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.
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.
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the beginning, VSL has pioneered a mission-driven approach rooted in the belief that advanced simulations can replace outdated, animal-centric paradigms that have limited applicability to humans.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!
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the beginning, VSL has pioneered a mission-driven approach rooted in the belief that advanced simulations can replace outdated, animal-centric paradigms that have limited applicability to humans.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 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 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.
One major difficulty in FIH dosing is considering variability in human response. The complexity of possible individual responses is challenging to account for using traditional FIH dosing methods, and failure to properly consider these possible variations can result in heightened risk of adverse effects in clinical trial participants. It can also increase the already high cost/time investment of clinical trials. This underscores the need for more sophisticated approaches in FIH dosing that can account for the myriad factors that influence individual human response.
One major difficulty in FIH dosing is considering variability in human response. The complexity of possible individual responses is challenging to account for using traditional FIH dosing methods, and failure to properly consider these possible variations can result in heightened risk of adverse effects in clinical trial participants. It can also increase the already high cost/time investment of clinical trials. This underscores the need for more sophisticated approaches in FIH dosing that can account for the myriad factors that influence individual human response.