The liver’s microenvironment holds the key to understanding and addressing complex liver diseases, from fibrosis to emerging infections. In this lecture, Prof. Stevenson-Lerner shares her experience leveraging Visiopharm software to explore the liver microenvironment, offering unique insights into macrophage-mediated immune responses and the use of advanced AI tools for spatial biology analysis. She also highlights how Visiopharm empowers her team to study liver diseases with unprecedented precision, ensuring reproducible and impactful research outcomes.

Prof. Heather Stevenson-Lerner 

Heather Stevenson-Lerner, MD, PhD, is a Professor in the Department of Pathology, Division of Surgical Pathology at the University of Texas Medical Branch. Her clinical focus includes liver, transplantation, and gastrointestinal pathology.

Skin acts as a protective barrier against external aggressions that our bodies are submitted to on a daily basis, although it can also be challenged by endogenous stresses. 3D reconstructed skin models are often used in the cosmetic industry as an alternative to in vivo animal models, but although very reproducible, they do not cover the entire complexity of the morphological and physiological characteristics of human skin. Ex vivo can be a more complex and complementary research model helping to understand skin responsiveness to internal & external factors (UV .. .) and to evaluate the effect of active ingredients and cosmetic products on biological mechanisms. Here we present an innovative ex vivo method consisting in a dynamic maintenance of human skin samples in culture for up to 19 days, that allows us to study skin response to environmental stresses or cosmetic products over a long period of time. This long-term culture makes it possible to adapt the culture time to the biological theme studied and allows to ensure perfect tissue viability on the window of use of our model for common studies. For example, up to 3 days to evaluate the exfoliating nature of a product, up to 10 days to evaluate the anti-aging effectiveness …

So, the development of this model up to 19 days is a proof of quality and allows us to be confident about the results delivered on the window of use of our explants for common studies. Through this presentation, we highlight the use of our ex vivo model to prove the exfoliating effect of a topically applied product, The Lotion. Finally, the quantification of the observed effect was done using specific “soft ware” tools where Al & deeplearning were implied.

Fanny Richard¹, Anissa Sahebdeen¹, Luca Poncelet¹, Helena Nygaard Regev², Emmanuelle Bouissou Cadio¹, Nada Andre¹, Youcef Ben Khalifa¹

1. IRD Chanel Fragrance & Beauty, Pantin, France
2. Visiopharm Hørsholm, Denmark

RNA-ISH has rapidly achieved prominence within translational research, long holding promise as being critical for novel diagnostic and therapeutic applications where other biomarker types cannot be used. However, there remain key barriers to greater clinical adoption for RNAISH, including validation of observed ”dots” and accurate identification of RNA within specific cells, particularly in cytoplasmic regions. These significant quantification challenges exist due to a lack of a robust assay validation methodology and difficulties in determining cell boundaries. Here we propose a novel collaboration to address both long-standing issues using a reagent-encoded approach (HCR™ Pro by MI) as well as downstream AI-enabled analysis software (Phenoplex by Visiopharm) to offer a proof-of-concept demonstration of end-to-end assay validation and quantification with high fidelity.

Dan Winkowski¹, Chun Hao Chen², Fabian Schneider¹, Joyce Yoo², Regan Baird¹, James Mansfield¹

1. Visiopharm A/S, Horsholm, Denmark
2. Molecular Instruments, Los Angeles, CA, USA

Autosomal dominant polycystic kidney disease (ADPKD) is an inherited systemic disorder mainly associated with mutations in the PKD1 gene and characterized by the development of multiple cysts in the kidneys and other organs. There is still a high unmet need for treatment options for patients with ADPKD because Tolvaptan, the only approved treatment, has limited efficacy and non-negligible side effects.

To mimic naturally occurring human PKD1 mutations, a Pkd1 inducible knockout mice strain was established at Novalix. Embark on an exciting journey as we explore the histological characterization of the PDK1flox/flox model using cutting-edge Visiopharm technology. We will unveil captivating insights into the disease’s origins and evolution, revealing the intricate structural changes that define this strain. Join us as we uncover the hidden stories within the tissues, paving the way for potential breakthroughs in understanding and treatment!

Florence Anquetil-Besnard. PhD

Florence Anquetil-Besnard is a Histology Project Manager at NovAliX. After a PharmD and a PhD in Immunology, she began her career in the autoimmune field (rheumatoid arthritis, diabetes) and specialized in histopathology and quantitative image analysis. She is a passionate advocate for digital pathology and loves to solve challenging projects using artificial intelligence (AI) tools. Florence joined the Galapagos team in 2020 to implement the newly formed kidney disease histology area. Her current work within NovAliX also includes oncology projects in diverse organs (brain, pancreas, liver, xenograft tumor…).

• Bladder cancer grading is crucial for treatment decisions, but the existing ISUP 2004 system is subjective, compromising its reliability and prognostic utility.
• By mathematically defining well-established WHO 2004 grading criteria as quantitative nuclear features (QNFs) and employing AI-driven image analysis to extract QNFs, we previously developed precise, reproducible models for expert consensus grading.
• QNFs serve as excellent building blocks for prognostic classifiers.
• Using QNFs, we externally validate grading models and create recurrence-free survival (RFS) models that outperform grades assigned by pathologists.

Minqi Xua¹, Katherine Lindalea¹, Ava Slotmana¹, Raquel Benitezb², Dan Winkowskic³, Robert J Goodinga¹, Amber Simpsona¹, Nuria Malatsb², David M Bermana¹.

1. Queen’s University, Kingston, Canada
2. Centro Nacional de Investigaciones Oncológicas , Madrid, Spain
3. Visiopharm A/S, Westminster, Colorado;

Cell proliferation is commonly assessed to grade neuroendocrine tumors (NETs) and aid in the evaluation of patient prognosis and treatment selection. To grade NETs, a proliferation index (PI) is evaluated based on the presence of immunohistochemical staining of the Ki-67 nuclear antigen. In the gastrointestinal tract, grading is performed using WHO criteria for PI as Grade 1-3 (less than 3%, 3%-20%, and greater than 20% respectively). It is recommended to count at least 500 cells followed by calculating the percentage of Ki-67 positive nuclei for cases with the Ki-67 index close to grade cut-offs on eyeballing. Ki 67 proliferation index near cut-offs is a real challenge for practicing pathologists.

Vidya Arole MD¹*, Jesse Kulewsky¹, Jenifer Caldara², Rachel Scarl DO¹, Swati Satturwar MD¹, Zaibo Li MD1, Wei Chen MD¹, Anil Parwani MD¹, Giovanni Lujan MD¹

1. The Ohio State University Wexner Medical Center
2. Visiopharm Corporation