Data Standardization, Pharmaceutical Drug Development, and the 3Rs.

Abstract

Despite the efforts, cost, and extensive use of animals for nonclinical research, only a small number of studies have methodically compared findings from animal toxicology studies to those from human clinical trials. Impediments to understanding the translation of nonclinical safety have included the lack of easy access to data and the need for extensive data curation given the diverse terminologies, formats, and data platforms in use. SEND and SDTM study data standards, developed by CDISC and about to become mandated by FDA, can address this and other drug development issues by facilitating access to data in ways that are not currently feasible. A consistent data standard across clinical and nonclinical will discourage the development of data silos, which easily become obstacles to data sharing and maximizing the value of animal and human data. The confluence of rapid scientific advances, increasingly larger quantities of diverse data, technological advances in data mining, and the FDA's requirements for standardized study data create new opportunities for the advancement of drug development and for refinement in the way we use animals.