A Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Project
My name is Kraig Delana and this is the webpage of my MSCA project on dynamic production sequencing to minimize patient delays for compounded medications.
Although approximately 90% of medications are industrially produced and distributed through retail or hospital pharmacies, when patients require personalized medications or medications that are otherwise unavailable, e.g., due to patients’ allergies or drug shortages, retail pharmacies must rely on compounding pharmacies that produce medications to order. Inspired by discussions with the management team of a compounding pharmacy, this project aims to improve patients’ access to compounded medications through the development of a dynamic production control algorithm designed to minimize production delays.
Our proposed approach is based on fluid model that captures production dynamics combined with a novel modification of a method widely applied in aerospace,
guidance systems, and autonomous robotics: the State-Dependent Riccati Equation (SDRE). We carefully adapt this technique to create a dynamic production control policy, that balances stochastic demands while exploiting efficient production sequencing.
In calibrated numerical experiments, we find that this policy can reduce delays for patients by up to 32.5% on average without increasing worst-case delays. Moreover, the approach can be generalized to other settings, tackling challenging dynamic decision problems where optimal solutions are intractable. This opens up future research opportunities across manufacturing, supply chain management, and beyond.
Develop an Implementable Sequencing Algorithm that will benefit patients:
Adapt the SDRE-based control approach to account for real-world compounding pharmacy production dynamics which reduces average waiting times for patients and enhances operational efficiency without sacrificing worst-case performance.
Generalize the approach:
Provide a framework that extends to other challenging dynamic decision making problems where optimal policies are intractable.
This project is the joint work of:
Assistant Professor of Operations Management at IE Business School
Assistant Professor of Operations Decisions and Technologies at Kelley School of Business
Associate Professor of Operations Decisions and Technologies at Kelley School of Business
The SDRE approach can be modified to function as a value function approximation and used as the basis of an implementable dynamic index policy to efficiently sequence production of compounded medications and significantly reduce delays for patients.
We use both our own and third-party cookies to enhance our services and to offer you the content that most suits your preferences by analysing your browsing habits. Your continued use of the site means that you accept these cookies. You may change your settings and obtain more information here. Accept