[Image courtesy of Proscia]
Cochran introduced the metaphor of a “forked road” in clinical trials, with one path representing the “lush and green” therapeutic landscape benefitting from advances such as the protein structure prediction AI AlphaFold 2, CAR-T cell therapy, mRNA vaccines and CRISPR-Cas9 gene editing.
This stands in contrast to the other side of the fork in the road, symbolizing what Cochran described as the “much rockier road” of diagnostic challenges. He emphasized that as the speed of drug development intensifies, thanks to computational biology advances, “that accelerated speed of development is going to pressure both the regulatory and the laboratory sides of clinical trials.” Cochran noted, “they’re going to have to keep pace with that drug development speed.” Given that context, pathologists face mounting pressure to deliver data faster than ever before, while dealing with an ongoing shortage of pathologists. This mismatch creates a dangerous bottleneck. If left unchecked, it threatens to slow down the very advances Cochran celebrates.
John Cochran, MD
Digital pathology as a digital microcosm
Digital pathology represents a paradigm shift, offering a potential solution to the challenges Cochran highlights. This shift aligns with the growing interest in AI and a range of new digital tools, including those used in genomic sequencing and advanced medical imaging, where AI has been making inroads for years, demonstrating the potential of such technologies across medicine. As Buchbinder explained, “You’re making a digital leap, digitizing these biopsies and creating these high-resolution images on which you can then create a new technology stack that is software-based, data-driven, and AI-enabled.”
This transformation opens up new possibilities for streamlining workflows, enhancing accuracy, and accelerating the drug development process.Lamba Saini outlined several key advantages of digital pathology in clinical trials, including “central review, training of the pathologists, application of computational pathology and image analysis, and very importantly, gain in workflow productivity.” In addition, she emphasized the importance of centralized review in multi-center and international trials, enabling streamlined processes and access to expert opinions for challenging cases.
Enhanced training possibilities
Dr. Monika Lamba Saini
Digital pathology also facilitates enhanced pathologist training through virtual platforms and feedback-guided software. Lamba Saini shared her experience during the COVID-19 pandemic, noting, “In front of my own eyes, from the training pathologist actually coming to the site, we moved on very, very swiftly to software or to virtual training,” she said. “So, now with the help of virtual training, you can actually train many more pathologists, and also you have feedback-guided software, where you can enter your responses.”
Lamba Saini highlighted the potential for multimodal and integrated diagnostic approaches, envisioning a future where “the boundary which was existing between, let’s say, diagnostic disciplines of radiology or pathology or genomics, that computational boundary will be blurred as far as computational capabilities are concerned.”
AI elevates the pathologist’s role, and thus their impact on drug development
Nathan Buchbinder
AI and machine learning are becoming increasingly central to digital pathology workflows. This integration will significantly impact workflows. Buchbinder highlighted the importance of AI in driving decision-making and accelerating drug development, stating, “I think that we can’t underestimate the impact that artificial intelligence and machine learning are having on driving decision-making in technology adoption and in the operations of clinical trials and drug discovery and development more broadly.”
In this context, the role of pathologists is evolving from primarily image interpretation to data-driven decision-making. “The role of the pathologist in the future ends up being less about how adept you are at looking under the microscope or looking at an image and identifying complex patterns, and more about what you choose to do with that data that you actually get,” Buchbinder said in the webinar. That is, the role becomes “more about how you leverage that data to drive decision making downstream. It’s a more elevated role for the pathologist.”
Filed Under: clinical trials, Drug Discovery, Oncology
