Hybrid Model Federated Learning RFI2024.2

NIIMBL is pleased to announce this Request for Information (RFI) to seek innovative approaches that combine Federated Learning with hybrid models (combining Physics-Based and AI/ML data-driven methodologies) specifically tailored for biopharmaceutical manufacturing processes. This request aims to gather insights and concepts for achieving integration and operationalization of these models in a practical, industry-relevant context. By fostering collaboration among a wide range of stakeholders, we aim to enhance prediction accuracy of Hybrid Models for biopharmaceutical process predictions using Federated Learning and other Privacy Preserving Computing approaches. This initiative seeks to train a centralized model using community data while maintaining data privacy.

This RFI is a preliminary step to gauge interest and gather insights which may shape future studies or funding opportunities in Hybrid Model Federated Learning. This RFI is not a solicitation for funding proposals. We encourage contributions from all interested parties to become integral parts of this innovative endeavor.