ECM2026, 14-17 June 2026, Copenhagen, DenmarkPrecision fibrogenesis in MASH: Finding the right patient for the right anti-fibrogenic therapy
Zoltan Derdak, Medical director, Takeda
Abstract: Fibrosis stage alone is often insufficient to identify patients most likely to benefit from anti-fibrogenic therapy in MASH. Patients with similar histologic fibrosis can have markedly different levels of active fibrogenesis, inflammatory activity, and treatment responsiveness.
This presentation will discuss the concept of precision fibrogenesis—moving beyond fibrosis stage toward biologically informed patient selection and treatment monitoring. Quantitative assessment of active fibrogenesis using PRO-C3, supported by practical enrichment tools such as AST, FAST score, and LiverPRO, can improve identification of patients with ongoing collagen formation and active fibroinflammatory disease. In parallel, qualitative stratification through the “hot” versus “cold” fibrosis framework highlights distinct immune-driven versus metabolically driven fibrogenic phenotypes, supported by proteomic, metabolomic, and lipidomic signatures.
Emerging tools for monitoring anti-fibrogenic response, including improved PRO-C3 measurement using automated platforms such as the Roche Cobas Elecsys® immunoassay system, as well as target-specific imaging approaches such as PDGFR-PET, may further strengthen early proof-of-concept decision-making. Finally, integration of biomarkers, imaging, and multi-omics through AI-driven approaches may help define the future of precision trial enrollment and anti-fibrogenic drug development in MASH.
Pharmaceutical superintelligence: How generative AI is reshaping ECM-targeting discovery for fibrosis, oncology, and inflammatory disease
Aisyah Sjöholm, Associate director, Insilico Medicine
Abstract: This session explores how generative AI, multimodal foundation models, and autonomous drug discovery platforms are transforming the development of extracellular matrix (ECM)-targeting therapeutics across fibrosis, oncology, and inflammatory diseases. As ECM biology becomes increasingly central to understanding disease progression, tissue remodeling, immune regulation, and therapeutic resistance, AI-driven approaches are enabling faster identification of novel targets, biomarkers, and precision therapeutics within complex biological systems. The session will examine the shift from fragmented computational pipelines toward integrated “prompt-to-drug” discovery workflows that combine generative chemistry, multimodal biological data analysis, and automated experimentation. It will also highlight Insilico Medicine’s landmark achievement of advancing the world’s first generative AI-discovered therapeutic into Phase 2a clinical validation, alongside publication in Nature Medicine, demonstrating the growing clinical maturity of AI-enabled drug development.
About the speaker: Dr. Aisyah Sjöholm is a physician and global health expert specializing in the application of artificial intelligence in drug discovery and development. At Insilico Medicine, she works with pharmaceutical, biotech, and academic organizations worldwide to integrate advanced AI platforms into translational research and therapeutic development strategies. Her work focuses on building cross-sector partnerships that accelerate innovation in AI-enabled drug discovery, including emerging approaches for complex diseases involving extracellular matrix dysregulation.
