StemCell Therapy

Leveraging Tissue Data and Analysis

By extracting and analyzing all the relevant data from tissue samples, and correlating that to genomic and other data in order to get a clear picture of what is happening inside a patient, several areas of diagnostic and drug discovery and development are impacted:

Evaluating combination therapies

With combination therapies, the diagnosisin terms of which drugs will be effective in combinationbecomes very complicated. Looking at tissue data in conjunction with the other patient data available enables researchers to combine many different molecules to understand which one tells the right storyin other words, which combination of those molecules demonstrate patterns that predict drug response, and thus which combination is the right one for a target group of patients.

Gaining insight into biological processes driving disease

In the past, the industry usually took a bottom up approach where a molecule or protein was considered first, and then researchers thought upward in terms of how that biological molecule could help a patient. This paradigm is changing and pathological data is now being used to drive biological research. By looking at tissue in a structured, statistical, and analytical way in addition to the molecules and pathways, new discoveries can be made, which ultimately triggers more purposeful research.

Identifying novel tissue diagnostics with prognostic or predictive value

Historically, researchers searching for biomarkers would stain certain proteins in the tissue, such as with immunohistochemistry (IHC), which they would then investigate with the naked eye. Much of this investigation is being automated now, however. Machines can identify more objects and more precise measurements in tissue than the human eye, and this approach is being used to identify biomarkers and develop diagnostics that could not previously be found.

The use of an integrated data approach to drug discovery and development has been slow to get off the ground, but the need and possibilities for a big data approach is growing. This is changing, however. Technologies are emerging that can collect, correlate, and structure a significant volume and multiple kinds of dataincluding genetic, tissue, clinical outcomes and other kinds of patient datain a meaningful way, giving researchers the ability to see the bigger picture and make discoveries that couldnt previously be found.

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How An Integrated Data Approach will Impact Personalized ...

This entry was posted on June 12, 2015 at 4:44 am and is filed under Personalized Medicine. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed. |