Abstract: Methods, systems, and computer program products for pharmacy substitutions obtain claims data associated with a claim for a prescription associated with a patient; determine, based on the claims data, a universal identifier for the prescription; obtain drug diagnosis data associated with known diagnoses for universal identifiers associated with prescriptions; determine, based on the universal identifier and the drug diagnosis data, a likely diagnosis associated with the prescription; determine, based on the claims data, a cost associated with the likely diagnosis; determine, for the likely diagnosis, using a machine learning model trained based on a training dataset, a potential alternative prescription to the prescription; update, based on user input, the training dataset to include the likely diagnosis associated with the alternative prescription; and train the machine learning model based on the updated training dataset.