Artificial intelligence companies are developing virtual drug trials that could help pharmaceutical firms predict whether experimental treatments are likely to succeed before moving deeper into costly human studies.
The technology uses AI models trained on medical, genetic and clinical data to simulate how different groups of patients might respond to a drug. Developers say these simulations could help researchers identify weaker drug candidates earlier and improve the design of clinical trials.
The push comes as drugmakers face high costs and low success rates in clinical development. By testing potential outcomes digitally, AI companies hope to reduce the number of unsuccessful candidates that reach expensive late-stage trials while helping researchers make better decisions about which treatments to advance.
Virtual trials are not expected to replace studies involving real patients. Instead, the technology is being positioned as an additional tool that could complement traditional clinical research, potentially making drug development faster, more targeted and less expensive.AI, Healthcare, Drug Development, Clinical Trials, Biotechnology, Pharmaceuticals, Technology
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