Charles River Analytics is one of four companies awarded an approximately $100K contract from the Defense Logistics Agency (DLA) to develop Probabilistic Reasoning on Supply Chain Readiness of International Pharmaceuticals using Trade Information (PRESCRIPTION).
PRESCRIPTION pulls together information from global trade networks, including potential disruptors to the supply chain, such as political turmoil or natural disasters; and pharmaceutical drug data, including raw materials and the country of origin. PRESCRIPTION displays this complex data in a simple dashboard visualization that allows users to quickly identify problems in the chain, such as an inaccessible road, and access information to address gaps, such as traveling a different route.
Dr. Alexis Bateman, Principal at SustainChain and Director at MIT Sustainable Supply Chains, is collaborating with Charles River on the PRESCRIPTION effort. Dr. Bateman will provide extensive expertise in mapping global supply chains for industrial partners, public agencies, global governance organizations, and non-governmental organizations.
PRESCRIPTION uses Charles River’s open-source probabilistic programming language, Figaro, a robust language that includes class structures for capturing dynamic probabilistic networks, and a library of inference and machine learning algorithms for inferring missing constructs within those networks. Figaro makes performing inference on the network structure of the supply chain a tractable problem.
“PRESCRIPTION’s going to let the DLA Customer Pharmacy Operations Center wargame the supply chain,” said Rebecca Dornin, Senior Software Engineer at Charles River. “It goes without saying that improving the availability of critical supplies during healthcare emergencies can save the lives of military personnel and their families.”
Contact us to learn more about PRESCRIPTION and our other Healthcare Support and Training capabilities.
Charles River Analytics wins federal contract for simplified pharmaceutical risk assessment system
This material is based upon work supported by the Defense Logistics Agency under Contract No. SP4701-21-P-0030. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Defense Logistics Agency.