Financially adaptive clinical trials via option pricing analysis

Shomesh E. Chaudhuri and Andrew W. Lo

Journal of Econometrics, 2024, vol. 240, issue 2

Abstract: The regulatory approval process for new therapies involves costly clinical trials that can span multiple years. When valuing a candidate therapy from a financial perspective, industry sponsors may terminate a program early if clinical evidence suggests market prospects are not as favorable as originally forecasted. Intuition suggests that clinical trials that can be modified as new data are observed, i.e., adaptive trials, are more valuable than trials without this flexibility. To quantify this value, we propose modeling the accrual of information in a clinical trial as a sequence of real options, allowing us to systematically design early-stopping decision boundaries that maximize the economic value to the sponsor. In an empirical analysis of selected disease areas, we find that when a therapy is ineffective, our adaptive financing method can decrease the expected cost incurred by the sponsor in terms of total expenditures, number of patients, and trial length by up to 46%. Moreover, by amortizing the large fixed costs associated with a clinical trial over time, financing these projects becomes less risky, resulting in lower costs of capital and larger valuations when the therapy is effective.

Keywords: Clinical trial design; Bayesian adaptive platform trial; Drug approval process; Real options; Capital budgeting (search for similar items in EconPapers)
JEL-codes: G11 G13 G31 G32 I10 I11 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:240:y:2024:i:2:s030440762030364x

DOI: 10.1016/j.jeconom.2020.08.012

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