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Expert interview: how to access, retain, contextualize and leverage siloed bioanalysis data

21st Mar 2019

In bioanalysis firms, there’s a lot of pressure to do more with less.

This means there’s a huge focus on increasing throughput in the laboratory, and contracting the QC timeline – either by the training of scientists or the use of software – whilst complying with legal regulations and continuing to build their reputation in the industry.

Ensuring the successful implementation of every scientific analytical tool requires coming together and collaborating with partners, both internal and external, to form a data strategy fit to the business.

The IDBS Bioanalysis Solution eases an organization’s QC burden, helps them manage workflows more efficiently and increases productivity. IDBS works closely with scientists to deploy the solution, guaranteeing the product meets their specific business requirements, helping them innovate and continue to grow.

In this expert interview, Graeme Dennis, Commercial Director of Preclinical Pharma at IDBS, describes how E-WorkBook and, by extension, the IDBS Bioanalysis Solution, can access, retain, contextualize, and leverage the siloed data from hundreds of analytical instruments at the bench, for current and future use.

Graeme’s role requires him to approach informatics from the perspective of the scientific domain and show scientists in the pharma sector how The E-WorkBook Cloud can help drive their business by treating data as an asset.

If you’d like to know more about how your lab can benefit by treating your data as an asset, then click here to discover more about the IDBS Bioanalysis Solution or get in touch – or watch the video below.

Graeme Dennis has twenty years of experience in scientific informatics implementation across North America, Europe, and Asia. As the Commercial Director of Preclinical Pharma at IDBS, he helps scientists understand how they can get the most out of the research and development platform IDBS offers to meet their business needs.

 

More topics:   Medicine of the future: personalizing with AI and machine learning
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