oncology


Where are the opportunities for medtech and pharma in 2020?

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It's that time when we start to look ahead to what next year holds for the life science sector...Lu Rahman outlines 2020s big medtech players A decade ago the healthcare advances create by AI would have seemed the stuff of dreams. But back in 2018 Theresa May announced plans to use artificial intelligence and data to transform the way certain diseases like cancer. The technology is moving at a pace – this year we heard that a team led by the University of Surrey had filed the first ever patent for inventions autonomously created by AI without a human inventor. Professor Ryan Abbott explained the implications this had for the life science sector: "These filings are important to any area of research and development as well as any area that relies on patents. Patents are more important in the life sciences than in many other areas, particularly for drug discovery. These tasks can be the foundation for patent filings. "As AI is becoming increasingly sophisticated, it is likely to play an increasing role in R&D including in the life sciences.


Artificial Superintelligence : An Intellect that Never Before Existed

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The pace of progress in artificial intelligence is astonishingly fast and it is growing at a rampant pace. Tech firms such as DeepMind, etc as well as countless academic teams at leading technical universities all over the world, have been working for years on the creation of an AI with a neural network capable of all the mental functions humans posses. Unless one has direct exposure to groups like Deepmind, you have no idea how fast AI is growing. However, it is fascinating to see how AI is transforming lives right now in its early stages of narrow intelligence: from disease detection to artificial organs, autonomous driving to manufacturing. Evolution -- the process by which different kinds of living organism are believed to have developed from earlier forms and evolution has created intelligence -- the humans, but we are the most "exceptional" form of life in existence.


Argonne National Laboratory Deploys Cerebras CS-1, the World's Fastest Artificial Intelligence Computer

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LOS ALTOS, CALIFORNIA and LEMONT, ILLINOIS – Cerebras Systems, a company dedicated to accelerating artificial intelligence (AI) compute, and the Argonne National Laboratory, a multidisciplinary science and engineering research center, today announced that Argonne is the first national laboratory to deploy the Cerebras CS-1 system. Unveiled today at SC19, the CS-1 is the fastest AI computer system in existence and integrates the pioneering Wafer Scale Engine, the largest and fastest AI processor ever built. By removing compute as the bottleneck in AI, the CS-1 enables AI practitioners to answer more questions and explore more ideas in less time. The CS-1 delivers record-breaking performance and scale to AI compute, and its deployment across national laboratories enables the largest supercomputer sites in the world to achieve 100- to 1,000-fold improvement over existing AI accelerators. By pairing supercompute power with the CS-1's AI processing capabilities, Argonne can now accelerate research and development of deep learning models to solve science problems not achievable with existing systems.


AI can help doctors identify cancer cells - ET HealthWorld

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New York: Researchers at University of Texas Southwestern have developed a software tool that uses Artificial Intelligence (AI) to recognize cancer cells from digital pathology images - giving clinicians a powerful way of predicting patient outcomes. The spatial distribution of different types of cells can reveal a cancer's growth pattern, its relationship with the surrounding micro-environment, and the body's immune response. But the process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone. "To make a diagnosis, pathologists usually only examine several'representative' regions in detail, rather than the whole slide. However, some important details could be missed by this approach," said Dr. Guanghua "Andy" Xiao, corresponding author of a study published in EbioMedicine.


Global Artificial Intelligence (AI) in Drug Discovery Market Study, 2019-2024 - Projected to Grow at a CAGR of 40.8%

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Growth in this market is mainly driven by growing number of cross-industry collaborations and partnerships, the need to control drug discovery & development costs and reduce the overall time taken in this process, the rising adoption of cloud-based applications & services, and the impending patent expiry of blockbuster drugs. On the other hand, a lack of data sets in the field of drug discovery and the inadequate availability of skilled labor are some of the factors challenging the growth of the market. The immuno-oncology segment accounted for the largest share in 2019. Based on application, the artificial intelligence in the drug discovery market is segmented into neurodegenerative diseases, immuno-oncology, cardiovascular disease, metabolic diseases, and other applications. The immuno-oncology segment accounted for the largest share of 44.6% of the AI in the drug discovery market in 2018, owing to the increasing demand for effective cancer drugs.


Artificial Intelligence (AI) in Cancer Care

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It is no secret that artificial intelligence is being tested in clinical settings around the world, but is it a realistic ambition to apply sophisticated algorithms to outdated healthcare systems? We speak to Matej Adam about the research being carried out by IBM. We invested in artificial intelligence by developing an AI platform, Watson, named after one of the founders of IBM. When we were developing the technology, it was evident from the beginning that its use in healthcare would make sense for multiple reasons. One reason is that AI can help to sift through a lot of unstructured data of different types and formats.


Artificial Intelligence

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Natsoft has expertise in developing and offering products & services to the Pharma and Biotech companies. Our Clinical Trial Intelligence platform provides a premier enterprise solution for both Pharma and Biotech companies to accelerate clinical trial design and approval of new novel cancer drugs. Our Machine Learning, AI and RPA (Robotic Process Automation) capabilities are increasing the process efficiencies and reducing the Drug Development time for our clients.


Machine Learning and the Cancer-Diagnosis Problem -- No Gold Standard NEJM

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Machine learning has the potential to be extremely useful in medicine, particularly in the interpretation of medical images. But it also has inherent limitations, especially when it comes to diagnosing early-stage cancer.


AI R&D is booming, but general intelligence is still out of reach

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Trying to get a handle on the progress of artificial intelligence is a daunting task, even for those enmeshed in the AI community. But the latest edition of the AI Index report -- an annual rundown of machine learning data points now in its third year -- does a good job confirming what you probably already suspected: the AI world is booming in a range of metrics covering research, education, and technical achievements. The AI Index covers a lot of ground -- so much so that its creators, which include institutions like Harvard, Stanford, and OpenAI, have also released two new tools just to sift through the information they sourced from. One tool is for searching AI research papers and the other is for investigating country-level data on research and investment. Most of the 2019 report basically confirms the continuation of trends we've highlighted in previous years.


MI GPS (Genomic Profiling Similarity) Score - Caris Life Sciences

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Caris has the largest and most comprehensive database of combined molecular and clinical outcomes data in the world, and we are actively employing advanced machine learning capabilities with the database to identify unique molecular signatures. These molecular signatures can be used to better identify cancer subtypes and predict patient response to certain therapies. Based off this work1, we are pleased to introduce MI GPS Score – a tool to help manage cancer of unknown primary (CUP) or cases identified by the ordering physician with atypical clinical presentation or clinical ambiguity. MI GPS Score provides a tumor type similarity score that compares genomic characteristics of the patient's tumor against the Caris database, in conjunction with a comprehensive pathology consultation (e.g. MI GPS Score will be performed and reported for all CUP cases and can be added to any solid tumor order by selecting the appropriate box on the req.