The SUPPLI project addresses supply shortages for the key chemicals required to manufacture pharmaceuticals by creating a tool guided by artificial intelligence (AI) that (1) calculates the risk of supply side shortages and prioritizes efforts based on demand, (2) reverse engineers the relevant molecules to derive the starting ingredients, and (3) predicts appropriate manufacturing facilities, conditions, and protocols for manufacturing the chemical components in US based facilities. There is no current published framework for quantifying the interdependence of the manufacturing process from regulatory starting materials (RSMs) to final product. SUPPLI aims to de-risk the supply chain with a focus on the domestication of RSM manufacturing with a targeted goal of creating a product that will optimize pharmaceutical lifecycles, improve process traceability, and provide sustainable process designs that provide more efficient access to pharmaceuticals with fewer supply chain disruptions. It will also aid in the optimization of costs of manufacturing, which may decrease the downstream cost burden on patients and allow more accessible therapeutics to a great number of Americans.