Technology and Data Management in Clinical Trials
This paper examines the growing role of technology in managing data within clinical trials, focusing on the shift from conventional paper-based methods to cloud-based solutions. It discusses how tools such as electronic data capture (EDC), electronic trial master files (eTMF), and risk-based monitoring (RBM) are streamlining research processes, improving data quality, and accelerating timelines. The paper also considers the broader transformation of the clinical trials business model, drawing on Morrison (2015) and the Weisfeld et al. (2012) report on envisioning a reformed clinical trials enterprise in the United States through 2020.
- Introduction: Technology driving disruption in clinical trials
- Cloud Technology and Its Emerging Role: Cloud adoption enabling regulated industry applications
- Shifting Business Models in Clinical Research: Legacy models replaced by modern data-driven approaches
- Stakeholder Collaboration and Technology Adoption: CROs, sponsors, and regulators embracing tech change
- Infrastructure for a Transformed Clinical Trials Enterprise: Weisfeld report agenda for 2020 reform goals
✍️ How to write this paper — guide, tools & examples ▾
What makes this paper effective
- The paper grounds its argument in a real-world policy report (Weisfeld et al., 2012), connecting technological developments to a recognized institutional agenda for reform.
- It provides a clear contrast between legacy paper-based systems and modern cloud solutions, giving readers a concrete sense of what is changing and why it matters.
- The inclusion of specific technologies — EDC, eTMF, RBM, eSource — demonstrates subject-area familiarity and adds credibility to the analysis.
Key academic technique demonstrated
The paper effectively uses synthesis: rather than summarizing sources independently, it weaves together Morrison (2015) and Weisfeld et al. (2012) to build a unified argument about the necessity and direction of technological transformation in clinical trials. This technique shows how multiple sources can reinforce a single analytical claim.
Structure breakdown
The paper opens with a broad observation about disruptive technology in clinical trials, then narrows to cloud computing and specific tools. It transitions to the business model implications, broadens again to consider multi-stakeholder adoption, and closes by anchoring the argument in a national policy agenda. This funnel-then-widen structure suits an overview essay at the undergraduate level.
Introduction
Even a casual observer will undoubtedly note the range of high-tech solutions causing disruptive change in the process of clinical trials. From webinars and multi-day meetings to an expanding body of literature, technology has established itself as the key to an era focused on measurable improvements — accelerating the research start-up phase, restructuring clinical trial information transmission, and overhauling research monitoring. The issue is no longer about finding a distinct solution to apparently intractable problems; instead, it revolves around sharing real-time information captured by these solutions to facilitate strategic decision-making by collaborators with regard to a study's status as it actually progresses.
This represents a drastic change from the conventional paper-based techniques that underlie the industry's costly and time-consuming methods of conducting international clinical research, in which data quality assessment depended on near-database locking or onsite monitoring — sometimes many years after initial data collection. With an increasing number of drugs in the development phase, clinical trial professionals require cloud-based capabilities for streamlining trial activities. Cloud technology has advanced to the stage where it can be applied to highly regulated industries. When some clinical researchers first began employing this technology, significant questions arose regarding cloud technology's maturity and its ability to integrate with internal systems. However, a reversal has occurred: individuals who would not have considered using the cloud a few years ago now regard it as mandatory (Morrison, 2015).
Cloud Technology and Its Emerging Role
Acceptance of cloud computing brings with it recognition of the technologies it supports, including eSource, electronic trial master file (eTMF), next-generation clinical analytical interfaces, and risk-based monitoring (RBM) founded on on-demand, virtual data warehouses. Cloud technology implementation necessitates a transformation of the existing business model — one formulated several decades ago in response to an era when research trials were quite different from today's international multi-site approaches.
Even the valuable development of the electronic data capture (EDC) system, which brought significant progress in the form of edit checks, quicker clinical trial data viewing, and an improved query process, was still grounded in the conventional business model and characterized by legacy methods of validation and monitoring. By contrast, other data-intensive sectors have modified their fundamental business models, and research suggests that the time is ripe for a similar transformation in the field of clinical trials (Morrison, 2015).
References
Morrison, R. (2015). Technology's role in clinical trials. Applied Clinical Trials Online. Retrieved May 13, 2016, from
Weisfeld, N., English, R. A., & Claiborne, A. B. (Eds.). (2012). Envisioning a transformed clinical trials enterprise in the United States: Establishing an agenda for 2020: Workshop summary. National Academies Press.
Always verify citation format against your institution’s current style guide requirements.