Advancements in AI & machine learning in chemistry are revolutionizing research by enhancing reaction predictions, material design, and drug discovery. Machine learning models analyze vast chemical datasets, accelerating compound screening and reaction optimization. AI-driven simulations reduce trial-and-error in experiments, making chemical processes more efficient and sustainable. Neural networks and predictive algorithms improve molecular modeling, enabling precise identification of novel compounds. Automation in data analysis streamlines workflows in spectroscopy, chromatography, and synthesis. The integration of AI with experimental chemistry fosters innovation across multiple fields, from pharmaceuticals to green chemistry. As computational power grows, machine learning continues to reshape chemical research, driving faster discoveries and smarter, data-driven solutions.
Title : Personalized and Precision Medicine (PPM) as a unique healthcare model through biodesign-inspired and upgraded business marketing to secure the human healthcare and biosafety
Sergey Suchkov, National Center for Human Photosynthesis, Aguascalientes, Mexico
Title : Eliminating implant failure in humans with nano chemistry: 30,000 cases and counting
Thomas J Webster, Brown University, United States