Chemical Liability Screening for Biotherapeutic Proteins – Using a Proteomic Approach and High-Throughput Data Analysis to Identify Antibody Chemical Liabilities in Early-Stage Discovery
In this webinar, learn how Sanofi is transforming early-stage drug discovery by integrating high-throughput chemical liability screening into its antibody development workflows. This innovative approach boosts screening throughput by up to 100-fold, enabling earlier identification of candidates with favorable developability profiles.
Dr Jennifer Kuehn, Lab Head Assays & Analytics at Sanofi, and Xiaohua Li, Principal Scientist at Sanofi, share how Sanofi and Genedata partnered to co-develop new functionalities in Genedata Expressionist that enable automated mass spectrometry (MS)-based analytics for early chemical liability screening. By combining proteomics-like measurements with advanced automation, intelligent data analysis, and a centralized repository, Sanofi accelerates candidate selection, reduces manual effort, and improves data quality.
Learn how:
- Chemical liability screening at an early stage during antibody therapeutics development increases the probability of success by improving molecule quality and accelerates the development process and time to clinic.
- Combining a proteomics approach with High-Throughput (HT) data analysis can increase the throughput of chemical liability detection up to 100-fold, enabling the screening of large sample libraries at an early stage with a limited amount of sample.
- Large-scale data collection enables the development of ML models for AI-based drug discovery.
Who should watch:
- Biopharma, Biotech, and CRO R&D managers, analytical scientists, and lab heads who are seeking to implement automated Mass Spectrometry (MS)-based analytics for high-throughput drug screening.
- Biopharma, Biotech, and CRO organizations looking for an enterprise platform to streamline MS analytics in early-stage drug discovery and across the biotherapeutic R&D.
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