Construction of patient trajectories to model clinical trial outcomes: Application to Myasthenia Gravis

Abstract Accurate prediction of patient outcomes in clinical trials is crucial for timely assessment of treatment efficacy. This study introduces a novel approach to predict patient response by constructing temporal trajectories from longitudinal clinical data. We aim to extrapolate these trajectories to forecast individual outcomes and identify when new patients align with established response patterns. Utilizing data from the MGTX trial of myasthenia gravis patients, we evaluate the predictability of these trajectories and discuss potential confounding factors. Furthermore, our analysis yields an automatic clustering of patients based on treatment success, revealing potential associations with age and smoking status. Competing Interest Statement Dr. Garbey is CEO of Care Constitution and has patents pending related to present technology. Dr. Kaminski is a consultant for Roche, Takeda, Cabaletta Bio, UCB Pharmaceuticals, Canopy Immunotherapeutics, EMD Serono, Ono Pharmaceuticals, ECoR1, Gilde Healthcare, and Admirix, Inc. Argenix provides an unrestricted educational grant to George Washington University. He is an unpaid consultant for Care Constitution. Dr. Kaminski has equity interest in Mimivax, LLC. He is supported by NIH U54 NS115054. The remainder of the authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding Statement The work was supported in part by the MGNet a member of the Rare Disease Clinical Research Network Consortium (RDCRN) NIH U54 NS115054. Funding support for the DMCC is provided by the National Center for Advancing Translational Sciences (NCATS) and the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by NSF-I Corp award 838792 (47354/1/CCLS 91906F). Dr. Garbey is CEO of Care Constitution, which supported digital tools and AI algorithms. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The National Institutes of Neurological Disorders & Stroke funded the trial and assembled an independent Data Safety Monitoring Board. Sites received local institutional review board (IRB)/ethics committee approvals, and each patient provided written informed consent before study entry including provision of serum samples. All data was deidentified and provided to the investigators. The George Washington University approved these investigations. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data produced in the present study are available upon reasonable request to the authors.