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Opportunities for CER Methods in Drug Discovery, Development and Commercialization
Lei Zhu, PhD, MBA GlaxoSmithKline
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Health Care Value Chain
Burns, L.R., et.al., The Wharton School Study of the Health Care Value Chain
Financial Intermediaries
Distributional Intermediaries
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The Trend of Evidence for Market Access
3
Adapted from Keiron Sparrowhawk’s seminar on “How payers value innovation and what are the implications for GSK R&D?”
Market Access Economic
Wei
ght o
f Evi
denc
e
Market Dynamics Clinical
US
France
UK Canada
Some plans are increasing their use of comparative effectiveness in the US
Potential use of economic evaluation in France
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• Safety – Side effects acceptable?
• Efficacy – Can it work? Net benefit optimal conditions
• Effectiveness – Does it work? Net benefit average conditions
• Efficiency – Is there sufficient value
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Evaluation Methods
• Evidence-Based Medicine (EBA) • Health Technology Assessment (HTA) • Comparative Effectiveness Research (CER)
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Relationships of Evidence Processes: EBM, CER, and HTA
Interna'onalWorkingGroupforHTAAdvancement.LuceBR,DrummondMF,JonssonB,NeumannPJ,SchwartzJS,SiebertU,SullivanSD.EBM,HTA,andCER:ClearingtheConfusion.MilbankMemorialFundQuarterly.Inpress.
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Implications for Pharmaceutical Industry • Transform from regulatory driven indication
development to patient-centric product development – CER makes a difference throughout the
drug development life cycle – Develop new strategies for R&D and
commercial to deliver products of value to patients and payers
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• Incremental efficacy or safety improvement
• QoL improvement • Improved compliance
Payers’ Assessment of Value
8
Avastin Sutent Glivec
Anti-TNFs
• Morbidity/mortality benefit • Targeted at a patient population with unmet need • Reduces the burden on the healthcare system
• New MoA; similar effectiveness • Sometimes indirect cost reduction
Level of Reimbursement
Rasilez
Aclasta/Reclast Prostap 3
Leve
l of V
alue
Keiron Sparrowhawk, “How payers value innovation and what are the implications for GSK R&D?”
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Demonstrate Value through Evidence Generation and Synthesis
• Randomized Clinical Trials/Pragmatic Trials
• Observational Studies
• Systematic Reviews
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CER Study Design
• Relevant comparators • Clinically relevant outcomes • Best available data • Well defined, rigorous, analytical methods
Explicitly characterize uncertainty Address issues of generalizability and transferability Adapted from Schwartz, S., “Comparative Effectiveness Research, Scope of the Problem”, http://www.cceb.upenn.edu/biostat/conferences/ClinTrials10/ Adapted from Drummond MD, Schwartz JS, Jonsson B, Luce B, Neumann PN, Siebert U, Sullivan SD. International Journal of Technology Assessment in Health Care. 2008;24:244-58; discussion 362–368.
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A Sample of CER Analysis Methods
• Indirect Comparison • Control for confounding in Observational Study • Subgroup Analysis
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Indirect Comparison • Well-validated statistical techniques from Canadian
Agency for Drugs and Technologies in Health (CADTH)(Wells et al., 2009) – The Bucher method of indirect comparisons – Network meta-analysis – Mixed treatment comparisons using Bayesian analysis
• Selection bias of the clinical trials and statistical methods
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Control for Confounding in Observational Study
• Stratified Analysis • Marginal Structural Model • Propensity Score • Instrumental Variable
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Subgroup Analysis • Multivariate Methods
– PCA, PLS, PLS-DA, Cluster Analysis, etc. • Data Mining Methods
– Recursive Partitioning, Bayesian Network, Support Vector Machine, etc.
• Prediction Modeling
• Identifiers for subgroup need to be easy to measure
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Patient Subgroup Analysis of Lipid Profiles Change from baseline at Week 24
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Prediction of Risk Potential risk factors associated with fluid retention by survival recursive partitioning
Pharmacogenetics and Genomics 2007, Vol 17 No 12
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Pharmacogenomics Approach to Personalized Medicine
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Design of Targeted Clinical Trial based on Predictive Biomarkers
• Imperfect predictive biomarker
• How the performance affect the trial efficiency – sample size?
• Early phase trial is an important CER tool
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Reward for Personalized Medicine
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• “Without major changes in how we conceive, design, conduct, and analyze RCTs, the nation risks spending large sums of money inefficiently to answer the wrong questions -- or the right questions too late.”
Luce BR, Kramer JM, Goodman SN, Connor JT, Tunis S, Whicher D, Schwartz JS. Rethinking randomized clinical trials for comparative effectiveness research: The need for transformational change. Annals of Internal Medicine. 2009;151:206-209.
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Summary • Statistical community can make significant contribution
to the design and analysis of CER studies – Design of large pragmatic trials; Bayesian adaptive
design – Methods for indirect comparisons, subgroup
analysis, and controlling confounding in observational studies
It is better to be approximately right than precisely wrong
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Acknowledgement • Kwan Lee • Alan Menius • Amit Bhattacharyya • Patrick Ryan • Xiwu Lin • Daniel Park • Jie Cheng