Stories about: modeling

Strengthening newborns’ immune systems: A secret in the plasma

Blood cells
The immunosuppressant effect in newborns’ blood comes not from blood cells themselves, but from the plasma that surrounds them (smaller.pathological.ca/Flickr)

There’s something different about newborns’ blood. In babies less than 28 days of age, the immune system still hibernates—making newborns more susceptible to life-threatening infections and less responsive to many vaccines. Ofer Levy, MD, PhD, and his colleagues at Boston Children’s Hospital have done extensive work toward understanding the newborn immune system, and now they’ve uncovered a mechanism to help explain why the system is so weak—and how it might be strengthened.

“If we can understand the molecular mechanisms causing the immune system to be different when we’re very young or very old, we can leverage that knowledge to develop new treatments,” says Levy.

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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