“In the future, 30% of trial data will come from the clinic, while 70% will be sourced by decentralised clinical trials (DCTs) or digital health technologies (DHTs),” said former MSD executive Dinesh Pillaipakkamnatt during a recent conference.
He noted that following the patient journey, even outside a clinical trial, results in valuable longitudinal data beyond the time window of the clinical trials.
However, he added that the ownership of the data lies with the patient, and thus it is significant to gain patient trust and consent for data collection, while speaking at the Clinical Data Management Innovation Conference 2025 in September 2025, in Princeton, New Jersey, US.
Strategies to increase patient engagement and reduce burden
According to Pillaipakkamnatt, one of the major challenges in clinical trials is patient retention, with nearly one-third of participants dropping out, often because research is conducted in clinics that patients do not typically visit. To address this, there is a growing need to reach patients where they are based, an area that represents nearly 80% of untapped potential, but requires robust logistical support.
Decentralised and digital tools can be applied in clinical trials to address some of these challenges. For instance, Pillaipakkamnatt mentioned that dry blood sampling offers an innovative solution for patients in remote areas such as those with rare diseases living far from central labs. Instead of relying on costly and impractical cold-chain shipping, patients can collect samples at home and send them to a central lab, even across continents.
Pillaipakkamnatt said that with individual patient data, researchers can analyse results across studies and geographies, potentially setting new gold standards and drug tolerance limits through meta-analyses.
Challenges of implementing digital solutions
While valuable in indications and trials requiring frequent patient interactions or multiple tests, However, implementing such digital solutions often comes at significant costs or challenges.
Pillaipakkamnatt noted that medical-grade devices such as the Apple Watch (classified as a Class II medical device), or “bring-your-own-device” models still require substantial data cleaning and management expenses.
Solely procuring and maintaining specialised equipment adds to the financial burden of running a clinical trial and thus striking a balance between innovation and cost-effectiveness remains a key challenge for the future of patient-centric trials.
Moreover, data quality and security is a critical issue while considering these approaches. Pillaipakkamnatt advised building secure cloud servers that should be siloed by both trial location and trial, as data crossing of trial data in one server is not ideal.
He acknowledged that despite recent advances, conducting a fully remote trial is very difficult and very rare to achieve. He added that in some cases such as myasthenia gravis, DCTs can lead to drug approvals, reduction in patient burden and positive outcomes, while in other indications, including paediatric antibiotic trials, using DCT models is not feasible.
Practical examples of DCT applications
Pain measurement is an example where data beyond that which is collected through questionnaires such as eCOAs is needed.
Pillaipakkamnatt said that since no dedicated device exists to measure pain, patient input and digital tools could prove essential to reduce patient burden of frequent clinic visits.
Digital biomarkers can be used in rheumatoid arthritis to monitor pain severity in wrists and ankles to assess the correct pain medication dose for the right population or to achieve dose escalation.
The former MSD executive commented that by combining supervised physiotherapist assessments with unsupervised patient-reported data through mobile solutions, correlations can be mapped to predict unreported pain, establish a pain index, and optimise dosing.
Pillaipakkamnatt also mentioned enabling remote patient services such as doctors, pharmacists, nutritionists and other providers, enabling telehealth solutions, personalised care and medication management at home. He noted that success of such services often depended on sustained patient engagement through alerts, nudges, and community groups to drive adherence through patient engagement modules.
When it comes to introducing new digital solutions in a study, lab-based informational trials can first assess usability and digital readiness, prior to being applied in a clinical trial setting. He concluded his presentation by stating the value of these informational trials, which allowed for rapid experimentation and quick validation of hypotheses through collaboration and served as a solution before starting full-scale clinical trials.
