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Clin Cancer Res. 2016 Jun 1;22(11):2618-22. doi: 10.1158/1078-0432.CCR-15-2645.

Nonclinical Evaluations of Small-Molecule Oncology Drugs: Integration into Clinical Dose Optimization and Toxicity Management.

Author information

1
Department of Safety Assessment, Genentech, San Francisco, California. International Consortium for Innovation and Quality in Pharmaceutical Development DruSafe Leadership Group, Washington, District of Columbia.
2
Office of Hematology and Oncology Products, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland.
3
International Consortium for Innovation and Quality in Pharmaceutical Development DruSafe Leadership Group, Washington, District of Columbia. Toxicology and Pathology, Eli Lilly and Company, Indianapolis, Indiana.
4
Preclinical Safety, Sanofi, Waltham, Massachusetts.
5
Office of Hematology and Oncology Products, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland. todd.palmby@fda.hhs.gov.

Abstract

Multidisciplinary approaches that incorporate nonclinical pharmacologic and toxicologic characterization of small-molecule oncology drugs into clinical development programs may facilitate improved benefit-risk profiles and clinical toxicity management in patients. The performance of the current nonclinical safety-testing scheme was discussed, highlighting current strengths and areas for improvement. While current nonclinical testing appears to predict the clinical outcome where the prevalence of specific adverse effects are high, nonclinical testing becomes less reliable for predicting clinical adverse effects that occur infrequently, as with some kinase inhibitors. Although adverse effects associated with kinase inhibitors can often be predicted on the basis of target biology, drugs can be promiscuous and inhibit targets with poorly defined function and associated risks. Improvements in adverse effect databases and better characterization of the biologic activities of drug targets may enable better use of computational modeling approaches in predicting adverse effects with kinase inhibitors. Assessing safety of a lead candidate in parallel with other drug properties enables incorporation of a molecule's best features during chemical design, eliminates the worst molecules early, and permits timely investigation/characterization of toxicity mechanisms for identified liabilities. A safety lead optimization and candidate identification strategy that reduces intrinsic toxicity and metabolic risk and enhances selectivity can deliver selective kinase inhibitors that demonstrate on-target adverse effects identified nonclinically. Integrating clinical and nonclinical data during drug development can facilitate better identification and management of oncology drugs. Follow-up nonclinical studies may be used to better understand the risks in a given patient population and minimize or manage these risks more appropriately. Clin Cancer Res; 22(11); 2618-22.

PMID:
27250932
DOI:
10.1158/1078-0432.CCR-15-2645
[Indexed for MEDLINE]
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