Explore our latest video series, "Amplifying the Future of Drug Discovery," shedding light on innovative technologies like LENSᵃⁱ™. These advancements aim to enhance efficiency, and expedite the development of new therapeutic options.   With LENSᵃⁱ, data exploration is dynamic, built to generate remarkable insights, not only for accelerating drug discovery but also potentially creating safer, more effective treatments.   Watch the first video in the series for a closer look into the future: https://lnkd.in/ezqcCpk7   #AI #Antibodies #BioTech #DrugDiscovery #LensAI IPA (ImmunoPrecise Antibodies)

The fusion of artificial intelligence and drug development signals a new chapter of innovation, characterized by unprecedented speed and efficiency. Genentech's groundbreaking ulcerative colitis project, completed in a fraction of the usual time, exemplifies AI's transformative impact. However, amidst the excitement, questions linger about AI's true efficacy in improving patient outcomes. While AI offers unprecedented speed and scale in certain aspects of drug discovery, it's essential to ensure that medications developed through AI are genuinely effective for patients, with human expertise remaining indispensable in decision-making processes. As we navigate this AI-driven frontier, it's crucial to strike a balance between leveraging technology's capabilities and preserving the irreplaceable value of human knowledge. The future of drug discovery is undoubtedly exciting, but it's imperative to approach it with a critical eye and a commitment to advancing patient care. #AI #DrugDiscovery #Healthcare #Innovation #Biotech

Quality content. Flexible data models. Power your LLM with the content you already trust. Elsevier journals. The overall innovation picture for you and Elsevier? see Mirit’s post below! 💡

Big pharma is buzzing about AI's potential to revolutionize drug discovery. Is it all hype, or are we on the cusp of a medical breakthrough? This interview dives into the current state of AI in pharma research, exploring the challenges and the promise it holds for the future of medicine.

Drug development, from discovery to market, costs about $1.8 billion per “new molecular entity,” according to a study published in Nature. Discover how GenAI can reduce the cost of drug discovery and accelerate time to adoption: https://gtnr.it/3rvxNb6 #GartnerHT #Technology #HighTech #AI

🚀 Harnessing AI for Pharma/Biotech Breakthroughs! 🌟 Dive into the future with us! Our latest white paper on AI is here to revolutionize your approach to drug discovery. 🧬💡 Why AI? Because it transforms raw data into lifesaving solutions. - 🎯 Identification: AI spots therapeutic targets hidden in complex biological data. - 💊 Drug Design: Generate molecules with the potential to heal. - 🔬 Discovery: Uncover biomarkers that steer towards precise treatments. - 🤖 Clinical Trial Optimization: AI designs better trials faster. - 🧪 Predictive Models: Anticipate drug effects and optimize therapy strategies. Unlock the potential of your data. Let AI take your research from the bench to the bedside swiftly and effectively! 🔗 Interested? Download the whitepaper below and dive into our detailed guide on leveraging AI in drug discovery! https://lnkd.in/gWKuAJZp #Pharma #Biotech #ArtificialIntelligence #DrugDiscovery #RevvitySignals

Big pharma is buzzing about AI's potential to revolutionize drug discovery. Is it all hype, or are we on the cusp of a medical breakthrough? This interview dives into the current state of AI in pharma research, exploring the challenges and the promise it holds for the future of medicine. https://lnkd.in/g9yYfUA4

Big pharma is buzzing about AI's potential to revolutionize drug discovery. Is it all hype, or are we on the cusp of a medical breakthrough? This interview dives into the current state of AI in pharma research, exploring the challenges and the promise it holds for the future of medicine. https://lnkd.in/gAqitb6u

𝗨𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗣𝗿𝗼𝘁𝗲𝗶𝗻-𝗟𝗶𝗴𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗹𝗲𝘅 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 In the realm of drug discovery, the ability to accurately predict protein-ligand complexes from sequence information is a game changer. 𝗨𝗺𝗼𝗹, a new AI system, promises to overcome the limitations of classical docking methods by predicting fully flexible all-atom structures without needing high-quality protein crystal structures. This advancement brings us closer to efficient AI-driven drug discovery. Umol has demonstrated significant potential in addressing the challenges of protein-ligand docking, offering a solution that does not rely on native protein structures. By utilizing sequence data and ligand 𝗦𝗠𝗜𝗟𝗘𝗦, Umol produces 3D structures that incorporate the necessary flexibility of proteins and ligands. This method shows a success rate of 18% without pocket information, which increases to 45% when pocket data is included, making it a robust tool for predicting complex structures. For biotech and pharma companies, Umol offers a more streamlined approach to identifying potential drug candidates, especially in scenarios where experimental protein structures are unavailable. This could revolutionize the early stages of drug development, significantly reducing the time and cost associated with experimental validation. Given these advancements, how do you foresee integrating AI-based systems like Umol into your drug discovery workflows? What other challenges do you think need to be addressed to fully leverage AI in this field? 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: contact@medvolt.ai Follow Medvolt for more such updates #DrugDiscovery #AI #Biotech #Pharma #ProteinLigandDocking

Big pharma is buzzing about AI's potential to revolutionize drug discovery. Is it all hype, or are we on the cusp of a medical breakthrough? This interview dives into the current state of AI in pharma research, exploring the challenges and the promise it holds for the future of medicine. https://lnkd.in/g-NsxPp3