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Everest analysis: How Medable eCOA solves speed, patient experience, and customer needs
eCOA has moved from a supporting tool to a foundational pillar of modern clinical trials, and Everest Group agrees. In its inaugural eCOA Products PEAK Matrix Assessment, Everest named Medable a Leader, citing strong market impact, accelerated timelines, and a platform built for real-world trial complexity. As the eCOA market surges toward nearly $1B in value, this recognition underscores how speed, patient experience, and AI-driven innovation are reshaping how trials are designed, launched, and scaled globally.


Playing catch-up: FDA wants “patient’s voice” ePRO in your oncology trial
For years now, the FDA has been making one point crystal clear to sponsors and CROs across our industry; they want the patient voice incorporated whenever possible in oncology trials.
The FDA's initiative is driven by the recognition that a patient's personal experience with a disease and its treatment is a unique and essential measure of a medical product's benefit and risk.
- Rationale: The FDA explicitly states that "patients provide a unique perspective on treatment effectiveness" and "some treatment effects are known only to the patient." Outcomes that truly matter to patients, such as functioning, quality of life, and the burden of side effects, are often best measured directly by the patient.
- Mandate: The Patient-Focused Drug Development (PFDD) effort, codified in part by the 21st Century Cures Act, requires the inclusion of such patient experience data in clinical research.
- Guidance series: To formalize this approach, the FDA has released a series of methodological guidance documents (the PFDD Guidance Series) that outline how stakeholders should collect, submit, and use patient input to inform medical product development.


Medable oncology solutions
Discover how Medable’s AI-powered oncology platform simplifies complex cancer trials by integrating eCOA, ePRO, and eConsent solutions—reducing trial time, improving patient retention, and enhancing data quality for faster, more efficient research.



