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Tempus AI Seeks Computational Biologist for Pharma R in Boston

Tempus AI Seeks Computational Biologist for Pharma R in Boston

Tempus AI Seeks Computational Biologist for Pharma R in Boston

U.S. Health Secretary Robert F. Kennedy Jr. Launches Initiative to Modernize Clinical Trials with UT Austin Partnership

U.S. Health Secretary Robert F. Kennedy Jr. Launches Initiative to Modernize Clinical Trials with UT Austin Partnership

U.S. Health Secretary Robert F. Kennedy Jr. has announced a new federal initiative called SURPASS (Simulation-augmented, Real-time Platform Adaptive Seamless Trials) aimed at transforming clinical trials in the United States. This program, unveiled in Austin, Texas, on September 30, 2026, seeks to accelerate the development of new drugs and biologics by utilizing advanced computational models, real-time analysis, shared infrastructure, and automation. The goal is to make clinical trials faster, more cost-effective, and less burdensome for patients. The Department of Health and Human Services (HHS), through its Advanced Research Projects Agency for Health (ARPA-H), is spearheading this effort. Secretary Kennedy emphasized that the current system is too slow, expensive, and demanding on patients. As part of this initiative, UT Austin's Dell Medical School will serve as a key academic partner for two complementary projects: STACK, which aims to expand the number of research sites capable of conducting clinica...

New AI Lab Ortet Launches with $500 Million Backing to Revolutionize Health AI

New AI Lab Ortet Launches with $500 Million Backing to Revolutionize Health AI

New AI Lab Ortet Launches with $500 Million Backing to Revolutionize Health AI

UVM Receives $38 Million Contract to Develop AI-Powered 'Digital Twins' for ICU Care

UVM Receives $38 Million Contract to Develop AI-Powered 'Digital Twins' for ICU Care

The University of Vermont (UVM) Larner College of Medicine, led by trauma surgeon and researcher Gary An, M.D., has secured a research and development contract worth up to $38 million. This funding, the largest in UVM's history, is from the Advanced Research Projects Agency for Health (ARPA-H), a federal agency within the U.S. Department of Health and Human Services. The initiative aims to develop artificial intelligence-powered 'digital twins' to personalize treatment for critically ill patients. These digital twins are mathematical models that use real-time patient data, including frequent blood samples and physiological monitoring, to predict disease progression and evaluate potential treatment strategies. The project, known as ReSCUED (Reprogramming Severe Critical Illness Using Extensible Digital Twins), focuses on addressing disordered immune responses in conditions like severe trauma, burns, and sepsis. Researchers believe this technology could reduce intensive care unit (ICU) stays by at least 25 p...

Novo Nordisk Foundation Commits $53 Million to Broad Institute for Genomic Research on Metabolic Diseases

Novo Nordisk Foundation Commits $53 Million to Broad Institute for Genomic Research on Metabolic Diseases

The Novo Nordisk Foundation has announced a $53 million commitment to renew and expand the Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at the Broad Institute. This funding aims to scale up transatlantic efforts to understand the biological mechanisms driving type 2 diabetes and obesity. The Center, led by managing director Kasper Lage, will utilize massive-scale data generation, artificial intelligence, and advanced cellular models to identify new targets for potential therapies. Since its launch in 2021 with an initial grant of $47.5 million, the Center has fostered collaborations across 18 research groups and over 120 scientists, hosting more than 37 Danish researchers through an exchange program. This initiative has positioned the Center as a global leader in mapping how genetic variants contribute to metabolic diseases, developing comprehensive cellular and genomic resources, scalable technologies for variant-to-function research, and advanced tools for large-scale genetic discover...

Johnson Johnson Seeks Director for World Model Agentic Learning in AI Development

Johnson Johnson Seeks Director for World Model Agentic Learning in AI Development

Johnson Johnson Seeks Director for World Model Agentic Learning in AI Development

AI Genome Analysis Raises Concerns Over Standards and Clinical Interpretation

AI Genome Analysis Raises Concerns Over Standards and Clinical Interpretation

Artificial intelligence (AI) is rapidly advancing the accessibility and speed of genome analysis, with systems like Claude now capable of interpreting entire genomes in minutes for a minimal cost. This marks a significant shift from the past, where such analyses required extensive human expertise and time. For example, a task that once took a team of 30 people nearly a year to complete can now be attempted by AI in about 30 minutes for approximately $5. While AI can re-identify important genetic findings, including disease risks and medication responses, its interpretations are influenced by factors such as the reference genome used and the sequencing technology. Many existing genomes were produced using 'short-read sequencing,' which can be unreliable in complex or repetitive DNA regions where disease-causing variants might occur. Furthermore, current reference genomes often do not adequately represent the full diversity of human genomes, potentially making variant detection difficult in under-represented...

National Cancer Institute Initiative Confirms High Fidelity of Next-Generation Cancer Models

National Cancer Institute Initiative Confirms High Fidelity of Next-Generation Cancer Models

The National Cancer Institute (NCI) Human Cancer Models Initiative (HCMI) has confirmed that its next-generation patient-derived cancer models accurately reflect the biology of patient tumors. This initiative, established to improve the accuracy of laboratory models, has generated 665 models spanning 25 cancer types, including rare diseases. Each model is linked to comprehensive genomic, transcriptomic, and clinical data and is openly available to researchers globally. A recent study, involving a collaboration of research partners worldwide, analyzed 421 matched tumor-model pairs. The results showed 97.8% genetic concordance, 95% epigenomic concordance, and 92% transcriptional similarity between the models and their originating tumors. This high level of agreement across genetic, epigenomic, and transcriptional dimensions provides strong evidence that these models are not only genetically similar but also biologically representative of how tumors function. ATCC, the authorized provider of the collection, r...

Kennesaw State Researcher Receives NIH Grant to Develop AI Tools for Sleep Apnea Treatment

Kennesaw State Researcher Receives NIH Grant to Develop AI Tools for Sleep Apnea Treatment

Shumit Saha, a researcher at Kennesaw State University, has been awarded a $235,520 grant from the National Institutes of Health (NIH). The grant will fund his work in developing artificial intelligence (AI) tools designed to analyze snoring patterns. The primary goals of Saha's project are to identify the precise location of upper airway collapse during sleep and to predict a patient's potential response to hypoglossal nerve stimulation, a treatment for obstructive sleep apnea. Obstructive sleep apnea is a condition where breathing repeatedly stops and starts during sleep, leading to fatigue and serious health problems if left untreated. Current methods for identifying the collapse location often involve invasive procedures, such as inserting a camera during sedation. Saha's research aims to provide a less invasive and more efficient diagnostic approach, ultimately reducing the trial-and-error process in selecting appropriate treatments for patients.

Profluent Partners with BioMarin to Design Novel Medicines Using AI for Genetically Defined Conditions

Profluent Partners with BioMarin to Design Novel Medicines Using AI for Genetically Defined Conditions

Profluent, an AI lab specializing in biology, has announced a collaboration with BioMarin Pharmaceutical Inc. to design and optimize novel enzyme therapies. This partnership aims to advance next-generation candidates for genetically defined conditions. Profluent will leverage its proprietary protein language models, which utilize the Profluent Protein Atlas—the world's largest protein sequence dataset with over 115 billion unique sequences—to generate and optimize enzyme candidates. BioMarin will then screen these AI-designed proteins to identify potential drug candidates with desired activity and stability profiles for further evaluation and preclinical testing. This collaboration combines Profluent's advanced AI models for de novo protein design with BioMarin's extensive expertise in enzyme replacement therapies.

Wearable Health Technology Market Sees Rapid Growth for Chronic Disease Management

Wearable Health Technology Market Sees Rapid Growth for Chronic Disease Management

The market for wearable health technology, including fitness trackers, smartwatches, and specialized health monitors, is experiencing rapid growth, particularly in the area of chronic disease management. These devices are transforming healthcare by enabling continuous monitoring, real-time data collection, and personalized treatment adjustments for conditions such as diabetes, cardiovascular diseases, and respiratory illnesses. This shift moves away from traditional periodic check-ups, providing real-time data on vital signs, activity levels, and medication adherence. Advancements in sensor technology have improved the accuracy and miniaturization of these devices, allowing for non-invasive monitoring of physiological parameters like blood oxygen levels and heart rate variability. The integration of AI and machine learning algorithms with wearable data is also unlocking new insights, with predictive analytics identifying early warning signs of health deterioration. Regulatory support and reimbursement fram...

AI-Powered Predictive Analytics and Polygenic Risk Scores Advance Preventive Healthcare

AI-Powered Predictive Analytics and Polygenic Risk Scores Advance Preventive Healthcare

Predictive medicine is undergoing a significant transformation through the integration of AI-powered predictive analytics and polygenic risk scores (PRS). These advanced tools are being utilized to identify individuals at high genetic risk for common chronic diseases such as heart disease and type 2 diabetes. Unlike conditions caused by a single gene, these chronic diseases result from the cumulative effect of hundreds or thousands of genetic variants, combined with lifestyle and environmental factors. PRS quantifies an individual's genetic predisposition to a disease, allowing for the potential implementation of earlier and more intensive interventions, including screening, lifestyle counseling, or preventive medication, before symptoms manifest. While PRS is an active area of research, its predictive accuracy can vary by disease and ancestry. AI is also broadly impacting healthcare by developing predictive models for risk stratification and diagnosis, enhancing efficiency and patient care. Additionally, ...