One benefit the use of AI brings to health systems is making gathering and sharing information easier. AI can help providers keep track of patient data more efficiently.
One example is diabetes. According to the Centers for Disease Control and Prevention, 11.6% of the US population has diabetes. Patients can now use wearable and other monitoring devices that provide feedback about their glucose levels to themselves and their medical team.
AI can help providers gather that information, store, and analyze it, and provide data-driven insights from vast numbers of people. Using this information can help healthcare professionals determine how to better treat and manage diseases.
Organizations are also starting to use AI to help improve drug safety. The company SELTA SQUARE, for example, is innovating the pharmacovigilance (PV) process, a legally mandated discipline for detecting and reporting adverse effects from drugs, then assessing, understanding, and preventing those effects.
PV demands significant effort and diligence from pharma producers because it’s performed from the clinical trials phase all the way through the drug’s lifetime availability. Selta Square uses a combination of AI and automation to make the PV process faster and more accurate, which helps make medicines safer for people worldwide.
Sometimes, AI might reduce the need to test potential drug compounds physically, which is an enormous cost-savings. High-fidelity molecular simulations can run on computers without incurring the high costs of traditional discovery methods.
AI also has the potential to help humans predict toxicity, bioactivity, and other characteristics of molecules or create previously unknown drug molecules from scratch.