Bioanalysis Zone

Chapter 9: The future of big data in regulated bioanalysis: clouds, trends and transparency

Doi: 10.4155/FSEB2013.14.196

Author

Nick Levitt
Principal
TwoCenter Technologies
nick@twocenter.com

About the Author

Nick Levitt is the founder and president of TwoCenter Technologies (MA, USA), a consulting company serving to help innovative small and mid-sized companies develop and market successful products in the laboratory instrumentation market. Prior to this, he launched many successful products into the laboratory instrumentation market, including several industry-leading MS platforms. One of his core interests is the interface between high performance instrumentation and the software which translates data into knowledge. He holds an undergraduate degree in nuclear engineering from the Massachusetts Institute of Technology (MA, USA) and an MBA from the Wharton School of Business (PA, USA).


The future of big data in regulated bioanalysis: clouds, trends and transparency

Abstract

Big data techniques used in regulated bioanalysis will significantly change the way data is stored, processed and checked. Though challenges remain, cloud computing is increasing in both its usage and effectiveness within this arena. The collection of communities of data within a single environment creates opportunities for better quality assurance and increased analysis of data sets. Trends toward accurate mass LC-MS and open clinical trial sets provide some interesting opportunities to post-trial analysis. However, significant hurdles remain.

Introduction

The intersection of pharmaceutical development and the computer revolution has bred significant innovations in pharmaceutical research methods, including grid-based computational biology systems for screening and compound optimization, large-scale genomic research initiatives for personalized medicine (such as the human genome project, genome-wide association study GWAS and other research techniques), and massive metabolism and toxicity databases for assessing and helping to predict molecule-specific behavior.

Compared to these intellectual and scientific breakthroughs, the effect of computing on the bioanalysis performed in clinical trials has been relatively minor. However, over the past 20 years, significant change has occurred. Fast algorithms to collect and process large amounts of complex data have given the instrumentation the ability to provide more robust and accurate information [1]. Laboratory information management systems (LIMS) such as WATSON LIMS™ and electronic laboratory notebooks (ELNs) have served to structure the collection of data and perform essential calculations relevant to the study [2]. Increasingly effective electronic signature, role and security features provided within the analytical software have contributed to the simplification of validating the systems as 21 CFR Part 11 compliant.

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