Assessing End of Phase 2 Decision Criteria

<div><p>The objectives of the Phase 2 stage in a drug development program are often to evaluate the safety and tolerability of different doses, select a promising dose range, and look for early signs of activity (i.e., to establish proof of concept). At the end of Phase 2 (EOP2), a decision to initiate Phase 3 studies is made that involves the commitment of considerable resources. One of the key factors in this decision is the expected efficacy and the associated predicted probability of success (PoS) in Phase 3. Making a decision based upon the PoS requires decision makers to select a benchmark (or PoS criterion) for the PoS, which if achieved would enable a “go-to-Phase 3” decision. However, appropriately choosing the criterion requires knowledge of the operating characteristics associated with the decision criteria. A key operating characteristic that a funder/sponsor requires to make such a choice is to understand the predicted conditional probability of making a go decision and subsequently failing in Phase 3. In this article, we show how such risks can be informed through the use of clinical trial simulation. We also highlight through a worked example in pancreatic cancer how this simulation exercise can help to decide between different development strategies for a specific indication. Supplementary materials for this article are available online.</p></div

A Quantitative Process for Enhancing End of Phase 2 Decisions

<div><p>The objectives of the phase 2 stage in a drug development program are to evaluate the safety and tolerability of different doses, select a promising dose range, and look for early signs of activity. At the end of phase 2, a decision to initiate phase 3 studies is made that involves the commitment of considerable resources. This multifactorial decision, generally made by balancing the current condition of a development organization's portfolio, the future cost of development, the competitive landscape, and the expected safety and efficacy benefits of a new therapy, needs to be a good one. In this article, we present a practical quantitative process that has been implemented for drugs entering phase 2 at Amgen Ltd. to ensure a consistent and explicit evidence-based approach is used to contribute to decisions for new drug candidates. Broadly following this process will also help statisticians increase their strategic influence in drug development programs. The process is illustrated using an example from the pancreatic cancer indication. Embedded within the process is a predominantly Bayesian approach to predicting the probability of efficacy success in a future (frequentist) phase 3 program.</p></div

Five Stages of the Systemic Therapy in Advancing or Metastatic Prostate Cancer: Evaluation of Drug Efficacy (STAMPEDE) trial

IDMC  = Independent Data Monitoring Committee; FFS  = failure-free survival; HR  = hazard ratio, where 0 ≤ d ≤ c ≤ b ≤ a ≤ 5.<p><b>Copyright information:</b></p><p>Taken from "Speeding up the Evaluation of New Agents in Cancer"</p><p></p><p>JNCI Journal of the National Cancer Institute 2008;100(17):1204-1214.</p><p>Published online 3 Sep 2008</p><p>PMCID:PMC2528020.</p><p></p

Stopping guidelines on the hazard ratio scale for the Systemic Therapy in Advancing or Metastatic Prostate Cancer: Evaluation of Drug Efficacy (STAMPEDE) trial

CI = confidence interval; HR = hazard ratio; Stop = stopping of accrual (rather than termination of follow up).<p><b>Copyright information:</b></p><p>Taken from "Speeding up the Evaluation of New Agents in Cancer"</p><p></p><p>JNCI Journal of the National Cancer Institute 2008;100(17):1204-1214.</p><p>Published online 3 Sep 2008</p><p>PMCID:PMC2528020.</p><p></p