Pushpendra Kumar’s Post

Welcome to 𝐓𝐡𝐞 𝐌𝐨𝐥𝐞𝐜𝐮𝐥𝐞 𝐀𝐈 𝐎𝐝𝐲𝐬𝐬𝐞𝐲! Today, we delve into an overview of 𝐡𝐨𝐰 𝐰𝐞 𝐚𝐫𝐞 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐝𝐫𝐮𝐠 𝐝𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 𝐛𝐲 𝐥𝐞𝐯𝐞𝐫𝐚𝐠𝐢𝐧𝐠 𝐀𝐈. 𝐀𝐧𝐭𝐢𝐛𝐨𝐝𝐲 𝐃𝐞𝐬𝐢𝐠𝐧: Drug design remains a challenging endeavor due to the complexity of the involved design space. Artificial Intelligence provides a unique shot at the problem due to its capability of enabling efficient horizon exploration. We are applying our AI capabilities in 𝐬𝐜𝐫𝐞𝐞𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐞 𝐧𝐨𝐯𝐨 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐚𝐧𝐭𝐢𝐛𝐨𝐝𝐢𝐞𝐬 and small molecule drugs against challenging targets such as intrinsically disordered pathogenic proteoforms involved in Parkinson’s disease. 𝐁𝐢𝐨𝐩𝐡𝐲𝐬𝐢𝐜𝐬 𝐗 𝐃𝐞𝐞𝐩𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Deep Learning has revolutionized many fields but still remains in the nascent stages for drug design. Models like AlphaFold provide a strong foundation for the field but end-to-end solutions need to go far beyond. Hence, 𝐰𝐞 𝐝𝐞𝐯𝐞𝐥𝐨𝐩 𝐧𝐨𝐯𝐞𝐥 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞𝐬, built using biophysics principles at the core. 𝐌𝐮𝐥𝐭𝐢𝐝𝐢𝐬𝐜𝐢𝐩𝐥𝐢𝐧𝐚𝐫𝐲 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞: Our team consists of an ideal mix of members having strong experience in 𝐛𝐨𝐭𝐡 𝐭𝐡𝐞 𝐟𝐢𝐞𝐥𝐝𝐬 𝐨𝐟 𝐛𝐢𝐨𝐩𝐡𝐲𝐬𝐢𝐜𝐬 𝐚𝐧𝐝 𝐀𝐈. We strongly believe in the importance of a multidisciplinary team for tackling the problem. #deeplearning #drugdiscovery #ai #pharma #startup #machinelearning

In the latest news related to harnessing AI and leveraging predictive sciences for rapid drug discovery, VantAI has announced a partnership with Bristol Myers Squibb to expedite the development of new molecular glue therapies. Through this collaboration, VantAI's state-of-the-art generative AI and geometric deep learning algorithms will be combined with Bristol Myers Squibb's well-known targeted protein degradation capabilities, paving the way for major improvements in the creation of small molecule therapeutics. Despite providing a revolutionary method of treating a wide range of illnesses, molecular glues have historically presented formidable obstacles to development. VantAI's creative application of AI aims to get over these obstacles by creating molecular glues that could transform proximity modulation as a therapeutic approach. It does this by utilizing its generative AI platform. Daniel Joseph Price, Mitali Bhagwat, Leydi Nino More details in the article - https://lnkd.in/g_6V-HrR #AI #artificialintelligence #drugdiscovery #molecularglues #targetedproteindegradation

AI in Healthcare: Demis Hassabis on AlphaFold 3 and the Digital Biology Era In a compelling Bloomberg interview on May 8th, DeepMind's CEO Demis Hassabis shared his insights into the future of AI. He believes that AI is "overhyped in the short term but probably underestimated in the long term." Over the next couple of years, we can expect to see AI exhibiting "more agent-like behavior," not just answering questions but also planning, acting, and achieving goals. Discussing the current challenges, including the significant energy and financial resources required for further AI development, Hassabis is optimistic. He asserts that the potential benefits, particularly in drug design and fusion energy, will "far outweigh" these hurdles. Within this broader context, Hassabis highlighted the pivotal role AI could play in humanity's future through its application in bioinformatics and drug design. His optimism is backed by developments at Isomorphic Labs—a #DigitalBiology company linked to Google and DeepMind—which recently launched #AlphaFold 3. This iteration of AlphaFold goes beyond predicting protein structures—a capability that its predecessor, AlphaFold 2, used to already boost biology once. It is now capable, according to Hassabis, of determining the structure of principally all molecules and their interactions. If this were really the case, this advancement would be key to understanding the "dynamic picture" of life’s molecular processes. Hassabis envisions Isomorphic Labs not only becoming a multi-100-billion-dollar enterprise but also delivering substantial societal and humanitarian benefits. Watch the Interview:

AI may be a cool tool, but it's a tool nonetheless, and not a panacea that's going to solve every single problem under the sun. It works well in areas where there's a significant amount of data associated with it; not so much in areas where there is not. So, what does this mean in #pharma? Atomic AI founder and CEO Raphael Townshend recently spoke to PharmTech about how #AI and #machinelearning can be best leveraged in #drugdiscovery, and where there are still gaps. Additional datasets are needed to address these limitations and push progress forward into the #drugdevelopment stages as well. 📺 Watch the interview: https://lnkd.in/engBrRYf 🕵🏽♀️ Learn how Atomic AI is generating RNA structural datasets and integrating machine learning foundation models with large-scale, in-house experimental wet-lab biology: https://lnkd.in/eTrdsXrw

🚀 Exciting Breakthrough in Xenotransplantation! 🐖➡️🧠 Hey Tech Wizards and AI Aficionados! Imagine a world where the shortage of human organs for transplants is a thing of the past. Well, we just inched a step closer! A groundbreaking medical experiment just showed us a glimpse of that future. A team of scientists hooked up a brain-dead patient to a gene-edited pig liver for a full three days — and it worked seamlessly! 🤯 Now, let's break this down — this isn't just about a pig liver keeping a human alive. It's about cracking the code of interspecies organ support. Gene editing is the magic wand here, helping to overcome the immense rejection issues that used to make such an idea a mere fantasy. As someone deeply passionate about technology's role in reshaping our world, this opens up a torrent of questions: How will AI contribute to the precision needed in gene editing? Could machine learning help predict organ compatibility or even enhance organ function? And while we're marveling at this, let's remember the ethical Pavlov's bell this rings. With AI arm-in-arm with biotech, are we ready to navigate the new moral mazes ahead? What's your take on this — a leap for medical science or a complex ethical puzzle? Drop your thoughts! 🤔✨ Let's keep pushing the boundaries and rewriting what's possible. For a deep dive into this stunning development, check out the full article from MIT Technology Review: https://lnkd.in/dptW2hmt And if you live for such groundbreaking content, smash that FOLLOW and LIKE button to not miss a beat in the tech and AI revolution! #Xenotransplantation #FutureOfMedicine #TechForGood #AI Remember, the future is not just what happens to us. It's what we create. Let's build it together. 🌐💪

🧬 Breakthrough in AI-Driven Drug Discovery: AlphaFold 3 Unveiled! 🚀 Google DeepMind and Isomorphic Labs have introduced AlphaFold 3, a game-changing AI that models DNA, RNA, and facilitates drug development. Here's why it's revolutionary: 🔬 50% more accurate than traditional methods in predicting biomolecular interactions 🧪 No pre-existing structural data needed 🏥 Accelerates research in medicine, agriculture, and materials science 💊 Streamlines drug development processes 🖥️ Accessible via AlphaFold Server for scientists worldwide At Allmatics, we're thrilled to see AI advancements in #healthtech. AlphaFold 3 represents a quantum leap in the industry, potentially saving millions of research years and drastically reducing costs in structural biology. This evolution in health-related #AI is incredibly inspiring. We're excited to continue our #development at the intersection of AI/ML/DS and Healthtech. Want to learn more about AlphaFold 3 and our insights on AI in #healthcare? Check out the links below! Google DeepMind blog: https://lnkd.in/etiXfCw8 AI + Healthcare Integration: https://lnkd.in/eCnkZgdK #AIinHealthcare #DrugDiscovery #AlphaFold3 #GoogleDeepMind

Exciting AI-Driven Innovation for Drug Discovery at NLSD: I’m thrilled to introduce Cortex Discovery's cutting-edge deep learning technology, which predicts molecular properties with accuracy that rivals experimental methods. Validated across multiple therapeutic areas, this innovation has led to new preclinical leads at negligible cost. We offer a wide range of services including: 🔹 Virtual High Throughput Screening 🔹 ADMET & off-target predictions 🔹 Virtual hit analog identification 🔹 De novo compound creation Our extensive libraries—ranging from FDA-approved to novel compounds—enable fast compound ordering. We specialize in seamless CRO collaborations, and can handle hit discovery and lead optimization in a single process. Next-gen Molecular Docking: Our new prototype, combining deep neural networks and molecular simulations (ultimately reaching the quantum level), allows for the fast exploration of new targets even without activity data, delivering unprecedented prediction accuracy—1000x faster than available alternatives. We are also partnering with leading labs to advance compounds for age-related disorders and life extension. Notably, we developed the first AI-discovered drug that extended lifespan in C. elegans by 33%. I would be happy to meet and discuss collaboration opportunities at NLSD! #AI #DrugDiscovery #virtualHTS #VirtualADMET #LifeExtension #Oncology #DeepLearning #Biotech #NLSD2024 #CortexDiscovery

Google DeepMind and Isomorphic Labs are revolutionizing biology and drug discovery with AI breakthroughs like AlphaFold 3, drastically accelerating protein research. 🧬 AlphaFold technology: By predicting protein structures in minutes, this AI model is unlocking new possibilities for scientific research and drug development. 💡 Pharmaceutical impact: Understanding protein interactions enhances drug targeting, reduces side effects, and opens new avenues for creating therapies. 🛠️ Reliability challenges: Ensuring AI reliability and safety remains critical as these tools expand in medicine and beyond. 🚀 Global competition: Other innovators like Meta and Genomenon are racing to develop similar models, signaling fierce competition and rapid advancements. #AIinHealthcare #DrugDiscovery #BiotechInnovation 🌍 This leap in protein-folding tech is helping solve complex scientific problems faster than ever before. 🧠 DeepMind's AI advancements are setting a high standard for safety and accuracy in healthcare technologies. https://lnkd.in/gy3V3ymP

At Medvolt, we harness the power of deep learning and AI-assisted in-silico techniques to revolutionize drug discovery. Our platform leverages specially designed deep learning models to process extensive datasets, uncover patterns, and predict drug-protein interactions with precision. Utilizing DeepMind's AlphaFold, we predict the 3D structures of proteins from amino acid sequences, a process enhanced by convolutional neural networks and attention mechanisms for accurate structure predictions and identification of binding sites. This approach allows us to analyze proteins even without prior structural data, employing algorithms for molecular docking and computational scanning to identify potential drug binding sites based on geometric compatibility and energy profiles. Our innovative use of technology facilitates the discovery of effective drugs by understanding protein-ligand interactions at a molecular level. Stay tuned as we continue to pioneer changes and set new standards! 𝐅𝐞𝐞𝐥 𝐟𝐫𝐞𝐞 𝐭𝐨 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐚𝐧𝐲 𝐢𝐧𝐪𝐮𝐢𝐫𝐢𝐞𝐬 𝐨𝐫 𝐫𝐞𝐪𝐮𝐢𝐫𝐞 𝐚 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧. 𝐖𝐞'𝐫𝐞 𝐡𝐞𝐫𝐞 𝐭𝐨 𝐚𝐬𝐬𝐢𝐬𝐭 𝐲𝐨𝐮 𝐚𝐧𝐝 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐜𝐥𝐚𝐫𝐢𝐭𝐲. Email: contact@medvolt.ai Website: https://www.medvolt.ai #AI #ML #Drug #Discovery #Innovation #Pharmaceutical #Development #drugdiscovery #llm #oncology

I have been working on a tumor detection model using machine learning, which merges the fields of biology and AI. This project required an understanding of several biological concepts that were outside my expertise. Thankfully, Amna Khan provided invaluable assistance in guiding me through the biological aspects necessary for developing the model. The result is a system capable of detecting not only brain tumors but also other types of tumors, significantly enhancing diagnostic accuracy and efficiency in the healthcare field. Looking ahead, I aim to improve this model by integrating additional features, such as patient history analysis, genetic data interpretation, and real-time imaging capabilities, which can further enhance diagnostic precision. By continuing to fuse technology with biological insights, this solution has the potential to revolutionize early detection, streamline medical workflows, and ultimately save lives by enabling timely and accurate diagnoses. I look forward to exploring how these advancements can transform healthcare, making it more efficient and responsive to patient needs. #ML #AI #biotech