The PAHO model for estimating the impact of changes in Intellectual Property Rights Joan Rovira,...
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The PAHO model for The PAHO model for estimating the impact of estimating the impact of changes in Intellectual changes in Intellectual Property Rights Property Rights Joan Rovira, Joan Rovira, Universitat de Barcelona Universitat de Barcelona Ismail Abbas Ismail Abbas , Universitat Politècnica de Catalunya , Universitat Politècnica de Catalunya
The PAHO model for estimating the impact of changes in Intellectual Property Rights Joan Rovira, Universitat de Barcelona Ismail Abbas, Universitat Politècnica
The PAHO model for estimating the impact of changes in
Intellectual Property Rights Joan Rovira, Universitat de Barcelona
Ismail Abbas, Universitat Politcnica de Catalunya
Slide 2
2 Content 1. Justification and objectives of the project 2.
Model specification and description 3. Illustrative results for
Colombia and Malaysia 4. Discussion Acknowledgement: This project
has been funded by the PAHO-WHO
Slide 3
3 Justification and objectives of the project
Slide 4
4 The changing environment of IPR regimes Global trends and
pressures towards an international upwards harmonization of IPR to
developed countries standards Regional agreements: Single European
Market-EU, NAFTA The TRIPS agreement Bilateral agreements National
implementation of agreements and other policies
Slide 5
5 The impact of changes in IPR regimes might affect, with
varying levels of uncertainty: Market exclusivity - competition
Prices Expenditure Consumption access health Foreign investment
Domestic production, employment Imports exports - balance of trade
R&D and innovation (global and domestic; general and on
country-specific diseases) Technology transfer
Slide 6
6 The timing of the impacts of changes in IPR provisions
Short-term Test data exclusivity Conditions for compulsory
licensing Date of enforcement, transitory periods ... Long term
(well all be dead, according to J M Keynes?) Duration of patent
(>20years) Scope of patentability ...
Slide 7
7 Information needs of decision-makers Decision-makers, such as
the negotiators of a trade agreement, must often consider and take
quick decisions on proposals related to IPR, which might have a
substantial impact on the future access to pharmaceuticals and,
ultimately, on the health status in their countries. Although it is
increasingly apparent to most developing countries negotiators that
stronger (TRIPS plus) patent protection is likely to have negative
net effects on drug accessibility and health status, trade
agreements often require trade-offs in a given sector in order to
obtain advantages (e.g. tariff reductions to agricultural exports)
in other sectors. If concessions have to be considered or made in a
given sector, it is important to be able to identify and quantify
as precisely as possible the future impact, in order to compare it
with the expected benefits from other sectors.
Slide 8
8 Objectives of the project To develop a user-friendly tool for
decision-makers that allows them to estimate the future impact of
changes in IPR and related pharmaceutical policies To collect the
required information, implement and test the model in several
countries (initially, Colombia, Costa Rica and Guatemala, later
Malaysia, Vietnam, India, ) To assess the information and knowledge
gaps and to propose an agenda for future research
Slide 9
9 Model specification and description
Slide 10
10 Development of a Model to Assess the Impact of Changes in
IPR Version: 17-11-2006 Development of a Model to Assess the Impact
of Changes in IPR Version: 17-11-2006 Content Justification and
objectives of the project. Introduction Literature review When to
evaluate the impact Options to evaluate How to evaluate the impact
Impact variables Presentation of the model of Impact of Changes in
the IPR Structure and general characteristics of the model of
Impact of Changes in the IPR Structure and general characteristics
of the model of Impact of Changes in the IPR Operation of the model
Translating IPR changes into model parameters Definition and
calculation of impacts Key assumptions of the model
Slide 11
11 Development of a Model to Assess the Impact of Changes in
IPR Version: 17-11-2006 Development of a Model to Assess the Impact
of Changes in IPR Version: 17-11-2006 Appendix 1: Model
Specification Appendix 2: Data required for the application of the
IPR Impact Model to a given country Appendix 3: Suggested Reporting
Format for Country Analysis Appendix 4: Abbreviated Users
manual
Slide 12
12 The PAHO IPR Impact Model A general model, not a country
application Deterministic (sensitivity analysis) Macroeconomic
(agreggated) Computer assisted simulation model (Excel)
Slide 13
13 The model estimates the impact of alternative scenarios on
pharmaceutical expenditure, consumption and market share of the
domestic industry over a defined time horizon. The baseline
scenario estimates the evolution of the variables under the
existing IPR rules. The alternative scenarios reflect the evolution
of the variables under other combinations of IPR rules that might
result from TRIPS enforcement, bilateral trade agreements or
autonomous IPR and pharmaceutical policies, in general. The impact
of a given alternative scenario x is defined as the difference in a
given outcome variable between the baseline and the alternative
scenario.
Slide 14
14
Slide 15
15 Final impact variables Impact of scenario x: IMV x :
Increase in expenditure/sales/market value rC x : Relative
reduction in consumption (in units) RMSD x : Reduction in the sales
of the domestic industry RMSD x : Reduction in the sales of the
domestic industry
Slide 16
16 The model first computes the number and proportion of AI
under exclusivity for all years over the time horizon: The data
input required includes: TAPto: Number of AI (active ingredients)
on the market at the beginning of the initial year AIi: Number of
AI entering the market each year AOi: Number of AI exiting the
market each year AIPPi: Number of AI entering the market with
patent protection each year AIDPi: Number of AI entering the market
with test data protection each year
Slide 17
17 The duration of the effective exclusivity time derived from
a patent is computed as: EEP = PD DT + PDE + TTC + DGE, where: PD
is the nominal patent duration DT is the time elapsed between
patent filling and registration/market authorization PDE is the
extension of patent duration due to compensation for delays in
patent approval, which might affect a certain proportion of AI,
pPDE) TTC is the time elapsed between the patent expiration time
and generic market entry (associated to Bolar provision) DGE is the
delay in generic market entry due to the linkage between
registration and patent, which might affect a certain proportion of
AI, pDGE)
Slide 18
18
Slide 19
19 The model then computes the average price differential of
medicines between the baseline and any alternative scenario by
means of a price index that takes the value 1 each year of the
baseline scenario: ( Alternative scenarios x are indicated by the
superindex ( x ) Pi = 1 P x i = [1+( pe x i pei)*(RPec 1) + (1- pe
x i)*(pdi- pd x i)*(RPbd 1)] pei: Share of the relevant market
under exclusivity in year i RPec: Relative weighted average price
of an AI under exclusivity (APe) vs. its price under competition
(APc) pd x i: share of branded products in the non-exclusive
segment RPbd: Relative weighted average price of an branded vs.
unbranded (INN) AI
Slide 20
20 Reduction in consumption (quantities demanded) and
expenditure increase are taken as proxis for reduction in access
caused by price increases. The demand function is assumed to have a
constant price-elasticity, e, and the following expression: q = k p
e where q: units demanded k: constant p: price (index) e:
price-elasticity of demand; e = (dq/q)/(dp/p) The price-elasticity
of demand indicates the relative change in the quantity demanded as
a response to a 1% change in price.
Slide 21
21 The expenditure/sales/market value in the baseline scenario
is computed as: MV i = MV i-1 *(1+) The expenditure/sales/market
value in the alternative scenario x is computed as: MVi x = MV x i
= MVi* P x i e+1
Slide 22
22 Impact of a change of the price on consumption and
expenditure
Slide 23
23
Slide 24
24 The reduction in market sales of domestic industry under
scenario x, RMSD x i is computed as: RMSD x i = MVDi - MVD x i = k
de * pei* MVi + k dc *(1-pei)* MVi - (k de *pei* MV x i + k dc
*(1-pe x i)* MV x i) where k de : market share of domestic industry
in markets under exclusivity k dc : market share of domestic
industry in markets under competition MVDi: Market sales of
domestic industry in year i
Slide 25
25
Slide 26
26 The main assumptions of the model are: 1. Under the
alternative scenario x, the units of the products now under
exclusivity, (pe x i pei), will attain a higher relative price than
under competition, Rpec. 2. The market share (in monetary terms) of
each AI is the same for all AI throughout their market life 3.
Competition in an AI market begins immediately or some years after
patent protection and test data exclusivity end. 4. The average
price of an AI instantaneously drops by a given fixed proportion
when competition starts.
Slide 27
27 5. The model assumes that the domestic industry will
maintain all the time and under any scenario the initial market
share in the markets under exclusivity and under competition. As it
is likely to have a higher share in the competitive market, as long
as the competitive market decreases in relative terms, the share of
the domestic industry in the total market will come down. The
absolute value of this market share cannot be unambiguously
predicted as it depends, as well, on the growth of the market. 5.
The model assumes that the domestic industry will maintain all the
time and under any scenario the initial market share in the markets
under exclusivity and under competition. As it is likely to have a
higher share in the competitive market, as long as the competitive
market decreases in relative terms, the share of the domestic
industry in the total market will come down. The absolute value of
this market share cannot be unambiguously predicted as it depends,
as well, on the growth of the market.
Slide 28
28 Preliminary results for Colombia The time horizon for the
simulation is 2005-2050. In the baseline scenario the share of the
market under exclusivity rises until 2019 and remains stable
thereafter at 43% If patent duration is extended to 21 years, the
market share under exclusivity levels off a year later, in 2020, at
a 47%, and pharmaceutical expenditure is 5.7% higher than in the
baseline scenario. Increasing by one year the duration of the
exclusivity for test data protection would imply a stabilization of
the market share under exclusivity in 2019 at 44% and a 1.5%
increase in expenditure over the baseline scenario. If Colombia had
not enforced product patent protection in 2000 and test data
protection in 2002, it might have saved an estimated 69% of the
pharmaceutical expenditure over the simulated period.
Slide 29
29 IPR Impact Model Preliminary Results in Malaysia Final
purpose of analysis was to estimate the likely impact a stronger
IPR protection on medicine prices in Malaysia if Malaysia signs the
US- Malaysia FTA bilateral agreement
Slide 30
30 Preliminary results based on currently available data The
time horizon for the simulation is 2007-2047 If all standard USFTA
provisions are accepted, the worst case scenario simulated would
result in increase in pharmaceutical expenditure of 46% or a
reduction in consumption of 56% If data exclusivity alone is
introduced, the worst case scenario simulated would result in a
reduction of consumption by 50% or an increase in expenditure of
38% If the proportion of medicines that are patented increases, the
worst case scenario simulated is a reduction in consumption of 36%
or an increase in expenditure of 28%
Slide 31
31Discussion The model has proved easy to understand and use by
decision-makers with no previous experience in simulation models
Most of the information required for running the model was
available and relatively easy to collect in the pilot test
countries The model results are very sensitive to the data and
assumptions on the initial number of AI, and of those entering and
exiting the market. The number of existing AI should be adjusted in
order to ensure that it reflects the number of AI in the market
that have a market share similar to the future new entrants.
Slide 32
32Discussion Additional analyses are also required on the price
differential of AI in competitive markets and in markets under
exclusivity conditions Although the results look plausible, it is
necessary to improve the evidence base by undertaking systematic
reviews and, when required, new analyses of the impacts of IPR
changes. The values of some of the parameters that define the
scenarios in the model directly reflect the options of the decision
maker, e.g. duration of the patent or year of enforcement of
pharmaceutical patents. For other parameters the values are less
straightforward, and will require specific studies and subjective
technical judgments. E.g. how will an hypothetical broader scope of
patentability affect the proportion of AI that will enter the
market with patent protection?
Slide 33
33
Slide 34
34 Months after First Generic Entry into Market Generic
Penetration of Brand Market: Units Sales and Price per Unit SOURCE:
Compiled by the PRIME Institute, University of Minnesota from data
found in Kidder, Peabody Generic Units as % of Total Unit Sold
Generic Price as % of Brand Price Commodity Equilibrium Price
Reached (Modest Price Inflation Expected) 6 Months Exclusivity
(Generic) Generic Price Competition (More Firms = Lower
Prices)
Slide 35
35 Estimating the price differential exclusivity-competition
The price of original drug under exclusivity is 100 The average
price of the generics after three years of patent expiration is 25
Market share of generics after three years is 85% and that of the
original product, 15% The final average price of the AI is: 100 x
0,15 + 25 x 0,85 = 38,75 The price of the AI under exclusivity is
2,5 times that of the price under competition
Slide 36
36 Source: Danzon and Furukawa, Health Affairs, 2003
Slide 37
37 Estimation of relative average prices of drugs Sales of
unbranded generics (UBG) / Total sales Sales of unbranded generics
(UBG) / Total sales
---------------------------------------------------------------------
=
---------------------------------------------------------------------
= Units of unbranded generics (UBG) / Total units Units of
unbranded generics (UBG) / Total units Units of UBG x average UBG
price / Total units x average price Units of UBG x average UBG
price / Total units x average price =
--------------------------------------------------------------------------------------------
= Units of unbranded generics (UBG) / Total units Units of
unbranded generics (UBG) / Total units average UBG price average
UBG price = --------------------------- = RELATIVE PRICE OF UBG =
--------------------------- = RELATIVE PRICE OF UBG average price
average price
Slide 38
38 Estimation of potential savings from an INN policy POTENTIAL
SAVINGS (in % of total sales) = POTENTIAL SAVINGS (in % of total
sales) = SHARE OF BRANDED GENERICS SALES x ( 1 - RELATIVE PRICE OF
UBG / RELATIVE PRICE OF BG ) x 100 Assumptions: In the absence of
brand names, competition would reduce the present prices of BG to
the level of UBG.
Slide 39
39
Slide 40
40 Impact of generic competition on pharmaceutical prices (1)
(A substantial share of) the reduction of ARV annual treatment
costs between 2000 and 2003 from US$ 10.000 to 300 should
(probably) be accounted to generic competition. A recent WHO-HAI
study, The price of medicines, shows ratios between generic and
branded originals in the range of 1:2 (Armenia), 1:3 (Sri Lanka),
and from 1:2 up to 1:7 in Kazakhstan
Slide 41
41 Impact of generic competition on pharmaceutical prices (2) A
recent study applied WHO-HAI methodology in Malaysia Survey was
conducted from October-2004 to January 2005. 48 drugs were surveyed
by using systematic sampling technique in four geographical regions
of Malaysia Babar et al, A survey of medicine prices in Malaysia by
using WHO/HAI methodology. UCSI-USM, October 2005.
Slide 42
42 Median MPRs of IB, MSG and LPG in Public for Procurement
Sector, Private Sector Retail Pharmacies and Dispensing Doctors
Sector Median MPRs of IB, MSG and LPG in Public for Procurement
Sector, Private Sector Retail Pharmacies and Dispensing Doctors
Sector Drugs Public Sector PSRPDDS Innovator Brands 2.4116.3515.40
Most Sold Generic 1.566.897.76 Lowest Price Generic
1.096.577.76
Slide 43
43 Private Retail Pharmacies
Slide 44
44
Slide 45
45 Thanks for your attention For additional information, please
contact Joan Rovira [email protected]
Slide 46
46 Fixed parameters YI: Initial year of simulation period YL:
Last year of simulation period TAPt n : Number of existing active
ingredient (AI) in the market in year t n; t n t n AOi: Number of
AI exiting the market in year i; i > t n DT: Time from patent
filling (or approval) of an AI to market registration (approval) of
the original product MVt o : Total sales/expenditure of the
relevant market in year t o : annual rate of growth of MV RPec:
Relative weighted average price of an AI under exclusivity (APe)
vs. its price under competition (APc) d: discount rate k de :
market share of domestic industry in markets under exclusivity k dc
: market share of domestic industry in markets under
competition
Slide 47
47 Scenario-dependent parameters YP: initial year of product
patent enforcement pp: Percentage of patented (product patent) AI
entering the market in year i PD: Patent duration in years YDP:
initial year of data protection enforcement AIDPi: Number of AI
entering the market in year i with test data protection DE:
Duration of exclusivity due to test data protection TTC: Time from
patent expiration to generic competition e: price-elasticity of
demand
Slide 48
48 Impact variables Impact of scenario x: IMV x i: Increase in
total sales/expenditure of the relevant market in year i. RICi:
Reduction in consumption (units) in year i RMSD x i: Reduction in
market sales of domestic industry in year i
Slide 49
49
Slide 50
50 ASEF ASIA-EUROPE FOUNDATION CULTURES &CIVILISATIONS
DIALOGUE 8th Talks on the Hill Re-righting Intellectual Property:
Economic and Social policy challenges in Asia and Europe Singapore,
7th-9th of May 2006 SELECTED ASEF ROUND TABLE RECOMMENDATIONS:
Slide 51
51 Allowing for greater flexibilities in using TRIPS Many of
the Europeans felt that their governments should be more
forthcoming about telling the developing countries that it is
acceptable for them to use the flexibilities that TRIPS provides.
In addition to governments, companies should also start to
recognise the flexibilities that are built in TRIPS for example
parallel imports.
Slide 52
52 Releasing the Pressure The group also called upon
governments and patent companies to refrain from using pressure
tactics that result in developing countries adopting higher
standards of intellectual property protection and enforcement than
they need to or are able to.
Slide 53
53 Understanding the depth of Intellectual Property Many of the
participants from developing countries recognised the need to gain
more concrete advice before signing on the treaties such as the
Patent Cooperation Treaty (PCT) and indicated that their
governments need to realise that intellectual property is far more
important and pervasive than previously thought.
Slide 54
54 Distinguishing between obligations and pressures Linked to
this point was the need for developing countries to focus on
dissecting much of the information that they are receiving from the
various international organisations as well as other governments
into obligations and pressures. In doing so, the countries would be
better able to more positively lay out their policy in alignment
with their priorities and national interest.
Slide 55
55 Diversifying the decision- making process National
governments should diversify the decision-making process on
treaties and other agreements linked to intellectual property. This
comes with a growing recognition that this issue can no longer be
limited to a few specialists. For example, professionals and
decision- makers from the health sector should be involved in the
discussion and negotiation of both FTA and internal policies when
they are likely to have an impact on the price and access to
medicines and health services.
Slide 56
56 Value in involving civil society at multilateral forums
Members of the group recognised that independent civil society has
a useful role to play at the multilateral level and their
involvement and views should be better taken into consideration in
the decision-making processes within the WTO and WIPO.
Slide 57
57 Thanks for your attention For additional information, please
contact Joan Rovira [email protected]