Stories about: adverse effects

A hole in the FDA’s approval process for pediatric drugs

ADHD long term drug safety rare adverse events FDA approval Kenneth Mandl Florence BourgeoisYou’d think drugs meant to be taken by children for years would be studied in children for a long time to measure their long-term safety.

You’d think drugs for a condition affecting millions of children would be tested in many, many children to catch any rare side effects.

You’d think all this would happen before the Food and Drug Administration, an agency known for its strict criteria, approved them for marketing.

But if a new PLoS ONE paper by Boston Children’s Hospital’s Florence Bourgeois, MD, MPH, and Kenneth Mandl, MD, MPH, is any indication, you’d be wrong.

In it, the pair reports that the FDA approved 20 attention deficit hyperactivity disorder (ADHD) drugs over the last 60 years without what would be considered sufficient long-term safety and rare adverse event data.

Their findings, they say, point to larger issues in how the FDA’s approval process addresses the long-term safety of drugs intended for chronic use in children.

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Unearthing unrecognized drug interactions, through search data

Google search cropAs we reported on Vector last year, once a new drug is on the market, regulators rely on a mix of surveillance, reporting and data mining to detect adverse drug events (aka side effects).

While those methods can work pretty well, a team of scientists from Microsoft, Stanford and Columbia wanted a better way to find rare or unforeseen interactions between drugs and recently tried a new tactic: looking at what people type into Internet search engines like Google, Microsoft and Yahoo. They hit pay dirt, unearthing evidence that the combination of two drugs—the antidepressant paroxetine and a cholesterol-lowering drug called pravastatin—leads to high blood sugar.

“Given how often patients turn to the Internet for information about the drugs they are taking, it’s not unexpected that we will identify new side effects sooner,” says John Brownstein, PhD, leader of the Computational Epidemiology Group in the Children’s Hospital Informatics Program (CHIP), and whose MedWatcher mobile app takes a crowdsourcing approach to drug side-effect reporting.

The work is another demonstration of the power that search tools, social media and other alternative data sources can bring to public health surveillance. In 2011, Brownstein and colleagues demonstrated that Google searches could reveal a lot about peoples’ health behaviors. “There is tremendous promise in a wide range of tools, from online search to patient forums. We are just now at the start of a new era for drug safety surveillance,” Brownstein notes.

At the same time, the work also emphasizes the need for the public, Internet companies, privacy advocates, health care thought leaders and other stakeholders to agree on ground rules for using data like these for health surveillance. We are, after all, in an era in which everything we do is online.

“As we uncover new uses for these data, there is an important conversation to be had,” says Ben Reis, PhD, leader of CHIP’s Predictive Medicine Group. Reis is working on ways of mathematically predicting possible adverse events. “We have to ensure that the public understands both the potential value of the data for helping society at large, as well as the safeguards that are in place to protect individual privacy.”

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Drug safety and side effects: Detection, or prediction?

There is no crystal ball to predict what side effects a new drug might cause. But a new mathematical model could help. (Bitterjug/Flickr)

A major challenge in drug development is figuring out what might go wrong. During the development process, a new drug might be given to a few thousand people, maybe fewer if it’s for a rare or orphan disease – just enough to tell whether it does what the researchers think it will and to establish its short-term safety.

Once a drug is approved and available to the public, and out of the controlled laboratory or clinical trial environment, regulators rely on a mix of surveillance, reporting (by doctors and patients) and data mining to catch problems.

But these methods can fall short when it comes to rare side effects, drug-drug interactions or adverse events that arise only after patients have been on a drug for a long time. It can be years before doctors and regulators gather enough data and address safety problems with label warnings, revised prescribing guidelines or, in extreme cases, removal from the market.

So while detection works to a point, wouldn’t it be better if we could predict adverse drug events before a drug even hits the market?

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