on the

success of Tacro. But for investors holding a large well-diversified portfolio the stock is consid-

ered a very attractive addition.

8. Conclusion

The biotech industry holds a variety of distinct characteristics. Including long periods without

revenue, dependence on patent protection, significant technological risk, a phased development

process, strict drug approval regulations, and a PLC that traditionally decrease drastically briefly

after patent expiry. Hence, it is preferable to forecast the entire life of the compound, as the sales

never reach a steady state, and therefore calculating a continuing value is inappropriate.

The biotech drug developing industry is associated with a high degree of uncertainty, and at the

same time the management has to make a number of stop/continue decisions along the way,

providing them with a significant amount of flexibility. The standard DCF model does not include

the upside of risk and the value of flexibility, why the inclusion of ROA is necessary when valuing

biotech projects.

The value of flexibility can be incorporate through DTA or ROA. DTA is based on subjective

probability assessments, and is further inconsistent, as it violates it violates the law of one price.

ROA is capable of handling the law of one price by applying portfolio replication theory or risk-

neutral probabilities. Risk-neutral probabilities are advised in this paper, as they are considered

easier to apply in practice.

Based on existing theories and empirical findings a 6-step framework for valuing biotech R&D

drug projects was developed:

1) The first step is to perform a comprehensive strategic analysis, including an external analysis

performed from both a macro and micro perspective, and an internal analysis.

2) Next the information gathered in step 1 along with empirical estimates is used to estimate the

relevant inputs for the DCF model.

3) Before setting up the DCF model the project specific discount rate needs to be estimated.

 

       

66  

4) Now the standard DCF model is created based on the information acquired in the previous

steps.

5) The next step of estimating the volatility of the underlying project is considered the most

challenging in the application of ROA. The use of Monte Carlo simulation is advised for the

purpose.

6) The sixth and final step is to calculate the value of the real options associated with the biotech

project. The author, in line with Shockley, advises the use of the binomial lattice, as this approach,

despite Copeland and Kodukula’s conflicting opinions, is capable of handling two sources of

uncertainty.

Veloxis is not a traditional biotech company, as it through its patented technology platform,

MeltDose, follow a strategy of developing improved versions of already commercialised patent

expired compounds. Thus, the technological risks encountered by Veloxis are significantly lower

than the industry averages.

The value of Veloxis is calculated as the estimated value of Tacro, added cash and cash equiva-

lents and the value of the risk adjusted deferred tax asset, subtracted the estimated future indirect

costs and their financial liabilities. The total value of Veloxis is estimated to DKK 1,908m of

which the ROA accounts for DKK 108m. Hence, ROA does not contribute with an extensive

amount, but enough to justify its application. Further, ROA justifies an effort for finding a

strategic partner to commercialise Tacro in the Japanese market.

The estimated value of Veloxis translates to a stock price of DKK 1.15, which is approx. twice the

current market price of DKK 0.58. It is also significantly higher than Danske Market’s target price

of DKK 0.80. The fierce competition in the US market, the recent NDA approval of Astagraf, and

Veloxis’ commercial inexperience are considered the main determinants for the low market value.

The estimated value of Veloxis is, in the eyes of the author, based on number of conservative

estimates, why the fair value of Veloxis is considered to be significantly higher than the current

market valuation. Even so, it needs to emphasised that investing in Veloxis is associated with a

significant amount of risk. If Tacro’s NDA gets declined by the FDA, Veloxis is history. Yet, for

investors holding a well-diversified portfolio, Veloxis could prove a very interesting addition to

their portfolio.

 

       

67  

References

Books:

• Koller, T., Goedhard, M., Wessels, D., 2010: Valuation – Measuring and Managing the Value

of Companies. Fifth Edition, Wiley

• Schack, B., 2009: Regnskabsanalyse og virksomhedsbedømmelse. Third Edition, Jurist- og

Økonomiforbundets Forslag

• Berk, J., DeMarzo, P., 2010: Corporate Finance. Second Edition, Pearson

• Verbeek, M., 2008: A Guide to Modern Econometrics. Third Edition, Wiley

• Porter, M. E., 1985: Competitive Strategy – Creating and Sustaining Superior Performance

• Porter, M. E.., 1980: Competitive Strategy – Techniques for Analyzing Industries and

Competitors

• Smit, H. T. J.,Trigeorgis, L., 2004: Strategic Investment – Real Options and Games, Princeton

• Copeland, T., Antikarov, V., 2003: Real Options: A Practitioner’s Guide, Thomson Texere

• Shockley, R. L., 2007: Real Options Valuation, Thomson South-Western

• Kodukula, P., Papudesu, C. 2006: Project Valuation Using Real Options: A Practitioner’s

Guide, FL: J. Ross Publishin

• Plenborg, T., Petersen, C. V., 2005: Regnskabsanalyse for beslutningstagere, Forlaget

Thomson

• Mun, J., 2006: Real Options Analysis: Tools and Techniques for Valuing Strategic Invest-

ments and Decision, Wiley & Sons

Annual and Interim Reports

• Veloxis Pharmaceuticals A/S Annual Reports 2007-2012

• Veloxis Pharmaceuticals A/S Interim Reports 2010-2013

• Astellas Pharma Inc. Annual Reports 2010-2012

• Santarus Inc. Annual Report 2012

• Dr. Reddy’s Labs. Ltd Annual Report 2012

• Neoral Annual Report 2012

Veloxis Presentations

• Company Announcement Nov 2012

 

       

68  

• Company Announcement May 21st 2013

• Company Presentation Feb 14th 2012

• Company Announcement no.9 2011

• Investor Presentation Q1 2008

• Study Presentation May 20th 2013

• Study Presentation June 27th 2013

• Investor Presentation Mar 3rd 2009

Web Pages

• http://www.evaluategroup.com/

• sciencebasedmedicine.org/what-does-a-new-drug-cost/

• veloxis.com

• meltdose.com/protection.cfm

• emedicine.medscape.com/article/1013392#a30

• isotechnika.com/dnn/ProductsInDevelopment/Voclosporin/ImmunosupressionMarket.aspx

• dddmag.com/articles/2012/02challenges-and-solutions-immunosuppressant-therapy

• ncbi.nlm.nih.gov/pmc/articles/PMC2994095

• optn.transplant.hrsa.gov

• bidmc.org/Centers-and-Departments/Departments/Transplant-Institute/Kidney/The-Benefits-

of-Transplant-versus-Dialysis.aspx (bidmc.org)

• drugs.com/availability/generic-prograf.html

• accord-healthcare.eu/company-facts

• thefreelibra-

ry.com/30,000+Renal+Transplants+Were+Performed+in+2005,+Increasing+to+43,000...-

a0144392207

• cdc.gov/nchs/fastats/bodymeas.htm (cdc.gov)

• medicalprogresstoday.com/drug-importation-and-price-controls/ (medicalprogresstoday.com)

• medscape.com/viewarticle/734143 (medscape.com)

• dddmag.com/articles/2012/02/challenges-and-solutions-immunosuppressant-therapy

(dddmag.com)

• Euroinvestor.dk

• Finance.yahoo.com

 

       

69  

• Damadoran-online

• ft.dk/sampling/20121/lovforslag/L218/index.htm

• medicinenet.com/tacrolimus/article.htm

• rxlist.com/prograf-drug/indications-dosage.htm

• lesi.org/docs/lesi-updates-and-news-

documents/f2008biopharmaceauticalroyaltyratedealterms-110108.pd

• nasdaqomxnordic.com/obligationer

• dst.dk

• isotechnika.com/dnn/ProductsInDevelopment/Voclosporin/ImmunosuppressionMarket.aspx

Articles

• Block, S., 2007: Are ”Real Options” Actually used in the Real World, Engineering Econo-

mist, p255-267

• Langer, L. W. et al., AktieUgeBrevet, Nr. 12, April 1st 2012. 10th Year

• Barberis, N., Huang, M., Santos, T., 2001: Prospect Theory and Asset Prices, The Quarterly

Journal of Economics, Vol. CXVI, Issue 1

• Walpole, S. C., Prieto-Merino, D., Edwards, P., Cleland, J., Stevens, G., Roberts, I, 2012: The

weight of nations: an estimation of adult human biomass, BMC Public Health

• Grabowski, H., Vernon, J., DiMasi, J. A., 2002: Returns on Research and Development for

1990s New Drug Introdructions, p11-29, Adis Internation Limited

• DiMasi, J. A., Hansen, R. W., Grabowski, H. G., 2002: The price of innovation: new esti-

mates of drug development costs, p151-185, Journal of Health Economics 22 (2003)

• DiMasi, J. A., Grabowski, H. G., 2007: The Cost of Biopharmaceutical R&D: Is Biotech

Different? P469-479, Wiley InterScience

• Valentin, F., Dahlgren, H., Jensen, R. L., 2006: Structure, Employment and Performance in

Biotech Firms: Comparison of Danish and Swedish Drug Dricovery Firms, Research Centre

on Biotech Business

• Light, D. W., Warburton, R., 2011: Demytholoqizing the high costs of pharmaceutical

research, BioSocieties

• Wapner, J., 2012: How Much Do Drug Companies Pay the FDA? PLOS/BLOGS (Wapner

2012)

 

       

70  

• Scholes, M., Black, F., 1973: The Pricing of Options and Corporate Liabilities, p637-654,

Chicago Journals

• Kellogg, D., Charnes, J. M., 2000: Using Real-Options Valuation Methods for a Biotechnolo-

gy Firm, Financial Analysts Journal, 2000

• Evans, R. W., Applegate, W. H., Briscoe, D. M., Cohen, D. J., Rorick, C. C., Murphy, B. T.,

Madsen, J. C., 2010: Cost-Related Immunosuppressive Medication Nonadherence Among

Kidney Transpland Recipients, Clin J Am Soc Nephtol, (Evans et al. 2010)

• Gulsun, T., Neslihan, R. N., Oner, L., 2009: Nanocrystal Technology For Oral Delivery of

Poorly Water-Soluble Drugs, p55-65, Fabad J. Pharm. Sci. 34, (Gulsun et al. 2009)

• Barro, R. J., Ursua, J. F., 2008: Macroeconomic Crises since 1870

• Abecassis, M. M., Seifeldin, R., Riordan, M. E., 2008:Patient Outcomes and Economics of

Once-Daily Tacrolimus in Renal Transplant Patients: Results of a Modeling Analysis, Else-

vier Inc.

• Møller, R., Jørgensen, A., 2010: Estimation af danske aktiers risikopræmie, Jyske Bank

Reports

• Martin, C., 2011: Generic Medications for Immunosuppresion – Where are we? University of

Minnesota Medical Center, Fairview

• GAO: New Drug Approval – FDA’s Consideration of Evidence from Certain Clinical Trials,

July 2010, United States Government Accountability Office (US Gao)

• Drug Discovery and Development: Understanding the R&D Process, February 2007,

PhRMA, innovation.org (DDD)

• King & Spalding: FDA Basics For Boitech Drugs, Biologics and Devices, Dvorah, A. R.

(FDA Basics)

• Patent Protection Strategies, By Peter Norman 2007, Business Insights Ldt. (Norman 2007)

• OECD Biotechnology Statistics 2009, By van Beuzekom, B., Arundel, A., 2009, OECD

• PricewaterhouseCoopers, 2011: Miniature Survey Regarding the Pricing of the Stock Market