Joel Karpiak
Head, Protein Design & Informatics GSK
Joel joined GSK in 2015 from UCSF, where he focused on large-scale modeling and virtual screening for orphan GPCRs. Initially working in small molecule design for over 5 years, he transitioned over into growing the Protein Design & Informatics group for the past 3 years. In this role, he championed how data can be generated and used to drive structure- and machine learning-based design of reagents, biocatalysts, and therapeutic proteins to support new ways of working in discovery and development. Now leading a department in the Data, Automation, and Predictive Sciences organization, the team is the predictive engine for R&D, focusing on researching and embedding new methods to enable the vision of automation of the entire Design-Make-Test-Analyze cycle, driving Lab-in-an-Automated-Loop frameworks from target discovery to the clinic.
Seminars
- Defining format-aware benchmarking strategies to quantitatively evaluate AI/CDD performance for complex protein therapeutics across function, developability, and manufacturability
- Integrating AI-driven protein design with experimental data generation to optimize for biological activity and CMC-relevant properties across bispecifics, multispecifics, and ADCs
- Addressing nuanced data generation, standardization, and scaling challenges relevant to complex proteins to improve predictive accuracy for stability, aggregation, and functional performance in advanced protein formats
