Informatics
Unlocking clinical trial data
Unlocking Clinical Trial Data to Uncover New Therapeutic Opportunities

Unlocking Clinical Trial Data to Uncover New Therapeutic Opportunities

By David Wang, Masha Hoffey and Dr Simone Sharma

This article discusses opportunities, challenges and best practices in leveraging infrastructure excellence and AI to unlock the value of early or inconclusive clinical trial data. The goal... driving stronger biomarker-based insights and decisions and helping to advance new cures and treatment approaches.

As we all know, data is increasingly king in our information-driven world and organisations that learn how to turn mega information into informed strategies are creating true sea changes in their industries. The opportunity to harness the power of data in new and exciting ways is also moving increasingly into life sciences.

In drug discovery, for example, AI can now be employed to mine the mountains of siloed and under-utilised data from early or inconclusive clinical trials. Having this capability helps feed the increasing demand for genotypic and phenotypic data, leads to deeper and faster bio-marker informed insights and helps support the development of new approaches and cures.

Achieving this can seem a herculean task, but there are growing examples of success and best practices around data management, organisational rigour and combining the best of science and technology domain expertise to meet the key challenges posed.

New data insights propel new thinking

The higher volume and variety of data being generated in our labs certainly brings more data management complexity, but it also brings greater potential for improving the success of clinical trials by better leveraging biomarker-driven science.

For example, routinely-collected biomarker or assay data is now being used to pre-define patient trial subsets around shared, common disease aetiology or molecular profiles. This approach is yielding results and appears to be compelling regulatory authorities, such as the US FDA, to encourage the use of technologies such as advanced analytics for next-generation sequencing and high throughput screening to identify those patients that could benefit most from emerging therapies....

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