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Good Apart, Bad Together

Using a new computer algorithm they created that compiles reams of data on adverse drug reactions, Stanford University researchers have shown thousands of previously unknown side effects caused when some drugs are taken in combination, reports Nature News' Heidi Ledford. "Although clinical trials are often designed to assess the safety of a drug in addition to how well it works, the size of the trials needed to detect the full range of drug interactions would surpass even the large, late-stage clinical trials sometimes required for drug approval," Ledford says. So this algorithm, published in Science Translational Medicine is another way for doctors and regulators to assess a drug's safety profile as it's used in real time.

To reduce the bias inherent in adverse drug reaction reporting — for example, Ledford says, certain drugs are taken by certain segments of the population, which may be suffering from co-morbidities — the algorithm is designed to match data from each patient taking a drug to a control patient with the same condition. "The approach automatically corrected for several known sources of bias, including those linked to gender, age, and disease," Ledford says.

The Scan

Not Kept "Clean and Sanitary"

A Food and Drug Administration inspection uncovered problems with cross contamination at an Emergent BioSolutions facility, the Wall Street Journal reports.

Resumption Recommendation Expected

The Washington Post reports that US officials are expected to give the go-ahead to resume using Johnson & Johnson's SARS-CoV-2 vaccine.

Canada's New Budget on Science

Science writes that Canada's new budget includes funding for the life sciences, but not as much as hoped for investigator-driven research.

Nature Papers Examine Single-Cell, Multi-Omic SARS-CoV-2 Response; Flatfish Sequences; More

In Nature this week: single-cell, multi-omics analysis provides insight into COVID-19 pathogenesis, evolution of flatfish, and more.