A Portfolio-Based Approach to Optimize Proof-of-Concept Clinical Trials

Abstract

Improving proof-of-concept (PoC) studies is a primary lever for improving drug development. Since drug development is often done by institutions that work on multiple drugs simultaneously, the present work focused on optimum choices for rates of false positive (α) and false negative (β) results across a portfolio of PoC studies. Simple examples and a newly derived equation provided conceptual understanding of basic principles regarding optimum choices of α and β in PoC trials. In examples that incorporated realistic development costs and constraints, the levels of α and β that maximized the number of approved drugs and portfolio value varied by scenario. Optimum choices were sensitive to the probability the drug was effective and to the proportion of total investment cost prior to establishing PoC. Results of the present investigation agree with previous research in that it is important to assess optimum levels of α and β. However, the present work also highlighted the need to consider cost structure using realistic input parameters relevant to the question of interest.

Key Words:

• Power
• Proof-of-concept
• Type I error

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Corrigendum

Notes

¹All trials assume a standardized effect size of 0.4 and that is the true effect size for the effective drugs.

²The rate of false positive results in PoC trials, is in two-tailed testing.

³True +s =power multiplied by number of effective drugs, False +s =False +rate multiplied by the number of ineffective drugs Ph III success rate =True +s/(True +s plus False +s).

Note. 1, Probability a compound will enter Phase III. Includes true positive and false positive Phase II compounds. 2, Probability that a Phase III compound is effective. 3, Probability a compound will be approved. Includes the 20% attrition in Phase III due to safety and other reasons not due to efficacy. 4, Development cost per compound: total Phase II cost +Phase III cost for compounds entering Phase III divided by number of compounds entering Phase II. 5, Number of compounds studied: the $5 billion budget divided by average cost per compound. 6, Number of compounds approved: number of compounds studied multiplied by approval probability. 7, Portfolio value =number of launches for fast to PoC and =number of launches ×1.2 for fast to registration.