It’s estimated that, on average, one new drug coming to market can take 1,000 people, 12-15 years, and up to $1.6 billion.
There has to be a better way—and now it seems there is.
Last week, researchers published a paper detailing an artificial intelligence system made to help discover new drugs, and significantly shorten the amount of time and money it takes to do so.
The system is called AtomNet, and it comes from San Francisco-based startup AtomWise. The technology aims to streamline the initial phase of drug discovery, which involves analyzing how different molecules interact with one another—specifically, scientists need to determine which molecules will bind together and how strongly. They use trial and error and process of elimination to analyze tens of thousands of compounds, both natural and synthetic.
AtomNet can’t actually invent a new drug, or even say for sure whether a combination of two molecules will yield an effective drug. What it can do is predict how likely a compound is to work against a certain illness. Researchers then use those predictions to narrow thousands of options down to dozens (or less), focusing their testing where there’s more likely to be positive results.
Check out the full article here: Drug Discovery AI Can Do in a Day What Currently Takes Months
Welcome to Clinical Research Trends, a new blog dedicated to providing breaking news on clinical trial recruitment, patient engagement, new technology and noteworthy trends. With this blog, we are working to provide clinical research organizations, sponsors and leading service providers with critical news and industry updates on a regular basis. If you want to learn more about the latest trends in clinical trial recruitment and drug development, you’ve come to the right place.