ENPICOM
Scientific presentation
Making data, analysis, and AI accessible to every scientist
Developing machine learning models for biologics discovery is no longer the hard part. The real challenge is making them usable and impactful within real-world biologics discovery and engineering workflows.
In this session, we examine why promising AI initiatives often stall before delivering value, and what it takes to move from isolated proof-of-concept to integrated, scalable solutions.
- Key roadblocks to AI adoption in biologics R&D
- Why a high-performance data foundation and pipeline automation are essential for AI success
- How a unified platform can streamline the entire ML model lifecycle: from data ingestion and training to deployment and consumption
Meet the speakers
Dr. Nicola Bonzanni founded ENPICOM to bridge the gap between life sciences and technology, empowering researchers with advanced computational tools. His expertise spans computational biology, NGS data analysis, and molecular biology, driving the creation of state-of-the-art software solutions that enhance biologics discovery and AI integration.
