Implementing Allotrope Framework in Biotech: Case Study with MacroMoltek & ZONTAL
Introduction
Monica Berrondo, CEO of MacroMoltek, and Dennis Della Corte, CSO of ZONTAL, presented a case study showcasing their collaboration. The project utilized SciY’s ZONTAL Data Platform as a data management hub, enabling the use of machine learning for data science. This integration significantly improved the efficiency and quality of MacroMoltek's analyses.
MacroMoltek's Vision and Approach
Goal: Transform antibody design from drug discovery to drug design using advanced AI.
Team: Experts in computer science, machine learning, biology, engineering, and therapeutic development.
Method: Use proprietary algorithms and neural networks to design antibodies, leveraging extensive structural and sequence data.
Data Management Needs
Challenges: Efficiently storing, cataloguing, and accessing vast amounts of data for cross-project analysis.
Solution: The Data Platform ensures data accessibility, searchability, and consistent tracking from early stages to validated antibodies.
Implementation Insights
Approach: Start with tabular models to demonstrate benefits without overwhelming details.
Process: Subject matter experts provide basic data model ideas; the Data Platform handles data FAIRification and ontology creation.
Outcome: Self-reporting data assets and democratized data access via searchable APIs.
Case Study Impact
Before: Data management involved individual Excel documents for each ELISA assay.
After: Data from multiple assays is mapped, preserved, and made available for comprehensive analysis on the Data Platform dashboard.
Benefits: Improved data monitoring, analysis, and feedback for AI algorithms.
This case study highlights how Data Management can facilitate the design of antibodies, using AI, in a Biotech setting.