17 Sep How AI Can Prevent Drug Shortages in the U.S. Pharmacies
In recent years, the pharmaceutical supply chain in the United States has faced growing challenges, especially in ensuring the availability of critical medications. From generic injectables to cancer treatments, drug shortages have become an all-too-common crisis affecting hospitals, pharmacies, and most importantly, patients. Traditionally, the response to such shortages has been reactive. By the time a pharmacy realizes that a product is unavailable, the damage has already been done: care is delayed, costs go up, and alternatives may not be readily accessible. But a technological shift is underway, one that could transform how we manage this ongoing risk. At the center of this transformation is artificial intelligence.
AI-powered forecasting is emerging as one of the most promising tools to address drug shortages proactively. Instead of relying just on historical usage or supplier reports, AI systems can analyze vast volumes of real-time data from diverse sources to detect early signs of disruption. These systems consider everything from inventory levels and prescription trends to weather events, geopolitical developments, and raw material exports. Intelligence doesn’t stop at identification. AI models can simulate shortage scenarios, predict when and where they will occur, and recommend alternative procurement or distribution strategies long before the effects are felt on the ground.
The need for this kind of innovation is urgent. According to the U.S. Food and Drug Administration (FDA), the number of active drug shortages in the country has reached its highest level in nearly a decade, with over 120 critical medications facing constrained supply. In early 2024, the U.S. Senate released a report sounding the alarm on the issue, highlighting that shortages were affecting 15 chemotherapy drugs essential to cancer treatment. These are not isolated incidents, they are symptomatic of a system that still depends on outdated planning mechanisms in an increasingly unpredictable world.
Artificial intelligence offers a new approach. When applied correctly, AI can identify patterns and correlations that are invisible to the human eye. For example, a sudden spike in prescriptions in a certain region, combined with delays in active pharmaceutical ingredient shipments from Asia and a warning from the CDC about a potential outbreak, might indicate an upcoming shortage of a specific antibiotic. A human analyst might miss that signal. AI can act on it in milliseconds.
However, the predictive power of AI can only deliver real world results if it is integrated into the systems that pharmacies, distributors, and manufacturers use daily. This is where ERP systems play a critical role. An ERP like DOit, when connected to AI driven forecasting tools, becomes not just a system of record but a system of action. When a prediction is generated, the ERP can automatically adjust purchasing strategies, launch restocking workflows, alert pharmacists, suggest substitutes, and document all activity for compliance, all within minutes. This tight integration between intelligence and operations is what transforms forecasting from a dashboard metric into a real, preventative solution.
Pharmacies across the U.S., especially those serving rural or underserved communities, stand to benefit the most from this shift. When a single supplier fails, these providers are often left scrambling. AI integrated with responsive ERP tools, offer them a fighting chance to stay ahead of disruptions. And as the industry prepares for full DSCSA compliance in 2025, the importance of complete visibility across the supply chain, including inventory flow, serialized data, and transaction verification, becomes even more critical. Forecasting tools that can plug into EPCIS traceability networks will not only help prevent shortages but also strengthen regulatory readiness.
The future of pharmaceutical supply chains in the U.S. will depend on our ability to predict and adapt, not just react. Drug shortages are not going away, but they no longer have to catch the system off guard. AI has proven its value in sectors like finance, e-commerce, and logistics. Now, it’s time to harness that power for healthcare, where the stakes are higher than ever.
The technology exists. The need is urgent. And for forward-thinking pharmacies and distributors, the opportunity to lead this transformation is now. AI won’t replace the complexity of pharmaceutical logistics, but it might just give us the foresight we’ve been missing.
At DOit, we closely follow the evolution of AI in healthcare and supply chain management, recognizing its potential to reshape how the industry anticipates and responds to challenges. While this technology is not yet part of our ERP platform, we see it as a promising direction and one we will continue to explore as the industry progresses.