Senior Lecturer Guadalupe Hayes-Mota writes for Forbes about the ways AI is reshaping drug development. “In the next three years, we can anticipate a more streamlined, efficient and cost-effective drug development process, ultimately leading to faster access to life-saving drugs for patients worldwide,” Hayes-Mota writes. “This is not just an evolution; it is a revolution in healthcare powered by the intelligence of machines.”
Landmark Bio, a cell and gene therapy manufacturing company co-founded by MIT and a number of other institutions, is focused on accelerating access to innovative therapies for patients, reports Rowan Walrath for Boston Business Journal. "Landmark's new facility includes laboratory space for research and early-stage drug development, as well as analytics tools,” writes Walrath.
MIT and a number of other local institutions have launched Landmark Bio, a cell and gene therapy manufacturing firm aimed at helping small startups develop experimental therapies that are reliable, consistent, and large enough to be used in clinical trials, reports Ryan Cross for The Boston Globe.
Washington Post reporter Pranshu Verma writes about how Prof. Dina Katabi and her colleagues developed a new AI tool that could be used to help detect early signs of Parkinson’s by analyzing a patient’s breathing patterns. For diseases like Parkinson’s “one of the biggest challenges is that we need to get to [it] very early on, before the damage has mostly happened in the brain,” said Katabi. “So being able to detect Parkinson’s early is essential.”
Forbes contributor Jennifer Kite-Powell spotlights how MIT researchers created a new AI system that analyzes radio waves bouncing off a person while they sleep to monitor breathing patterns and help identify Parkinson’s disease. “The device can also measure how bad the disease has become and could be used to track Parkinson's progression over time,” writes Kite-Powell.
A new tool for diagnosing Parkinson’s disease developed by MIT researchers uses an AI system to monitor a person’s breathing patterns during sleep, reports Hiawatha Bray for The Boston Globe. “The system is capable of detecting the chest movements of a sleeping person, even if they’re under a blanket or lying on their side,” writes Bray. “It uses software to filter out all other extraneous information, until only the breathing data remains. Using it for just one night provides enough data for a diagnosis.”
Boston Globe reporter Hiawatha Bray speaks with Radio Boston host Tiziana Dearing about how MIT researchers developed an artificial intelligence model that uses a person’s breathing patterns to detect Parkinson’s Disease. The researchers “hope to continue doing this for other diseases like Alzheimer’s and potentially other neurological diseases,” says Bray.
Researchers at MIT have developed an artificial intelligence sensor that can track the progression of Parkinson’s disease in patients based on their breathing while they sleep, reports Conor Hale for Fierce Biotech. “The device emits radio waves and captures their reflection to read small changes in its immediate environment,” writes Hale. “It works like a radar, but in this case, the device senses the rise and fall of a person’s chest.”
MIT researchers have developed a new artificial intelligence system that uses a person’s breathing pattern to help detect Parkinson’s sisease, reports Susannah Sudborough for Boston.com. “The device emits radio signals, analyzes reflections off the surrounding environment, and monitors the person’s breathing patterns without any bodily contact,” writes Sudborough.
Researchers at MIT and other institutions have developed an artificial intelligence tool that can analyze changes in nighttime breathing to detect and track the progression of Parkinson’s disease, reports Casey Ross for STAT. “The AI was able to accurately flag Parkinson’s using one night of breathing data collected from a belt worn around the abdomen or from a passive monitoring system that tracks breathing using a low-power radio signal,” writes Ross.
Prof. Andrew Lo speaks with Forbes contributor Russell Flannery about his work using finance to help lower the cost of drug development for cancer treatment and therapies. “I started thinking about how we could use finance pro-actively to lower the cost of drug development, increase success rates, and make it more attractive for investors,” says Lo. “Because that's really what the issue is: you need investors to come into the space to spend their billions of dollars in order to get these drugs developed.”
TechCrunch reporter Devin Coldewey spotlights how MIT researchers have developed a machine learning technique for proposing new molecules for drug discovery that ensures suggested molecules can be synthesized in a lab. Coldewey also features how MIT scientists created a new method aimed at teaching robots how to interact with everyday objects.
MIT researchers have developed a new technique that uses deep learning to improve the process of drug discovery, reports Jonathan Vanian for Fortune. “The technique addresses a common problem that researchers face when using A.I. to develop novel molecular structures: life sciences experts can often face challenges synthesizing A.I.-created molecular structures,” writes Vanian.
Bloomberg Businessweek reporter Peter Coy spotlights how the loss of several people close to Prof. Andrew Lo inspired him to explore how the field of finance could help advance treatments for orphan diseases. “Finance plays a huge role, sometimes way too big a role, in how drugs get developed,” says Lo. Fixing the financing model, could have a “tremendous, tremendous impact on health care.”
CNBC reporter Charlie Wood features tProf. Connor Coley's work developing a new system that could be used to help automate molecule manufacturing. “It tries to understand, based on those patterns, what kind of transformations should work for new molecules it’s never seen before,” says Coley.