Profiling with CourseMap AI
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CourseMap AI: digital twin technology for patients with neurodegenerative disorders
CourseMap AI is Qairnel’s award-winning patented digital twin technology designed to predict individual disease trajectories, quantify patient heterogeneity, and improve the design and analysis of neurological clinical trials. By transforming complex longitudinal data into actionable prognostic insights, CourseMap AI strengthens decision-making across clinical development.
What CourseMap is
CourseMap AI is a disease progression modeling technology that creates individualized digital representations of patients based on clinical, imaging, and biological data. These digital twins capture both population-level structure and individual variability, enabling robust long-term trajectory estimation.
Developed and validated over a decade of academic and translational research, CourseMap AI is designed for use in real clinical trial settings.
Why CourseMap AI matters
Neurological clinical trials are strongly impacted by patient heterogeneity and slow, variable disease progression. These factors reduce statistical power, inflate sample sizes, and complicate treatment effect estimation—particularly in early-stage studies.
CourseMap AI addresses these challenges by providing a principled, validated way to model disease trajectories, identify fast progressors, and account for inter-individual variability in trial analyses.
Who CourseMap AI is for
CourseMap AI is for sponsors aiming for phase 2 or 3 trials in neurodegenerative diseases
- supporting trial design
- facilitating go/no decision with more precise estimates of the treatment effect
- lower sample size in pivotal trials
- increasing the odds of detecting efficacy if the treatment is effective
From modeling to trial execution
CourseMap AI is deployed as part of an operational, trial-ready workflow designed to minimize sponsor burden. Blinded baseline trial data are securely shared, locked and versioned models are executed, and patient-level prognostic covariates are returned in formats directly usable by sponsor biostatistics teams within standard analysis frameworks (e.g., MMRM).
This workflow has been executed end-to-end in Phase 2 trials under strict timelines, with turnaround times of less than four weeks following database lock and prior to any result disclosure—allowing outputs to be incorporated into ongoing decision-making processes.
Scientifically validated, operationally robust
CourseMap AI is grounded in peer-reviewed research, including large independent validation studies published in leading scientific journals. The technology has demonstrated state-of-the-art performance in long-term cognitive decline prediction and clinically meaningful impact on trial design parameters.
By combining scientific validation with rigorous operational execution, CourseMap AI turns digital twin modeling into a reliable, deployable asset for neurological clinical development.