John Guanjing Zhang’s Post

Delighted to complete the course in Artificial Intelligence in Pharma and Biotech at MIT Sloan. This is a fantastic course providing insights into how AI and machine learning can be applied in pharma, biotech and life sciences organisations. I had the pleasure of learning from many of MIT Sloan leading professors and industry contributors. #MITSloan #AI #Pharma #Biotech #ContinousLearning #MITSloanSchoolofManagement

The potential for AI to increase the efficiency of biotech research is immense—from speeding up drug discovery processes to tailoring medical treatments at a genetic level. In a future where resources are increasingly scarce, I'm keen to see how AI will help us deliver greater benefits to more patients, using fewer resources. Better is the new More. https://lnkd.in/e4pdxjSY Florence Bosco Benoit Macq Eric Schmidt

🚀 SPARROW: Revolutionizing Drug Discovery with AI 🧬 MIT researchers have developed SPARROW, an advanced AI algorithm, to streamline the complex process of drug discovery. With SPARROW around, it sounds like soon we'll have robots discovering new drugs while we're still struggling to find the TV remote. 🔍 SPARROW, which stands for Synthesis Planning and Rewards-based Route Optimization Workflow, automates the selection of optimal molecules by considering the cost of materials, the likelihood of success, and the shared intermediary compounds involved in synthesis. This holistic approach ensures that pharmaceutical companies can test multiple candidates simultaneously, enhancing efficiency and reducing costs. 🔗 The framework integrates data from online repositories and AI tools, comprehensively analyzing molecular design, property prediction, and synthesis planning. SPARROW's versatility extends beyond drug discovery, potentially benefiting agrichemicals and organic electronics. 🧑🔬 Connor Coley, a senior author and assistant professor at MIT, emphasizes the importance of using predictive tools to guide molecular selection, transforming an art into a science. Evaluated through real-world case studies, SPARROW demonstrated its ability to handle hundreds of potential candidates, showcasing its practicality and scalability. 🎯 Supported by DARPA, the Office of Naval Research, and the National Science Foundation, SPARROW represents a significant leap toward fully autonomous drug discovery, promising faster, cost-effective development of new treatments. Finally, an AI that can do more than just suggest movies we’ve already seen! #AI #DrugDiscovery #Innovation #Healthcare #MIT #Pharmaceuticals #Biotech #Research #Science #Technology #FutureTech ------------------------ To know more follow us: LinkedIn: https://lnkd.in/gaAzt-Fi Website: www.aidevsimplified.com ------------------------ Want to improve your business by implementing AI? We can help. Book a free consultation: https://lnkd.in/gE-wFxpR

Being able to predict protein structure is a major win for AI technologies (thanks to AlphaFold and others). What is even more important is being able to computationally build novel proteins that can do useful stuff for us. There are some great and well-funded companies in this space, like Generate:Biomedicines, Absci, ProteinQure, and Cradle. Andrii Buvailo, Ph.D. had a conversation with Stef van Grieken, co-founder and CEO of Cradle, an AI-driven synthetic biology company with a cool platform for designing useful proteins. In the interview, Stef shed light on how cutting-edge AI tech is accelerating the pace of innovation in protein engineering and the intriguing story behind Cradle's partnership with Ginkgo Bioworks, Inc., one of the most sophisticated experimental biology companies out there. Read the interview in our latest newsletter, "Where Tech Meets Bio" (link in the comments). The newsletter also features the following topics: How Does Industry Embrace Organ-on-Chips? A a 2024 Status Update; How Moderna Taps ChatGPT internally; New AI in Drug Discovery Startup Launched with $1 billion: Discussing Xaira Therapeutics's impressive announcement. #biotech #artificialintelligence #deeplearning #tech Image credit: Viraj Mehta, contributor at BiopharmaTrend

The WIPO Patent Landscape Report shows China leading in GenAI patents, with over 38,000 inventions filed between 2014-2023. GenAI technology, like ChatGPT and Google Gemini, is transforming industries. The rise in patents reflects technological advancements. WIPO aims to guide policymakers in shaping GenAI development for societal benefit. Top applicants include Tencent and IBM. China dominates in GenAI patents, focusing on image and video data. Molecule, gene, and protein-based GenAI patents are rapidly growing.

Diving into AI's Role in Biotech Transformation ✨ #ArtificialIntelligence is revolutionising #Biotech, transcending traditional approaches with innovative solutions. The industry is a testament to the boundless possibilities when cutting-edge tech meets biological research. AI's data-crunching capabilities enable us to pinpoint patterns within genetic codes, opening doors to tailored treatments and #PersonalisedMedicine. From drug discovery to early diagnostics, AI is a catalyst for efficiency. Machine learning algorithms sift through vast datasets, deciphering complex biological information at an unprecedented pace. This speeds up the lengthy process of identifying potential therapeutic targets, reducing time and costs significantly. But it's not just about speed; it's about precision. AI in biotech fosters the development of precise diagnostic tools, enhancing the accuracy of predictions and treatments for various diseases. The technology's influence is a beacon of hope for those battling rare conditions, with AI-powered analyses paving the way for customised care plans. #InnovativeHealthcare #BiotechAI #FutureOfMedicine #Biotech #Biopharma

Does it ever feel like AI gets stuck in biotech/pharma? I’ve been mulling over this question for a few weeks. There are no shortage of reports of AI models that have gleaned some fundamental understanding of biology. That’s great. But to translate that into a discovery engine that will benefit patients down the line requires many moving parts to align. Before the AI magic happens at scale, you need the right scientists, data, data access, compute, methods, a committed budget, and leadership buy-in. (Am I missing anything?) None of these elements are particularly out of reach for any organization that tries, but to have them all aligned simultaneously seems like a high bar. Very curious to hear of success stories from my network. Thoughts? #biotech #pharma #compbio #computationalbiology #bioinformatics

At MAbSilico, we strategically apply machine learning to transform biotech discovery. Our approach goes beyond accelerating processes; it delves deeply into exploring new possibilities for effective medications. Join us on our journey as we navigate the future of drug development, where technology meets biology. 🧬 🌐 mabsilico.com #Antibody #AI #ML #DrugDesign #DrugDiscovery

AI is revolutionizing scientific discovery by accelerating research across various fields. Tools like DeepMind's AlphaFold are making it possible to predict the 3D structures of proteins, leading to breakthroughs in drug discovery and material science. AI's ability to process vast amounts of data quickly and accurately is transforming how we understand complex systems, pushing the boundaries of innovation.#AI #ScientificDiscovery #Innovation #Biotech #FutureTech #SecWebXperts