Department of Mathematics

United States Pharmacopeia

Proposed Project for the MSU Industrial Math Students

Risk-Based Approach for Regulating Medicines

Background:

Medicines quality is a major issue in developing countries where there are limited resources and poor quality medicines abound due to limited capacity for oversight. Over the past year, PQM developed a Medicines Risk Index (MRI) to determine which products should be prioritized for testing. This quantitative model uses logistic regression to make decisions about resource allocation with cost-benefit analysis. As PQM moves towards more quantitative decision making, new data is being collected. The MRI and related methodologies need to be validated by larger data sets.

Objectives:

  1. To validate the Medicines Risk Index as a decision model
  2. To improve the performance of the Medicines Risk Index
  3. To analyze the new data set

Planned Steps and Anticipated Analytical Methodologies/Tools:

  1. Data preprocessing in preparation for logistic regression
  2. Performing & monitoring performance of logistic regression
  3. Collect information about economic costs of various medicines/products
  4. Build front-end and back-end of application to calculate MRI and build prioritized queue

Technologies Required:

  1. Python
  2. sci-kit-learn
  3. numpy

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