Technology and Data Management in Clinical Trials

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).

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.

Cloud Technology and Its Emerging Role

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).

Veterans in the industry acknowledge and embrace the changes that technology is offering them. Technology users observe that streamlined technologies and processes are condensing the research timeline through effective data collation and improved adherence to contract timelines. As stakeholders — including contract research organizations (CROs), regulators, clinical sites, and sponsors — collaborate to bring greater effectiveness to the struggling clinical trials sector, both process and technological changes have been recognized as the key drivers of improvement.