Company Overview
Gutz Analytics builds AI models to better understand human disease through subtyping. Our mission: lower patient care costs and pave the path for treatments that actually work.
Our Dynomics platform uses Dynamic Variational Autoencoders (DVAE) to create digital twins from multi-omics data—microbiome, metabolomics, proteomics, genomics—enabling precision approaches that match treatments to individual biology.
Our Current Focus: Autism Spectrum Disorder
We’re applying our platform to autism, where we’ve achieved >80% prediction accuracy in our published meta-analysis. Our Nature Neuroscience publication established the autism-gut-brain axis connection, and we’re validating our approach through collaborations with leading research institutions.
Broader Applications
The same platform powers applications in oncology (immunotherapy response), autoimmune diseases, and other neurological conditions—demonstrating the broad utility of our disease subtyping approach.
Leadership Team
James Morton, PhD
Founder & CEO
Dr. James Morton is a pioneer in biostatistical and machine learning methodologies for multi-omics applications, with research published in Nature journals. He received his PhD in Computer Science from UC San Diego and founded Gutz Analytics in 2019 after serving as an investigator at the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), where he led development of biostatistical methods for high-dimensional, multi-modal longitudinal modeling.
Jonathan Sanders, PhD
Co-Founder & CSO
Dr. Jonathan Sanders is an evolutionary biologist and bioinformatician with nearly two decades at the forefront of gut microbiome research. He earned his PhD in Organismic and Evolutionary Biology from Harvard University and has contributed to over 75 papers in journals including Science, Nature, and PNAS. With expertise spanning wet lab specimen processing to computational analysis of massive datasets, Jon has led efforts to develop high-throughput metagenomic protocols and flexible cloud-based analytical pipelines.
