Nijmegen, The Netherlands – Aiosyn, a medical software company specializing in AI-powered pathology solutions for cancer and kidney diseases, has announced the formation of its Scientific Advisory Board. The advisory board is being formed to provide scientific and medical guidance for the continued development of Aiosyn’s Kidney AI Suite. Within this platform, Aiosyn is developing AI-powered algorithms that provide objective quantification of kidney lesion scores, with the aim to ultimately improve the efficiency and reproducibility of results.
Aiosyn maintains a close collaboration with a distinguished panel of renal pathology and transplantation experts that form the Scientific Advisory Board, each possessing years of experience, involvement in numerous research projects, and a passionate drive to make a difference in the field of kidney diseases.
The Scientific Advisory Board members are:
Jesper Kers, MD, PhD, serves as a specialized consultant pathologist in kidney, immuno-, and transplant pathology at Amsterdam University Medical Centers (AMC and VUmc) and Leiden University Medical Center in the Netherlands. He leads a research group that investigates the use of decision support systems to improve the management of nephrological diseases with a focus on kidney transplant pathology. This includes the use of computer vision deep learning technologies to assess digitized whole slide kidney biopsy images.
Maarten Naesens, MD, PhD is a nephrologist at University Hospitals Leuven, where his primary focus lies in kidney transplantation. Alongside his clinical responsibilities, he conducts translational research at the Department of Microbiology, Immunology, and Transplantation at KU Leuven, concentrating on risk factors, diagnosis, and the impact of kidney transplant rejection. Dr. Naesens is Deputy Editor-in-Chief of Transplant International, the official journal of the European Society of Organ Transplantation and is involved in the organization of the ESOT and Banff congresses.
Mark D. Stegall, MD, is a transplant surgeon and researcher based at the Mayo Clinic in Rochester, Minnesota, USA. With more than 30 years of experience, Dr. Stegall’s research endeavors are centered on enhancing outcomes for kidney transplant recipients. A significant aspect of his recent research has been the development of more quantitative and objective methods for assessing renal transplant biopsies, with the aim of better predicting graft failure based on early histologic changes. Dr. Stegall has received several awards including the 2023 Medal of Excellence from the American Association of Kidney Patients and is currently the Co-Chair of the Transplant Therapeutics Consortium.
With 850 million individuals globally impacted by kidney disease (1) and Chronic Kidney Disease (CKD) expected to become the fifth most common cause of death by 2040 (2), there is an urgent need for advancements in diagnosis and treatment. Aiosyn’s Kidney AI Suite has the potential to assist researchers by providing a detailed assessment of histopathologic features in renal biopsies. These insights will complement ongoing R&D studies, enabling the identification of new and existing biomarkers with the aim to drive precision medicine for CKD.
The formation of Aiosyn’s Scientific Advisory Board for kidney disease represents a significant milestone in the company’s mission to transform the diagnosis of cancer and CKD through the power of artificial intelligence.
Aiosyn is a Dutch medical device software company that develops AI-powered pathology solutions for cancer and kidney diseases. Aiosyn’s solutions are integrated into standard pathology workflows. The Aiosyn team has been built upon more than 20 years of research experience in the field of pathology and is rooted in the pathology practice.
- Jager, K. J., Kovesdy, C., Langham, R., Rosenberg, M., Jha, V., & Zoccali, C. (2019). A single number for advocacy and communication—worldwide more than 850 million individuals have kidney diseases. Nephrology Dialysis Transplantation, 34(11), 1803-1805.
- Foreman, K. J., Marquez, N., Dolgert, A., Fukutaki, K., Fullman, N., McGaughey, M., … & Murray, C. J. (2018). Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016–40 for 195 countries and territories. The Lancet, 392(10159), 2052-2090.