2026 Spring AC - From Instruments to Intelligence: Scaling ASM Across the Lab Enterprise

2026 Spring AC - From Instruments to Intelligence: Scaling ASM Across the Lab Enterprise Presented by: Wolfgang Colsman, ZONTAL; Chris Siegler & Vinny Antonucci, MSD Despite widespread adoption of FAIR data principles, many laboratory organizations still struggle to answer fundamental scientific and operational questions in real time. The challenge is no longer data availability—it is transforming instrument data into decision-ready intelligence. This presentation shares MSD’s journey implementing the Allotrope Simple Model (ASM) at enterprise scale across a heterogeneous, multi-modal instrument landscape. We highlight the realities of scaling ASM beyond chromatography, where structural variability, validation complexity, and SME dependency quickly break traditional project-based integration models. We introduce a new architectural paradigm: integration factories. By treating instrument families as repeatable patterns and industrializing converter generation, validation, and onboarding, MSD and ZONTAL transformed integration from bespoke projects into scalable infrastructure. This shift reduced onboarding timelines from months to days, improved data quality through “correct-by-construction” validation and created reusable enterprise assets. Building on this foundation, we connect ASM to the broader ICAD (Integrate, Contextualize, Analyze, Decide) framework, demonstrating how standardized, contextualized data with full lineage enables cross-instrument traceability, governed comparisons, and AI-ready decision-making. The result is a transition from static data products and delayed insights to on-demand intelligence, where scientists can ask novel questions, trace results end-to-end, and receive answers in seconds rather than days. Attendees will gain practical insights into: · Scaling ASM across diverse instrument ecosystems · Overcoming validation and variability challenges · Designing and operationalizing integration factories · Enabling lineage-driven, AI-native lab intelligence This session outlines a clear path from FAIR data to real-time, enterprise-wide scientific decision-making.