Australian researchers develop Big Data tool to test new medicines

November 27, 2015

Australian scientists have developed a a rapid detection tool to map the effects of new medicines already on the market.

Rapid detection tool

Australian scientists have developed a rapid detection tool to map the effects of new medicines already on the market, potentially saving millions of health practitioners from prescribing medicines with lesser-known yet serious side effects.

Lead researcher Dr Nicole Pratt, a senior research fellow at the University of South Australia‘s School of Pharmacy and Medical Sciences, has been working with the Asian Pharmacoepidemiology Network (AsPEN) to develop a mathematical algorithm that charts the temporal relationship between a new medicine and reports of adverse side effects around the globe.

“At the time a new medicine is first released onto the market less than 50% of the side effects are known.”

The rapid detection tool is able to quickly analyse large population datasets of up to 200 million people, containing information about the time a patient is prescribed a new medicine (captured at the point of purchase) and recorded hospitalisation events.

“We look at the link between starting a new medicine and a hospitalisation event and determine whether there is an association between those two events,” says Pratt.

At the time a new medicine is first released onto the market less than 50% of the side effects are know.

On average, new medicines are tested on less than 2000 people before they are prescribed – too few to determine if rarer, serious side effects exist.

Pratt’s rapid detection tool has the potential to become a real time surveillance tool for drug administration bodies, researchers and general practitioners, helping them to identifying the effects of new medications before they lead to widespread complications.

“We’d like to see it reach the point where we are constantly looking at the data and trying to capture problems as soon as they happen rather than let them happen for years and years and then do a big study to find that there have been a whole heap of heart attacks.”

The tool is already being used in several countries, including Japan, Korea, Taiwan, Canada and Australia to look at the side effects of a heartburn medication prescribed for reflux, and a medication for diabetes associated with heart failure.

In analysing the populations’ use of the heartburn medication, “all of the datasets found very similar results in terms of this medicine causing serious gastrointestinal infections,” says Pratt.

But when they analysed the diabetes medication, Pratt says they started to see differences between the five countries, indicating the drug might have a different effect on people depending on their ethnic background.

“When we looked at the association in the Asian population, we weren’t able to see the effect, but when we looked in the Caucasian population in Australia and Canada, we found the association.

“So the application is to start to look at whether there is some genetic differences in the way people respond to medicines and know what the risks and the benefits might be across ethnicities,” she says.

One of the challenges Pratt faced in developing the highly mathematical tool has been making it accessible for more people.

She says UniSA Professor Libby Roughead has been instrumental in helping her to apply the numerical tool visually in a “real-world” healthcare setting.

At the moment, “the datasets are held by either the governments or the hospitals in each of the countries, but the actual output of the tool should be available to general practitioners, scientists and regulators,” says Pratt.

“So what we are trying to do is visually provide an output to the people who are going to use it at the point of prescribing medicines.”

“Some of the things we’ve been trying to do is look at how the data can tell you stories, rather than just give you numbers.”

At the moment the tool produces a visual graph charting when medicines are prescribed and superseded across populations, while highlighting peaks in adverse effects at certain points in time.

“I’d like to see s this work integrated into the regulatory systems of all these countries and make it a world-wide surveillance system.”

Pratt met with her colleagues from AsPEN in Thailand this week, to discuss the global expansion of the rapid detection tool.

This article was first published by The Lead on 24 November 2015. Read the original article here.

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