Development of a mobile-accessible virtual assistant for MALDI-TOF MS microbial identification guidance: Proof of concept - Mónica Prieto; Igor Palotay; Florencia Rocca; Claudia Barberis; Marisa Almuzara; Carlos Vay (The Microbe, 2025)
Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) mass spectrometry has transformed microbial identification but poses challenges in interpreting results for unusual organisms and ambiguous cases. We developed MALDI-BOT, a Spanish-language virtual assistant leveraging natural language processing (Gemini 1.5 Flash API) to provide instant access to evidence-based MALDI-TOF interpretation guidelines from Argentina’s National Network for Microbiological Identification by Mass Spectrometry (RENAEM). A six-week pilot study with 18 professionals across five laboratories demonstrated high usability (100 % rated interface as “easy” or “very easy”), significant time savings (80 % reduction in reliance on static documents) and robust support for interpreting rare organisms and ambiguous results. Freely accessible, MALDI-BOT represents an innovative approach to democratizing specialized microbiological knowledge in Spanish-speaking regions and offers a scalable model for AI-driven diagnostic tools in resource-limited settings.