Esther Abels, Senior Director Business Development Pharma Solutions, Philips Digital Pathology Solutions
Digital pathology has become an international talking point, especially since the diagnostics industry saw the first whole slide scanning device marketed for routine use in the clinical lab. However, its impact on drug discovery, and beyond that to translational medicine, may be even more significant. It has the potential to substantially accelerate and improve drug development across discovery, preclinical and clinical trials. Ultimately, digital pathology may have a role to play not only in aiding diagnosis, but in predicting its outcome.
Research requires innovation and collaboration across specialties, including pathology, to develop new medical discoveries that will improve health. New drug and biomarker discovery increasingly depends on tissue pathology and the analysis of large volumes of tissue samples. Further, gene-expression analysis has opened up another area of opportunity.
Harnessing the power of digital pathology offers the potential to significantly decrease the total time spent on research studies, speeding the pathway for novel discoveries and advancements in medicine. At every stage of the research pathway, the use of intelligent workflow solutions could improve quality and efficiency, as well as streamline and harmonize processes.
Multisite pathology integration
As an emerging technology, digital pathology provides the innovation necessary to handle volume workloads, while creating high quality whole slide images of glass slides that can be reviewed remotely by expert pathologists. Wherever that person is located, the digitized images can be used to identify, quantify, and document key characteristics, reactions, or responses within a specific set of tissue samples.
With the high financial stakes at play, biotech and pharmaceutical industries are increasingly seeking new ways to accelerate performance while maintaining standards of quality and reproducibility. Digital pathology would enable them to create a multi-site, digitized environment, facilitating immediate web based consultations between, for example, preclinical biomarker teams or clinical researchers.
In this way, experts would be able to collaborate and review tissue based toxicity and efficacy studies with far greater speed, while increasing precision and accuracy. Additionally, with the benefits of standardization and automation, they can more confidently expect to remove subjectivity and fully capitalize on the objective algorithms of computational assessment.
Companies could see their animal computational models and safety assessments far more smoothly implemented and validated. In turn, this could bestow greater confidence when presenting a business case for funding to progress to next stage trials, or justify calling an early halt to further research.
Having flexible tools for image and data management is critical in pharma discovery labs and CROs. For these organizations, it would be invaluable to have access to a web-based platform of digitized information, for example, on clinical outcomes, as well as molecular and summary genomic data alongside whole slide images or tissue microarray studies. This would create an integrated environment for digital pathology workflows suitable for their complex tissue-based experiments as well as non-clinical safety studies and high volume slide management.
It may well require a leap of organizational faith by the pharma companies to create the integration challenges that this cross-platform approach requires but there is ample evidence of how it can be successfully handled from many other industries. For this to work, it requires the active support of both senior management and the vendor. The starting point would be to set down common goals and standard operating practices that can be agreed across all parties. This would cover every stage of tissue-based research, from sample collection, histology, pathology scoring and image analysis as well as archiving.
The use of whole slide images, from the starting point of drug discovery, through to preclinical biomarker teams and clinical researchers, may have significant benefits for the patient.
As we move towards an era of precision medicine, we will see greater emphasis on global collaborations between pharma companies and the experts in artificial intelligence. Driving this is the need to develop clinical algorithms, which could more accurately determine the diagnosis, treatment and life expectancy for each patient. Collaborations are already taking place between vendors and pharma companies which could see the translation of their algorithms into a deep learning variant to accelerate performance and greater diagnostic and predictive accuracy.
Disclaimer: In seeking to foster discourse on a wide array of ideas, the Digital Pathology Association believes that it is important to share a range of prominent industry viewpoints. This article does not necessarily express the viewpoints of the DPA, however we view this as a valuable point with which to facilitate discussion.