Image Analysis: A Vital Tool in Drug Discovery

Ahead of the Discovery Summit 2016, read an interview with Amanda Lowe, Senior Vice President & Andreas Schønau, Chief Scientific Officer of Visiopharm, about the latest innovations in image analysis and how it is fundamental to digital pathology.

“We are at a very exciting time when it comes to digital pathology and image analysis as we are now seeing the first pathology laboratories use Visiopharm image analysis for in-vitro diagnostics. This is a huge step forward and a step that will benefit not only laboratories and patients, but also the pharmaceutical and diagnostic industry as it will enable more widespread use of quantitative measures that have so far been limited to high-end discovery and research facilities,” says Andreas Schønau, Chief Scientific Officer, Visiopharm.

Visiopharm, is a solution provider company, attending the marcus evans Discovery Summit 2015 in Las Vegas, Nevada, September 21-22.

What knowledge is missing from drug discovery today?

Amanda: The way that the knowledge is generated is not always effective. A lot of the knowledge created around, for example target validation or the testing of lead compounds, is often very subjective and qualitative.

Image analysis enables drug companies to eliminate subjectivity, and provide verifiable, quantitative results. It can also reduce inter and intra reader variability by creating standardized best practices for obtaining important information about tissue samples. Important decisions can then confidently be made by maximizing the scientific study of tissue in a measurable and reproducible way.

How can pharmaceutical companies improve their discovery process?

Amanda: Most importantly, the quality of scientific data must be reproducible and verifiable. Data must lead to confident, go or no-go decisions around the drug development process.

The process should also be done in a productive and cost effective way by making accurate decisions to achieve more results, in less time. That is where quantitative digital pathology, whole slide scanners and image analysis software, can really make a difference. Quantitative digital pathology is the right innovation to drive up productivity, control costs, and provide the scientific data required to make confident decisions.

Andreas: Image analysis can improve the discovery phase by providing metrics that cannot be achieved in any other way. It supports testing of samples in ways that are too complicated to be achieved and reproduced by the human eye. It also leads to workflow improvement, by allowing the scientists to analyze more samples and get more accurate results out of the available material, thereby reducing the risk of failed studies.

Digital pathology and image analysis are tools that support the sharing of images, methods and results in a more non-subjective way. It promotes collaboration between academia and pharmaceutical sectors and helps them to speak the same language, alleviating misunderstandings and eliminate unexpected interpretations.

What is the key in evolving research into clinical practice?

Andreas: Bridging the gap between research and clinical practice is an everyday challenge for drug development companies. Tools and methods for drug research and discovery have to be very open and flexible, yet quantitative and precise, to accommodate the many questions and validate the many hypotheses that are investigated during the early phases of drug development.

In clinical practice, the demands change, and tools have to be standardized, easy to use and very robust in order to meet the requirements and challenges of analyzing real patient samples in a busy routine laboratory.

Image analysis has been used in research for years but now the technological development of image analysis software and whole slide scanners is getting to a stage where it not only offers opportunities for significant value creation in pharma research, but also allows for implementation in routine clinical diagnostics. Quantitative Digital Pathology is the strong bridge that will span the gap between research and clinical practice, while ensuring high quality, consistent data and workflow improvements at the same time.

For more information, email Leyana Daccache or to view the event, click here.