Katalin Gocze
Chief Operating Officer at Pathology Innovation Incubator Ltd, Budapest, Hungary
Intro to pathology? My path to pathology was unconventional – I began in preventive medicine and public health. I’ve always been a problem solver, drawn to finding ways to improve health outcomes early on. My research started with using microRNA biomarkers to predict HPV progression before it becomes cancer, aiming to enhance screening and intervention. Later, I focused on injury prevention in athletes, especially women and adolescents, researching ways to ensure long-term, injury-free performance.
Joining the Pathology Innovation Incubator (Pi2) allowed me to continue my passion for prevention while helping to build a unique partnership between pathology and diagnostics companies. Pi2 aims to turn scientific discoveries into innovative cancer diagnostic solutions. Although I'm not a practicing pathologist, I use my diverse experiences to support Pi2 in operations, relations, and management. Our first project focuses on advancing immunohistochemistry to address complex diagnostic challenges.
Throughout my career, I’ve been inspired by brilliant pathologists and remain committed to supporting technologies that enable early intervention in cancer diagnostics. This, I believe, is the most impactful way I can contribute.
Biggest challenge in pathology? The challenge we face in pathology for cancer diagnostics, especially here in Europe, is the aging and shrinking of the pathology team. As senior leaders retire, there are not enough people from the younger generations considering pursuing pathology, which puts additional workload on the people still left in the lab. At the same time, cancer diagnostics is becoming more complex, which increases the burden on pathologists and can ultimately affect patients.
From an operations perspective, this is really two challenges: reducing pressures on the existing pathology team and building the pipeline of incoming talent. We can help to address the first challenge by automating more lab processes where possible, which also has the benefit of standardization. The second challenge also requires investment but can be extremely rewarding to individual labs as well. At Pi2 we welcomed our first two medical student interns last fall to work on histological diagnosis of tumors and identification of tumor biomarkers. Besides the hands-on experience these students gained, our pathology team benefited tremendously from the opportunity to share their knowledge with the next generation.
Exciting developments and trends? In immunohistochemistry and digital pathology where my work is focused, AI is definitely an exciting new frontier. For software to be able to find irregularities in tissue samples quickly and at scale, and potentially make diagnosis more accurate and efficient, would be a game-changer for both labs and for patients.
There is interesting work happening to use AI in IHC to help make a pre-diagnostic assumption that can then be checked by a pathologist, but it is still being tested. And AI will not replace the importance of upstream laboratory techniques and quality – for software to read a digital image of tissue, the sample needs to be the highest quality, meaning quality tissue processing, quality staining or reagents, quality slides, and a quality scanner.
Beyond the accuracy standard, we also need to figure out the ethical and scientific standards for publishing research using AI. It’s an exciting opportunity, but we must remember that ultimately there is a person on the receiving end of every diagnosis. It’s crucial that we get it right.
