One paper presented at IEEE International Conference on Future Machine Learning and Data Science 2025 covers Verseon’s superior predictions of drug-target interactions; another covers how the company’s AI produces more accurate estimation of biological age.
FREMONT, Calif., Nov. 6, 2025 /PRNewswire/ — Verseon has presented two separate papers at the November 2025 IEEE International Conference on Future Machine Learning and Data Science that demonstrate the advantages of its VersAI™ platform in the life sciences. One paper describes Verseon’s novel AI-based approach for predicting drug-target interactions to aid in drug discovery and development. The other paper describes Verseon’s latest innovation to predict a person’s “true” biological age. IEEE will make the full text of Verseon’s papers publicly available in approximately one month.
Predicting drug-target interactions is an important consideration during the process of developing novel drugs. Building on the company’s advances in graph neural network architectures to better capture the topology of knowledge graphs, Verseon’s first paper, “A novel graph neural network approach for predicting drug-target interactions,” presents techniques that dramatically outperform current state-of-the-art methods, producing results with a 41% lower error rate in benchmark tests on the widely used ChG-Miner dataset.
“The implications of more accurately predicting drug-protein interactions are profound. These predictions accelerate drug discovery efforts, reduce the costs imposed by exploring ‘dead-end’ drug candidates, and improve the safety of drug candidates that advance through clinical trials and reach market,” says Verseon’s CSO David Kita.
The second paper describes VersAge, Verseon’s approach to better characterize the biological aging process. Verseon has focused on making significantly more accurate predictions based on routinely collected blood biomarkers, urine biomarkers, and other physiological measurements. VersAge provides significantly more accurate results than similar biological aging clocks, with a 27% lower error rate than the nearest competing method.
Accurate estimates of biological age are a crucial component in understanding aging—and developing therapeutics to address its adverse effects.
“The papers and data we’ve presented at the November IEEE conference show how Verseon’s advances in AI produce superior results in life-science applications,” said Verseon’s Head of AI Ed Ratner. “Our innovations will expand the frontiers of what modern medicine can do.”
About Verseon
Verseon International Corporation (www.verseon.com) is a clinical-stage, technology-driven pharmaceutical company transforming the delay, prevention, and treatment of disease. Using its Deep Quantum Modeling + AI platform, Verseon is rolling out a steady stream of life-changing medicines. Each of the company’s drug programs features multiple novel candidates with unique therapeutic properties. None of these candidates can be found by other current methods. Verseon’s fast-growing pipeline addresses major human diseases in the areas of cardiometabolic disorders and cancers. The company’s supporters and advisors include multiple Nobel laureates, former heads of R&D of major pharmaceutical companies, and various key opinion leaders in medicine.
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SOURCE Verseon International Corporation
