通过期权定价分析进行财务适应性临床试验

IF 9.9 3区 经济学 Q1 ECONOMICS
Shomesh E. Chaudhuri , Andrew W. Lo
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引用次数: 0

摘要

新疗法的监管审批过程涉及耗资巨大的临床试验,时间可能长达数年。从财务角度评估候选疗法时,如果临床证据表明市场前景不如最初预测的那么好,行业赞助商可能会提前终止项目。直觉表明,可以根据观察到的新数据进行修改的临床试验(即适应性试验)比没有这种灵活性的试验更有价值。为了量化这种价值,我们建议将临床试验中的信息累积建模为一连串的实数期权,这样我们就能系统地设计早期停止的决策边界,使申办者的经济价值最大化。在对选定疾病领域的实证分析中,我们发现当一种疗法无效时,我们的自适应融资方法可以将申办者在总支出、患者人数和试验长度方面的预期成本最多降低 46%。此外,通过随着时间的推移摊销与临床试验相关的巨额固定成本,这些项目的融资风险也会降低,从而在疗法有效时降低资本成本,提高估值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Financially adaptive clinical trials via option pricing analysis

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.

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来源期刊
Journal of Econometrics
Journal of Econometrics 社会科学-数学跨学科应用
CiteScore
8.60
自引率
1.60%
发文量
220
审稿时长
3-8 weeks
期刊介绍: The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal''s interests. The Annals of Econometrics is a supplement to the Journal of Econometrics.
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