A University of Toronto research team has built MaaTRx, an AI-powered platform designed to flag drug shortage risks up to a year in advance. By combining real-world purchasing data with AI forecasting, it gives hospitals, pharmacies, and policymakers a head start on finding alternatives. In validation testing, 25% of high-risk drugs flagged by the platform went into actual shortage.
Drug shortages are a persistent challenge for Canada's health system — and right now, most of the response is purely reactive. Pharmacists often don't learn a drug is unavailable until a wholesale order simply doesn't show up. A new AI-powered platform called MaaTRx, developed by researchers at the University of Toronto, aims to change that by giving healthcare leaders an early warning — weeks or even months ahead of a shortage.
MaaTRx pulls together real-world purchasing data and dozens of other data sources to predict which medications are likely to face supply disruptions within the next year. The forecast is updated monthly and is designed to help hospitals, pharmacy networks, and policymakers plan therapeutic substitutions and manage inventory before a crisis hits — reducing duplicated work and protecting patient safety.
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Why it matters: Drug shortages aren't just an inconvenience — they can increase mortality, especially when critical medications like cancer drugs run out. A proactive forecasting tool could meaningfully reduce the strain on healthcare workers and help protect patients before a crisis unfolds.
