Medical Device Developments的动态

AI against antibiotic resistance?? Let's explore how artificial intelligence is revolutionizing the discovery of new antibiotics! ?? The current antibiotic resistance crisis threatens to render current antibiotics ineffective and increase morbidity from bacterial infections. This crisis has been exacerbated by the lack of new antibiotics. For this reason, a deep learning approach has been developed for the discovery of potential antibiotics. Neural network models have been used to identify chemical substructures that are linked to antibiotic activity. This has allowed for more accurate prediction of structural classes of antibiotics. Using explainable graph algorithms, structural elements with high potential antibiotic activity and low cytotoxicity have been identified. This work has been empirically validated, finding compounds selective against resistant bacteria such as methicillin-resistant S. aureus and vancomycin-resistant enterococci, with promising efficacy in murine models of systemic methicillin-resistant S. aureus skin and thigh infection. This approach demonstrates that artificial intelligence can be a powerful and explanatory tool in drug discovery. https://lnkd.in/dZY8Vdge #biomedicalengineering #upf #upfcomunicació #engineering #pompeufabra #bioengineering #technews

Researchers at University of Cambridge have developed an AI tool that can identify drug-resistant bacteria within hours, significantly outperforming traditional testing methods. This advancement promises to speed up diagnosis and treatment! #artificialintelligence #machinelearning #drugdiscovery #singlecell #bacteria #computationalbiology #computationalchemistry

???????????????? ????????????????????????: ????-???????????? ???????????????????? ?????????????????????? I wanted to share some fascinating news from the University of Texas at Austin. Researchers have used artificial intelligence (AI) to develop a new antibiotic that shows promise in fighting antibiotic-resistant bacteria. This innovative approach leverages AI to modify an existing drug, making it safe and effective for human use. Key points from the research: ? AI in Drug Development : By using a large language model, similar to ChatGPT, scientists have engineered a version of an antibiotic called Protegrin-1. This new version, bsPG-1.2, is effective against bacteria but safe for humans. ? Animal Trials : In trials with mice, this new antibiotic significantly reduced bacterial infections without harming the host. ? Future Implications: This breakthrough could revolutionize how we develop antibiotics, making the process faster and more efficient, and potentially addressing the growing issue of antibiotic resistance. For more details, you can read the full study in Nature Biomedical Engineering: [Link: https://lnkd.in/g89tAErQ] Question: How do you think this AI-driven approach to antibiotic development could change the future of healthcare? Looking forward to your thoughts! #Healthcare #Innovation #Antibiotics #ArtificialIntelligence #BiotechResearch

Inspiring medical news today- Unveiling the Power of Research: How the New MRSA Antibiotic Cracked AI's 'Black Box' In the realm of scientific breakthroughs, the power of research often lies in its ability to challenge the status quo and push the boundaries of what's possible. One common misconception is that if something hasn't been done before, it can't be done. However, history has shown us that this perspective is flawed. Countless discoveries have emerged from endeavors that initially seemed destined for failure. It's this very notion—the belief that what appears to be a dead-end can transform into a path of success through research—that fuels the spirit of innovation. Once again recent inspiring innovation from MIT - #Ai used in #drugdevelopment and cracked #mrsa infections prove it again How did they do Wong and his colleagues first mined 39,000 compounds for antibiotic activity against MRSA. They fed information about the compounds' chemical structures and antibiotic activity into their machine learning model. With this, they "trained" the model to predict whether a compound is antibacterial. Next, they used additional deep learning to narrow the field, ruling out compounds toxic to humans. Then, deploying their various models at once, they screened 12 million commercially available compounds. Five classes emerged as likely MRSA fighters. Further testing of 280 compounds from the five classes produced the final results: Two compounds from the same class. Both reduced MRSA infection in mouse Whether you're a scientist, a student, or a concerned citizen, there are numerous ways to contribute to the advancement of knowledge and the pursuit of groundbreaking solutions. Let's join forces to harness the power of research and drive meaningful change in the world. #Research #Innovation #Science #MRSA #Healthcare #AI

AI lab news? Uses of AI/ML in the lab . 18.03.2024There are numerous ways that both simple and complex AI tools can aid a clinical laboratory. These include:?*Automated spectroscopic data analysis and disease detection multivariate analysis of disease conditions. *test interpretation.*Digital image analysis for microbiology, haematopathology, immunology, and forensics.Data entry automation for specific tasks and processes.*Creating standardised reports for lab test results and automated entry into Laboratory Information System (LIS).*Minimising laboratory testing for inappropriate test orders. *predicting test results from other available data on patient chart, and reducing redundancy and duplication of lab tests, based on prior type and date of tests already performed.*Data analytics for laboratory operations planning, such as predicting volume workflow, employee staffing requirements, etc.*Identifying and alerting for abnormal test results.?*Auto-verification of test results for quality control.Ref : mayo clinic laboratory. 18.03.2024 #AI? #ML? #LIS??#medicallaboratory?#clinicalpathology

Facing the challenge of pan-resistant bacteria ??, AI opens new doors ??. SyntheMol, an AI model, crafts molecules to fight these threats ???. This led to six novel molecules with antibacterial properties ????, showing AI’s potential in antibiotic design. #AIResearch #AntibioticResistance #Innovation Read more about this groundbreaking work here: (https://lnkd.in/dd-QeurP)

?? **AI Revolutionizing Healthcare and Microbiology: A Breakthrough in Disease Detection** ??? What if diagnosing complex diseases like cancer or identifying harmful pathogens could be done in minutes instead of hours?? Researchers at Washington State University have developed a deep learning AI model that can detect signs of disease in tissue images faster and, in many cases, more accurately than humans. This innovation is a game-changer not just for medical diagnostics but also for microbiology.? In microbiology, where analyzing samples for pathogens is often time-consuming and labor-intensive, this technology could dramatically speed up processes like identifying bacterial or viral infections. Imagine the impact on global health—faster diagnostics during outbreaks, improved pathogen research, and more efficient treatment development.? The future of healthcare and microbiology is here—a blend of human expertise and AI efficiency. Exciting times ahead for medicine and science!? What do you think about AI’s potential in these fields? Let’s discuss! ??? #AI #HealthcareInnovation #Microbiology #MedicalBreakthroughs

Clemson University researchers are at the forefront of integrating artificial intelligence into precision medicine, pioneering a transformative approach that promises to revolutionize patient care. Their latest research utilizes AI to develop personalized medical treatments that are more effective and tailored to individual patients' genetic profiles. This advancement not only enhances the accuracy of diagnoses and the efficacy of treatments but also reduces the risk of adverse reactions, setting a new standard in healthcare. The implications of this AI-driven precision medicine are vast. By accurately predicting the best treatment protocols for each patient, healthcare can become not only more effective but also more cost-efficient, potentially lowering overall healthcare costs while improving outcomes. The future of healthcare looks promising with such innovations, pointing towards a system where treatment is not only reactive but also predictively personalized. This approach is a significant step toward a healthcare revolution, where each patient receives care that is specifically optimized for their unique health profile. #PrecisionMedicine #AIinHealthcare #ClemsonResearch #FutureOfHealthcare #CSIMGT725 #ProfTimRN

By delivering greater insight into protein sequence, structure, and function, #AI and #MachineLearning make it possible to program novel medicines that can treat a variety of diseases. Join this webinar with Drug Discovery News where Dr. Alex Snyder of Generate:Biomedicines will discuss: - How generative AI is being leveraged to fill critical gaps in medical treatments by identifying and developing new drug targets; and - The synergistic integration of computational (dry-lab) and experimental (wet-lab) approaches to accelerate the drug development pipeline, leading to more personalized and efficacious medical solutions.

Pan-resistant bacteria are driving the urgent need for new antibiotics. Traditional AI methods for discovering antibiotics face challenges: property prediction models struggle with scalability, and generative models often produce hard-to-synthesize molecules. SyntheMol, a new generative model, overcomes these issues by designing easy-to-synthesize compounds from nearly 30 billion molecules. Applied to combat Acinetobacter baumannii, a problematic Gram-negative bacteria, SyntheMol's designs led to the synthesis and validation of 58 molecules, with six showing antibacterial activity against A. baumannii and various other bacteria. This success highlights the potential of AI in creating novel, synthesizable, and effective antibiotics. https://lnkd.in/gvVY7zEi