Medvolt

𝐒𝐞𝐧𝐬𝐢𝐭𝐢𝐳𝐢𝐧𝐠 𝐏𝐚𝐧𝐜𝐫𝐞𝐚𝐭𝐢𝐜 𝐂𝐚𝐧𝐜𝐞𝐫 𝐭𝐨 𝐈𝐦𝐦𝐮𝐧𝐨𝐭𝐡𝐞𝐫𝐚𝐩𝐲: 𝐀 𝐍𝐞𝐰 𝐏𝐚𝐭𝐡 𝐅𝐨𝐫𝐰𝐚𝐫𝐝 Immunotherapy has been transformative for many cancers, but pancreatic ductal adenocarcinoma (PDAC) remains largely resistant. 🛡️ Less than 5% of PDAC patients respond to this approach, and unfortunately, the prognosis is often poor due to late detection and limited treatment options. Breaking Through PDAC’s Protective Barrier: PDAC tumors have a defense mechanism— the CXCL12 coating—that repels immune T cells, blocking them from penetrating the tumor. But what if there was a way to weaken this barrier? In a new study, researchers have discovered that folinic acid may hold the key to allowing T cells into PDAC tumors. When used in conjunction with immune checkpoint inhibitors, folinic acid helps boost type I interferon signaling in the tumor, an immune response pathway that may finally open the door for immunotherapy in PDAC. Key Findings: - NKT Cells & Interferon Signaling: NKT cells, a unique type of T cell, are crucial in activating type I interferon production within the tumor. This boosts antitumor immunity and paves the way for other immune cells to enter. - Folinic Acid’s Role: This commonly used drug, known for enhancing chemotherapy efficacy, also appears to promote NKT cell infiltration in PDAC, potentially sensitizing these tumors to immunotherapy. - Combination Therapy: When folinic acid was combined with an anti-PD-1 antibody, tumor growth was halved in mice with functional NKT cells and interferon signaling. The Road Ahead: While these results are promising, much remains to be explored. The next steps involve understanding the treatment’s impact on human tumors, especially given the complexity of immune interactions in humans compared to mice. With folinic acid already a staple in cancer treatments, researchers are hopeful that future studies will advance this combination approach to human trials, offering new hope for those battling this aggressive disease. 📜 Paper: https://lnkd.in/dwGzEdmE At Medvolt, we harness the power of generative AI, alongside other large language models (LLMs) and deep learning technologies, through our innovative platform 𝐌𝐞𝐝𝐆𝐫𝐚𝐩𝐡. 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. Visit our website: https://www.medvolt.ai or reach out to us via email: [email protected] Follow Medvolt for more 🙏 #CancerResearch #Immunotherapy #PancreaticCancer #HealthcareInnovation #MedicalResearch #Oncology #PDAC #ScientificBreakthrough #medvolt

𝐁𝐫𝐞𝐚𝐤𝐢𝐧𝐠 𝐍𝐞𝐰 𝐆𝐫𝐨𝐮𝐧𝐝 𝐢𝐧 𝐂𝐚𝐧𝐜𝐞𝐫 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡: 𝐇𝐨𝐰 𝐁𝐫𝐞𝐚𝐬𝐭 𝐓𝐮𝐦𝐨𝐫𝐬 𝐌𝐢𝐦𝐢𝐜 𝐍𝐞𝐮𝐫𝐨𝐧𝐬 𝐭𝐨 𝐈𝐧𝐯𝐚𝐝𝐞 𝐭𝐡𝐞 𝐁𝐫𝐚𝐢𝐧 🧠 A groundbreaking study published in Science has uncovered a novel route breast cancer cells may use to invade the brain via the bone marrow. This discovery opens new doors for potential treatments targeting cancer metastasis. Breast cancer cells, through a process called 𝐥𝐞𝐩𝐭𝐨𝐦𝐞𝐧𝐢𝐧𝐠𝐞𝐚𝐥 𝐦𝐞𝐭𝐚𝐬𝐭𝐚𝐬𝐢𝐬, manage to survive in the harsh environment of the membranes covering the brain and spinal cord. Researchers from Duke University found that these cancer cells can crawl along blood vessels connecting the bone marrow to the brain, bypassing the bloodstream. Once there, the cancer cells mimic neurons by tricking macrophages into secreting molecules like GDNF, which helps them survive in this tough terrain. Key Highlights: - Leptomeningeal metastasis occurs in 5-10% of patients with solid tumors, and this study may offer new treatment options - Cancer cells utilize integrin a6 and NCAM proteins, strategies typically seen in neural cells, to adapt to and survive in the brain. - Blocking GDNF in mouse models resulted in longer survival times, indicating a promising therapeutic target. This innovative research provides hope for new, targeted treatments to improve the life expectancy of patients battling cancer that has spread to the brain. At Medvolt, we harness the power of generative AI, alongside other large language models (LLMs) and deep learning technologies, through our innovative platform 𝐌𝐞𝐝𝐆𝐫𝐚𝐩𝐡. 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. Visit our website: https://www.medvolt.ai or reach out to us via email: [email protected] #CancerResearch #BreastCancer #BrainMetastasis #Oncology #LeptomeningealMetastasis #MedicalBreakthrough #InnovationInHealth

🔬 Revolutionizing RNA Editing with DeepREAD! Shape Therapeutics introduces DeepREAD, a cutting-edge AI platform designed for precise and efficient RNA editing. By leveraging high-throughput screening and generative machine learning, DeepREAD creates gRNAs that enhance the efficiency and specificity of ADAR-mediated RNA editing. This breakthrough is opening new doors for therapeutic applications, including promising results targeting the MECP2R168X mutation in Rett Syndrome. 🌐Learn more about how DeepREAD is transforming genetic disease treatment - https://lnkd.in/ggYB-4XZ At Medvolt, we harness the power of generative AI, alongside other large language models (LLMs) and deep learning technologies, through our innovative platform 𝐌𝐞𝐝𝐆𝐫𝐚𝐩𝐡. 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. Visit our website: https://www.medvolt.ai or reach out to us via email: [email protected] #AI #RNAEditing #Genetics #Biotech #Innovation #MachineLearning #Therapeutics

𝐄𝐦𝐛𝐞𝐝𝐒𝐢𝐦𝐒𝐜𝐨𝐫𝐞: 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐏𝐫𝐨𝐭𝐞𝐢𝐧 𝐒𝐢𝐦𝐢𝐥𝐚𝐫𝐢𝐭𝐲 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 Understanding protein similarities is fundamental to breakthroughs in computational biology, impacting areas like drug discovery, protein engineering, and evolutionary studies. Traditional metrics, like the widely used TM-score, often miss critical local structural nuances that define functional similarities between proteins. ✨ 𝐄𝐧𝐭𝐞𝐫 𝐄𝐦𝐛𝐞𝐝𝐒𝐢𝐦𝐒𝐜𝐨𝐫𝐞 – a groundbreaking self-supervised model designed to compute protein similarities with unmatched precision by jointly analyzing local substructures and global architectures. 𝐊𝐞𝐲 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭𝐬 𝐨𝐟 𝐄𝐦𝐛𝐞𝐝𝐒𝐢𝐦𝐒𝐜𝐨𝐫𝐞: 1. Multiscale Structural Alignment: By leveraging local and global protein views, the model ensures that even subtle local substructures play a role in determining protein similarities. 2. Contextual Integration: Utilizing embeddings from pre-trained protein language models, EmbedSimScore captures functional and evolutionary relationships that may not be evident from structure alone. 3. Contrastive Learning: Through this method, local subgraphs are compared, further refining the ability to distinguish between structurally and functionally similar proteins. 🌍 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐈𝐦𝐩𝐚𝐜𝐭: - EmbedSimScore accurately identifies protein similarities overlooked by traditional TM-scores, uncovering intrinsic relationships and aiding in applications such as drug discovery and protein engineering. - From designing new enzymes to identifying therapeutic targets, this approach opens new doors for targeted biological applications. For researchers and professionals in the field, EmbedSimScore offers a promising new tool to advance both academic research and real-world applications in biotechnology. 📜 Paper: https://lnkd.in/drSMZHxd Are you passionate about the latest biotech advancements, cutting-edge drug discovery news, and groundbreaking research papers? Look no further! Subscribe to Medvolt's FREE newsletter: https://lnkd.in/d6Fmfu-N #ProteinEngineering #DrugDiscovery #ComputationalBiology #AI #MachineLearning #Biotechnology #medvolt

𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐃𝐫𝐮𝐠 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲: 𝐓𝐡𝐞 𝐑𝐨𝐥𝐞 𝐨𝐟 𝐈𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬 𝐢𝐧 𝐌𝐨𝐝𝐞𝐫𝐧 𝐌𝐞𝐝𝐢𝐜𝐢𝐧𝐞 💊 The landscape of drug discovery is being transformed by cutting-edge informatics, enabling more efficient and targeted approaches to finding new therapies. Key advancements are being made in High-Throughput Screening (HTS) and Structure-Based Drug Design (SBDD). 📊 High-Throughput Screening (HTS) HTS allows rapid testing of vast compound libraries against specific drug targets. Informatics plays a pivotal role in managing and analyzing the enormous datasets generated, helping identify promising hits and lead compounds faster than ever. 🧬 Structure-Based Drug Design (SBDD) SBDD utilizes computational models to analyze the 3D structure of drug targets like proteins or enzymes. This approach helps in predicting and optimizing potential drug candidates' binding affinity, selectivity, and potency, streamlining the drug development process. 💻 The Power of In-Silico Modeling   The adoption of in-silico modeling tools is revolutionizing drug discovery by providing a cost-effective, time-efficient alternative to traditional lab experiments. These tools enable the virtual screening of vast compound databases, predicting drug behavior, toxicity, and interactions with high precision. 📈 Market Dynamics   The global drug discovery informatics market is set to grow from USD 2.96 billion in 2022 to an estimated USD 7.44 billion by 2031, at a CAGR of 10.8%. North America leads this growth, driven by robust pharmaceutical and biotechnology industries, favorable regulations, and significant R&D investments. 🌍 Regional Insights   - North America holds the largest market share, projected to grow at a 10.5% CAGR. - Europe is expected to grow at a 10.6% CAGR, with substantial R&D investments and a strong focus on innovative drug discovery. 🏥 Opportunities Ahead The rising incidence of chronic diseases globally creates a pressing need for novel therapeutics. Informatics tools are instrumental in accelerating the development of new drugs, offering hope for effective treatments for cardiovascular diseases, cancer, diabetes, and more. As we look to the future, the integration of informatics and AI in drug discovery promises to unlock new possibilities, driving innovations and improving healthcare outcomes globally. At Medvolt, we harness the power of generative AI, alongside other large language models (LLMs) and deep learning technologies, through our innovative platform 𝐌𝐞𝐝𝐆𝐫𝐚𝐩𝐡. 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. Visit our website: https://www.medvolt.ai or reach out to us via email: [email protected] #DrugDiscovery #Informatics #HealthcareInnovation #Pharmaceuticals #Biotechnology #AIinHealthcare #MedicalResearch #DrugDevelopment

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𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐏𝐫𝐨𝐭𝐞𝐢𝐧-𝐁𝐚𝐬𝐞𝐝 𝐁𝐢𝐨𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐔𝐬𝐢𝐧𝐠 𝐄𝐯𝐨𝐑𝐚𝐧𝐤! Researchers at The University of Texas at Austin have unveiled EvoRank, a groundbreaking AI model designed to transform protein engineering and drug development. This innovative tool leverages nature's evolutionary processes to design more effective and less toxic protein-based therapies and vaccines. 🔍 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐄𝐯𝐨𝐑𝐚𝐧𝐤 EvoRank harnesses the vast diversity of naturally evolved proteins, studying millions of variations across different organisms. By analyzing these patterns, it identifies beneficial mutations, guiding scientists in designing proteins with enhanced stability and functionality. This process provides a road map for developing novel therapeutics and vaccines. 💡 𝐖𝐡𝐲 𝐈𝐭 𝐌𝐚𝐭𝐭𝐞𝐫𝐬: Traditional protein engineering relies heavily on time-consuming trial and error. EvoRank accelerates this process by predicting optimal mutations, potentially shaving years off drug development timelines and significantly reducing costs. With a global protein therapeutics market projected to grow by 50% in the next decade, the impact could be enormous! 🔬 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬: Supported by a $2.5 million grant, the team is already collaborating with vaccine developers to apply EvoRank in the fight against herpesviruses. Early results show promise in stabilizing viral proteins in ways that were previously unimaginable. 🚀 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐏𝐫𝐨𝐭𝐞𝐢𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠:   The team is now working on an advanced "multicolumn" version of EvoRank to evaluate the effects of multiple mutations simultaneously. This will further enhance our understanding of how proteins function and evolve, opening new avenues for innovation in biotechnology. The journey from nature's blueprint to therapeutic innovation has never been more exciting! 🌟 📜Paper: https://lnkd.in/d_3aVSxv At Medvolt, we harness the power of generative AI, alongside other large language models (LLMs) and deep learning technologies, through our innovative platform 𝐌𝐞𝐝𝐆𝐫𝐚𝐩𝐡. 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. 𝐖𝐞'𝐫𝐞 𝐡𝐞𝐫𝐞 𝐭𝐨 𝐚𝐬𝐬𝐢𝐬𝐭 𝐲𝐨𝐮 𝐚𝐧𝐝 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐜𝐥𝐚𝐫𝐢𝐭𝐲. Visit our website: https://www.medvolt.ai or reach out to us via email: [email protected] Follow Medvolt for more #AI #Biotechnology #ProteinEngineering #EvoRank #UTAustin #DrugDevelopment #Innovation #Science #drugdiscovery

𝐓𝐚𝐫𝐠𝐞𝐭𝐢𝐧𝐠 𝐌𝐀𝐓𝟐𝐀: 𝐀 𝐍𝐞𝐰 𝐀𝐯𝐞𝐧𝐮𝐞 𝐢𝐧 𝐂𝐚𝐧𝐜𝐞𝐫 𝐓𝐡𝐞𝐫𝐚𝐩𝐲 & 𝐁𝐞𝐲𝐨𝐧𝐝 In a groundbreaking study, researchers have uncovered the crucial role of MAT2A, an enzyme deeply involved in cellular metabolism and gene expression, as a potential therapeutic target in cancer treatment. 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐌𝐀𝐓𝟐𝐀? MAT2A regulates the synthesis of S-adenosylmethionine (SAM), a key molecule that influences gene expression, protein function, and cellular metabolism. Dysregulation of MAT2A has been linked to various cancers, making it a promising target for new cancer therapies. 𝐊𝐞𝐲 𝐅𝐢𝐧𝐝𝐢𝐧𝐠𝐬: - Synthetic Lethality: MAT2A inhibition shows synthetic lethality with MTAP deficiency, a genetic alteration found in ~15% of all cancers. This opens up new treatment opportunities, particularly for aggressive tumors like glioblastoma and pancreatic cancer. - Drug Development: Several MAT2A inhibitors are being developed, including IDE-397 and AMG193, currently in clinical trials. These inhibitors have shown promise in preclinical models, paving the way for more targeted cancer treatments. 𝐁𝐞𝐲𝐨𝐧𝐝 𝐂𝐚𝐧𝐜𝐞𝐫: MAT2A's role extends beyond oncology. Studies indicate that inhibiting MAT2A can restore metabolism and improve muscle function in aged skeletal muscle, suggesting potential benefits for age-related conditions like sarcopenia. 𝐅𝐮𝐭𝐮𝐫𝐞 𝐃𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧𝐬: The path ahead involves refining these inhibitors to minimize side effects and enhance efficacy. The potential to expand MAT2A inhibition to non-cancerous diseases is a thrilling prospect, hinting at broader therapeutic applications. 𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧: Targeting MAT2A could revolutionize cancer treatment and potentially offer new hope for age-related diseases. Continued research and clinical trials are essential to unlocking the full potential of this therapeutic strategy. Follow Medvolt for more ✨ #CancerResearch #MAT2A #DrugDiscovery #PrecisionMedicine #Oncology #Biotechnology

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠 𝐃𝐫𝐮𝐠𝐒𝐲𝐧𝐭𝐡𝐌𝐂: 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐃𝐫𝐮𝐠 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 𝐰𝐢𝐭𝐡 𝐌𝐨𝐧𝐭𝐞 𝐂𝐚𝐫𝐥𝐨 𝐒𝐞𝐚𝐫𝐜𝐡 The landscape of drug discovery is changing rapidly with the introduction of DrugSynthMC, a novel algorithm that leverages Monte Carlo Search to generate drug-like molecules in a robust and interpretable manner. 💡𝐖𝐡𝐚𝐭 𝐢𝐬 𝐃𝐫𝐮𝐠𝐒𝐲𝐧𝐭𝐡𝐌𝐂? DrugSynthMC stands out by producing drug-like compounds using an atom-based search model, generating molecules as SMILES, character by character. Unlike conventional methods, it requires no prior training datasets, making it highly versatile and easy to explain. 🔍 𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬: - Rapid Generation: Capable of creating thousands of novel, drug-like molecules per second. - High Synthesizability: Generates compounds with a high probability of being synthesizable. - Compliance with Drug Properties: Designed molecules follow Lipinski’s “rule of 5,” ensuring drug-like properties. 🧬 𝐖𝐡𝐲 𝐈𝐭 𝐌𝐚𝐭𝐭𝐞𝐫𝐬: Most current deep learning methods struggle with the synthesizability of generated molecules. DrugSynthMC overcomes this hurdle, offering a more practical approach to expanding chemical libraries without sacrificing chemical diversity or novelty. 🌐 𝐕𝐞𝐫𝐬𝐚𝐭𝐢𝐥𝐞 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬: The flexibility of DrugSynthMC means it can be fine-tuned for various targets, paving the way for more efficient and targeted drug discovery processes. This is a significant step forward in computational chemistry and medicinal research. 🔗 Explore more about DrugSynthMC: [GitHub Repository](https://lnkd.in/dmrQeGrd) At Medvolt, we harness the power of generative AI, alongside other large language models (LLMs) and deep learning technologies, through our innovative platform 𝐌𝐞𝐝𝐆𝐫𝐚𝐩𝐡. 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. 𝐖𝐞'𝐫𝐞 𝐡𝐞𝐫𝐞 𝐭𝐨 𝐚𝐬𝐬𝐢𝐬𝐭 𝐲𝐨𝐮 𝐚𝐧𝐝 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐜𝐥𝐚𝐫𝐢𝐭𝐲. Visit our website: https://www.medvolt.ai or reach out to us via email: [email protected] Follow Medvolt for more #DrugDiscovery #AIinPharma #ComputationalChemistry #AIResearch #Pharmaceuticals

🚨 𝐁𝐫𝐞𝐚𝐤𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐢𝐧 𝐑𝐚𝐫𝐞 𝐃𝐢𝐬𝐞𝐚𝐬𝐞 𝐓𝐫𝐞𝐚𝐭𝐦𝐞𝐧𝐭!🚨 A clinical trial has shown that the cancer drug pomalidomide effectively treats hereditary hemorrhagic telangiectasia (HHT), a rare bleeding disorder affecting 1 in 5,000 people worldwide. The trial was halted early after significant reductions in nosebleeds and improved quality of life for patients. This discovery, supported by the NIH, could offer new hope for those living with this life-threatening condition. At Medvolt, we harness the power of generative AI, alongside other large language models (LLMs) and deep learning technologies, through our innovative platform 𝐌𝐞𝐝𝐆𝐫𝐚𝐩𝐡. 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. 𝐖𝐞'𝐫𝐞 𝐡𝐞𝐫𝐞 𝐭𝐨 𝐚𝐬𝐬𝐢𝐬𝐭 𝐲𝐨𝐮 𝐚𝐧𝐝 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐜𝐥𝐚𝐫𝐢𝐭𝐲. Visit our website: https://www.medvolt.ai or reach out to us via email: [email protected] Follow Medvolt for more. #DrugDiscovery #RareDiseases #ClinicalTrials #HealthcareInnovation #medvolt