Addressing Pharmaceutical Supply Chain Issues

Jacqueline Griffin, David Kaeli, Ozlem Ergun, Stacy Marsella & Casper Harteveld

MIE Associate Professor Jacqueline Griffin, ECE Professor David Kaeli, MIE Professor Ozlem Ergun, and affiliate faculty members Stacy Marsella and Casper Harteveld were awarded a $750k NSF grant for “Designing an Improved Information Infrastructure for Better Decision Making in Pharmaceutical Supply Chains.” This grant is one of the awards NSF is supporting in their Strengthening American Infrastructure program.

Abstract Source: NSF

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.

The American medical system experiences recurrent shortages of critical pharmaceutical products. Efforts to address drug shortages depend on significant innovations in data collection, identification of critical data, and tools for converting the data into desired action. This SAI research project addresses this need to design a new Information Infrastructure for pharmaceutical supply chains. The research focuses on three important challenges to inform the design of a new infrastructure. One is developing secure mechanisms for sharing information. Another is enhancing the analytical structure to support decision-making. The third is to achieve a better understanding of the diversity of decision-making behaviors and how these behaviors are influenced by the available information. The research supports the development of transparent policies to address pharmaceutical supply chain issues.

Working with experts on drug shortages and pharmaceutical policy, a diverse set of stakeholders, and the private technology sector, the project is organized around four research thrusts. Thrust 1 develops new and realistic models of human behavior of pharmaceutical supply chain stakeholders, focusing on the inputs into decision-making. Thrust 2 advances understanding of human reasoning and decision-making through methodological innovations and development of new analytical methods for extracting actionable data that characterize behaviors. Thrust 3 introduces new network-based metrics for identifying risks and vulnerabilities within complex systems and extends the metrics to address spatio-temporal considerations in service networks. Thrust 4 considers new models for balancing the needs of privacy, security, and transparency through development and comparison of prototype service systems that build on the principles of data harmonization and differential privacy. The research focuses on the pharmaceutical industry, but this convergent and integrative research approach serves as a reusable model for other areas of decision-making and analysis of system-wide effects of changes in infrastructure.

This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences.

This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.

Related Faculty: Jacqueline Griffin, David Kaeli, Casper Harteveld, Ozlem Ergun

Related Departments:Electrical & Computer Engineering, Mechanical & Industrial Engineering