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Regulating the machine: Europe’s race to get to grips with AI drugs
10 Apr

By Pharmatrax Author

Category: Technoloy

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Regulating the machine: Europe’s race to get to grips with AI drugs

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How do you regulate a drug developed by artificial intelligence? That’s the question Europe’s regulators are grappling with as AI medicines speed toward market.

At the heart of a regulator’s job is the responsibility to ensure that the benefits of a new medicine outweigh the inevitable risks. But, with AI starting to remake how drugs are developed, they could soon have some very different-looking submissions on their desks.

Pharma companies could use algorithms at all stages of the drug-development process: to identify which molecules could best target a specific disease; to select patients for clinical trials based on how they’re expected to respond to a drug; and to extract trial data and complete forms for regulators. AI’s predictive powers could even eliminate the need to test drugs on animals.

All this poses a regulatory challenge, raising questions about the transparency of the algorithms, the risk of AI failure and most importantly, the impact on a patient’s health. And while those in charge of approving new drugs in Europe are racing against the clock to be ready for the coming change, they’re not quite there yet.

“When things are going to evolve, and how big the change is, is unclear,” said Peter Arlett, head of the European Medicines Agency (EMA)’s pharmacovigilance department, in an interview with POLITICO. “But we need to be ready for it by having expertise and experience, and having thought of what the potential risks might be and the potential challenges, but also the opportunities.”

Balancing the risk

The Amsterdam-based EMA is set to publish a reflection paper later this year, laying out where there is consensus so far on their plans to regulate AI. It is thinking about how to express the way that the risks and uncertainties around AI could impact the benefit-risk assessment of a drug, or make this less clear cut, explained Ralf Herold, senior scientific officer for the EMA’s task force on regulatory science and innovation.

In a comment piece published in the journal Nature in November, several EMA staff, including Herold and Arlett, set out four principles that they will use to regulate AI: ensuring decisions are evidence-based; using expertise from industry, academics and patients; bridging medicines and medical device regulations; and aligning with international partners.

But tricky questions remain, such as whether they’ll want to access an underlying algorithm’s code and the datasets that have been fed into it, and if their approach will vary depending on how much human oversight there is and to what extent the AI is “self-learning.”

Meanwhile, the developers of these shiny new drugs are waiting in anxious anticipation to see what direction regulators will choose to go. The fear? Policymakers nervous of Big Bad AI may over-regulate the space, stifling innovation.

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