Bridging Critical Data Gaps in Veterinary Medicine Via Artificial Intelligence and Advanced Large Language Models to Procure Real-Time Antibiotic Use Data in Livestock Poultry and Companion Animals

Project SummaryAntibiotic resistance stands as a formidable challenge in both human and veterinary medicine demandingcomprehensive strategies to monitor and regulate antimicrobial usage. This FDA proposal brings together theesteemed Food Animal Residue Avoidance Databank (FARAD) and the pioneering data analytics prowess of the1DATA consortium to confront this urgent issue head-on. With a dual focus the project aims to (AIM 1) extractantimicrobial use data for major livestock and poultry species and (AIM 2) extend data collection efforts toencompass minor species and companion animals. FARAD a stalwart institution with over four decades ofexperience serves as the bedrock of evidence-based withdrawal recommendations in veterinary practice.Through a collaborative network spanning prominent veterinary colleges nationwide FARAD has cultivateddatabases and tools to meticulously curate and analyze antimicrobial usage data across diverse animaldemographics. Harnessing FARAD's reservoir of expertise this project endeavors to birth the Long-termAntimicrobial Use with AI web-crawler (LAMU-AI) a revolutionary platform poised to bridge existing datalacunae. LAMU-AI emerges as a beacon of innovation amalgamating data streams from FARAD's secure caserepository regulatory bodies veterinary medical teaching hospitals and online repositories to furnish real-timeinsights into antimicrobial utilization trends. Armed with cutting-edge data analytics machine learning artificialintelligence methodologies and a large language processing model LAMU-AI promises scalable andmultifaceted visualization of antimicrobial deployment patterns. This groundbreaking approach empowersstakeholdersbe it veterinarians producers regulatory agencies or researcherswith the ammunition to makejudicious decisions regarding antimicrobial stewardship and public health. Central to this initiative is theintegration of disparate data sources including FARAD's databases and regulatory testing datasets to furnish acomplete view of antimicrobial utilization practices. The advent of a sophisticated Big Data Dashboard andVisualization system promises to democratize the analysis and interpretation of intricate datasets fosteringcollaboration and knowledge propagation across sectors. Furthermore robust data security protocols willsafeguard the sanctity and confidentiality of sensitive information assuring stakeholders of the integrity of thedata ecosystem. In summation this project represents a paradigm shift in veterinary medicinea concertedeffort to confront critical data lacunae through the fusion of advanced data analytics and artificial intelligence.By marrying FARAD's unparalleled expertise with the avant-garde technology of the 1DATA consortium weaspire not only to redefine antimicrobial surveillance but also to catalyze global endeavors aimed at combatingantibiotic resistance at its core.