Client success story
Computational Chemistry Modeling
Business Value Delivered: Higher Quality Leads Identified
Summary: Improved Productivity Through Design Tool Adoption
bPrescient worked with a drug company in the oncology degrader medicines space to apply modern cheminformatics tools to structure-based and ligand-based drug design to increase discovery productivity.
Challenge: Lack Of Cheminformatics Skills Slows Progress
An early-stage therapeutics company in the protein degrader space aspires to use up-to-date computer-aided drug design techniques to improve their productivity, but lacked in-house expertise to drive tool adoption and define best practices. Without these productivity gains, the company risked falling behind their competitors and not gaining their next round of funding.
Solution: Knowledge Transfer Leads To Adoption And In-House Expertise
bPrescient provided a computation chemistry subject matter expert who provided expertise in drug design degrader optimization, and protein homology mapping, computational chemistry software such as Schrodinger and Biovia, and programming tools such as KNIME and ProteinPilot. The expert worked with the customer’s cross-functional teams to mentor staff, define SOPs and develop modeling and simulation skills across the discovery organization.
Outcome: Improved Drug Design
The customer’s team increased their expertise in computational chemistry, gained knowledge of new commercial tools, and received newly-developed applications to meet their cheminformatics needs. These capabilities allowed the customer to more efficiently identify new candidate molecules and move those candidates into in vitro validation.
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