Solutions > Computational Lead Generation and Optimization Across Modalities

Computational Lead Generation and Optimization Across Modalities

Many modalities are emerging that necessitate the formation of models connecting modality properties with their structure. Screening of therapeutic antibodies, cell therapies, and nucleic-acid-based therapeutics often require bespoke methods and tools with little commercial support. bPrescient can help, with data-driven, multi-parametric optimization for molecule performance. We provide a quantitative approach to structure-activity relationship for small molecules, antibodies, mRNA, and antisense oligonucleotides.

Solution Overview

Our solution for Computational Lead Generation and Optimization Across Modalities includes:

Both classic small molecule and novel modality translation of high-throughput and high-content screening into quantitative structure-activity relationship models.

Development of machine learning and AI methods to predict molecular properties.

Multi-parametric approaches to optimize molecular properties across a frontier of performance criteria.

Optimization of screening approaches and experiment designs to maximize per-assay information yield.

Development of lead generation data strategy that brings together best-in-breed tools for registration, sample tracking, plating, screening, analysis, and validation.

Implementation of platforms for screening, analysis, and reporting using off-the-shelf and custom tools with emphasis on data integration to build an end-to-end solution.

Solution Benefits

Partnering with bPrescient benefits your R&D program in a variety of ways:

Rapid QSAR development to accelerate the hit to lead and lead to candidate processes.

Optimization methods to improve the performance of prioritized molecules in their pipeline phase transitions, increasing downstream success rates of hits.

Optimal use of limited materials and time to maximize information yield of assay campaigns.

End-to-end data tracking of screening and validation processes leads to improved throughput and continuous process refinements.

Robust registration and sample management lead to more efficient and accurate lab work and interfaces with partners and CROs.

Relevant Expertise

This service draws on our expertise in the following areas:

Strategy & Roadmap Development

Scientific Informatics: Software Design and Implementation

Laboratory Data Systems Design, Integration & Optimization

AI & Machine Learning: Generating Novel Insights

Computational Sciences for Biology & Chemistry Research

Data Engineering, MLOps, and CloudOps

Let’s talk

Tell us about your toughest R&D challenge and let’s discuss how bPrescient can solve it.

Computational Lead Generation and Optimization Across Modalities

Solution Overview

Solution Benefits

Relevant Expertise

Example Tools and Data Sources

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