Modernization of Tissue-based, Biomarker-led Clinical Research Dr Stephanie G. Craig Lecturer in Precision Medicine at the Patrick G. Johnson Centre for Cancer Research, Queen's University Belfast Automated staining platforms and digital slide scanners have revolutionized tissue-based biomarker research by providing a powerful platform in which to conduct reproducible, quantitative biomarker-led studies at scale. Use of machine learning and artificial intelligence approaches to analyze these biomarkers enables sensitive, specific, and rapid biomarker assessment in situ. In this talk, we will be reviewing the implementation and technical challenges faced in modern tissue-based, biomarker-led research from wet-lab validation to digital assessment. To do so we will review published work from our lab that has utilized automated staining and slide digitization as an aid to clinical research (for research use only. Not for use in diagnostic procedures) in immunohistochemistry, RNA in situ hybridization, multiplex immunofluorescence, and artificial intelligence studies. Learning Objectives Learn how automated staining and slide digitization can reduce staining variability and aid in quantitative biomarker assessment at scale Understand how digitization of molecular pathology assessment lends itself to multi- and cross-disciplinary research investigations For Research Use Only. Not for use in diagnostic procedures. About the presenter Dr Stephanie G. Craig , Lecturer in Precision Medicine at the Patrick G. Johnson Centre for Cancer Research, Queen's University Belfast Stephanie is a Lecturer in Precision Medicine at the Patrick G. Johnson Centre for Cancer Research, Queen’s University Belfast. She has a breath of experience in the application and validation of translational cancer research methodologies using molecular pathology techniques (immunohistochemistry, in situ hybridisation, multiplex immunofluorescence) and statistics. Her research focuses on predictive biomarker studies and understanding confounding variables that influence the prediction of poor prognosis subgroups in cancer research including reproducible study design, choice of molecular test and assessment criteria. Related Content The Power of Spatially Resolved Staining Multiplex Detection: From Discovery to Clinical Practice Leica Biosystems content is subject to the Leica Biosystems website terms of use, available at: Legal Notice. The content, including webinars, training presentations and related materials is intended to provide general information regarding particular subjects of interest to health care professionals and is not intended to be, and should not be construed as, medical, regulatory or legal advice. The views and opinions expressed in any third-party content reflect the personal views and opinions of the speaker(s)/author(s) and do not necessarily represent or reflect the views or opinions of Leica Biosystems, its employees or agents. Any links contained in the content which provides access to third party resources or content is provided for convenience only. For the use of any product, the applicable product documentation, including information guides, inserts and operation manuals should be consulted. Copyright © 2024 Leica Biosystems division of Leica Microsystems, Inc. and its Leica Biosystems affiliates. All rights reserved. LEICA and the Leica Logo are registered trademarks of Leica Microsystems IR GmbH. RELATED PRODUCTS Aperio GT 450 - Automated, High Capacity Digital Pathology Slide Scanner Aperio CS2 — High quality digital slides from your desktop Aperio VERSA Brightfield, Fluorescence & FISH Digital Pathology Scanner Aperio ImageScope - Pathology Slide Viewing Software RELATED TAGS AND TOPICS Automated Digital Workflow, Whole Slide Imaging, Digital Analysis, Multiplex RELATED CONTENT The Power of Spatially Resolved Staining Multiplex Detection: From Discovery to Clinical Practice Contact Our Product Expert Now If you have viewed this educational webinar or training and would like to apply for continuing education credits with your certifying organization, please download the form to assist you in adding self-reported educational credits to your transcript. Apply for self-reported educational credits Subscribe to our mailing list to learn about our upcoming symposiums and new research-focused product launches. 登録 SHARE Facebook Twitter LinkedIn Email
