Sep 19,2023

Deep Bio Announces Market Authorization from Swissmedic for DeepDx Prostate, Paving the Way for European Expansion

Deep Bio, a leader in artificial intelligence (AI)-powered cancer diagnostics, announced today that it has obtained marketing authorization from Swissmedic for DeepDx Prostate, its AI-powered prostate cancer diagnostic software. Swissmedic is the Swiss regulatory authority responsible for the authorization and supervision of therapeutic products. With this key approval, Deep Bio is now eligible to launch DeepDx Prostate in Switzerland, marking a significant milestone in the company's plans to expand its footprint in Europe. DeepDx Prostate is an AI-powered software for the assessment of prostate cancer on digital whole slide images of hematoxylin and eosin-stained prostate core-needle biopsies. Deep Bio continues to expand its global reach through partnerships with digital pathology leaders in the US, Europe, and India.

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Sep 19,2023

AccessHope adds Johns Hopkins to its cancer care network

Employer-focused cancer startup AccessHope announced it is adding Johns Hopkins Medicine's Sidney Kimmel Comprehensive Cancer Care Center to its network of National Cancer Institute-designated organizational partners. AccessHope connects employers offering self-funded health plans and employees' treating physicians with cancer-focused expertise from NCI-Designated Comprehensive Cancer Centers nationwide to increase access to quality oncology-based care, research and patient outcomes. The company is a wholly owned subsidiary of cancer treatment and research center City of Hope. Its existing National Cancer Institute partners include City of Hope, the Dana-Farber Cancer Institute, Emory Healthcare, Northwestern Medicine and the Fred Hutchinson Cancer Center. One company utilizing AccessHope's offerings for its employees is tech and retail giant Amazon. The company touts the offering as one of four health benefits employees can use on their first day.

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Sep 19,2023

PathAI Announces Expansion of BioPharma Lab to Provide End-to-End Central Pathology and Histology Services

PathAI, a global leader in AI-powered pathology, today announced the expansion of its BioPharma Laboratory Services. Capitalizing on the 30-year history of delivering high quality pathology services in the PathAI Diagnostics clinical laboratory (formerly known as Poplar Healthcare), PathAI offers biopharma partners a comprehensive, GCP/GCLP compliant histology and digital pathology lab to support prospective clinical trials across oncology, liver, and gastrointestinal indications. The lab offers pharmaceutical companies access to unparalleled histological laboratory services and comprehensive operational support, encompassing the full end-to-end tissue processing from kitting and logistics management, tissue processing and staining across H&E, IHC, and special stains; local and remote pathology tapping into PathAI’s network of >500 US board-certified pathologists; and AI-driven analysis from PathAI’s menu of algorithms and clinical trial software.

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Sep 12,2023

Dell Technologies and University of Limerick Join Forces to Advance Predictive and Diagnostic Cancer Research

Dell Technologies (NYSE:DELL) has joined forces with the University of Limerick's Digital Cancer Research Centre to develop an artificial intelligence (AI) platform and digital twin technology to power predictive and diagnostic research in oncology. The technology can help clinicians provide more effective cancer care for those with B-cell lymphoma from speeding diagnosis to providing enhanced treatment and improving long-term outcomes for patients in Ireland and worldwide. Dell created an AI platform for the University that delivers high performance computing power to accelerate oncology and precision medicine research. The platform sits within the Digital Cancer Centre's multicloud ecosystem. It is powered by Dell's latest storage arrays and Dell PowerEdge servers optimised for AI to produce cancer patient digital twins for better diagnostics.

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Sep 08,2023 TOP STORY

Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study

Artificial intelligence (AI) as an independent reader of screening mammograms has shown promise, but there are few prospective studies. The aim of this study was to conduct a prospective clinical trial to examine how AI affects cancer detection and false positive findings in a real-world setting. ScreenTrustCAD was a prospective, population-based, paired-reader, non-inferiority study done at the Capio Sankt Göran Hospital in Stockholm, Sweden. The primary outcome was screen-detected breast cancer within 3 months of mammography, and the primary analysis was to assess non-inferiority (non-inferiority margin of 0·15 relative reduction in breast cancer diagnoses) of double reading by one radiologist plus AI compared with standard-of-care double reading by two radiologists. From April 1, 2021, to June 9, 2022, 58?344 women aged 40–74 years underwent regular mammography screening, of whom 55?581 were included in the study. 269 (0·5%) women were diagnosed with screen-detected breast cancer based on an initial positive read: double reading by one radiologist plus AI was non-inferior for cancer detection compared with double reading by two radiologists. Single reading by AI and triple reading by two radiologists plus AI were also non-inferior to double reading by two radiologists.

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Sep 05,2023

Massive Bio Announces Partnership with the Newly Launched Cancer Community Hub

Massive Bio, a global leader in AI-driven solutions for cancer treatment and clinical trial matching, is thrilled to announce its strategic support for the Cancer Community Hub. This groundbreaking online platform promises to reshape the landscape of cancer education and foster a supportive community for all those affected by the disease. Drawing upon the strengths and expertise of Massive Bio, the collaboration aims to further enrich the offerings of the Cancer Community Hub. Key Features of the Cancer Community Hub include: An interactive space for discussions, Updates and insights into ongoing trials, and Diverse educational and news content.

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Sep 06,2023

Veracyte and Gustave Roussy Announce Collaboration to Help Biopharmaceutical Companies Accelerate Development of Novel Cancer Therapies

Veracyte, Inc., a global diagnostics company, and Gustave Roussy, a leading cancer center worldwide, announced today that they have entered into a collaboration to bring together their respective capabilities to provide novel insights into the underlying biology of metastatic tumors, which may help biopharmaceutical companies accelerate development of new cancer therapies. Through the partnership, Gustave Roussy’s Department of Therapeutic Innovation and Early Clinical Trials (DITEP) will provide metastatic tumor samples and data for multiple cancer indications that are derived from its major innovative research projects, particularly for new immunotherapies. Veracyte will combine these assets with its multi-omics testing and machine learning capabilities to create a Veracyte Biopharma Atlas reference database of genomic and immunomic biomarkers. The company will then leverage this deep characterization of each tumor’s biology, particularly its immune contexture, to derive further insights about tumors that are more likely to respond to a particular therapy.

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Aug 31,2023

AI Predictions for Colorectal Cancer: One Step Closer to Efficient Precision Oncology

Colorectal cancer (CRC) ranks second in leading causes of cancer-related deaths globally, according to the WHO. For the first time, researchers from Helmholtz Munich and the University of Technology Dresden (TU Dresden) show that artificial intelligence (AI)-based predictions can deliver comparable results to clinical tests on biopsies of patients with CRC. This novel model for biomarker detection represents a significant stride towards the realization of precision therapy approaches in the field of oncology. The method is now published in Cancer Cell. A team of scientists around Dr. Tingying Peng from Helmholtz Munich and Prof. Jakob N. Kather from TU Dresden show that AI can predict specific biomarkers in stained tissue samples of patients with CRC. They used so-called transformer networks, a recent deep learning (DL) approach, to identify patterns and support diagnostic decisions in cancer management. The new method significantly improves previous approaches for biomarker detection.

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Sep 01,2023 TOP STORY

AI specialist Intelligent Omics bags J&J deal

UK artificial intelligence (AI) specialist Intelligent Omics has entered into a research collaboration with Johnson & Johnson, within weeks of joining the big pharma's JLABS incubation programme. The Nottingham-based start-up has developed a proprietary AI platform designed to seek out new biological targets based on the use of artificial neural networks (AANs) that can evaluate tens of millions of data points in a short period of time. It uses machine learning to extract insights from transcriptomic data sets from diseased tissue. The new alliance with J&J's Janssen Pharma unit is focused on finding new targets for the treatment of haematological cancers, a key growth area for J&J, as it builds on blockbuster drugs like Darzalex (daratumumab) and Imbruvica (ibrutinib) with a new generation of therapies headed by bispecific antibodies and CAR-Ts.

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Aug 30,2023

Combining AI Models Improves Breast Cancer Risk Assessment

Combining artificial intelligence (AI) systems for short- and long-term breast cancer risk results in an improved cancer risk assessment, according to a study published in Radiology, a journal of the Radiological Society of North America (RSNA). For this study, Dr. Lauritzen and his research team sought to identify whether a commercially available diagnostic AI tool and an AI texture model, trained separately and then subsequently combined, may improve breast cancer risk assessment. The researchers used the diagnostic AI tool Transpara and a texture model that was developed by the researchers. A Dutch training set of over 39,000 exams was used to train the models. The short- and long-term risk models were combined using a three-layer neural network. Compared to the diagnostic and texture models alone, the combined AI model showed an overall improved risk assessment for both interval and long-term cancer detection. Interval cancers are those that are found between routine screenings. The model also enabled identification of women at high risk for breast cancer.

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