Accepted by: Joshua Kriger and Lauren Williams
The foundation of Picket Pharmaceuticals, Inc.’s approach is to first acquire, then integrate, large healthcare datasets—such as shortage data, manufacturing information, unit usage, pricing, price variation and many more—that capture the universe of healthcare interactions that surround each patient’s walk from diagnosis to completion of care through their piece of the healthcare system.
Using the Wolfram technology stack, Picket has conducted interesting work with insights on the points of failure and where inefficient markets exist in the supply chain. Of note, computation techniques used include projecting large amounts of healthcare supply and medication usage data into images. These images become the data fed to repurposed visual neural net training procedures that result in AI/machine learning models that are able to accurately recognize signals that predict future drug shortages.
Working with Wolfram’s Consulting Group, Picket has also verified a derived new class of economic measures, titled the Sutherland measures, made feasible by taking into account special economic qualities and situations of supplied medicines for the generic drug markets.