Use of precision methods to accelerate drug development in oncology. Issue 2 (4th March 2017)

• Record Type: Journal Article
• Authors: O'Sullivan Coyne, Geraldine; Ivy, S. Percy; Conley, Barbara A.
• Is Part Of: Expert review of precision medicine and drug development. Volume 2:Issue 2(2017)
• Page Start: 109
• Page End: 120
• Publication Date: 2017-03-04
• Subjects: Precision medicine -- patient derived models -- genomically-engineered models -- biomarkers -- cancer -- drug development -- genomics; Personalized medicine -- Periodicals; Drug development -- Periodicals; 615.19005
• DOI: 10.1080/23808993.2017.1311773
• Languages: English
• ISSNs: 2380-8993

Abstract

ABSTRACT: Introduction : To allow broader application of cancer precision medicine, consideration of how use of molecular abnormalities could enhance the drug development plan and how these findings inform drug combination therapy should begin early. This requires a framework to define molecular 'actionability, ' and a screening plan for enrichment of clinical trials with patients thought most likely to benefit. Areas covered : Literature was reviewed to illustrate how preclinical studies, including patient derived models and genetically engineered models are used to find initial predictive biomarkers. Co-clinical trials and studies of exceptional responders can postulate which molecular variants predict response. 'Actionable mutations (or molecular variants)' are refined during early clinical trials, based initially on preclinical evidence, but gathering additional signals from clinical trials and exceptional responders. Use of biomarkers in early drug development to understand the drug's interaction with the intended target enhance confidence that future development will be fruitful. Expert commentary : Issues remaining to be solved include the timing of tumor profiling for optimal use of precision medicine, assessment of the effect of tumor heterogeneity within individual patients and development of efficient methods for testing combinations and for understanding the functional impact of various genomic variants, such as mutations and co-mutations.