Finding the intended use population for a new treatment

Area of Science:

• Genomic medicine
• Clinical trial design
• Pharmacogenomics

Background:

• Many human diseases exhibit molecular heterogeneity, impacting treatment response.
• Current therapeutics often have a high number needed to treat (NNT), exposing non-benefiting patients to adverse effects.

Purpose of the Study:

• To introduce a novel paradigm for identifying and validating the intended use population for therapeutics.
• To address the challenge of patient stratification in clinical trials.

Main Methods:

• Developed a new approach for estimating the intended use population within randomized phase III clinical trials.
• Framed the determination of the intended use population as a classification problem.
• Ensured the preservation of the trial's type I error rate.

Main Results:

• The proposed method provides an internally validated estimate of the intended use population.
• The approach treats patient stratification as a classification task, distinct from multiple hypothesis testing.

Conclusions:

• This new paradigm enhances the accurate identification of patient populations likely to benefit from targeted therapeutics.
• It aims to minimize patient exposure to ineffective treatments and associated risks.
• The method offers a robust framework for optimizing drug development and clinical trial design.