For years, FDA has been progressively accepting in silico evidence. PBPK models, MIDD frameworks, virtual bioequivalence, and computational approaches have been finding their place in regulatory submissions across drug development.
But June 3, 2026 marks something new.
For the first time, FDA‘s CDER has accepted the first Letter of Intent for an in silico Drug Development Tool (DDT) under the ISTAND programme. An AI-driven model to predict Drug-Induced Liver Injury (DILI).
This is a significant shift in how FDA is engaging with in silico science. It is no longer just about accepting outputs from validated models. FDA is now actively encouraging and creating a formal qualification pathway for the development of new in silico software tools themselves.
That is a different conversation entirely. đ
â„ From accepting in silico evidence to qualifying the tools that generate it
â„ From case-by-case regulatory flexibility to a structured DDT qualification programme
â„ From computational methods as a complement to AI-driven tools as regulatory-grade instruments
The accepted tool uses AI to compare chemical structures of new drug candidates against historical reference drugs with known DILI risk. Supporting smarter, faster preclinical decision-making before Phase I even begins.
DILI is one of the most common reasons drugs fail in clinical trials. Getting this prediction right earlier matters enormously. For patients, for timelines, and for cost.
At InSilicoMinds, we have been building toward exactly this moment. Helping pharma and biotech companies develop PBPK-based toxicity frameworks, MIDD strategies, and regulatory-grade in silico evidence that regulators are increasingly ready to trust.
The infrastructure is being built. The pathways are opening. đ
Is your drug development strategy positioned to take advantage of this?
We are here to help. đ€
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