Chinese and US scientists create AI model to help develop new drugs
- ActFound performed better in tests than competing models and could offer a cost-effective alternative to traditional methods
Scientists in China and the United States say they have developed a new artificial intelligence (AI) model that could help overcome some major challenges to drug development and discovery.
The model, called ActFound, outperforms competing models while bypassing challenges to using machine learning in bioactivity prediction, according to a paper published in Nature Machine Intelligence.
“Bioactivity encompasses various properties of compounds, such as their interaction with targets, impact on biological systems and therapeutic effects,” said the researchers from Peking University, the University of Washington and AI tech firm INF Technology Shanghai.
The main challenges to using machine learning include limited data labelling and incompatibility between assays, the tests that measure the activity or potency of drugs.
The model not only outperforms competing AI models, but also functions as well as free-energy perturbation (FEP) – a traditional computational method.
Although FEP calculations have a high level of accuracy, the team warned that they “require extensive computational resources that are often not affordable for large-scale applications”.
