Decentralized/Virtual Clinical Trials

Manu Swami,

Senior Vice President,
Data and Analytics | Cloud | HealthCare and Life Science Solutions

Published: January 17, 2023

Subject A, a resident of a small village in the US, suffers from a severe medical condition. As her current medications to manage her medical condition have not been yielding the expected outcomes, her provider is looking for new medications in the market that can help. The provider comes across a trial underway in a faraway city/state, which seems to address the exact condition Subject A faces today.

However, with a conventional site-centric clinical study setup, although Subject A is a right fit, logistical challenges encompassing multiple visits to the clinical sites and the impact on quality of life, including work interruptions, do not allow her to participate. Meanwhile, the pharma company conducting the trial faces challenges in recruiting and enrolling suitable patients, amending protocols, and facing delays, eventually costing a lot more money than budgeted.


Challenges of clinical trial patient recruitment


on average spent on patient recruitment and retention

up to $8 million/day

in lost sales due to delays in patient recruitment

Clinical Trial Awareness


Of clinical trials fail to retain enough patients


of sites enroll one or no patients in their studies


of patients drop out of a clinical trial


of clinical trails fail to finish on time


of the total US Pharmaceutical clinical trial budget goes toward recruitment ($1.89B)

Conventional site-centric setup often leads to challenges or inefficiencies in patient recruitment, engagement, and retention and increases costs. Also, with the rise in precision medicine, oncology, and rare disease trials, finding participant cohorts becomes mandatory, and expanding the available participants becomes paramount for success.

Decentralized Clinical Trials

Stream of technological advancements in areas such as IoT, Data Science, Edge Computing, and Telehealth, and their convergence, has enabled companies to conduct De-centralized/virtual clinical trials (DCT). Mobile and home healthcare and alternative-care locations enable more procedures or trial operations to occur away from research sites. Tools such as eConsent, telehealth, remote patient monitoring (RPM), electronic Patient-reported outcomes (ePRO), and electronic clinical-outcome assessments (eCOAs) allow to maintain links to trial participants without in-person visits.

With DCT, Subject A can be screened for the trial, trained for participation, get the required supplies delivered to her, be remotely monitored, share updates with the investigator remotely, and feel connected to the trial - everything from the comfort of her home.

DCT brings in the much-needed flexibility and control to sponsors, easy access to patients, improved diversity, reduced administrative costs, improved efficiencies, and most importantly, brings innovation faster to the market and allows sponsors to adapt to the results during the trials.

On the other hand, investigators/sponsors have a real-time view of the patient data, can monitor adherence, analyze for outcomes, and adapt as required.


DCT adoption has been improving year on year, given its benefits. While Covid has played a part in acceleration, further drivers could be the industry challenges of drug pricing reforms and declining RoI on research and development observed by the Pharma companies.
Complex trials requiring imaging through heavy diagnostic devices or activities requiring lab assistance could operate on a hybrid mode. In this mode, the trial is digital in all aspects other than the unavoidable manual touchpoints.

Adoption Challenges

Digital/Decentralized clinical trials can significantly change the clinical development business models. Many new and existing market players offer decentralized clinical trial platforms to allow companies to adopt DCT. The notable players are Medable, Science 37, Thread, Medidata, Castor, LabCorp, Iqvia, etc.

However, the shift to Digital Clinical Trials brings its own set of challenges beyond platform adoption. It requires transformation across the spectrum of clinical trials and consideration that each trial is different.

Establish Trust – Sponsors need to build the patient's trust in delivering the care through technology, assuring a better treatment despite no/limited physical interactions with the investigator. Although trust in health using digital technologies has improved a lot post the pandemic, sponsors still need to reassure the participants by showcasing an understanding of the needs of the participants/condition

User education – All patients do not share the same level of technology literacy. Sponsors must put up easy-to-follow training materials and establish a support system to train the patients on various systems, including setup, sample collections, and devices that are part of the trial. It is important to enable them to reach out for technical help easily and overcome their aversion to change 

Logistics – Requires extensive planning to have the devices for home monitoring delivered to participants in time, ensure the procedure is followed to collect samples and ship to the facility, and manage order refills, returns, or complaints.

Data Handling – With quality and real-time data flowing in from the participant's systems/devices and integrating across different participant systems, data integrity, privacy, storage, and processing are crucial for success

Cybersecurity and Fault-tolerance – Wearables, sensors, and digital products communication must be safeguarded from cyber-attacks and have fault-tolerant mechanisms in place to manage events like sensor malfunction.

Site Monitoring and Auditing – With Trials becoming hybrid and decentralized, sponsors need to look for technology that can facilitate remote source review and adhere to emerging ways of monitoring and auditing, as it is essential to measure the quality of the trials

Technology Complexity and Compliance Challenges – Leveraging a connected ecosystem driven by intelligent AI algorithms drives additional complexity like FDA approvals. Hybrid semi-automated approaches must be explored to ensure early adoptions.

Regulations – This is a relatively new area, regulations and guidelines continuously evolve. It is necessary to keep abreast of new regulations and keep investigators or sites informed of the updates.


The way forward

DCT is constantly emerging with newer technologies, and that can further expand patient centricity and reduce costs, such as:

  • AI/ML – AI/ML could be ubiquitous, spreading across all areas of clinical development. Potentially drive the Digital companion/Investigator to a patient in providing contextual recommendations and support to the patients undergoing trials. For sponsors, it can help determine eligibility criteria, recognize patterns, clinical data noise reduction, bio-markers creation, etc., to further ease development and research. Engaging the patient-based machine-driven algorithms based on clinical claims and SDoH data sets will be critical to reducing dropout rates and ensuring the efficacy of clinical trials.
  • Open-to-Trial (OTT) Databases – Tap into the patient networks or databases where patients volunteer information into the network to aid trial recruitment, so sponsors can proactively reach out to the subjects for trial participation through their preferred channel for communication. Use Geo-location to drive recruitment of patients based on open and priority databases.
  • User experience –Create Multi-lingual and intuitive mobile/ web apps leveraging design thinking to allow patients to manage all their trial needs in one location. Leverage technologies like NLP for ease of patient inputs or chatbots/Conversation AI (CAI) based engagement to up patient experience and retention. These apps can also be expanded as a digital supplement to the drug on commercialization. These apps can also be used as online collaboration forums to discuss clinical trial outcomes with caregivers, providers, peer subjects, and patient advocacy groups.
  • Integration – Integrate with clinical systems, wearables, and other systems to understand any recent updates to the participant's condition beyond the trial, notify the participant or investigator, and allow intervention or update the care plan as required. Leverage real-time integration with EHR systems to drive recruitment when patients consult with physicians.
  • On the fly analysis/edge computing – Process data from sensors and other products on edge to spot anomalies, respond quickly to an emerging situation, and provide clinical insights or alert an investigator.
  • Mixed Reality – Effectively train the participants to self-help using the systems/devices related to the trial and guide participants through sample collection procedures. Engage with fellow participants across the country/globe and allow them to participate in sponsor events.


DCT will continue to evolve with technology - with today's innovative features turning into essential/must-have features tomorrow.



Manu Swami

Senior Vice President,
Data and Analytics | Cloud | HealthCare and Life Science Solutions

Manu is a seasoned Data & Analytics professional with 20+ years of global experience in leading transformation programs across Data Platform Modernization, Advanced Analytics, AI and Master Data Management domains. He currently leads the Healthcare and Life Sciences solutions and technology practices for Virtusa.

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