OMNI-BD Bioinformatics Scientists are partnering with DevSci Informatics to develop advanced models to predict clinical outcomes in patients with MS, and to better identify patients who may benefit the most from high-efficacy therapies. Two projects are highlighted to reflect the ongoing work in this direction that seeks to advance personalized healthcare and patient stratification in MS. The first, statistical and machine learning models for predicting progression, aims to develop a framework for evaluating predictive models using MS clinical trial data. This effort combines clinical, imaging, and biomarker data to identify progressors versus non-progressors, and to assess the time to clinical worsening. The second, biomarker profiles for informing treatment response in MS, utilizes the breadth of fluid biomarkers (partially collected for safety assessments) to identify clusters of patients who may have differential responses to ocrelizumab versus comparator treatment. Both projects have already yielded important insights into the mechanisms of progression, and may serve as foundational work in advancing care for patients with MS.
