From Lead Optimization to Drug Candidate Triage: A Data-Driven Approach to Drug Discovery

Sponsored by Revvity Signals Software, Inc., formerly PerkinElmer Informatics

How does a potential hit compound evolve into a lead and then a potential drug candidate? In the pursuit of the one potential successful candidate, many are made and tested through the discovery, clinical and regulatory approval stages. The development of a novel drug candidate requires engagement of various scientific expertise domains including chemistry, biology, bioinformatics, pharmacology and ADME/PK. Often these domain experts work in disparate locations or even disparate companies, as CROs may be involved in the process.

The Signals Research Suite covers the functionality of the entire Make-Test-Decide Workflow effectively and Cloud implementation permits accessibility from disparate locations. Beginning with the Make process- drawing structures with ChemOffice+ or reading in a database of structures in a variety of supported data formats and searching vendor catalogs for synthesis materials (within the same platform environment, including biologics). Compound registration to Test (submitting compounds to assay (plating, instrument files)) to Decide (analysis of data, graphing and publishing results), and sharing all results transparently stored in the Cloud. Pharmacologists can plan animal tests, and dosing studies. Formulations can be developed and spectroscopic and SPR assay studies stored within the Signals Research platform as well.

This presentation illustrates the use of the Signals Informatics Platform from lead optimization to drug candidate triage, with Signals Notebook (Make); content data capture and collaboration with Signals Vitro Vivo (Test); and results – data-driven scientific decisions with Signals Inventa (Decide).

A case study will be described which illustrates improved productivity and data transparency through enhanced collaboration, and improved workflows all performed in the Cloud.

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