908 Devices’ Post

A good listen with our own Kevin J. Knopp as guest in the pharmaphorum Podcast!

Did you know AI is revolutionizing drug discovery? 🧬 𝐍𝐕𝐈𝐃𝐈𝐀, the tech giant, is using AI to transform pharmaceutical research! 🔬 𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐚𝐭'𝐬 𝐞𝐱𝐜𝐢𝐭𝐢𝐧𝐠 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞𝐢𝐫 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡: 🔹 New generative virtual screening NIM Blueprint 🔹 Powerful AI microservices: 𝐀𝐥𝐩𝐡𝐚𝐅𝐨𝐥𝐝2, 𝐃𝐢𝐟𝐟𝐝𝐨𝐜𝐤, 𝐚𝐧𝐝 𝐌𝐨𝐥𝐌𝐈𝐌 🔹 Predicts protein structures and molecular interactions 🔹 Optimizes molecule properties for better drug candidates 𝐖𝐡𝐲 𝐈𝐭 𝐌𝐚𝐭𝐭𝐞𝐫𝐬: 🔸 Accelerates identification of potential drug candidates 🔸 Reduces time and cost of traditional screening methods 🔸 Enhances efficiency of the entire drug discovery pipeline Follow us for more updates on AI. #aidrugdiscovery #biotech #nvidia #aiinnovation #technews

Thinking about deploying an LLM for use in pharma or biotech? Check out a webinar from our very own Swetabh Pathak on helpful considerations and useful tools 🤔 https://lnkd.in/eW2f4Gbt

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

How is AI currently reshaping the pharmaceutical landscape?     Some of the ways AI is making an impact are:  • Enhanced drug target identification: AI algorithms can analyse vast datasets to identify novel drug targets with greater accuracy and efficiency.  • Streamlined pre-clinical testing: AI can be used to design and conduct virtual experiments, reducing the need for animal testing and accelerating the development process.     AI plays a key role when developing effective discovery computational models, and our data team has identified 50+ pre-clinical CROs that offer computational chemistry and bioinformatics services.     Stay tuned for our featured companies within the space, including Luo Automation, one of our Disruptor Watchlist “Start Ups to watch”. 📈    #AIinPharma #Pharma #AIDrugDiscovery #ComputationalChemistry 

#AI_in_Pharma_and_Biotech Market In-depth Analysis Report by Size, Share, Regional Analysis and Global Forecast to 2032. >> https://lnkd.in/dBUiqhAz AI in #pharma and biotech uses artificial #intelligence to enhance various aspects of #drug discovery, development, and #manufacturing. AI algorithms analyze vast #datasets to identify potential drug #candidates, predict #clinical trial outcomes, and optimize #production processes. This #technology accelerates research #timelines, reduces costs, and increases the accuracy of #predictive models. BenevolentAI Insilico Medicine Recursion Atomwise Cloud Pharmaceuticals, Inc. Deep Genomics Exscientia Schrödinger #healthcareindustry #pharmaceuticalindustry #healthcareresearch #biotechnology #artificialintelligence #manufacturing #clinicaltrial #biotech 

Learn how knowledge graphs & LLMs can help you search and discover hidden causal relations 🔬🧬 Advancing drug discovery or biomarker identification in pharma R&D is challenging when critical insights are spread across internal, public, and commercial databases. ⚡️Join our upcoming webinar with metaphacts GmbH where we’ll explore how #AI & knowledge graphs are transforming pharma research. One use case we’ll focus on is scientific validation, showing how LLMs can precisely identify causal relationships from unstructured full text, which can then be used to enrich established knowledge graphs like Open Targets and annotate scientific databases like Dimensions. 🗓️🕐 13th November 2024, 4pm GMT | 11am ET 🔗 Secure your spot: https://ow.ly/jKkp50TQRES Digital Science #Pharma #ResearchInnovation #Biotech #KnowledgeGraphs

AI can be used in all aspects of drug development – from discovering biological targets, through developing chemical compounds, to conducting clinical trials. As we expected, this year at JP Morgan's Healthcare Conference, the AI theme was pervasive in almost every presentation, with key players presenting impressive new capabilities relevant to every stage of the value chain. Where does CytoReason fit into this growing trend? We use AI to model disease biology and drug effects. Our Computational Disease Models enable data integration across-the-board for decision making. The main goal is to help pharma enterprises improve probability of phase 2 success. Link to articles in comment below👇 #pharma #computationalbiology #biotech #drugdevelopment #jpm2024

Poll results are in! What’s the next big breakthrough in biotech? With “AI in Drug Discovery” taking the lead, it's clear that many of us are excited about the potential of artificial intelligence to revolutionize how we discover and develop therapeutics. AI/ML’s ability to analyze vast datasets and uncover patterns beyond human reach promises to make drug discovery faster, safer, and more cost-effective. So what’s next? We’re interested to hear which specific applications of AI in drug discovery excite you most. How do you envision these breakthroughs impacting biotech in the next decade? Explore Wheeler Bio, Inc.’s tech-forward approach: https://lnkd.in/e_PTWteS #biotechnlogy #biotech #pharmaindustry #drugdiscovery

📌 PharmTech magazine features Syngene's strategic insights on enhancing formulation efficiency.   Sibaji Biswas, Syngene's ED and CFO, shares insights on how machine learning (ML) and artificial intelligence (AI) have the potential to provide the biopharmaceutical industry with significant opportunities to enhance the formulation process and avoid potential failures.   Read the full article here 👉 https://lnkd.in/gCdHRQ_N #Syngene #Pharmtech