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Telladarla, Lakshmi Chaitanya (2013) Data Visualization and Visual Analytics in Clinical trials. [Dissertation (University of Nottingham only)] (Unpublished)

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Abstract

In clinical trials even small amounts of data is critical in shaping the successful formulation of a drug and there is an increasing demand for easy and intuitive access to the data. Large, multicentre studies with different data collection techniques yield critical clinical information through every phase. The more efficiently study data is managed, the quicker the data can be extracted and analysed. During the initial stages of clinical trials, access to data is a serious need for resolving issues while they are still controllable and within the predicted cost frame. Data visualization empowers clinical development teams to quickly visualize and interact with huge volumes of clinical data in a single interface to support progressive decisions, rather than reviewing and tracking of results. Streamlining clinical trial data analysis with real time access to clinical data during all phases of clinical developments allows the user to interact with the data as soon as it is collected. Interactive visualizations allow users to explore the data easily and play around with it by applying filter criteria and decision making questions. Review and analysis of peripheral data using visual analytics can bring into light site performance and study resources, allowing enhancement of trial operations. Benefits of exploring crucial data (adverse events, demographics, lab values, drug exposure and response) in primary stages of clinical trial process are many. They serve to increase productivity by 20-40% by reducing errors and improving quality. Besides survival analysis capabilities that offer detailed models for patient accrual, dropout and time-to-event, valuable tools for study management, pharmacometrics, trial operations, pre-marketing security and post-marketing observation are also more feasible now with Data Visualization and Visual Analytics. The illustrations, statistical graphics can be exported for use in a variety of submission formats like presentation, publication with ease enabling managers and employees to exploit the technology to the fullest in everyday operations.

Item Type:	Dissertation (University of Nottingham only)
Depositing User:	EP, Services
Date Deposited:	15 Dec 2021 14:29
Last Modified:	15 Dec 2021 14:29
URI:	https://eprints.nottingham.ac.uk/id/eprint/26460

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