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Interaction Prediction

Facebook has developed an artificial intelligence approach that it says can quickly predict how drugs will interact within cells and help identify combinations of drugs that could be used to treat cancer, New Scientist reports.

As researchers led by Facebook's David Lopez-Paz report in a preprint posted to BioRxiv, they developed an approach dubbed Compositional Perturbation Autoencode (CPA) to model and predict single-cell changes that occur with exposure to different drugs and doses, across cell types. According to New Scientist, the researchers found that their CPA approach could predict cell responses with about 90 percent accuracy and say this approach could hasten researchers' abilities to develop new treatments, including for cancer.

The US National Cancer Institute's Eytan Ruppin, who was not part of the study, tells it that the study is "important" first step, but that more testing is needed, especially as CPA predicts RNA changes that occur in the cell following treatment, but not whether that treatment leads the cell to die. "We have cured cancer one hundred times in salines and mouse models. They have shown nothing at all that is relevant to patients," he adds at New Scientist.

The Scan

Call to Look Again

More than a dozen researchers penned a letter in Science saying a previous investigation into the origin of SARS-CoV-2 did not give theories equal consideration.

Not Always Trusted

In a new poll, slightly more than half of US adults have a great deal or quite a lot of trust in the Centers for Disease Control and Prevention, the Hill reports.

Identified Decades Later

A genetic genealogy approach has identified "Christy Crystal Creek," the New York Times reports.

Science Papers Report on Splicing Enhancer, Point of Care Test for Sexual Transmitted Disease

In Science this week: a novel RNA structural element that acts as a splicing enhancer, and more.