Multiple sclerosis has long been defined by unpredictability — patients don't know how their disease will progress, and clinicians can't always pinpoint the best therapy or the right time to switch. Precision medicine aims to change that by tailoring treatment to each patient's unique clinical history, imaging, biology, and preferences, rather than relying on population-level averages.

In the final installment of NeurologyLive's roundtable series Precision Medicine in Multiple Sclerosis: Advances & Unanswered Questions, experts from Cleveland Clinic's Mellen Center share their vision for the field's future. Neurologist Marisa McGinley, DO, describes a predictive model her team developed to estimate the risk of disease activity returning after a patient stops disease-modifying therapy — a critical question for aging patients on long-term immunotherapy. Like an MRI, the tool is designed to inform shared decision-making, not replace it.

Robert Bermel, MD, envisions embedding such tools directly into the electronic health record, while nurse practitioner Rebecca Cebull notes that patients crave concrete numbers to weigh their risks — one patient even described MS as "a fear disease" due to anxiety over both under- and overtreatment. Bermel frames precision medicine as "the antidote to unpredictability."

Key Takeaways:

• Predictive models for therapy discontinuation risk could reshape how MS treatment decisions are made
• Individualized, data-driven tools are intended to support — not override — shared clinician-patient decision-making
• Integrating these tools into EHR systems could make precision medicine a routine part of MS care

Why it matters: For the millions living with MS, treatment decisions carry enormous stakes. Tools that quantify individual risk could reduce both overtreatment and undertreatment, empowering patients and clinicians to make more confident, personalized choices.