Decision Intelligence Can Save Lives: How AI Can Combat Drug Shortages

According to a report by the American Society of Health System Pharmacists, there are 301 drugs that are currently listed as experiencing shortages, a 40% increase over the last five years. These drugs range from pediatric allergy medications to anesthesia drugs, and from oncology to cardiac medications.

Pharmaceutical companies understand the life-and-death ramifications of drug shortages, and want to do all they can to assure supply. However, even with these good intentions, the situation is currently so dire that drug shortages have been classified as a national security threat in the United States and the US Senate is exploring legislation to find a solution to the growing shortages.

If you’re like me, you’ve seen stories about these shortages in your news feed. One that resonated strongly for me was that of Jeff Bolle, who is suffering from stage 4 bile duct cancer. While overall prognosis for this diagnosis in general isn’t good, his doctors thought they could extend his life with Cisplatin, a medication manufactured in China and distributed through Canada. However when he went to receive his third round of chemo, he was told, “I’m sorry, we don’t have any medication to give you.”

Without new approaches to sourcing, supply chain planning, and distribution processes, all signs point to these problems like the one outlined above becoming worse, not better, over time. But there are solutions available that will allow drug manufacturers to mitigate these issues.

How AI Helps Pharma Companies Adapt and Overcome Shortages

Supply chains are strained due to interruptions, predominantly with contact manufacturers (CMOs) in India and China, as well as quality and financial issues that impact CMOs’ ability to deliver on-time and in-full.

Currently, there is no supply chain planning solution that addresses all of the pieces of the puzzle. This complicated situation requires new technologies that can handle the complexity of the problem.

Decision Intelligence combines the end-to-end visibility, AI and machine learning capabilities, executional capabilities, and user engagement to digitize pharma supply chain decision making. A Decision Intelligence platform can act at machine speed and scale to analyze data, run a multitude of scenarios, identify the best course of action, and make holistic recommendations and decisions.

Also, a Decision Intelligence platform can find patterns in data that teams of people might miss – allowing it to positively guide supply chain planning, supplier collaboration, distribution plans, financial plans, product quality, and more.

Moreover, the platform not only identifies ways that pharma companies can provide lifesaving care, but future-proofs their operations with velocity, accuracy, and scale. The outcome is that pharmaceutical companies are prepared to make important decisions across multiple, interconnected, lines of business, with the ability to scale those operations easily for years to come.

How Decision Intelligence Alleviates Drug Shortages

The data that can reduce or eliminate pharmaceutical shortages exists today. Unfortunately, much of this data cannot be accessed or analyzed before it becomes obsolete and no longer valuable.

In fact, according to IDC’s presentation “Enterprise Intelligence: Digital Differentiation with Decision Velocity,” 34% of executives receive data they aren’t using, whether due to lack of bandwidth or because they can’t keep up with the volume. In other words, one-third of organizations are missing potential positive outcomes simply because they are unable to look at the data and make a decision in time.

Yet even if companies had ready access to all the data, and enough people to analyze it quickly and accurately, there simply isn’t enough time to make all the decisions needed to optimize and future-proof pharmaceutical supply chains. The tools and processes pharma companies have relied on in the past cannot keep up with the challenges of today.

Decision Intelligence has the power to help pharma companies deliver the quality treatments that patients need. Aera Decision Cloud™ transforms how enterprises make and execute decisions. Here are five implemented Aera Skills™ that address these problems at multiple pharma companies:

• Parameter Setting – Identifies key indicators, such as minimum order quantities and lead times, that can alert teams proactively to potential pharma supply-chain disruptions
• Inbound Risk Management – Uses forecast data to bring forward purchase orders for ingredients, in order to avoid production delays. Among other things, this Skill also can determine the best mode of transportation for those raw materials in order to maintain service levels.
• Prioritization – Understands your current production capacity and product demand, and recommends an optimal production plan across different manufacturing facilities.
• Inventory Rebalancing – Analyzes real-time data and demand patterns, then recommends opportunities to transfer available inventory, expedite transfer, or increase production to avoid shortages. This Skill also tracks stock that is at risk of expiring and offers solutions to avoid product waste.
• Strategic Risk – Identifies alternative suppliers to avoid potential risks that may arise with current suppliers, calculated according to a supplier score that considers a range of factors, such as price, supplier reliability, and more.

To learn more about how Aera can help pharmaceutical companies, register for our webinar, “Decision Intelligence is the Cure for Underperforming Pharma Supply Chains.”