Focusing on the key challenges Focusing on the key challenges

Decision-making & Decision-making & drug developmentdrug development

Peter HertzmanPeter Hertzman

Paul MillerPaul Miller

RationaleRationale

1. From societal perspective the case for bayesian analysis (BA) to inform adoption decisions for new technologies is strong

2. From an individual firm’s perspective there may be a lot more (other) reasons to use bayesian analysis

3. (2) may be the best foundation for (1)• benefits (internal to the firm) during drug development

will provide incentives to invest (promote) in BA• this will impact societal HTA

Q1. What are the objectives of Q1. What are the objectives of

pharmacoeconomics?pharmacoeconomics?

Sales Sales RevenueRevenueSales Sales

RevenueRevenue

11stst Objective of Objective of PharmacoEconomicsPharmacoEconomics

PRICEPRICE VOLUMEVOLUME

ApprovalApproval

22ndnd Objective of PharmacoEconomics Objective of PharmacoEconomics

REIMBURSEMENTREIMBURSEMENT

FORMULARY LISTINGFORMULARY LISTINGPRICING APPROVALPRICING APPROVAL

(PRODUCT LICENSING)(PRODUCT LICENSING)

33rdrd Objective of PharmacoEconomics Objective of PharmacoEconomics

R&D R&D CostsCostsR&D R&D CostsCosts

Assist internal decision-makingand resource allocation during drug development

R&D CostsR&D CostsR&D CostsR&D Costs

Sales Sales RevenueRevenue

ApprovalApproval

Q2. Which tools do we use?Q2. Which tools do we use?

The EconomistThe Economist

The Phase III TrialThe Phase III Trial

Q3. Which tools could we use?Q3. Which tools could we use?

Bayesian AnalysisBayesian AnalysisLongitudinal DatabasesLongitudinal Databases

CTSCTS

Conjoint AnalysisConjoint AnalysisQoL AssessmentQoL Assessment

Contingent ValuationContingent Valuation Economic ModellingEconomic Modelling

PROsPROs

Value of InformationValue of InformationThreshold AnalysisThreshold Analysis

So, how can we deliver more?So, how can we deliver more?

1. Exploit methodological advances in economic evaluation and decision theory

2. Integrate these into a broader range of activities

3. Review the timing of these activities in the product lifecycle

Gathering information

Modelling

Predicting

Optimizing decisions

Benefits

Synthesis of Evidence

Quantifying Uncertainty

Need for Bayesian AnalysisNeed for Bayesian Analysis(Regulator’s perspective)(Regulator’s perspective)

• To synthesise all available evidence in an explicitly quantitative analysis

• To quantify uncertainty• To understand the marginal value of more

information – Weigh contribution of more information

(certainty) vs. Opportunity costs of delayed adoption

• Adopt in awareness of level of uncertainty; or• Adopt, retricted to more certain domains (populations)• Reject, value of more information > cost to society

Need for Bayesian AnalysisNeed for Bayesian Analysis(Pharma perspective)(Pharma perspective)

• Where ’regulator’ requires it! Eg.UK NICE– Still not viewed as a real barrier to market access

• What proportion of global sales will be affected?– “only one (small) market” argument

• Does Pharma need to change the way it works?• Weak incentive: “the stick” is not perceived as big enough!

• Carrots may be more effective!– scope for bayesian analysis in drug development

process is large

Drug Development ProcessDrug Development Process

1. Test 5,000 -10,000 compounds, to identify candidates for further development

2. Send approx. 250 for pre-clinical testing 3. Enter approx. 5 into:

– Phase 1 trials (<100 healthy volunteers, to determine safety and dosage). If successful:

– Phase 2 trials (<300 volunteers, to test for efficacy and side effects). If successful:

– Phase 3 trials (> 1,000 volunteers, to monitor longer-term use and adverse reactions). If successful:

4. Approval of the new drug: license– 10+ years after identification for development– Cost incurred per NCE = $ 600 million

5. Pricing & Reimbursement discussions

ObservationsObservations

• Process is long, costly and risky!

• Highly regulated industry:– Gather drug profile information for

regulatory authorities to make decisions (license, price, reimburse)

– Some information then used for promotional claims to persuade customers to make decisions (also regulated)

Two fundamental questionsTwo fundamental questions

1. Which projects do we invest in?

2. How do we maximise the efficiency of the projects we do choose?

(i.e allocative and technical efficiency issues)

uncertainty

time

Select candidate drugs to develop

Clinical trial design?

NICE REVIEW

Clinical indication?

Stop/go?

I II III

P&R strategy?

DecisionsDecisions

PreclinicalPreclinical Phase IPhase I Phase IIPhase II Phase IIIPhase III Phase IVPhase IV

LAUNCHLAUNCH

Pilot outcomes & resource use questionnairePilot outcomes & resource use questionnaire

Collect cost & outcome dataCollect cost & outcome data

Populate economic modelsPopulate economic models

Inform external decision-makersInform external decision-makers

PreclinicalPreclinical Phase IPhase I Phase IIPhase II Phase IIIPhase III Phase IVPhase IV

LAUNCHLAUNCH

Pilot outcomes & resource use questionnairePilot outcomes & resource use questionnaire

Collect cost & outcome dataCollect cost & outcome data

Populate economic modelsPopulate economic models

Inform external decision-makersInform external decision-makers

Ongoing evaluation in ‘real world’Ongoing evaluation in ‘real world’

Scenario Modelling:estimate c/e ranges

estimate budget impactdetermine price bands

Scenario Modelling:estimate c/e ranges

estimate budget impactdetermine price bands

Inform internal decisions:1. Project management2. Portfolio management

Inform internal decisions:1. Project management2. Portfolio management

Early = data vaccum?Early = data vaccum?

• Not necessarily…

• Use what we do know!– PK & PD data, CTS, predict drug profile – Disease knowledge & Epidemiology – Market knowledge– Competitor knowledge– Regulatory requirements

Project ManagementProject Management

• Clinical development programme design: optimising decisions, eg.

• Number and timing of decision points• Speed of development• Order of trials• Dose• Sample size • Sample selection

• About efficiency in trial design• Optimise what? Intermediate or final endpoints?

Portfolio ManagementPortfolio Management

References:

• Burman CF, Senn S. Examples of option values in drug development. Pharmaceut Statist. 2003;2:113-125

• Poland B, Wada R. Combining drug-disease and economic modelling to inform drug development decisions. Drug Discovery Today 2001: 6(22):1165-1170.

• Shih Y-C T. Bayesian approach in pharmacoeconomics: relevance to decision-makers. Expert Rev. Pharmacoeconomics Outcomes Res. 2003; 3(3): 237-250.