Publications & Blog
A New Era: Human-First Drug Development
On July 4, 2025, the National Institutes of Health (NIH) unveiled a groundbreaking policy shift poised to redefine the future of biomedical research. NIH announced that it is moving away from traditional animal-only models and will prioritize cutting-edge, human-based research technologies such as artificial intelligence (AI) that offer greater clinical relevance, precision, and ethical responsibility.
A New Era: Human-First Drug Development
On July 4, 2025, the National Institutes of Health (NIH) unveiled a groundbreaking policy shift poised to redefine the future of biomedical research. NIH announced that it is moving away from traditional animal-only models and will prioritize cutting-edge, human-based research technologies such as artificial intelligence (AI) that offer greater clinical relevance, precision, and ethical responsibility.
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AI-Driven Integration of Transcriptomics, Quantum Mechanics, and Physiology for Predicting Drug-Induced Liver Injury in Data-Limited Scenarios
The approach used in the study, especially the incorporation of knowledge-based features to enrich AI models, holds tremendous promise for not only assessing safety and toxicity assessments of drug candidates but also in other aspects such as target engagement and efficacy of these candidates, early in the development phase.
AI-Driven Integration of Transcriptomics, Quantum Mechanics, and Physiology for Predicting Drug-Induced Liver Injury in Data-Limited Scenarios
The approach used in the study, especially the incorporation of knowledge-based features to enrich AI models, holds tremendous promise for not only assessing safety and toxicity assessments of drug candidates but also in other aspects such as target engagement and efficacy of these candidates, early in the development phase.
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FDA Signals a New Era for Drug Development — VeriSIM Life Is Already There
From the beginning, VSL has pioneered a mission-driven approach rooted in the belief that advanced simulations can replace outdated, animal-centric paradigms that have limited applicability to humans. The FDA now explicitly affirms that AI-based computational modeling can reliably simulate how monoclonal antibodies (mAbs) distribute through the human body, predict side effects based on molecular features, and accelerate therapeutic delivery without compromising safety. That’s exactly what VSL already enables and more!
FDA Signals a New Era for Drug Development — VeriSIM Life Is Already There
From the beginning, VSL has pioneered a mission-driven approach rooted in the belief that advanced simulations can replace outdated, animal-centric paradigms that have limited applicability to humans. The FDA now explicitly affirms that AI-based computational modeling can reliably simulate how monoclonal antibodies (mAbs) distribute through the human body, predict side effects based on molecular features, and accelerate therapeutic delivery without compromising safety. That’s exactly what VSL already enables and more!
VeriSIM Life’s Alignment with Recent FDA Draft Guidelines
VeriSIM Life's BIOiSIM platform is highly aligned with the core principles of new FDA documents, as it leverages advanced artificial intelligence (AI) and machine learning (ML) approach to simulate complex pharmacokinetics and pharmacodynamics models. This approach ensures robust predictions of drug behavior in diverse patient populations, aligning directly with the guideline's emphasis on physiologically based pharmacokinetics (PBPK) and quantitative systems pharmacology.
VeriSIM Life’s Alignment with Recent FDA Draft Guidelines
VeriSIM Life's BIOiSIM platform is highly aligned with the core principles of new FDA documents, as it leverages advanced artificial intelligence (AI) and machine learning (ML) approach to simulate complex pharmacokinetics and pharmacodynamics models. This approach ensures robust predictions of drug behavior in diverse patient populations, aligning directly with the guideline's emphasis on physiologically based pharmacokinetics (PBPK) and quantitative systems pharmacology.
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Introducing AtlasGEN™ Novel Drug Designer
AtlasGEN Novel Drug Designer efficiently identifies new molecules based on favorable chemical properties and simultaneously evaluates them for clinical safety and effectiveness based on biology using VeriSIM Life’s groundbreaking Translational Index™ technology.
Iterative ranking of target engaging hits by their Translational Index values reduces the time and cost associated with other computational hit discovery approaches, while compressing the hit-to-lead refinement and optimization process by pre-validating hits for translatability. This unique integration dramatically reduces the number of compounds to evaluate in subsequent experimental research.
The ability to generate target engaging compound hits depends largely on the size of the molecular search library. The AtlasGEN search space is supported by more than 1 trillion compounds. Generative AI and deep learning techniques deliver unprecedented discovery capability.
AtlasGEN accurately predicts protein-lygand binding affinity by combining geometric conformer analysis with machine learning based on experimental data 72% more efficiently than molecular docking-based approaches.
