Scientists are leveraging artificial intelligence to accelerate the discovery of new drugs to combat tuberculosis, a disease that has seen a 16% rise in cases from 2022 to 2023, with over 9,600 reported cases in the US. Researchers like Kyle Rohde from the UCF College of Medicine are partnering with biotech companies like Atomwise to harness AI’s potential in testing millions of potential drugs against disease models. This collaboration has led to the development of a proprietary AI model that can predict inhibitors of selected targets, identifying top antibiotic candidates. With AI, the research process is significantly accelerated, saving time and money. Rohde believes that AI-based virtual drug screening has the potential to revolutionize the discovery of new antibiotics, providing affordable treatment options for global health problems like TB. This partnership marks a significant step forward in the fight against drug-resistant infections, and its success could have far-reaching implications for the future of scientific research.
AI Boosts TB Drug Discovery
With the help of AI, Atomwise was able to eliminate more than two million compounds unlikely to inhibit the TB bacteria.
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