Greenstone Biosciences’ Post

Here's another example of AI driving innovation in drug discovery. Scientists leveraged GenAI to process data points focused around deep feature synthesis, causality inference, and de novo pathway reconstruction to develop a potential target list for pulmonary fibrosis. From this list, millions of data points were analyzed from sources such as publications, grants, patents, and clinical trial databases. This generated a target: TNIK - a kinase that regulates fibrotic growth. Next up was innovating an inhibitory compound, and Insilico Medicine’s generative chemistry engine went to work on a dataset to produce a lead candidate. 18 months from target discovery to lead candidate selection! https://lnkd.in/d-UxhMwb

DeepCure Selects First AI-Generated Drug Candidate, DC-9476, for Clinical Trials Learn more & get our take 👇 https://lnkd.in/gXXmmyPf “New therapeutics such as DC-9476 that have a novel mechanism to address simultaneously multiple pathways while also having an excellent safety profile, are extremely promising for the field.” — Professor Francesco Del Galdo, M.D., Ph.D., at University of Leeds “We’re excited to announce our first AI-generated candidate, which we plan to advance into clinical trials next year. This validates our generative AI and physics-based drug discovery engine.” — Kfir Schreiber, CEO & Co-Founder at DeepCure #drugdiscovery #ai #SoHCNews

🔬 Exciting advancements in drug target identification are on the horizon! 🧪 A recent article published in Clinical Pharmacology & Therapeutics discusses the future application of Machine Learning (ML) in drug target identification. By taking into account multi-Omics data for causality, reversibility, and druggability, in addition to leveraging structural biology knowledge alongside toxicity prediction, ML is poised to bring interesting advancements in the field. If you're interested in learning more about the cutting-edge research and the perspective, check out the article here: https://lnkd.in/dDcACxpE

Discover our fully integrated Car-T cells protocol ! At Parean Biotechnologies, we've developed tailored wet lab and data science workflows, designed specifically for cell therapy developers. We are able to detect, select, isolate and fully characterize cell therapies, before and after infusion in patient. We're one of the few service providers in the EU offering a fully integrated solution, combining flow cytometry, cell sorting and single cell omics. This unique approach drastically enhance data quality and accelerates your program from discovery to clinical trial success. Key advantages for cell therapy developers: -> In Preclinical phases: optimize your innovation, strengthen your research, and prepare for a successful IND submission -> In Clinical phases: monitor treatment efficacy, gain critical patient insights, support regulatory submissions and reduce risks in your clinical plan. Ready to learn more ? check out our process here ! Valentin Quiniou Pierre Barennes Hang Phuong PHAM 10x Genomics

Exciting news 💚 ! Our latest publication in Nature Biotechnology unveils groundbreaking advancements: 1. We harnessed AI to pinpoint TNIK as a novel anti-fibrotic target 2. Conducted a comprehensive "hallmarks of aging assessment," revealing TNIK's notable scores across multiple hallmarks 3. Leveraged Chemistry42, our generative AI for chemistry, to craft a novel molecule with optimal safety and efficacy 4. Executed extensive in vitro and in vivo experiments, identifying three promising preclinical candidates for lung and kidney fibrosis. 5. Successfully completed a clinical safety trial in humans. Explore the details below, and for further insights, delve into the full paper https://lnkd.in/dKsHTm_Z

A recent Nature paper demonstrated how machine learning can predict and identify small molecule ice recrystallisation inhibitors (IRIs), crucial for protecting cells during freezing. This breakthrough paves the way for innovative cryoprotectants, significantly enhancing cold chain solutions. Imagine predictive AI algorithms that can not only tailor cryopreservation protocols but also rapidly identify novel cryoprotectants, ensuring higher cell viability and functionality—especially for sensitive cell therapies.💡❄️ #Cryopreservation #CellTherapies #Machinelearning https://lnkd.in/dmeSHYzD

During the end of my recruitment career I was working with a lot of biotech co.'s on the west coast who were involved in Ai aided drug discovery. This was very interesting at the time but now I am studying Ai/ML at Oxford and I've gotten an entirely new perspective. Insilico Medicine, a pioneer in AI-driven drug discovery, has revealed its process for developing an experimental drug targeting idiopathic pulmonary fibrosis (IPF). Target Identification: Insilico used their AI tool called PandaOmics to find a possible target for treating IPF. Selection: They then used another AI tool called Chemistry42 to design and test different drugs. This story serves as a testament to the transformative potential of AI in drug discovery, propelling us into an exciting era of innovation and possibility. Seems to be very exciting times. #ai #drugdiscovery #ml

🤯 Protein-making AI in drug discovery! 🧬💊 From cancer to COVID, new treatments are on the horizon. 🤫Check this out: : [ https://lnkd.in/due2mEBz ] #AI #DrugDiscovery #Biotech #FutureofMedicine #HealthTech 🙌 What are your thoughts? Share below! 👇

George Church's latest venture, GC Therapeutics, is tackling tough medical challenges with a fresh approach to cell therapy. Their "plug-and-play" tech aims to deliver off-the-shelf iPSC-based medicines up to 100 times faster than conventional methods. They're engineering "SuperCells" with improved or new functions, potentially reducing the number of cells needed for treatment. I can't wait to see how this plays out in #clinicaltrials and the broader #biotech landscape—and how it impacts #investor sentiment in the industry! https://loom.ly/nUjOSr8

✨Introducing TAmiRNA´s small RNA-sequencing-based molecular characterization of EVs. Since we launched the revolutionary EVscale™️ - Extracellular Vesicles at scale – platform, which was developed in partnership between Phoenestra GmbH, Evercyte GmbH, and TAmiRNA GmbH, we are highlighting key components and features of this platform in a series of posts, explaining how this cutting-edge platform is transforming the way EV therapeutics are produced: TAmiRNA is an expert in RNA biomarker discovery and validation. Under the lead of Kseniya Khamina-Kotisch, PhD and Andreas Diendorfer it has developed a small RNA-seq workflow for absolute quantification of microRNAs that are carried by EVs. The platform, which is called miND®, is a game changer in the identification of the molecular constituents of EVs and understanding on therapeutic potency of these complex products. By combining miRNomics with transcriptomic and proteomic analyses, TAmiRNA supports EVscale™ by decoding the molecular signature of EVs and identifying key cargo that can be utilized for the quality control as well as for further engineering of EV potency. Browse TAmiRNA´s offerings for EV characterization at https://lnkd.in/dTAfRmvi   🚀 Stay tuned for further posts on our transformative journey towards scalable and efficient EV production for therapeutic purposes. #ExtracellularVesicles #EVscale #microRNA #sequencing #biomarker