Tissue Phenomics Blog

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Topics:  Immunotherapy, personalized medicine, cancer diagnostics, precision medicine, cancer vaccines

Promising results with personalized cancer vaccines highlight the need for novel diagnostics to personalize cancer treatments

Aug 9, 2017 7:00:00 AM

Personalized medicine aims at bringing the right drug to the right patient at the right time. Getting many things right at the same time is challenging. There are many potential treatments for cancer patients and many of these can be combined with each other resulting in a lot of potential combination treatments. This growing number of treatment options makes it increasingly difficult to determine the right one for an individual patient. Biomarkers that help to predict response to a treatment are highly needed to guide treatment selection to maximize efficiency for both patients and payers.

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Topics:  personalized medicine, companion diagnostics, reimbursement, market access, quantitative IHC

Enabling Market Access for Quantitative IHC-Based Companion Diagnostics

Jun 5, 2017 6:00:00 AM

The complexity of the tumor microenvironment represents a significant challenge to the personalized medicine movement in the field of oncology. While genetic and genomic analyses enable an understanding of the patient’s genotype, this does not necessarily translate to active tumor microenvironment expression – phenomics – through which pharmacodynamic pathways are modulated by targeted therapies. Similarly, while single biomarker immunohistochemistry (IHC) can effectively quantify expression of a particular biomarker, it fails to evaluate the entire picture of the tumor microenvironment, where a myriad of potentially confounding factors exists to distort the causal relationship between expression of a single marker and treatment response. 

Enter context-based analysis of biomarker expression – quantitative, multiplex IHC technology leveraging “big data” capabilities to overcome the inherent limitations of existing diagnostic techniques and more precisely assess the tumor microenvironment. Applied as a companion diagnostic (CDx), quantitative IHC or IF (qIHC/IF) using image analysis (IA) technology represents a potentially paradigm-shifting approach to predict patient response to oncologics and thus bring the movement of personalized medicine to fruition. Read More

Topics:  image analysis, personalized medicine, biomarker, immuno-oncology, tissue diagnostics, companion diagnostics, tissue biomarkers, diagnostics, diagnostic test, precision medicine, biomarker signature

3 ways tissue image analysis will shape the future of cancer treatment with immunotherapies

Nov 7, 2016 1:00:00 AM

As healthcare continues its transition towards precision medicine, physicians are eager to maximize both the quantity and quality of data obtained from their patients’ tissue samples.  In the current “one drug, one test” paradigm, physicians struggle to balance the number of tests required to make a treatment decision with the limited amount of tissue that is available.  Further complicating treatment decisions is the use of imperfect biomarkers associated with targeted therapies, as the patients who are identified to be ideal candidates for a targeted therapy respond only some of the time while patients who are not expected to respond do.  This dilemma is of great concern for those who are responsible for paying for these expensive therapies - payers and patients – who would like to avoid unnecessary expenses for drugs that may not work and possibly cause debilitating side effects.  Of course, of even greater concern is helping the patient identify the best therapeutic option that allows them the best opportunity to treat their disease and maximize their quality and quantity of life.

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Topics:  personalized medicine, big data, tissue phenomics, oncology, digital pathology, colorectal cancer

Towards Personalised Pathology Through Tissue Phenomics®

Sep 14, 2016 3:00:00 AM

Path to personalised medicine

Pathology is one of the main driving forces behind personalised or precision medicine. In fact it has always striven towards the accurate diagnosis and prognosis of a patient’s disease through the observation of tissue architecture under the microscope. Through the application of international staging guidelines, such as the Tissue, Node, Metastasis (TNM) system in the majority of cancers, pathologists are very good at predicting prognosis at the population scale but not so good at predicting a prognosis for the individual patient. For example, if a patient presents with stage II colorectal cancer (CRC) they are predicted to have 20-30% chance of succumbing to their disease. However, it is currently difficult to accurately identify if an individual patient will be within that 20-30% group.

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Topics:  image analysis, personalized medicine, tissue phenomics, data mining

Five Major Benefits of Tissue Phenomics®

Aug 8, 2016 3:00:00 AM

Seeing is believing – this is an important aspect of Tissue Phenomics, where cellular structures in tissue slides taken from patients are investigated in real space. Observing directly what type of structures form and what kind of interactions take place is in general of much higher value than concluding indirectly from other type of data. I experienced this factor very clearly thirty years ago when people speculated about the atomic structure on the surfaces of matter from indirect measurement. When we could, however, image atomic structures directly, it became obvious that most of those speculations were wrong. This is the reason why even for a genetic disease like cancer, genetic information could not push histology aside. Observing the structures and the interactions in tissue slides on the cell level enables insights into the disease of a specific person that is decisive and cannot be created otherwise. Tissue Phenomics builds upon histological information and pathologists’ knowledge and is by no means about replacing it. The mission is rather to gain an even deeper insight into biological processes detectable in cell structures for the enablement of new and successful treatments of patients and their specific diseases. In the beginning there was the question how far one can get with the Tissue Phenomics approach, or more concretely, how far can we go beyond what the experts already know today? What can be achieved when the computer investigates all kind of cell patterns in tissue and correlate them with biological and medical relevance and meaning, represented e.g. by clinical outcome? Today we know better.

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