Microsoft has partnered with and invested in US-based Adaptive Biotechnologies to map the human immune system genetics using artificial intelligence (AI) for early detection and diagnosis of multiple diseases, including cancer.
The light-sensitive layer found at the back of a person's eyes contains more than just cells that detect shadows and light — it also contains information about the health of a person's entire body. And now, artificial intelligence can glean this information from a single snapshot, new research suggests.
Experts generally agree that, before we might consider artificial intelligence (AI) to be truly intelligent —that is, on a level on par with human cognition— AI agents have to pass a number of tests. And while this is still a work in progress, AIs have been busy passing other kinds of tests.
The quest to better detect cancer has made a potentially huge strides. A study out of Yokohama, Japan, has potentially harnessed artificial intelligence to help detect colorectal cancer even before benign tumors become malignant.
Strategic collaboration to leverage BigHat’s AI/ML (Artificial Intelligence / Machine Learning) guided Milliner platform to design high-quality next-generation protein therapeutics BigHat Biosciences, a biotechnology company with an artificial intelligence/machine learning-guided antibody discovery and development platform announced a collaboration with Janssen Biotech Inc., a Johnson & Johnson company. This strategic collaboration combines the drug discovery, clinical development and data science expertise from Johnson & Johnson with BigHat’s Milliner platform, a suite of machine learning technologies integrated with a high-speed wet lab, to guide the design and selection for high-quality antibodies for multiple Neuroscience therapeutic targets. The agreement was facilitated by Johnson & Johnson Innovation. BigHat’s antibody design platform, Milliner, integrates a synthetic biology-based high-speed wet lab with machine learning technologies into a full-stack antibody discovery and engineering platform, to engineer antibodies with more complex functions and better biophysical properties. This approach reduces the difficulty of designing antibodies and other therapeutic proteins ...
Dive Brief A U.K. agency outlined its position on the regulation of artificial intelligence as a medical device in a policy paper published Tuesday.The Medicines and Healthcare products Regulatory Agency (MHRA) said many AI products that can be put on the market now without conformity assessment will move to a higher risk category in upcoming reforms.The paper explains how MHRA interprets a government AI strategy focused on principles such as safety, security and robustness and aligns it with international standards. Dive Insight The U.K. government committed to five cross-sector principles for the regulation of AI in February. A consultation found “strong support” for the principles, the government said, and established them as the basis for a regulatory framework designed to keep pace with rapidly advancing AI technology. Days later, the government wrote to the MHRA to request details of its approach to AI. In response, the MHRA published a policy ...
Blood drawing is performed billions of times each year worldwide, playing a critical role in diagnostic procedures. Despite its importance, clinical laboratories are dealing with significant staff shortages, which impact their ability to deliver timely test results and maintain satisfactory patient care. Now, an innovative robotic blood drawing device for the medical laboratory market could help ease staff workload and provide a more consistent patient experience. Developed by Vitestro (Utrecht, The Netherlands), this innovative blood-drawing device is designed to perform safe and accurate blood draws. It utilizes artificial intelligence (AI) for ultrasound-guided 3D reconstruction and ensures submillimeter precision in needle insertion. This high level of accuracy and consistency in blood collection is achieved through a combination of AI, advanced imaging technologies, and robotics. By automating blood draws, Vitestro’s device not only reduces the physical demand on staff but also enhances the satisfaction of both patients and healthcare providers. The ...
BEIJING, April 29, 2024 /PRNewswire/ — In recent years, the rapid development of artificial intelligence has introduced new possibilities across numerous scientific disciplines. As an AI for Science pioneer, DP Technology is continually collaborating with partners to explore the transformative impact AI can bring to science. During its DevDay held in Beijing on April 12th, DP Technology showcased a series of large science models, including the DPA large atomic model[1], Uni-Mol 3D molecular model[2], Uni-Fold protein folding model[3], Uni-RNA ribonucleic acid model[4], and Uni-SMART large language model for multimodal scientific literature[5] among others. About DP Technology DP Technology is a global leader in the “AI for Science” research paradigm, where AI learns scientific principles and data, then tackles key challenges in scientific research and industrial R&D. DP’s commitment to interdisciplinary research has led to the creation of the “DP Particle Universe,” an array of pre-trained large science ...
Deciphera Pharmaceuticals is set to be acquired in a $2.4bn buyout, as the biopharma announced that it has commenced a definitive merger agreement with Ono Pharmaceutical. Under the terms of the offered transaction, Ono will make a cash purchase of all outstanding shares of Deciphera’s common stock at $25.60 per share and subsequently merge Deciphera with a wholly-owned subsidiary of Ono upon the deal’s completion. The deal has been unanimously approved by both companies’ boards of directors and is expected to close in Q3 2024. Following the announcement of acquisition, Deciphera’s stock has jumped 71.9%. Waltham, Massachusetts-based Deciphera brings to the table an extensive kinase inhibitor pipeline, kinase drug discovery expertise, and a strong commercial and sales platform in the US and European markets that is meant to advance Ono’s capabilities and presence in the oncology space. Upon the successful completion of the acquisition, Ono will gain access to Deciphera’s ...
Researchers from ETH Zurich have developed a new generative artificial intelligence (AI)-based computer process to develop drug molecules based on a protein’s three-dimensional surface. The new process could revolutionise drug research, making it possible to generate active pharmaceutical ingredients quickly and easily. The new computer process’ algorithm was developed in collaboration with ETH’s professor Gisbert Schneider and former doctoral student Kenneth Atz, using AI to design new active pharmaceutical ingredients. Researchers trained the AI model with information from hundreds of thousands of known interactions between chemical molecules and the corresponding three-dimensional protein structures. The algorithm generates the blueprints for potential drug molecules that can increase or inhibit the activity of proteins with a known three-dimensional shape. The generative AI then designs molecules that bind specifically to the protein according to the lock-and-key principle to be interacted with. “This means that when designing a drug molecule, we can be sure that ...
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