Drug Repurposing and Precision Stratification in Autoimmune Disease
Sjogren's Disease is a chronic autoimmune disease with no approved disease-modifying therapy. Traditional drug discovery approaches have struggled to identify effective therapeutic targets, responsive patient populations, and biomarkers that reflect tissue-level disease activity.
From disease modeling to therapeutic nomination to clinical evaluation to biomarker discovery.
APPROACH
Stratica applied multimodal single-cell and spatial biology to patient-derived autoimmune disease tissues in collaboration with NIH investigators. Using StraticaOS, the team reconstructed disease-associated cellular ecosystems, identified dysregulated JAK-STAT signaling, and performed computational drug-to-cell matching to nominate a JAK inhibitor strategy for clinical evaluation.
The program has now entered a second phase: matched clinical trial tissues are returning for deeper Stratica analysis to compare responder and non-responder biology before and after treatment. These paired pre-treatment and post-treatment datasets are being used to identify predictive biomarkers, refine patient stratification strategies, evaluate companion diagnostic potential, and uncover additional therapeutic opportunities for future drug repurposing and development.
KEY OUTCOMES
JAK-STAT signaling identified as a disease-associated pathway
JAK inhibitor therapeutic strategy nominated through tissue-based computational modeling
Therapeutic hypothesis translated into prospective human clinical evaluation
Paired pre-treatment and post-treatment Sjogren's Disease tissues profiled with Xenium spatial transcriptomics, spatial proteomics, bulk transcriptomics, and multi-biofluids proteomics
Ongoing responder and non-responder analysis to support biomarker discovery, companion diagnostic development, and future patient stratification
Clinical trial-linked tissue data now feeding back into disease modeling and next-generation therapeutic discovery
IMPACT
This program demonstrates the full biological intelligence loop: starting with human tissue, identifying disease-driving biology, nominating a therapeutic strategy, supporting clinical evaluation, and using patient response data to improve future disease models. Rather than ending with a single analysis, the program creates a continuously learning system for drug repurposing, biomarker discovery, companion diagnostics, and precision stratification in autoimmune disease.
APPLICATIONS
Mechanism-of-Action Support in Inflammatory Lung Disease
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