How AI Is Helping Keep Critical Medicines on Pharmacy Shelves

While AI is transforming everyday industries like finance and logistics, its impact on healthcare goes far beyond convenience — it’s actively saving lives.

Today, nearly 1 in 5 Americans (18%) have experienced delays or availability issues involving critical prescriptions or medical products, according to a National Institutes of Health report, putting timely access to treatment at risk.

By being more proactive than reactive, artificial intelligence can spot gaps between global supply chains and patient demand, flagging and addressing issues before pharmacies and hospitals face shortages.

In other words, AI is like an early-warning radar system. Instead of waiting for a drug to run out, AI connects various pieces of data to predict which medicines are at risk of disappearing from shelves.

A lack of drugs can delay essential medical care, force physicians to use less effective alternative treatments, increase the risk of medication errors, and ultimately lead to worse health outcomes — or even higher mortality rates — for patients.

How AI Helps Prevent Drug Shortages

“AI has the potential to help companies anticipate and respond to potential supply issues earlier,” says Kirk Wroblewski, Chief Information Officer of ProPharma, a Raleigh, North Carolina-based company that helps organizations navigate the development and deployment of new medicines and medical devices.

“By analyzing historical demand alongside emerging trends and other signals, AI can help predict where and when demand may increase, giving manufacturers more time to adjust production, inventory and distribution before a potential shortage becomes a crisis,” Wroblewski adds.

AI can also help companies respond more quickly when changes are needed. “For example, if a manufacturer needs to change a production process, supplier, facility or information submitted to regulators, teams may need to review a significant amount of documentation before moving forward,” explains Wroblewski.

“Much of the shortages are linked to economics, and so AI helps with better forecasting,” confirms Carolina Milanesi, president and principal analyst at Creative Strategies, a Silicon Valley–based technology research firm. “Because drug production is planned much in advance, often on previous years’ data, AI could help ensure patients get what they need, as opposed to rationing, switching drugs and avoiding price hikes.”

Machine learning models continuously scan for external disruptions like trade bottlenecks, extreme weather and geopolitical friction, allowing drug companies to proactively pivot their logistics.

Lessons from COVID-19 also highlight how AI can assess epidemiological trends, whether from a global pandemic or localized disease outbreaks, to help companies and governments dynamically shift inventory to where it’s most needed.

From Factory Floor to Pharmacy Shelf

Milanesi says AI can also help monitor factories, such as anticipating machinery failure, defects in packaging and flagging possible contamination.

In fact, surplus can also be an issue. Automated inventory systems can reroute expiring or surplus medications to other areas, reducing pharmaceutical waste by up to 30%, according to the National Library of Medicine.

AI, when paired with IoT (Internet of Things), can help sensors monitor temperature-sensitive medications in transit. Exposure to extreme heat, humidity or freezing temperatures can break down a drug’s chemical structure and make it lose effectiveness or become unsafe. For pharmaceutical companies, AI leveraged in this way could also prevent multimillion (or even multibillion)-dollar losses caused by damaged drugs.

Building Trust in AI-Powered Healthcare

According to Wroblewski, AI supports — rather than replaces — the experts making these important decisions.

The industry is excited about AI, but is “appropriately cautious,” believes Wroblewski. “Nearly every client conversation we have today includes some discussion about how AI and technology can improve productivity, accelerate processes, reduce costs or create new capabilities.”

“Because pharmaceutical companies operate in one of the most highly regulated industries in the world, the consequences of getting something wrong can be significant — and so companies need to understand how a technology works, what data it is using, how that data is protected, and how its outputs are validated,” he adds.

Milanesi agrees safeguards should be in place, but isn’t convinced AI replacing humans on spreadsheets is necessarily inviting a higher risk of error. “An AI error could result in over-forecasting, which results in wasted drugs, or under-forecasting, which results in shortages. But if you tune the model to slightly overforecast demand, you limit the risk of lost revenue and, more importantly, reduce the risk of impacting patients.”

As drugmakers, healthcare providers and regulators look for ways to strengthen medicine supplies, AI is emerging as a valuable tool for helping patients get the treatments they need without unnecessary roadblocks.

Marc Saltzman is the host of the Tech It Out podcast and is the author of the book Apple Watch For Dummies (Wiley).
Reporting by Marc Saltzman, Special to USA TODAY / USA TODAY. USA TODAY Network via Reuters Connect.