Multimodal generative machine learning for non-clinical safety evaluations in drug discovery and development

In the evolving landscape of pharmaceutical drug development and a constant reimagination of the Ideas to Patient journey, the integration of multimodal foundation models, generative machine learning, and AI-driven chatbot interfaces has marked a significant leap forward. This talk will present our recent work in building and deploying multimodal foundation models specifically designed for drug toxicity evaluations, as well as the production of intuitive chatbot interfaces to facilitate knowledge discovery and human-in-the-loop assessments throughout the process. Our multimodal foundation models are engineered to process and interpret a variety of data types, including molecular structures, biological assay results, and textual data from scientific literature, along with imaging and computational toxicity data from non-clinical safety studies and toxicologic pathology processes. By harnessing these models, we have enhanced our ability to predict and evaluate potential drug toxicities early in the development pipeline. This not only accelerates the identification of safer drug candidates but also substantially reduces the costs and time associated with traditional toxicity testing methods. In parallel, we have developed and productionized sophisticated chatbot interfaces that serve as powerful tools for knowledge discovery. These chatbots enable teams to interact seamlessly with complex datasets and analytical tools, democratizing access to critical insights and fostering a more collaborative research environment. The chatbots are designed to understand and respond to natural language queries, making advanced data analysis accessible to users regardless of their technical expertise. This talk will showcase applications and case studies where our multimodal foundation models and chatbot interfaces have been successfully implemented. We will discuss the potential impact of these technologies on non-clinical safety evaluations, and improvements in accuracy, efficiency, and decision-making processes. Additionally, we will explore the challenges encountered during development and deployment, as well as the future directions and potential expansions of these innovative tools.