Chemical Liability Screening for Biotherapeutic Proteins – Using a Proteomic Approach and High-Throughput Data Analysis to Identify Antibody Chemical Liabilities in Early-Stage Discovery
Chemical liabilities can derail even the most promising biotherapeutic candidates, making early, systematic risk assessment essential. In this webinar, discover how Genedata enables a unified, data‑centric strategy for identifying and mitigating chemical instability across diverse protein formats.
You’ll see how Genedata brings together biologics formulation software, advanced sequence‑structural analysis software, and high‑throughput developability screening software to streamline liability detection at scale. By integrating antibody informatics, ADC development workflows, and comprehensive in silico screening software, Genedata equips discovery teams to pinpoint oxidation, deamidation, and other degradation‑prone hotspots before they become downstream bottlenecks.
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.
The session also highlights how AI-driven developability prediction software, generative AI protein design software, and modern analytics operationalize AI in drug development, enabling scientists to evaluate chemical risks earlier and more accurately within broader drug discovery and development programs. With this integrated developability assessment platform, organizations can confidently prioritize stable, manufacturable molecules and accelerate the path to high‑quality biologics.
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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