László Fónyad, M.D. Ph.D.
Jordi Temprana, MD
Jordi Temprana, MD
Markus D. Herrmann, MD/PhD (Senior Medical Director, Pharma Personalized Healthcare, Roche Pharma)
Landon Inge, PhD (Medical Affairs Lead, Medical Affairs Oncology & Pathology, Roche Diagnostic Systems)
Pathology is undergoing a digital revolution as pathology laboratories and pathologists are moving from review of glass slides under a light microscope to virtual microscopy of digital whole slide images on a computer monitor.With ever widening availability of whole slide images and technical advances in machine learning (ML) and artificial intelligence (AI), novel ML/AI-based image analysis algorithms for detection, classification, or grading of tumors are emerging and are starting to support pathologists in their daily workflow. Moreover, these ML/AI-based image analysis algorithms enable novel data-driven approaches to tissue biomarker discovery in biomedical research that promise to advance tissue diagnostic testing in clinical practice and to address unmet medical needs of cancer patients.
Roche has a long standing commitment to develop personalized healthcare solutions that enable pathologists to render more accurate and timely diagnosis and thereby provide oncologists with the relevant information they need to make optimal treatment decisions for their patients. Roche is now working on delivering on the promise of digital and computational pathology by turning advances in imaging and data science into innovative diagnostics. We work collaboratively across our Diagnostics and Pharma divisions to develop hardware and software products along the full value chain of digital and computational pathology to assist pathologists in the rendering of diagnostic decisions that ultimately inform or guide the treatment of cancer patients.
This symposium will share with the audience Roche’s work in the field of digital and computational pathology, by providing insights into our ongoing research and product development efforts, describing the medical value of our current portfolio of digital and computational pathology solutions, and sharing our vision for integrated diagnostics using multi-modal data. To this end, we present selected examples of ML/AI-based computational pathology solutions in the context of a cancer patient’s journey from diagnosis to treatment selection and initiation to treatment response monitoring, and describe how these solutions facilitate clinical decision making. Our presentation will also share the criticality of sample and image quality and robust data as the foundation of computational image analysis. Last but not least, we will present our efforts to integrate data from different imaging modalities in pathology and radiology to enable interdisciplinary clinical decision making across medical domains to optimally support cancer patient care and to ensure the right treatment for the right patient at the right time.
Landon Inge, PhD (Medical Affairs Lead, Medical Affairs Oncology & Pathology, Roche Diagnostic Systems)
Pathology is undergoing a digital revolution as pathology laboratories and pathologists are moving from review of glass slides under a light microscope to virtual microscopy of digital whole slide images on a computer monitor.With ever widening availability of whole slide images and technical advances in machine learning (ML) and artificial intelligence (AI), novel ML/AI-based image analysis algorithms for detection, classification, or grading of tumors are emerging and are starting to support pathologists in their daily workflow. Moreover, these ML/AI-based image analysis algorithms enable novel data-driven approaches to tissue biomarker discovery in biomedical research that promise to advance tissue diagnostic testing in clinical practice and to address unmet medical needs of cancer patients.
Roche has a long standing commitment to develop personalized healthcare solutions that enable pathologists to render more accurate and timely diagnosis and thereby provide oncologists with the relevant information they need to make optimal treatment decisions for their patients. Roche is now working on delivering on the promise of digital and computational pathology by turning advances in imaging and data science into innovative diagnostics. We work collaboratively across our Diagnostics and Pharma divisions to develop hardware and software products along the full value chain of digital and computational pathology to assist pathologists in the rendering of diagnostic decisions that ultimately inform or guide the treatment of cancer patients.
This symposium will share with the audience Roche’s work in the field of digital and computational pathology, by providing insights into our ongoing research and product development efforts, describing the medical value of our current portfolio of digital and computational pathology solutions, and sharing our vision for integrated diagnostics using multi-modal data. To this end, we present selected examples of ML/AI-based computational pathology solutions in the context of a cancer patient’s journey from diagnosis to treatment selection and initiation to treatment response monitoring, and describe how these solutions facilitate clinical decision making. Our presentation will also share the criticality of sample and image quality and robust data as the foundation of computational image analysis. Last but not least, we will present our efforts to integrate data from different imaging modalities in pathology and radiology to enable interdisciplinary clinical decision making across medical domains to optimally support cancer patient care and to ensure the right treatment for the right patient at the right time.
Joachim Schmid, VP of R&D Spatial Informatics
Nina Radosevic, Biopathologist and platform director, Centre Jean Perrin
The NanoString symposium will showcase our innovative discovery and translational research spatial solutions. Our platforms allow researchers to combine whole tissue imaging, gene expression, and protein data. Achieve multicellular analysis with GeoMx® Digital Spatial Profiler, or zoom in to view single cells with the CosMx™ Spatial Molecular Imager (SMI). Join us to see into the private lives of these cells in situ, at both cellular and subcellular levels supported by AtoMx™ Spatial Informatics Platform (SIP). Gain spatial biology insights anytime, anywhere using AtoMx™, a cloud-based solution that provides advanced data analytics and global collaboration capabilities. Nina Radosevic's team used GeoMx DSP to find potential biomarkers and/or therapeutic targets in triple negative breast cancers that relapse rapidly after or progress under neoadjuvant chemotherapy. GeoMx DSP was crucial in revealing 2 proteins specifically highly expressed in the tumor center of such tumors as well as the disappearance of one biological process in those cases compared to the never-relapsing ones.
Nina Radosevic, Biopathologist and platform director, Centre Jean Perrin
The NanoString symposium will showcase our innovative discovery and translational research spatial solutions. Our platforms allow researchers to combine whole tissue imaging, gene expression, and protein data. Achieve multicellular analysis with GeoMx® Digital Spatial Profiler, or zoom in to view single cells with the CosMx™ Spatial Molecular Imager (SMI). Join us to see into the private lives of these cells in situ, at both cellular and subcellular levels supported by AtoMx™ Spatial Informatics Platform (SIP). Gain spatial biology insights anytime, anywhere using AtoMx™, a cloud-based solution that provides advanced data analytics and global collaboration capabilities. Nina Radosevic's team used GeoMx DSP to find potential biomarkers and/or therapeutic targets in triple negative breast cancers that relapse rapidly after or progress under neoadjuvant chemotherapy. GeoMx DSP was crucial in revealing 2 proteins specifically highly expressed in the tumor center of such tumors as well as the disappearance of one biological process in those cases compared to the never-relapsing ones.
Junya Fukuoka, MD
Rita Canas Marques, MD
This seminar will provide an overview of recent clinical studies on the use of AI in the diagnosis of prostate and breast cases, including the assessment of HER2 IHC scoring, in support of broader adoption of artificial intelligence-based applications in routine pathology practice.
Rita Canas Marques, MD
This seminar will provide an overview of recent clinical studies on the use of AI in the diagnosis of prostate and breast cases, including the assessment of HER2 IHC scoring, in support of broader adoption of artificial intelligence-based applications in routine pathology practice.
Dr. Uttara Joshi
AI applications trained on multi-modality data can identify novel markers in histopathology images and help improve risk stratification, better predict responses to therapy, and enable personalized management protocols. All of these capabilities have the potential to enhance the role of pathologists in the diagnosis and prognostication of cancer -- pathologists can more proactively impact therapeutic decisions than ever before. We discuss this changing role of the Pathologist in the cancer care pathway using example applications.
AI applications trained on multi-modality data can identify novel markers in histopathology images and help improve risk stratification, better predict responses to therapy, and enable personalized management protocols. All of these capabilities have the potential to enhance the role of pathologists in the diagnosis and prognostication of cancer -- pathologists can more proactively impact therapeutic decisions than ever before. We discuss this changing role of the Pathologist in the cancer care pathway using example applications.
Juan C. Santa Rosario MD,
Medical Director / Core Plus