Generating reliable evidence in rare diseases has always been a challenge, resulting in a field forced to make consequential decisions on evidence that would not pass scrutiny elsewhere, not because researchers are careless, but because the available data rarely allow for anything better.
Research and discussions at ISPOR 2026 pointed to digital and novel data collection methods as a proposed answer to this long-standing problem.1-5 Social media listening and patient community platforms can surface how patients experience a condition day to day in ways no registry captures. Wearable sensors and smartphone-based assessments can measure gait, motor function, and mobility continuously, tracking gradual change a quarterly clinic visit will miss. Natural language processing applied to electronic health records can identify patients who were misdiagnosed or never diagnosed and these records can be used to construct comparison groups where randomised comparators are not feasible.
The appeal of novel data sources for rare disease research is genuine, and for conditions where the alternative is no evidence at all, these methods represent real progress. But concern at ISPOR 2026 was just as prominent as enthusiasm, and rightly so. Social media and patient forums reflect people who are online and engaged, not a cross-section of everyone living with a condition. Wearable endpoints remain unvalidated in most rare disease contexts; for example, the field is still exploring what a meaningful change in accelerometer data looks like clinically in Duchenne muscular dystrophy. Digital control arms carry biases due to population confounding, misclassification, data missingness, and heterogeneity across sources; these biases can be difficult to detect, let alone correct. The real question is whether these tools answer the questions that matter, or simply the ones that are easier to address.
If these tools are to be used as rare disease evidence sources, where are they most defensible? One use case could be as earlier-stage tools for finding signals worth investigating further. A social media analysis surfacing an under described symptom cluster is a starting point, not a finding. An accelerometer study suggesting a treatment is preserving motor function is a reason to look harder, not a basis for a labelling claim. The temptation to skip from signal to conclusion, under the pressure of small patient numbers and urgent unmet need, is understandable. But this is where the most consequential errors of judgment tend to happen.
Ultimately, the rare disease field needs these tools. But it cannot afford to let volume substitute for quality. More data are only useful when it is in service of something a well-designed study can eventually confirm.
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If you would like any further information or advice on the themes presented above, please get in touch, or visit our Rare Diseases page to learn how our expertise can benefit you. Sarah Neubert (Consultant) and Jessica Maturo (Analyst) created this article on behalf of Costello Medical. The views/opinions expressed are their own and do not necessarily reflect those of Costello Medical’s clients or affiliated partners.
