Study presents new method for predicting frequency of medication side effects

Identifying the frequency of medication side effects among the public is a key challenge for the process of developing new drugs. Until now, this frequency could only be determined experimentally, through clinical trials, in a process with many limitations. Some side effects are only discovered after the drug is launched on the market
应用数学
23 十一月 2020
Study presents new method for predicting frequency of medication side effects

Two researchers at Fundação Getulio Vargas’ School of Applied Mathematics (FGV EMAp), Alberto Paccanaro and Diego Galeano, have developed a new method for predicting the frequency of medication side effects. Together with Dr. Shantao Li of Stanford University and Professor Mark Gerstein of Yale University, they carried out a study on this subject that was published recently in Nature Communications.

Identifying the frequency of medication side effects among the public is a key challenge for the process of developing new drugs. Until now, this frequency could only be determined experimentally, through clinical trials, in a process with many limitations. Some side effects are only discovered after the drug is launched on the market.

The method developed by Paccanaro and Galeano is therefore a breakthrough. It is the first computational method for predicting the frequency of medication side effects in the population. They developed an artificial intelligence algorithm based on matrix decomposition, which learns about a small group of components (latent factors) that encode biological interactions between drugs and generate side effects involving multiple types of drugs.

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