Opportunities In Preclinical Development

Preclinical development encompasses various scientific disciplines, from pharmacology and drug metabolism to formulations and bioanalysis. Each domain generates critical data that must be managed effectively to meet regulatory requirements. However, streamlining these processes involves more than just implementing informatics solutions. It requires a holistic approach that combines efficient lab workflows with robust data management strategies.

This white paper delves into the specific challenges each preclinical domain faces, from noisy data in pharmacology to automated decision-making in drug metabolism and the critical role of bioanalysis in sample management. We also examine best practices for improving the "data value chain," which connects all preclinical domains, ensuring data is accessible, accurate, and ready for regulatory submissions. Moreover, we discuss how many organizations have navigated these challenges, offering lessons on avoiding common pitfalls, such as attempting overly ambitious projects too soon.

By addressing both laboratory and informatics processes, this white paper provides actionable insights for optimizing preclinical development while reducing project delays and increasing overall efficiency.