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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Genotype-based risk and pharmacogenetic sampling in clinical trials
Nicholas J Schork1, Eric J Topol
1Scripps Translational Science Institute and Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, USA. nschork@scripps.edu
Journal of Biopharmaceutical Statistics
|March 24, 2010
Summary
Selecting trial participants based on genetic variations identified in genome-wide association studies can significantly reduce sample sizes. This approach enhances clinical trial efficiency for common complex diseases and pharmacogenetic studies.
Area of Science:
- Genetics
- Clinical Pharmacology
- Biostatistics
Background:
- Genome-wide association studies (GWAS) reveal links between genetic variations (SNPs) and complex diseases.
- Genotyping can stratify populations for disease susceptibility and drug response.
- Clinical trial design can be improved by incorporating genetic information.
Purpose of the Study:
- To evaluate the utility of genotype-based participant selection in clinical trials.
- To assess the impact of GWA-identified variants on trial sample sizes.
- To determine sample size bounds for pharmacogenetic trials.
Main Methods:
- Constrained analysis of disease outcome risks by genotype.
- Incorporated observed drug responses from clinical trials.
- Evaluated hypothetical trial designs for multiple diseases (macular degeneration, obesity, heart disease, type II diabetes, prostate cancer, Alzheimer's).
Main Results:
- Restricting trials to specific genotypic profiles substantially reduces required sample sizes.
- Demonstrated significant sample size reductions across various disease contexts.
- Derived realistic sample size estimations for pharmacogenetic studies.
Conclusions:
- Genotype-guided participant selection is a powerful strategy for optimizing clinical trial efficiency.
- Leveraging GWA findings can lead to smaller, more targeted clinical trials.
- This approach has broad applicability in developing drugs for complex diseases.
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