Design More Patient-Centric Trials
Renal indications are typically not candidates for decentralized trials since eGFR trajectories and proteinuria measurements are primary endpoints and central laboratory standardization is non-negotiable for regulatory acceptance. However, a hybrid approach that focuses on reducing ancillary visit burden enables trials to better accommodate patients. The following hybrid strategies are worth considering:
- Local or satellite labs that handle safety blood samples between key study visits
- Telehealth check-ins to replace some in-person visits for stable patients
- Home nursing to aid patients with mobility limitations
Hybrid trial elements should be designed under advisement from key stakeholders to ensure that patient convenience is not gained at the cost of data quality or safety. By adjusting protocols, visit schedules, and support services to reduce burden on a small and medically complex population, sponsors bolster enrollment and retention goals.
Sponsors should also incorporate feedback and insight obtained from patient advocacy groups as they design protocols. Patient communities can provide their perspectives, flagging visit burden, travel distances, and procedure anxiety that are not visible in epidemiology data. For conditions with well-developed patient registries and advocacy groups — such as Alport syndrome, FSGS, and IgAN — patient advocacy organizations can collaborate on developing compliant recruitment messaging and mapping referral pathways via the investigator network and study communication plan.
For rare kidney diseases, patient advocacy organizations and disease registries are often the fastest route to an engaged patient pool. Sponsors need to foster relationships with these bodies to facilitate introductions and co-develop institutional review board (IRB) or ethics committee (EC)-approved awareness content. Investigators should verify that all communications meet applicable FDA, EMA, and local authority guidance on patient recruitment, while registries provide de-identified feasibility data that informs site selection and screen-failure forecasting to reduce the risk of inflated enrollment expectations.