Computational creativity and the future of AI

Virtual safety panel predicts drugs' side effects


June 14, 2012

The computer model uses “similarity ensemble approach” (SEA), to detect similarities betwe...

The computer model uses “similarity ensemble approach” (SEA), to detect similarities between the chemical drugs of the compounds and the molecules that cause side effects

A team of scientists from the UCSF School of Pharmacy, Novartis Institutes for Biomedical Research (NIBR) and SeaChange Pharmaceuticals has developed a set of computer models that can predict negative side effects associated with existing drugs. By speeding up the process and increasing accuracy, the software could potentially save billions in research and decrease the number of animals used in toxicity tests.

The model, based on UCSF’s “similarity ensemble approach” (SEA), uses the similarities between the shape of each drug and thousands of other compounds to predict possible side effects. The theory behind SEA technology is that proteins can be related by their pharmacology, and these network relationships can be explored to discover new targets for established drugs.

The team ran a computer screen on 656 drugs that are already on the market, with known side effects and benefits, to predict which ones were most likely to bind to the 73 target proteins that appear on Novartis’ safety panel for testing drugs for side effects such as heart attacks. Then those targets were related to known side effects through a statistical method developed by NIBR. The computer model identified 1,241 possible side-effect targets for the 656 drugs. Of the total, 348 were already in Novartis’ database of drug interactions while another 151 hits revealed new side effects which were later confirmed in lab testing. They managed to predict potential side effects half of the time.

“The model isn't intended to replace existing safety approaches, like lab testing and animal models, but rather as a way to prioritize very early on what sorts of lab tests must be run or which research compounds might require fewer such tests than others,” said Michael Keiser, co-founder of SeaChange, whose work is focused on using computational simulations to identify new targets for known drugs.

Although it is not meant to replace testing, the new modelling has the potential to reduce animal testing. “Right now, some of the unsafe compounds that make it all the way to animal tests might be caught earlier by the computer model instead. This would reduce unnecessary animal suffering and also save money because each stage of the safety testing process is more expensive than the stage before it,” added Michael.

Adverse side effects are one of the pharmaceutical industry’s biggest sources of financial losses because, after inefficacy, they are the second most common reason that new drugs fail in clinical trials. The costs are huge, estimated at around US$1billion over a period of 15 years. With the computer model, it becomes possible to construct a preliminary “virtual safety panel” for almost any drugs or preclinical compound, said Michael. “You'd run your drug, or even your ten thousand compounds from which one or two might someday become drugs, and ask whether any undesirable side effects ‘light up’ against that panel,” he added.

Current scientific standards cannot predict how drugs will behave in relation to the targets linked to the side effects of medicines used clinically. Often, they hit more than 10 percent of the targets and the side effect targets are unrelated to previously known ones.

Can we expect a future when computer programs will be so sophisticated that they will be able to predict with complete accuracy the side effects of new drugs, making testing a thing of the past? “I don't know the answer to this question, though I certainly hope you're right," said Michael. "There are some exciting efforts going on right now in massive simulations of tissues, organs, and full systems. It's a tough problem; a grand challenge. Some of this effort is being supported by programs and agencies, such as in Europe. I'm excited to see where it goes.”

More details of the research appeared online this week in the journal Nature.

Source: UCSF

About the Author
Antonio Pasolini Brazilian-Italian Antonio Pasolini graduated in journalism in Brazil before heading out to London for an MA in film and television studies. He fell in love with the city and spent 13 years there as a film reviewer before settling back in Brazil. Antonio's passion for green issues - and the outdoors - eventually got the best of him and since 2007 he's been writing about alternative energy, sustainability and new technology.   All articles by Antonio Pasolini
1 Comment

Making more money for the drug companies is great! Now how about using the same concept on foods so that people could get a better handle on food sensitivities. Use the same concept to make homes, and communities safer by seeing how the chemical compounds in the environment interact with people. People could save money and feel better knowing that they are avoiding things that make them sick. They could then use this technology to understand which foods and communities promote their health. That is when people will lead better lives!

Carlos Grados
14th June, 2012 @ 03:25 pm PDT
Post a Comment

Login with your gizmag account:

Or Login with Facebook:

Related Articles
Looking for something? Search our 31,346 articles
Recent popular articles in Medical
Product Comparisons