ENPICOMMaximize AI potential in biologics discovery and development: From model training to consumption
We will discuss the key challenges in creating and deploying machine learning for biologics discovery. While creating complex models for discovery and development is becoming commonplace, managing the entire ML model lifecycle is essential for effective use in therapeutic research and maximizing AI investment returns. Discover how a unified platform can streamline AI use in biologics discovery, from model training to consumption.
Meet the speaker
At ENPICOM, Néstor focuses on analyzing customer requirements, and oversees project setup, management, and execution. During his PhD in Immunology, he isolated and expressed monoclonal antibodies after vaccinations and developed high-throughput sequencing library preparation protocols for B cell repertoires in humans, non-human primates, and other animal models.
