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.