Issue:March 2023

CLINICAL TRIALS – New Technology & the Global COVID Pandemic Drive the Need for More Decentralized Trials


Remote clinical trials are becoming the new standard in clin­ical research. A variety of terms have been used to describe re­mote trials that incorporate patient-facing technologies, such as tablets, smartphone apps, or wearable sensors. They have been described as virtual trials, decentralized trials, remote trials, di­rect-to-patient trials, siteless trials, and hybrid trials. Whereas a digital trial is defined by the method used to capture the clinical trial data, a true digital clinical trial is one in which all data are captured without the use of any paper forms during the conduct of the study.

The COVID-19 pandemic has accelerated the ongoing shift to remote clinical trial monitoring. Remote site access and mon­itoring platforms are now an essential element of the clinical trial process and a vital connection between the sponsor, the clinical research organization (CRO), and the research site.


By digitizing the entire clinical trial process, remote clinical trial monitoring is becoming critically important to both sponsors and trial site administrators, offering the following benefits:

Complete access to remote clinical trial sites – By digitally con­necting sponsor and trial site systems, the clinical trial adminis­trator can securely access the site’s documentation from anywhere at any time. Sponsors and CRO monitors can securely access sites that they need to manage. This secured access allows monitors to complete their work remotely without onsite restric­tions, saving considerable time and reducing overall cost.

Site and sponsor communication – The digitization of clinical tri­als allows for streamlined communication in the form of trial alerts and notifications, real-time dashboards, messaging, and email push notifications. These features improve communications and consolidate all conversations in which the work gets done – in the system itself.

Process compliance and trial oversight – The digitization of clin­ical trials creates a secure environment in which to comply with both HIPAA and 21 CFR Part 11 regulations. Built-in audit trails and the ability to view and verify trial documents provide a path to compliance. Adaptive data integration is used to integrate het­erogeneous systems data. The ideal environment delivers “de­fense of depth” security, whereby security is controlled from a physical structure, such as entry to data centers, hardening net­works, and servers. When it comes to application, implementing security at the user interface (UI), business, and data access layer component (DALC) levels enables data protection via concentric layers of security.

Automated workflows and repeatable standardized processes – With the digitization of clinical trial systems, the documents needed for submission to FDA and the workflow for review and approval can be automated. All trial documents are stored cen­trally and streamlined with secured access to all privileged users. With digitization, routing of documents is automated via a unified platform that allows administrators to easily redact, edit, and cap­ture data as well as update versions of documents in a single database. The industry is moving toward a unified platform with a single database for all clinical trial products like electronic data capture (EDC), clinical trial management systems (CTMS), electronic trial master files (eTMFs), and elec­tronic patient-reported outcomes (ePRO).

Easy tracking of study progress and trial sites – Digitization helps improve site per­formance and enables real-time tracking of study progress without site staff assis­tance. System alerts and notifications for document completion and other site activ­ity can be easily set up for comprehensive tracking. Analytics with dashboards can provide a singular view of site efficiency, study timelines, document completion, and outstanding actions to manage trial activi­ties more effectively.

Comparative Analysis: Traditional & Virtual Clinical Trial Processes1

Click image to enlarge


Remote/virtual clinical trials have in­creased in popularity since the start of the COVID-19 pandemic, in response to the adaptations and the contingency plans that every industry, including the life sciences, have had to implement.

The technological advances made throughout the past 5 years have made remote clinical trials possible. With the technology tools available today, remote/virtual clinical trials bring clinical research directly into the participant’s home via a central and virtual coordinating site.

Remote clinical trials utilize devices that monitor and deliver vital information about patients. Wearables like Apple Watch, Fitbit, electrocardiogram (EKG) monitors, blood pressure monitors, and glucose monitors are also used to get a complete picture of the patient’s health.

Mobile health applications and tele­health technologies are used to collect medical data from participants and trans­mit this information to the central study center. Video conferencing has revolution­ized the ability to remotely monitor and en­gage with patients and clinical trial managers. Clinical trial research compa­nies believe the use of patient-facing tech­nology helps in widening the pool of trial participants/volunteers, enhancing patient retention, improving data quality, and fos­tering a holistic, patient-centric experience. Patient-facing systems are designed to pro­vide a wide range of computer- or internet-based services that support patient interactions with the healthcare system. Ex­amples of these systems include patient portals, mobile applications, and online peer support communities.

The need for remote clinical trials is increasing because:

  • Remote clinical trial solutions can signif­icantly improve recruitment of patients and site staff, safety monitoring, patient education, pre-screening, and data ver­ifications.
  • Remote trials can deliver significant cost efficiencies to pharmaceutical and biotechnology companies, positively impacting their bottom lines.
  • Implementation of decentralized and remote solutions also accelerates time-to-market for new drugs by reducing the overall length of the clinical trial life cycle. Other benefits include reduced enrollment periods, faster study initia­tions, lowered patient dropout rates, and improved data collection features.
  • Remote visit set-ups can reduce the overall cost of conducting virtual clinical trials, compared to conventional clinical trial methods. Additional capital savings can result from the reduced number of operational clinical sites and lower pa­tient travel reimbursements.


The growth of decentralized clinical trials is being enabled by several key tech­nologies that span the entire clinical trial spectrum. Notable technology enablers in­clude the following:

Patient-facing technologies – In remote clinical trials, patients need to be provided with choices related to accessing trial in­formation, user-friendly training materials, video visits, and direct-to-patient study supplies, among other options. The avail­ability of technologies that enable these choices can optimize a patient’s clinical trial experience, which is especially impor­tant to the overall success of any remote clinical trial.

Unified data platform – With the advent of data lakes and unified data platforms that support the entire life cycle of clinical trials, the effectiveness of decentralized tri­als has improved vastly. In decentralized trials, there is a variety of data sources, in­cluding devices, imaging technologies, electronic health records (EHRs), labora­tory information systems (LIS), EDC, CTMS, and ePRO. Data platforms allow for real-time/remote access to all clinical trial data, and enable the deployment of automated and intelligent processes to provide near real-time data review. In addition, data platforms can facilitate the following:

  • Real-time compliance monitoring to un­derstand data completeness
  • Data monitoring for safety
  • Monitoring for data quality and com­pleteness

On-site/remote consent from patients – Electronic automation of the patient con­sent process can enable flexibility and con­sistency in information exchange and data capture. The digitization of remote clinical trials provides easy-to-understand infor­mation and the ability to access consent information throughout a trial, ensuring appropriate regulatory compliance.

Clinical trial protocol development and design capabilities – The protocol is the playbook for any clinical trial. The advent of technologies that can connect patients remotely to trial sites can enhance the sponsor’s understanding of site and pa­tient burden during protocol development and design, and can help determine the appropriate level of “decentralization” within a specific trial, increasing its overall probability of success.


In the past few years, technologies like artificial intelligence (AI), machine learning (ML), and natural language pro­cessing (NLP) have made an enormous impact across all aspects of clinical re­search.

Advanced analytics tools that use AI and ML are providing clinical trial admin­istrators the power to make sense of the vast amounts of data collected through clinical trials. These tools enable advanced statistical predictive modeling and process automation to enhance overall study qual­ity

Today, the volume, variety, and veloc­ity of structured and unstructured data generated by clinical trials are outpacing traditional data management processes. The reality is that there is simply too much data coming from too many sources to be manageable by human teams alone. At Anju Software, we are constantly innovat­ing tools, such as TrialMaster, an intuitive EDC suite that accelerates Phase 1-4 clin­ical trials and delivers features to drive de­centralized trials. TrialMaster improves efficiencies and reduces workflow impact while enhancing data quality, resulting in faster study submission times.

As the remote clinical trial environ­ment continues to evolve, AI/ML technolo­gies show remarkable potential to automate data standardization while en­suring quality control, in turn easing the burden on researchers with minimal man­ual intervention.

The use of AI/ML-driven data man­agement does more than accelerate data capture or provide generalized insights. These platforms seamlessly integrate large volumes of data from a breadth of sources and feature automation tools to streamline the review process. They can also clean and house all data in a single location and use custom ML algorithms to identify data errors, outliers, and false entries. As a sub­set of AI, NLP can identify site- or study-specific risks in both structured and unstructured data.

AI/ML technologies also enable pre­dictive analytics that can maintain patient safety and improve site performance by detecting and mitigating potential safety issues. They can also facilitate site selec­tion, more effective risk-based quality management, enhanced patient recruit­ment and engagement, and overall effi­ciency throughout the clinical trial life cycle.

AI and ML cannot solve every prob­lem in clinical research. However, AI/ML tools can increase the amount of data col­lected, pull from multiple data sources, and ensure the “cleanliness” of data for researchers to properly analyze. In a few hours, these tools can accomplish tasks that would take human researchers months or even years. In short, as the in­dustry leaps into new frontiers, AI/ML strategies are redefining the clinical devel­opment cycle like never before. With digi­tal transformation leading the way, drug companies can redouble their efforts to get to the right therapies into the hands of pa­tients faster, yielding advances that will revolutionize the space forever.


  1. Yaakov, R.A., Güler, O., Mayhugh, T., Serena, T.E. Enhancing patient centricity and advancing innovation in clinical research with virtual ran­domized clinical trials (vRCTs). Diagnostics 11:151 (2021).

Suhas Gudihal is Co-Founder, Anju Software, where he drives product strategy and direction as well as oversees Anju’s technology architecture and product development. Throughout his career, he has created and managed product engineering labs across various environments. He has successfully built and scaled up engineering teams for start-ups to large enterprises. He has successfully integrated over 20 acquired companies. He oversees Anju teams responsible for the development and commercialization of adaptive technologies for clinical trials, medical affairs, and data with world-class customer support. Leveraging AI and data-driven analytics, Anju’s leading suite of solutions, including TrialMaster, delivers data and application integration capabilities to the global pharmaceutical, biotech, and contract research Life Sciences markets. He earned his BS in EE, his MS in Computer Systems, and his MBA with specializations in High Technology and Innovation. He is also a Certified Management Accountant of the IMA, and a Fellow of Management Accountant institute of India.