Search Results for “artificial intelligence” – Page 13 – media

Ono Pharmaceutical acquires cancer-focused biopharma Deciphera for $2.4bn

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 ...
- Source: drugdu
- 107
- May 3, 2024
ETH Zurich researchers use AI to develop drug molecules based on protein structures

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 ...
- Source: drugdu
- 83
- May 1, 2024
AI-Powered Digital Imaging System to Revolutionize Cancer Diagnosis

The process of biopsy is important for confirming the presence of cancer. In the conventional histopathology technique, tissue is excised, sliced, stained, mounted on slides, and examined under a microscope to identify cancerous markers. This lengthy procedure often results in patients waiting weeks or months for their results, causing treatment delays and heightened anxiety. Now, a breakthrough digital medical imaging system promises to transform cancer detection by offering instantaneous results, facilitating timely and effective treatment across all cancer types. The Photon Absorption Remote Sensing (PARS) system, an innovative, built-from-scratch technology developed by researchers at the University of Waterloo (Ontario, Canada), marks a radical departure from traditional cancer detection methods, promising diagnoses within minutes and enabling rapid surgical intervention. The system utilizes lasers to irradiate tissue samples, producing a comprehensive, high-resolution data set. This data is then processed by an artificial intelligence (AI) system that converts it into a conventional histopathology ...
- Source: drugdu
- 112
- April 29, 2024
Parexel partners with Palantir to accelerate clinical data delivery

Under the collaboration, Parexel will leverage Palantir’s Foundry and Artificial Intelligence Platform (AIP) to further power its clinical data platform, focused on driving clinical trial efficiency while maintaining the safety and regulatory rigor Parexel and Palantir Technologies has announced a multi-year strategic partnership to leverage AI to help enhance and accelerate the delivery of safe and effective clinical trials for the world’s biopharma customers. Under the collaboration, Parexel will leverage Palantir’s Foundry and Artificial Intelligence Platform (AIP) to further power its clinical data platform, focused on driving clinical trial efficiency while maintaining the safety and regulatory rigor. Parexel is the first CRO working with Palantir in this capacity, building on the companies’ existing collaboration over the past year. Jonathan Shough, Chief Information Officer for Parexel said, “We’re thrilled to expand our collaboration with Palantir — a leader in artificial intelligence technology — as we build on our application of AI ...
- Source: drugdu
- 103
- April 29, 2024
Exo adds FDA-cleared AI tools to handheld ultrasound system

Dive Brief Exo has made new artificial intelligence tools available on its Iris handheld ultrasound system, the company said Tuesday. The Food and Drug Administration cleared Exo’s AI tools for analyzing ultrasound images of the heart and lung last year. Exo sees the new capabilities as particularly beneficial for health systems and caregivers in rural and under-resourced settings because they simplify the collection and interpretation of images. Dive Insight Exo received a 510(k) nod for its original Iris device in 2021 and added imaging modes and indications to the clearance the following year. The clearances cover handheld portable diagnostic ultrasound systems, similar to Butterfly Network’s iQ, that enable healthcare professionals to measure body structures and fluids in adults and children. Users can view the images on smartphone screens. In 2023, Exo gained additional FDA clearances for AI products. One clearance covered software that uses machine learning to help quantify bladder ...
- Source: drugdu
- 111
- April 28, 2024
AI Tool Precisely Matches Cancer Drugs to Patients Using Information from Each Tumor Cell

Current strategies for matching cancer patients with specific treatments often depend on bulk sequencing of tumor DNA and RNA, which provides an average profile from all cells within a tumor sample. However, tumors are heterogeneous, containing multiple subpopulations of cells, or clones, each potentially responding differently to treatments. This variability may explain why some patients either fail to respond to certain treatments or develop resistance. Single-cell RNA sequencing offers higher-resolution data than bulk sequencing, capturing data at the single-cell level. This approach to identify and target individual clones may lead to more lasting drug responses, although, single-cell gene expression data are more expensive to generate and less accessible in clinical environments. In a proof-of-concept study, researchers at the National Institutes of Health (NIH, Bethesda, MD, US) have developed an artificial intelligence (AI) tool that leverages data from individual tumor cells to predict how well a person’s cancer might respond to ...
- Source: drugdu
- 133
- April 23, 2024
Researchers introduce new AI tool to help clinicians capture uncertainty in medical images

The Tyche model could help clinicians and researchers capture crucial information in images Researchers from the Massachusetts Institute of Technology (MIT), the Broad Institute of MIT and Harvard, and Massachusetts General Hospital have introduced a new artificial intelligence (AI) tool to capture the uncertainty in a medical image. Funded by the National Institute of Health, the Eric and Wendy Schmidt Center and Quanta Computer, the Tyche machine-learning model could help clinicians and researchers capture crucial information. In biomedicine, AI models help clinicians by highlighting pixels that show signs of a certain disease or anomaly. However, these types of models usually only provide one answer. “Having options can help in decision-making” and “so it is important to take this uncertainty into account,” said MIT computer science PhD candidate, Marianne Rakic. Researchers developed Tyche after modifying a straightforward neural network architecture. After feeding the tool a few examples of segmentation tasks, such ...
- Source: drugdu
- 71
- April 23, 2024
GlobalData

Biopharmaceutical companies are regaining interest in metabolic dysfunction-associated steatohepatitis (MASH) innovator drug development. MASH innovator drugs witnessed over $2.5 billion increase in the total value of partnership deals from 2020 to 2024 year-to-date (YTD), with more than $2 billion forged in Q1 2024 alone, reveals GlobalData. MASH, previously known as nonalcoholic steatohepatitis (NASH), is a disease characteriSed by liver inflammation and damage caused by the accumulation of fat. Madrigal Pharmaceuticals’ Rezdiffra (resmetirom), a small molecule THRB agonist, was the first drug approved by the FDA for MASH in March 2024. Alison Labya, Business Fundamentals Analyst at GlobalData, comments, “Interest in MASH has returned in light of the FDA approval of Madrigal’s Rezdiffra, as well as the success of GLP-1 obesity drugs and their potential efficacy in MASH, as demonstrated by Eli Lilly’s Zepbound (tirzepatide; also known as Mounjaro for type 2 diabetes) in its Phase II SYNERGY-NASH trial readout.” However, ...
- Source: drugdu
- 132
- April 20, 2024
Image-Based AI Shows Promise for Parasite Detection in Digitized Stool Samples

Infections from soil-transmitted helminths (STHs), commonly known as intestinal parasitic worms, are among the most widespread neglected tropical diseases and impose a significant health burden in low- and middle-income countries, particularly among school-aged children. These infections often lead to chronic health issues that can cause disability, social stigma, and for their substantial economic impacts on communities. STHs are notorious role in nutrient loss, which can contribute to neurocognitive impairments, stunted growth and development, and persistent fatigue in affected children. Additionally, these parasites are a major cause of morbidity and complications during pregnancy. The standard diagnostic method for STHs involves manual microscopy, which requires up to 10 minutes per slide and is hindered by a lack of skilled professionals and access to necessary equipment and lab infrastructure in highly affected regions. There is a pressing need for improved diagnostic techniques, particularly for detecting infections of mild intensity, to effectively manage and ...
- Source: drugdu
- 128
- April 19, 2024
Deep Learning Powered AI Algorithms Improve Skin Cancer Diagnostic Accuracy

Artificial intelligence (AI) algorithms are increasingly being utilized in various clinical settings, such as dermatology. These algorithms are developed by training a computer with hundreds of thousands or millions of images of various skin conditions, each labeled with details like the diagnosis and patient outcomes. Through a process known as deep learning, the computer learns to identify patterns in the images that are indicative of specific skin diseases, including cancers. Once sufficiently trained, the algorithm can suggest potential diagnoses based on new images of a patient’s skin. However, these algorithms do not operate in isolation; they are used under the supervision of clinicians who evaluate the patient, make their own diagnostic assessments, and decide whether to follow the algorithm’s recommendations. Now, a new study led by researchers at Stanford Medicine (Stanford, CA, USA) has found that AI algorithms, which utilize deep learning, can enhance the accuracy of diagnosing skin cancers. ...
- Source: drugdu
- 113
- April 18, 2024

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