Drug discovery

Innovating at the intersection of chemistry, biology, and engineering, Professor Brad Pentelute and the Pentelute Lab at MIT invent new chemistry, platforms, and techniques that might revolutionize therapeutics. Their formula in brief: nature-inspired research that begins at the molecular level, infused with state-of-the-art machine learning and automation, aimed at solving real-world problems. Take, for example, biotechnology’s longstanding protein delivery problem. …

Huge libraries of drug compounds may hold potential treatments for a variety of diseases, such as cancer or heart disease. Ideally, scientists would like to experimentally test each of these compounds against all possible targets, but doing that kind of screen is prohibitively time-consuming. In recent years, researchers have begun using computational methods to screen those libraries in hopes of …

Should artificial intelligence be allowed to make care decisions for patients? Though the future of AI may conjure up doomsday visions of robots and computers intent on rendering human existence superfluous, the MIT Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) addressed questions surrounding the use of AI in health through their inaugural summer program focused on …

Discovering new materials and drugs typically involves a manual, trial-and-error process that can take decades and cost millions of dollars. To streamline this process, scientists often use machine learning to predict molecular properties and narrow down the molecules they need to synthesize and test in the lab. Researchers from MIT and the MIT-Watson AI Lab have developed a new, unified …