Proscia Launches Commercial Research Edition of Digital Pathology Platform

April 11, 2019
Applied Clinical Trials

Applied Clinical Trials

Chief Product Officer for Proscia, Nathan Buchbinder, discusses Proscia’s Concentriq and its benefits for CROs and life science organziations.

Nathan Buchbinder is the Chief Product Officer for Proscia, a digital software company that seeks to perfect cancer diagnosis with intelligent software.

ACT: How does Proscia’s Concentriq platform work from a typical clinical trial operational standpoint? For example, taking samples at the investigative site, sending them via slide to a centralized lab or CRO, and the translated to the digital format.

NB: Concentriq makes it extremely easy for a CRO or life science organization to deliver images and image-
based data to sponsors and clients. After the organization performs required lab work, the slides are digitized on a whole slide image scanner. Automated scanner synchronization - a feature of the Concentriq platform - transitions slides from the scanner right onto the platform. These slides can either be automatically placed in client- or sponsor-specific repositories based on barcoded information, or placed into an all-image list and quickly triaged. At this point, the lab can provide access to the client or sponsor through a web portal login, with secure and credentialed login. While the client or sponsor can't add any additional whole slide images of their own, they can optionally be given access by the site that the performed the imaging to edit case-related data or provide input. This portal login gives immediate access to a potentially enormous quantity of study data to any number of selected individuals, anywhere in the world, instantly.

ACT: How does the platform impact short-term benefits for a specific clinical trial?

For any given clinical trial, the main concerns are always confidence in quality, keeping costs down, and getting the work done in a timely manner. The Concentriq platform opens up new ways to drive consistency, reduce dependence on many error-prone and expensive manual tasks, and decrease much of the logistical hurdles that add time to conducting a study. A few examples of this include:

 

●      Faster Access to Medical Expertise – The geographic dispersion of medical professionals and pathologists adds time and cost to obtaining diagnostic input on clinical trial specimen by necessitating a logistically burdensome process of shipping specimen to various locations. Concetriq provides a digital platform that enables the originating lab to digitally obtain review from pathologists anywhere in the world without physically shipping the specimen. 
 

●      Consistency in Assessment - The Concentriq platform additionally affords study coordinators with multiple quality-assuring opportunities not available in working with physical tissue specimen. This includes the centralization of pathology resources in a single site to reduce the number of readers and ensure consistency between interpretation. Analytics tools provide additional guidance quantifying otherwise error-prone assessments.
 

●      Reducing & QCing Error-Prone Labor - Concentriq uniquely automates many of the data import, aggregation, and dispersion processes that typically consume a large amount of manual labor. This not only saves time, but also provides an additional checkpoint at which any discrepancy between data sources can be flagged or corrected.
 

●      Rapid Access to Results - In trials with multiple clinically-based go/no-go checkpoints, immediate access to results and raw data is paramount to making decisions that influence when a trial can proceed and what next steps are required. Concentriq makes results and raw data accessible to any required reviewer, who can instantly review and offer guidance on how a trial moves forward. For CROs or groups conducting trials on behalf of a third party, this ability to disseminate results and raw data offers a significant advantage over traditional results sharing in trials.

ACT: How does the platform impact the investment by a pharma company in the long-term? How would the platform benefit a CRO or other service provider in the long-term?

Life science organizations generate an enormous amount of data as part of the routine process of performing clinical trials. For this most part, once a trial is complete, that data remains unused, sitting in biobankings or slide filing cabinets. 

Concentriq functionalizes that enormous data asset by enabling pharma companies and CROs to create robust, searchable databases of pathology whole slide images and metadata. Many pharmaceutical companies have already formed in-house expertise in artificial intelligence to capitalize on existing data. Access to this vast trove of information through Concentriq serves as a force multiplier, enabling these companies to gain insight into new trials. It also allows them to tap into existing data to develop new products and companion diagnostics as well as gain earlier, faster insight into the likelihood of success of a new drug candidate. For CROs, which offer an ability to access patient data as well as insight and expertise into particular specialties, this database serves as an additional, attractive resource that can be leveraged as an asset for augmenting trials.

ACT: There appears to be great promise for Concentriq in the area of drug discovery and faster identification of potential patients for clinical trials recruitment. Do you believe this is true and how do you envision that growing?

I believe this is true, and see it as tying to the related notion of personalized medicine. Personalized medicine captures the concept that two individuals don’t necessarily respond identically to the same therapies or, similarly, that they would not be equally as viable a candidate for clinical trial recruitment. The patterns of these subpopulation responses to various treatments are not always intuitive, leading to the rejection of many compounds or necessitating the introduction of a companion diagnostic. AI provides a means of finding the patterns that help correlate the likely response to various attributes about prospective study participants, serving as a software companion diagnostic that can be applied both in the context of marketing a new drug as well as in the clinical trial recruitment process.