Adding Quality Control and Validation to Drug Discovery with AI
Two Stories:
Linking biowaivers to clinical endpoints
The proliferation of powerful AI models, including GPTs, has revolutionized how the life sciences industry consumes information and uses it for accelerating and validating research. For example, by leveraging GPTs researchers can complete what would normally be weeks long literature review and data extraction tasks in a matter of minutes or hours. In addition, these models also enhance complex R&D tasks by harnessing massive amounts of information and delivering it in easy to consume formats.
One area where AI can provide immense value in providing the data and insights needed to drive drug development tasks – such as validating the toxicity of molecules or building and annotating mechanistic models that demonstrate the complex interactions of drugs within the human body. For example, significant amounts of data need to be collected to defend a model, but what if GPTs can deliver this data for you to enable interactive models that can be reviewed and validated by colleagues and regulators?
In this webinar, experts from Certara will share novel approaches for leveraging AI to enhance data accessibility and analysis needed for drug development. They’ll provide an educational overview on recent innovations in AI and the critical considerations teams need to take to successfully deploy AI and GPT models within the life sciences R&D pipeline. In addition, attendees will also receive a demonstration of Certara’s application of GPTs for modeling purposes.
Learning Objectives:
• Key considerations for applying private AI models within life science
• Enabling unstructured data access for informing mechanistic models
• Simplified approaches for research data collection
• Visualizations for enabling QC in newly designed models
Sponsored by Certara
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