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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