A decision theoretical modeling for Phase III investments and drug licensing
Journal article, 2018

For a new candidate drug to become an approved medicine, several decision points have to be passed. In this article, we focus on two of them: First, based on Phase II data, the commercial sponsor decides to invest (or not) in Phase III. Second, based on the outcome of Phase III, the regulator determines whether the drug should be granted market access. Assuming a population of candidate drugs with a distribution of true efficacy, we optimize the two stakeholders' decisions and study the interdependence between them. The regulator is assumed to seek to optimize the total public health benefit resulting from the efficacy of the drug and a safety penalty. In optimizing the regulatory rules, in terms of minimal required sample size and the Type I error in Phase III, we have to consider how these rules will modify the commercial optimization made by the sponsor. The results indicate that different Type I errors should be used depending on the rarity of the disease.

rare diseases

Clinical trials

sample size

optimal Type I error

drug regulation

Author

Frank Miller

Stockholm University

Carl-Fredrik Burman

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Journal of Biopharmaceutical Statistics

1054-3406 (ISSN) 1520-5711 (eISSN)

Vol. 28 4 698-721

Integrated DEsign and AnaLysis of small population group trials (IDEAL)

European Commission (EC) (EC/FP7/602552), 2013-11-01 -- 2016-10-31.

Subject Categories

Pharmaceutical Sciences

Biomedical Laboratory Science/Technology

Social and Clinical Pharmacy

DOI

10.1080/10543406.2017.1377729

PubMed

28920757

More information

Latest update

8/31/2018