Innovative Clinical Trial Design and Management

Summary

Innovative Clinical Trial Design and Management
Trends, success stories and impact upon R&D budgets

Report overview Key findings...

The costs associated with developing drugs have risen dramatically over the past decade and fewer drugs are obtaining regulatory approval. The pharmaceutical industry is continually exploring new ways of improving drug developments and one area of focus is adaptive clinical trial designs. These innovative clinical trial designs use accumulating data to guide potential modifications to the study as it progresses, without undermining the validity and integrity of the trial. The advantages of such designs include the reduced length and cost of clinical trials, lower patient numbers and the ability to stop a trial early where a drug has not shown efficacy.

'Innovative Clinical Trial Design and Management' is a new report published by Business Insights that explores the major types of adaptive design and their role in dose-finding. The report investigates seamless Phase 2/3 trials and adaptive trials in pharmacogenomics, assesses the logistical implications of adaptive trial implementations and reviews the current regulatory standpoints of the FDA and EMEA. Detailed case studies of recent adaptive clinical trials are provided and the companies offering statistical expertise in this area are profiled. This report also includes a breakdown of the potential cost and time savings that innovative trial designs can offer throughout the clinical development process.

Use detailed case studies to explore recent adaptive trial implementations, identify the companies pioneering and supporting innovative designs and understand the most effective planning and logistics strategies... 15

Key findings...

Major pharma companies are implementing adaptive trials to improve dose-finding in the Phase 2 setting. The use of adaptive clinical trials will increase across the industry over the next 2-3 years.

Adaptive clinical trial designs are more effective than traditional designs in cases where there is uncertainty surrounding the dose, effect size and variability, clinical endpoint or patient populations.

The planning and execution of adaptive designs is more complex than the traditional approach. Successful implementations require teams of statisticians, data managers, clinicians and drug supply and logistics managers to work together as early as possible.

Predictive biomarkers have been found to require detailed prospective analysis far earlier in the clinical development process, and with the same clarity as traditional drug approvals. Post-hoc correlations were previously thought to be good enough for identifying the biomarkers used to predict the patients most likely to respond well to a new treatment.

Regulatory authorities are supportive of adaptive trials, particularly in the Phase 2 setting. However, there are concerns over the confidentiality of data and companies have been asked to demonstrate that the parties involved in running the study will remain unaware of ongoing adaptations.

Key questions answered...

• How can adaptive trials improve the success rates of clinical drug projects?
• How are pharma companies implementing adaptive trials and what major hurdles can prevent such implementations?
• What is the position of the FDA and EMEA in regards to different types of adaptive trial?
• How can logistical and strategic planning be managed most effectively?
• Which companies are offering services to support adaptive clinical trials?
• Which companies are co-developing drugs and diagnostic products?

Key issues examined by this report...

• Adaptive trial implementations. The aim of adaptive trials is to improve the information value of clinical trials whilst maintaining their integrity and validity. The use of adaptive trials in the early phases of drug development should yield better information and lead to the earlier termination of unsuccessful compounds.
• Dose finding improvements. The availability of new Bayesian study designs that acknowledge prior information and allow for the testing of a wider range of doses has enabled more accurate dose-finding. This may have important consequences for the success of future Phase 3 clinical programs
• Seamless trial speed. Major pharma companies are interested in the prospect of combining drug development phases into 'seamless trials', with the potential to reduce the length of clinical development programs in the Phase 2b/3 setting
• Regulatory issues. Engaging with the FDA/EMEA during the protocol design stages of an adaptive trial is important, especially for studies intended for use in packages of pivotal clinical data. The EMEA's current position on adaptive clinical trial design is summarized within a reflection paper published in October 2007, while draft FDA guidance is expected in 2008.

Contents

• Innovative Clinical Trial Design and Management
• Executive Summary
• Introduction
  • Adaptive clinical trials
  • Adaptive dose-finding studies
  • Seamless adaptive trials
  • Adaptive trials in drug-diagnostic co-development
  • Simulation, logistics and technology in adaptive trials
  • Regulating adaptive trials
  • Outlook for adaptive trials in the pharma industry
• Chapter 1 Introduction
  • Summary
    • State of the industry
    • Rising development costs
    • Longer development times
    • Increasing complexity
    • Higher attrition
    • Increasing innovation
    • Innovation in drug discovery and development
    • Adaptive clinical trials - an introduction
    • Report outline
• Chapter 2 Adaptive Clinical Trials
  • Summary
  • Introduction
    • Adaptive designs
    • Flexibility in adaptive trials
    • Statistics for adaptive designs
    • Group Sequential Designs
    • Stopping early for benefit - controversy
    • Case study: RALES - a Searle Phase 3 Group Sequential Design
    • Case study: CAPTURE - a Centocor study in refractory unstable angina
    • Case study: Proof-of-concept study in neuropathic pain - GlaxoSmithKline
    • Case study: PURSUIT - a Millennium Pharmaceuticals study in unstable angina
    • Sample size re-estimation
    • Case study: a group sequential study for sample size re-estimation
    • Case study: GlaxoSmithKline pivotal study for Advair Diskus
    • Response adaptive randomization
    • Case study: Troxacitabine in acute myeloid leukemia
    • Case study: Eli Lilly out-patient study in depression
    • Case study: Three dosing schedules of decitabine in myelodysplastic
    • syndrome
    • Case studies: A study of sorafenib in different types of cancer
    • Bayesian methods in First in Man studies
    • Conclusions
• Chapter 3 Adaptive Dose-Finding Studies
  • Summary
  • Introduction
    • Case study: ASTIN
    • Case study: Phase 2 Pfizer dose-ranging study in neuropathic pain
    • Case study: Phase 2 Merck dose-finding study of anti-migraine compound
    • Case study: Phase 3 Napo Pharmaceuticals study in HIV patients with diarrhea
    • The PhRMA Adaptive Dose-Ranging Studies Working Group
    • Conclusions
• Chapter 4 Seamless Adaptive Trials
  • Summary
  • Introduction
    • Pros, cons and controversy
    • Speeding up clinical development
    • Efficiency gains in seamless trials
    • When are seamless designs appropriate?
    • Regulatory view of seamless Phase 2b/3 studies
    • Case study: Phase 1/2 trials in oncology
    • Case study: Phase 2b/3 Novartis study in a chronic disease indication
    • Case study: HORIZON III an AstraZeneca study in oncology
    • Conclusions
• Chapter 5 Adaptive Trials in Drug-Diagnostic Co-Development Projects
  • Summary
  • Introduction
    • Biomarkers and classifiers
    • Co-development of drugs and companion diagnostics
    • Pivotal Phase 3 trial designs using predictive biomarkers
    • Enrichment designs
    • Patient stratification
    • Sample size calculation for enrichment and stratification designs
    • Adaptive signature designs
    • Biomarker adaptive threshold determination
    • Case study: identifying a classifier of response to Velcade
    • Conclusions
• Chapter 6 Simulation, Logistics and Technology in Adaptive Trials
  • Summary
  • Introduction
    • Preplanning and simulation
    • Case study: A study design and simulation using Cytel's East simulation package
    • Logistical issues
    • Real-time data collection
    • Electronic data capture (EDC)
    • Electronic patient reported outcomes (ePRO)
    • Interactive voice recognition and interactive web response
    • Companies involved in real-time data collection
    • Maintaining data confidentiality
    • Minimizing operational bias and assuring consistency between study stages
    • Clinical supply management
    • Case study: simulating drug supply
  • Summary - Logistical Considerations for Adaptive Trials
    • Conclusions
• Chapter 7 Regulating Adaptive Trials
  • Summary
  • Introduction
    • FDA guidance on adaptive designs
    • EMEA guidance on adaptive designs
    • PhRMA working groups
    • Conclusions
• Chapter 8 Outlook for Adaptive Trials in The Pharma Industry
  • Summary
  • Introduction
    • Adaptive trials and success rates in clinical drug development
    • Costs in adaptive clinical trials
    • Time means money
    • Costs in a dose-finding clinical trial
    • Cost savings in a seamless Phase 2b/3 trial
    • Cost savings in a random adaptive allocation trial
    • Costs in a sample size re-estimation study
    • Costs of clinical trials in pharmacogenomics
    • Pharma's uptake of adaptive designs
    • Outlook for adaptive trials
• Chapter 9 Appendix
  • Primary research methodology
  • Index
  • Glossary
  • Glossary
• List of Figures
  • Figure 1.1: New drug approvals versus R&D costs, 1995-2006
  • Figure 1.2: Trend towards longer drug development times, 1997 to 2005
  • Figure 1.3: Increasing complexity of clinical trial
  • Figure 1.4: Change in attrition rates, 1994 to 2000
  • Figure 1.5: Increasing innovation in drug development
  • Figure 1.6: Attrition rates and development times by drug novelty status
  • Figure 2.1: Summary of motivations for using adaptive trials
  • Figure 2.2: Examples of motivations for adapting clinical trials
  • Figure 2.3: Advantages and disadvantages of increasing the flexibility of adaptive trial designs
  • Figure 2.4: Bayes Theorem explained
  • Figure 2.5: How Bayesian statistics work
  • Figure 2.6: Data from interim monitoring visits during the RALES study
  • Figure 2.7: The random play-the-winner trial design
  • Figure 2.8: Response adaptive randomization - case study with troxacitabine
  • Figure 3.1: Advantages of adaptive dose-finding studies over traditional methods
  • Figure 3.2: Structure of the ASTIN study
  • Figure 3.3: Data from the ASTIN study
  • Figure 4.1: Structure of an adaptive seamless clinical trial
  • Figure 4.2: Key aims of each phase of drug development
  • Figure 4.3: Seamless trials in Phases 1, 2 and
  • Figure 4.4: When to use seamless adaptive Phase 2b/3 designs
  • Figure 4.5: Novartis' ongoing seamless adaptive Phase 2b/3 study design
  • Figure 5.1: Examples of targeted treatments and their companion diagnostics
  • Figure 5.2: Definitions of predictive and prognostic biomarkers
  • Figure 5.3: Co-development of a drug and companion diagnostic
  • Figure 5.4: Types of study design for use in drug-diagnostic co-development
  • Figure 5.5: The enrichment design
  • Figure 5.6: Including classifier positive and negative patients: stratification
  • Figure 5.7: Marker-based strategy for patient stratification
  • Figure 5.8: Adaptive signature designs
  • Figure 5.9: Discovery and testing of a predictive classifier for Velcade
  • Figure 6.1: Case study: stopping probabilities calculated using Cytel's East software
  • Figure 6.2: Integrative electronic systems in adaptive trial designs
  • Figure 6.3: Working Group proposal for sponsor involvement in decision making
  • Figure 6.4: Working Group proposal for selection decisions
  • Figure 6.5: Choosing an adaptive design: infrastructure and process requirements
  • Figure 8.1: Attrition rates and costs in drug development
  • Figure 8.2: Adaptive trials may help to restore success rates
  • Figure 8.3: Adaptive trials may help to restore success rates
  • Figure 8.4: Cost savings in a hypothetical seamless Phase 2b/3 adaptive trial
• List of Tables
  • Table 1.1: Advantages and disadvantages of using adaptive clinical trial designs
  • Table 1.2: How adaptive designs can fight attrition
  • Table 2.1: Group sequential study design may save time
  • Table 2.2: Consequences of incorrect planning- treatment difference and/or standard deviation
  • Table 2.3: Comparison of simple randomization and response-adaptive randomization
  • Table 2.4: Results of a response adaptive randomization study in depression
  • Table 3.1: Bayesian designs can investigate more doses
  • Table 4.1: Advantages and disadvantages of seamless adaptive designs
  • Table 5.1: Efficiency of enrichment study designs
  • Table 5.2: Comparison of number of patients needed for enrichment designs: gefitinib example
  • Table 5.3: Free software available for calculating sample sizes in pharmacogenomic studies
  • Table 6.1: Integrity and validity in adaptive clinical trials
  • Table 6.2: Companies offering statistical expertise for adaptive trials
  • Table 6.3: Providers of software, tools and services for adaptive trials
  • Table 6.4: Clinical trial supply simulation software providers
  • Table 8.1: Cost savings for various options in COPD trial
  • Table 8.2: Retrospective analysis identifies benefits of an adaptive design
  • Table 8.3: Effect of HER2 testing on the development of Herceptin
  • Table 8.4: Potential additional sales for a drug targeted to 25% of patients tested
  • Table 8.5: Phase distribution of case studies, PhRMA Adaptive Designs Working Group
  • Table 8.6: Indications in which Bayesian adaptive designs have been used