Tissue Phenomics Blog

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Topics:  Immunotherapy, tissue phenomics, tissue biomarkers, cancer immunotherapy, diagnostics, tissue-based diagnostics, io-panel

The Power of Predictive Quantitative Tissue-Based Diagnostics in Cancer Immunotherapy

Nov 21, 2017 8:00:00 AM

The American Society of Clinical Oncology named Immunotherapy 2.0 “Advance of the Year” at its 2017 Annual Meeting in Chicago, IL. This recognition comes after decades of incremental progress in our understanding of how the human immune system interacts with cancerous lesions. It also is the culmination of recent successes with checkpoint inhibitor therapy that promised dramatic changes in clinical practice and the approach to cancer treatment. What started with cutaneous melanoma in 2011 is now rapidly showing remarkable results also in other
cancer types. Just over the past year, the Food and Drug Administration (FDA) approved the use of checkpoint inhibitors in five additional cancer indications: lung, head and neck, bladder, kidney, and classical Hodgkin lymphoma.

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Topics:  image analysis, clinical trials, tissue phenomics, machine learning

Benefits of Automated Slide Reading as a Way to Decrease Human Error in Clinical Trials and thus in Patient Care

Sep 14, 2017 8:28:20 AM

Human error is natural. It is a result on how the human brain works and its biological limitations. Though human error is inevitable and also normal in highly specialized experts such as pathologists, it should not end in failure and affecting the quality of diagnosis and the selection of the adequate treatment. However, mistakes also help us and any system to learn. The error rate for complex logic errors (which applies to reading and interpreting tissue slides) is about 5% overall. Despite extensive training and education, it does not seem to drop below this natural threshold.

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Topics:  image analysis, Immunotherapy, immuno-oncology, tissue phenomics, real world evidence

Three reasons image analysis should be incorporated into your immunotherapy real-world evidence development strategy

Jan 9, 2017 5:00:00 AM

Clinical trials are extremely important to assess the safety and effectiveness of a new therapy or of a currently-available therapy in a new indication. However, there are a few drawbacks to clinical trials, such as:

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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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