Neuroscientists have trained artificial intelligence (AI) to predict drug responses with over 80% accuracy, offering hope for targeted and personalized medicine. Led by neuroscientist Kirill Martemyanov at The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology in Florida, an international team used a molecular tracking technology to profile the action of more than 100 prominent cellular drug targets. They then developed and trained an AI-anchored platform using this data, which accurately predicted how cell surface receptors would respond to drug-like molecules in 80% of cases.
The team’s long-term goal is to refine the AI tool to help design precision medications. Currently, many medicines have a one-size-fits-all approach, but individuals have tremendous variability in their cell receptors. By knowing the exact genetic alteration a person has, doctors could prescribe drugs tailored to their specific needs, improving effectiveness and reducing the risk of harmful side effects.
One-third of all drugs work by binding to cell-surface receptors called G protein-coupled receptors (GPCRs), which are involved in a range of biological activities. These receptors are complex structures that cross the cell membrane, with a docking station on the cell’s exterior and a branch that extends into the cell. When a drug binds to a GPCR, it triggers a cascade of changes inside the cell.
The team’s research focused on cataloging the activity of GPCRs and their genetic variations. They used a technology called bioluminescence resonance energy transfer to observe and document the signaling in a comprehensive way. By gathering data on the activation rate, amplitude, and selectivity of GPCRs, as well as incorporating genetic variants, the team was able to train the AI to make predictions based on this nuanced information.
The potential impact of this research is significant. By gaining a deeper understanding of GPCRs and their activities, and by incorporating genetic variation data, drug developers could create safer medicines more efficiently and at a lower cost. The researchers’ ultimate goal is to predict how individual genetic variants respond to drugs, enabling the custom tailoring of prescriptions and paving the way for precision medicine.
The team’s study, published in the journal Cell Reports, has attracted attention in the scientific community and is likely to inspire further research into the role of GPCRs in drug response. By leveraging AI and molecular tracking technology, researchers are making strides towards a future where medicine can be personalized and optimized for individual patients’ needs.
