The conference TRICON is in its 33rd year, and will be held in San Francisco May 4-5, 2026. The conferences has three main tracks, "Diagnostics Innovation," "Artificial Intelligence," and "Precision Medicine."
(And it comes right on the heels of Dark Report Pathology War College in New Orleans, April 27-29, and AMA CPT in Chicago, April 30-May 1.)
Find the conference website here:
https://www.triconference.com/
I gave the agenda(s) to Chat GPT and asked for a write-up.
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AI CORNER
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Summary:
The 2026 TRI-CON Precision Medicine conference highlights the rapid convergence of AI, multi-omic diagnostics, and digital pathology. Across three coordinated tracks—Artificial Intelligence, Diagnostics Innovation, and Precision Medicine—the meeting reflects a field moving toward AI-enabled interpretation of complex biological data and decentralized deployment of advanced molecular testing. For molecular pathologists and precision medicine specialists, the program signals a transition from isolated diagnostic tests to integrated computational systems guiding clinical decision-making.
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The 33rd Annual TRI-CON Precision Medicine conference, returning to San Francisco in May 2026, brings together leaders in biotechnology, diagnostics, and computational medicine to explore how emerging technologies are reshaping healthcare. Organized around three overlapping tracks—Artificial Intelligence, Diagnostics Innovation, and Precision Medicine—the program illustrates how the next generation of diagnostics will increasingly depend on the integration of genomics, pathology, imaging, and clinical data within AI-driven analytical frameworks.
A dominant theme across the conference is the emergence of AI-driven multimodal biomarkers. Sessions in the Artificial Intelligence track explore how machine learning models can combine histopathology images, genomic sequencing data, radiology signals, and real-world clinical outcomes to improve biomarker discovery and therapeutic targeting. Digital pathology and computational pathology play a central role in this transformation, with speakers describing how foundation models trained on histology data may enable new biomarker strategies and accelerate clinical trial design. Several presentations also emphasize “agentic AI” systems, in which multiple AI models coordinate across datasets and clinical guidelines to support oncologists and multidisciplinary teams in treatment selection and clinical trial enrollment.
The Diagnostics Innovation track highlights another major shift: the migration of testing from centralized laboratories toward point-of-care and at-home diagnostic environments. New molecular technologies—including CRISPR-based detection platforms and portable multiplex testing systems—are being developed to bring complex molecular assays closer to the patient. However, presenters note that reimbursement policy, site-of-service restrictions, and regulatory frameworks remain major barriers to broader adoption of decentralized molecular diagnostics.
Meanwhile, the Precision Medicine program focuses heavily on liquid biopsy technologies, particularly minimal residual disease (MRD) testing and multi-cancer early detection. These sessions emphasize the growing importance of multi-omic signals—DNA mutations, methylation patterns, RNA expression, and protein markers—interpreted through AI-enabled analytics to detect cancer earlier and monitor disease progression more precisely. While oncology remains the dominant application, the conference also explores precision approaches in metabolic disease, neurology, and population health.
Taken together, the TRI-CON agenda suggests that diagnostics are evolving toward AI-mediated, multimodal clinical intelligence systems, combining laboratory science, computational modeling, and decentralized testing to support more personalized and proactive healthcare.
