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NephroPath platform

Through the NephroPath platform, we provide a detailed evaluation of histological biomarkers in preclinical and clinical kidney samples1. Our AI-based quantification offers reproducible, consistent, fast, and more detailed scoring of renal pathology biomarkers compared to traditional human reading.

 

Explore our image analysis services and partner with us to improve your (pre)clinical studies.

 

1. The NephroPath platform is for Research Use Only and should not be used for diagnostic procedures. 

Whole rat kidney analysis

Automated quantification and multi-class prediction on an entire rat kidney through the NephroPath platform. Notable classes include normal tubuli, atrophic/dilated tubuli, glomeruli, abnormal/sclerotic glomeruli, arteries, and interstitium.

AI-assisted image analysis services

  • Standard whole kidney analysis
  • Custom kidney analysis
  • Enrich your study with AI-powered whole kidney tissue quantification. We offer insights into your data through: 

    Accurate segmentation and delineation of relevant kidney structures

    Extent of glomerulosclerosis and fibrosis

    (Immune) cell quantification, including spatial relation to tissue

    Online/offline access to all results

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  • Leverage Aiosyn’s expertise in AI and the latest technology to create a tailored analysis for kidney tissue. We offer development and prototyping of robust and performant models with a quick turn-around time:

    IHC/Biomarker quantification in specific animal models 

    Treatment response grouping

    Tissue microenvironment analysis 

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How can we assist your team?

Segmentation of main tissue classes

Our AI can accurately segment relevant kidney structures, among which: (sclerotic) glomeruli, proximal/distal/atrophic tubuli, arteries & capsule. Leveraging this data, we can provide a wide variety of quantitative and spatial measurements, such as the number of glomeruli in a biopsy or the tissue area consisting of interstitium.

AI-Powered quantification of fibrosis

Renal fibrosis is a key biomarker for CKD progression and for prognosis of kidney transplantation. Current scoring systems are based on crude semi-quantitative assessments, limited to the capability of the human eye. AI-based fibrosis quantification yields an objective and precise measurement that can aid pathologists and biopharma services with their assessments. 

Localization and counting of glomeruli

The assessment of glomeruli is a quality assessment of every renal sample. Our AI-powered algorithms provide a quantitative glomerular count, boosting the efficiency and reproducibility of kidney tissue evaluations.

Glomeruli analysis

Glomeruli are identified and classified by our kidney AI algorithms. In addition, the total and specific areas are calculated and shown in µm2.

Kidney Scientific Advisory Board

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Jesper Kers, MD, PhD

Consultant pathologist at Amsterdam and Leiden University Medical Centers

Jesper Kers, MD, PhD, is a consultant pathologist specialized in kidney, immuno- and transplant pathology at the Amsterdam University Medical Centers locations AMC and VUmc, and the Leiden University Medical Center in the Netherlands. His consultation practice covers a large part of the Dutch Randstad conurbation as well as the Caribbean Islands. He studied medicine at the University of Amsterdam, postgraduate training at the French National Institute for Medical Research INSERM in Paris (France) and ULB’s Institute for Medical Immunology in Brussels (Belgium) and extended residency training (computational immunology) at the Ragon Institute of MGH, MIT and Harvard University in Cambridge (US). Currently, Jesper 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. In 2023 he joined Aiosyn as a consultant to guide the implementation of computational renal pathology software in daily clinical practice. 

Maarten Naesens, MD, PhD

Nephrologist at University Hospitals Leuven and KU Leuven

Maarten Naesens is a nephrologist at the University Hospitals Leuven, with specific interest in kidney transplantation. Next to the clinical duties, he performs translational research at the Department of Microbiology, Immunology and Transplantation at the KU Leuven, focusing on risk factors, diagnosis, and impact of kidney transplant rejection. He 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. He has published more than 240 peer-reviewed articles in the field of kidney transplantation.

Mark D. Stegall, MD

Transplant surgeon and researcher at Mayo Clinic

Dr. Stegall is a transplant surgeon and researcher at the Mayo Clinic in Rochester, Minnesota, USA.  He has more than 30 years of experience.

Mayo Clinic has 3 transplant sites (Minnesota, Arizona and Florida) that collectively perform more than 1000 kidney transplants each year.  Dr. Stegall conducts research involving all 3 Mayo sites and has been the Principal Investigator on numerous multicenter trials enrolling more than 1500 patients over the past 8 years. His large research group maintains a biorepository that includes more than 15,000 digitized renal transplant biopsies. 

Dr. Stegall’s research aims to improve the outcomes of kidney transplant recipients.  A major thrust of this recent research has been in developing more quantitative, objective methods for evaluating renal transplant biopsies to better predict graft failure from early histologic changes.  His group has had a long-standing collaboration with Dr. Jeroen van der Laak at Radboud University in using Deep Learning Algorithms to automate the scoring of histologic changes in renal transplant biopsies.  Dr. Stegall also has extensive experience in investigator-initiated clinical trials and in regulatory issues regarding new drug and device development. 

Dr. Stegall is the James C. Masson Professor of Surgery Research.  The author of more than 300 publications, he has received several awards including the 2023 Medal of Excellence from the American Association of Kidney Patients and the 2011 Paul Terasaki Clinical Science Award from the American Society of Histocompatability.  He is currently the Co-Chair of the Transplant Therapeutics Consortium, a public-private partnership between the US Food and Drug Administration and the transplant community with the goal of developing new pathways for drug approval in transplantation.

Harness Aiosyn’s expertise in AI-powered kidney analysis

Our kidney analysis team is driven by the pursuit of innovative solutions that not only advance discovery but also yield actionable data to inform decision-making. Guided by our Scientific Advisory Board, Aiosyn’s team leverages its extensive research experience in deep learning-based evaluations of kidney tissue. This expertise fuels the continued development of our kidney AI algorithms.

 

Key scientific publications: 

1. Hermsen, Meyke, et al. “Convolutional neural networks for the evaluation of chronic and inflammatory lesions in kidney transplant biopsies.” The American Journal of Pathology 192.10 (2022): 1418-1432.(10), 1968.

2. Hermsen, Meyke, et al. “Deep learning–based histopathologic assessment of kidney tissue.” Journal of the American Society of Nephrology: JASN 30.10 (2019): 1968.

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