According to GlobalData’s Clinical Trials database, AI-related pharmaceutical research in clinical trials predominantly occurs in areas such as oncology and metabolic disorders. AI has been utilised in more than 50 metabolic disorders clinical trials, four of which have been captured by GlobalData’s database so far in 2024. These clinical trials focus on type 2 diabetes (T2D) and obesity.
AI is crucial for the development of metabolic disorders research, since its integration in diabetes and obesity research marks a shift towards a data-driven approach utilising machine learning algorithms for pattern recognition. It is reshaping diabetes research by creating pharmaceutical solutions and developing regulating devices.
In the past two months, clinical trials Structure Therapeutics’s GSBR-1290 and Gubra’s GUB-002496 have begun. The development of these drugs includes the usage of Schrödinger’s and Gubra’s AI platforms consecutively. The clinical trials for GSBR-1290 and GUB-002496 have displayed the potential for advancement in AI-influenced research in metabolic disorders. GSBR-1290 is in Phase II for T2D and obesity. It is one of the only clinical trials set to complete in 2026. Similarly, GUB-002496’s clinical trial was also recently initiated, and it has not yet concluded. GSBR-1290’s likelihood of approval in Phase II is above Phase II’s threshold and GUB-002496’s likelihood of approval in Phase I is above the threshold, so both drugs will be studied in more clinical trials.
Oncology is the dominant therapy area for AI-involved drug research. Notable oncology drugs that used AI in their development include Gritstone Bio Inc’s GRANITE-001, pharmaand GmbH’s satraplatin, and RenovoRx Inc’s gemcitabine hydrochloride. The use of AI in metabolic disorders research began increasing in 2023. Obesity and T2D research have been the focus of research since the development of Novo Nordisk’s Ozempic (semaglitude). Treatments that are more effective and have fewer side effects can be developed with the use of AI since it contributes to the R&D phases of drugs. AI can rule out adverse approaches, making the drug discovery phase faster, which will be beneficial for metabolic research.
More clinical trials in metabolic research should be expected, especially since pharma giants have entered partnerships with AI companies. For example, Eli Lilly has started a partnership with Open AI, and the Australian Government is willing to fund AI’s use in drug research, according to GlobalData’s News database. Even though this funding is currently focused on cardiovascular research, the funding can also go into metabolic disorders research.
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