Looking Into Using Technology in Managing Data in Clinical Trials Capstone Project

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Technology in Managing Data in Clinical Trials

Even a casual observer will undoubtedly make note of the range of high-tech solutions that are causing disruptive change in the process of clinical trials. From webinars and multi-day meetings to an expanding pool of literature, technology has been establishing itself as the key to an era fixated on measurable improvements like accelerating the research start-up phase, restructuring clinical trial information transmission, and overhauling research monitoring. And the issue is no longer a distinct solution to apparently intractable glitches; instead, it revolves around sharing real-time information captured by these solutions for facilitating strategic decision-making by collaborators, with regard to a research's status as it is actually progressing. This constitutes a drastic change from the conventional paper-based techniques that underlie the industry's costly and time-consuming methods of carrying out international clinical research, in which data quality assessment depended on near-database locking or onsite monitoring, sometimes, many years after first 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 one can begin applying it to highly regulated industries. When some clinical researchers began employing technology, tremendous questions arose with regard to Cloud technology's maturity and its ability to integrate with internal systems.

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However, a reversal of direction has occurred, with individuals who wouldn't ever consider using the Cloud some years back, now considering it mandatory (Morrison, 2015).

Acceptance of Cloud computing implies the technologies supported by it, like eSource, electronic trial master file (eTMF), next-gen clinical analytical interface, and risk-based monitoring (RBM) founded on-demand, virtual data warehouses, which are also recognized. Cloud technology implementation necessitates a transformation of the existing business model. The model was formulated several decades ago, as a response to the time when research trials were quite different from the present international multi-site approaches. Even the valuable development of the electronic data capture (EDC) system, which brought immense progress in the form of edit checks, quicker clinical trial information viewing and an improved query process, was still grounded on 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, with research suggesting that time is ripe for a similar transformation in the field of clinical trials (Morrison, 2015).

Veterans in the industry acknowledge and embrace….....

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