Drug developers increasingly incorporate computational/in silico solutions to reduce costs and improve translation from the bench to the clinic. But even with these tools, challenges persist in determining efficacy, disease pathways, mechanism of action, toxicity, best route of administration and ideal formulation.
Now, predictive AI and machine learning techniques are filling gaps previously out of reach to traditional approaches.
View this recorded discussion with VeriSIM Life CEO & Founder Dr. Jo Varshney and Dr. Jeff Barrett, CSO at Aridhia, to learn:
- What is model-informed drug development (MIDD)
- High level level paradigm for yielding outputs from data inputs
- Role of machine learning in a "fused" framework
- Explainability
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