GATC Health Highlights Expert Presentations at Veterinary Conference, Underscoring Commitment to Eliminating Animal Testing
DATE
May 19, 2025
CATEGORY
Company
Irvine, CA – May 19, 2025 – GATC Health Corp announces the expert presentations by Chief Science Officer Ian Jenkins and Scientific Advisory Board Chair Dr. Jonathan RT Lakey at the recent Pet Stem Cell Conference, hosted by DLEAP, held recently in Nassau, Bahamas. Their presentations were part of GATC Health’s broader initiative to bring visibility to advanced technologies that aim to replace animal testing with human-relevant, AI-driven solutions.
Animal testing has long been considered a necessary, if controversial, step for assessing drug safety in pre-clinical research. But public opposition, animal welfare advocate groups, and now the federal government are moving to reduce and eventually eliminate the practice. This is due to the overwhelming evidence that human-relevant methodologies, and specifically advancements in artificial intelligence, provide more accurate results, in less time and lower cost, while eliminating ethical concerns regarding animal harm.
Ian Jenkins’ Presentation: Advancing Beyond Animal Models
Ian Jenkins delivered a featured talk, “From Animal Models to Algorithms: Pioneering Ethical Innovation in Preclinical Animal and Human Drug Safety with AI,” emphasizing the limitations of traditional animal testing in drug development. He highlighted that approximately 90% of drugs passing animal studies ultimately fail in human trials, largely due to species-specific differences that limit translational validity. Jenkins outlined how GATC Health’s Multiomics Advanced Technology™ (MAT) platform leverages artificial intelligence to simulate human biochemistry, enabling more predictive and ethical preclinical research.
GATC Health’s MAT platform integrates genomics, proteomics, and metabolomics data to model disease states and predict drug efficacy, safety and off-target effects. This approach aligns with the FDA’s Modernization Act and AI adoption plans, as well as recent NIH guidance, both of which encourage the adoption of New Approach Methodologies (NAMs) that prioritize human-relevant data over animal models. By replacing or augmenting animal testing with validated in silico models, GATC Health’s technology can significantly reduce costs, accelerate timelines, and improve the likelihood of clinical success, while sparing millions of animals annually.
Dr. Lakey’s Expertise in Regenerative Medicine
Dr. Jonathan RT Lakey, PhD, MSM a recognized leader in diabetes and islet transplantation, contributed insights on advances in regenerative medicine and stem cell therapies. His presentation complemented GATC’s vision for a future in which AI-driven platforms support both human and veterinary health without reliance on animal testing.
“The conference was an opportunity to discuss GATC’s novel AI technology in reducing animal use in biomedical research and to discuss stem cell technologies that can benefit companion pets. This annual conference was attended by both leading biotechnology researchers and government agencies in the Bahamas and surrounding Caribbean countries,” stated Dr. Lakey.
A Broader Commitment to Human-Relevant Innovation
The DLEAP Conference presentations are part of GATC Health’s ongoing commitment to advancing ethical, efficient, and scientifically robust alternatives to animal testing. By championing AI-powered NAMs, GATC Health is helping to set a new industry standard—one that delivers safer, faster, and more equitable access to therapies while meeting evolving regulatory and societal expectations.
About GATC Health Corp
GATC Health Corp. is a tech-bio company transforming drug discovery and development through its AI-driven platform and approach. The company’s validated and proprietary Multiomics Advanced Technology™ (MAT) simulates human biochemistry’s billions of interactions to rapidly create novel therapeutics, identify and confirm targets, accelerate development, and derisk drug pipelines by predicting efficacy, safety, and off-target effects.
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