Kurt Soost, CFA’s Post

We have a big announcement! ⤵️ The healthcare industry needs a greater understanding of human genetics. Back in 2010, we embarked on this mission by creating the DISGENET platform to support companies and researchers in leveraging complex biomedical data 🧬 In response to growing demand, we founded our company, MedBioinformatics, in 2020. Today, many years on, we continue to be as motivated as ever, working towards this goal. Which is why we are thrilled to be rebranding! We’ve partnered with krieen, a creative agency with wide experience in healthcare, to create a brand identity and website that reflects our commitment to helping you develop innovative and safer products that prioritize human health and well-being. Stay tuned for updates in the coming weeks as we reveal more about DISGENET, our gene-disease association platform, our new look and our vision for the future! If you’re interested in precision medicine, drug discovery, AI and NLP solutions for pharmaceutical and biotech - follow MedBioinformatics for more. #genomics #drugdiscovery #NLP #biotech #precisionmedicine

AI-powered therapeutic target discovery Disease modeling and target discovery are crucial initial steps in the drug discovery process and significantly impact on the success of drug development. Given the advantages of analyzing large datasets and complex biological networks, artificial intelligence (AI) is playing a growing role in modern drug target identification. The researchers discuss the use of deep learning models for target discovery, AI-identified targets validated through experiments, and the use of synthetic data produced using generative AI for target identification. Novelty, in addition to druggability and toxicity, is a crucial factor in target selection. There is a trade-off between choosing high-confidence and novel targets. Over the past few years several AI-derived drugs have entered clinical trials, signaling the dawn of a new era in AI-driven drug discovery. #sciencenewshighlights #ScienceMission https://lnkd.in/gsvHqTs2

The AI transformation of drug discovery is underway. A new story from Rachel Brazil in The Pharmaceutical Journal looks at how we are leveraging AI capabilities, computing power, and purpose-built data to identify novel biomarkers and targets, and accelerate the drug discovery pipeline end to end. ◾ She writes: "The pharmaceutical industry has been successfully using computers and mathematical models to identify and design new drugs for several decades, but the development of generative AI — based on deep neural networks and large language models capable of understanding and generating text — has brought big changes." ◾ In the article, Imran Haque describes how Recursion's approach involves collecting microscopy images from human cell assays, taking pictures to compare disease and healthy states, and feeding those images into trained AI models that identify 1,000 different features in each image. “This turns out to be an incredibly powerful capability,��� he says. Read the full article: https://lnkd.in/gBSNG_at #ai #techbio #pharma #drugdiscovery #biotech #biopharma Pharmaceutical Journal Publications

We share benchmarking data on our #computationalChemistry models that underpin Balto, our chat-based AI assistant for drug discovery (accessible now, comment below if you want an invite)! We're just getting started, so we'd LOVE to hear what you think and what other tests we should be running. We're also partnering with folks to validate the models, so drop a message in the comments if you're interested. #compChem #chemistry #AI #ML #docking #virtualScreening #chemProps #molecularModeling

How can we leverage #artificialintelligence in a way that goes beyond the hype? To answer this question, #AI and #analytics expert Volodimir Olexiouk, BioLizard's #PrincipalScientist and Director of Scientific Engagement, shared his insights with me for the inaugural article of our latest #blogseries on #AI in the #lifesciences 👇

Artificial intelligence is swiftly becoming a cornerstone #technology in the early stages of drug discovery and #preclinical development, and we're witnessing an increasing number of AI-driven breakthroughs in this field… right? Let's take a look at the application of #AI in #biomedicine: its ongoing challenges, its areas of greatest potential, and how to truly leverage it effectively - beyond a mere tip of the hat to the hype. A sneak peak? We're convinced that AI isn't the key piece of the puzzle all on its own. It will take the 𝘁𝗲𝗮𝗺𝘄𝗼𝗿𝗸 𝗼𝗳 𝗔𝗜 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿 𝘄𝗶𝘁𝗵 𝗵𝘂𝗺𝗮𝗻 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 to fulfil the promise of more efficient and effective #drugdiscovery 💪 Read the whole story here 👉https://lnkd.in/e9dJKX-3 #drugdevelopment #ArtificialIntelligence #AIforHealth #dataanalytics #lifescience #tech #biotech | Volodimir Olexiouk | Alex Cloherty, PhD 🦠💬

Artificial intelligence is progressing at an unprecedented rate, surpassing initial expectations. Particularly in the realm of health, I believe it will transcend conventional boundaries and reach heights beyond our current imagination. #ai #deeplearning #healthai #pharma "Discovery of a structural class of antibiotics with explainable deep learning" https://lnkd.in/dgnD6833

Alphafold3: This is just awsome! AI- and deep learning-powered prediction of complex structures and modelling across the biomolecular space! https://lnkd.in/dAPAGY_h

Safeguarding Mail-Order DNA Synthesis in the Age of Artificial Intelligence I'm excited to share Steph Batalis (current CSET researcher), Caroline Schuerger (former CSET researcher), and JHU's Matthew E. Walsh and Gigi Kwik Gronvall's work that explores the potential impact of AI on DNA synthesis screening protocols and offers informed recommendations for the development and implementation of this new mandate. Key Takeaways: 1️⃣ Immediate Implementation of a Screening Framework: Utilize existing best practices for initial steps, such as the HHS' Screening Framework Guidance for Providers and Users of Synthetic Nucleic Acids and protocols from the International Gene Synthesis Consortium, to curb the synthesis of high-risk DNA sequences. 2️⃣ Framework Updates and R&D Investment: Future-proof the screening framework by ensuring its adaptability and investing in research to find more comprehensive screening methods. Given that current protocols could be circumvented, integrating AI tools into the screening process, similar to those used by potential adversaries, might be a prudent strategy. 3️⃣ Legislative Support for Screening Regulations: Encourage Congress to formalize the EO's new screening guidelines to maintain consistency in DNA synthesis security, regardless of administrative changes. 4️⃣ Enhanced Biosecurity Training: Broaden the focus beyond screening protocols by augmenting biosecurity education for researchers and model developers. Understanding the potential misuses of their work enables professionals to consciously design projects with safety as a priority. 🔗 Discover more in the full publication in the Applied Biosafety journal: https://lnkd.in/eV8XxZYz Notably, Executive Order 13859 underscores the significance of DNA synthesis screening in federally-funded biological research, marking a vital move towards more responsible biological advancements. Relatedly, in November 2023, Steph Batalis and Vikram Venkatram delved into the bio-relevant aspects of Biden's AI executive order in a comprehensive blog post, highlighting it as a positive step forward. Read more here: https://lnkd.in/ea8t37DQ

🔥Are you curious about how Generative AI is changing the way drugs are discovered in pharmaceuticals? 🚀Generative AI is transforming drug discovery in pharmaceuticals. By analyzing vast datasets, it can design and optimize novel drug candidates efficiently, accelerating the discovery process, reducing costs, and increasing the likelihood of identifying successful treatments. ➡️Swipe through to uncover the latest innovations driving the future of medicine. #datascience #machinelearning #artificialintelligence #deeplearning #nlp #generativeai