How AI is transforming drug discovery with Rouken Bio

A perspective on AI driven therapeutic discovery from Aimee Cliens. The successes, and the remaining challenges. #AItherapeutics #antibodytherapeutics #drugdiscovery #biologics

RoukenBio, this is an excellent deep dive into the accelerating role of AI in drug discovery. We fully agree that the future lies in combining the predictive power of computational tools with robust experimental validation. At MAbSilico, we employ a fully integrated AI-driven pipeline followed by experimental validations in our wet-lab, that significantly de-risks and accelerates the antibody discovery curve. Our methodology is built on a few core pillars: 1. Design & Prediction: We use structure-based biophysics to generate, optimize or characterize antibodies. 2. Multi-Parametric De-risking: We profile hits for developability (aggregation risk, PTM liabilities...) and off-target binding before we commit to costly wet-lab experiments. This ensures that the candidates advancing for synthesis have the highest probability of success. 3. Strategy & IP: Our MAbFactory platform with the most extensive manually curated data set from thousands of patents to map the competitive and epitope landscape of any target allows discovery teams to potentially identify novel epitopes giving the program built-in Freedom-to-Operate (FTO) advantage. The key is that the computational solutions do not just suggest hits; they deliver pre-validated, high-quality candidates to the wet lab, making the screening process more efficient and focused. We are happy to discuss, feel free to reach out! #AIDiscovery #Techbio #Biotech #DrugDesign #InSilico #Biologics #AntibodyEngineering #DrugDiscovery

Big news from the UK biotech scene: Oxford spinout Genomics has launched Mystra, a cutting-edge AI platform designed to accelerate drug development by leveraging vast genetic data. With Mystra, Genomics aims to empower pharmaceutical companies to identify new therapeutic targets more efficiently, potentially transforming the drug discovery process. CEO Peter Donnelly is actively engaging with pharma leaders to integrate this innovative tool into the industry's research pipelines. This move underscores the growing importance of AI and genomics in modern drug development. As Mystra enters the market, it could set a new standard for how genetic insights are utilized in the quest for novel treatments. #Genomics #AIinPharma #DrugDiscovery #BiotechInnovation #OxfordSpinout #Mystra #PharmaTech #GeneticData #HealthcareInnovation #PharmaceuticalResearch https://lnkd.in/eH7CVdZJ

Takeda is expanding its partnership with Nabla Bio to design new biologics using AI-powered models. Another example of the shift of use of AI from “experimental” to core R&D strategy. The focus now is speed and precision to get to focused candidates faster. Where do you see AI making the biggest impact first — molecule design, screening, or clinical planning? Teams that pair these new tools with biology are starting to separate themselves by turning AI into a real advantage instead of just a buzzword on a slide. #AIDrugDiscovery #BiotechInnovation #PharmaStrategy https://lnkd.in/eCeCfntd

What an inspiring few days at the Festival of Biologics! One of the talks that really stood out for us was from IGI who showcased their BEAT® platform — a plug-and-playtechnology for advancing multispecific antibodies into the clinic. Their approach focuses on delivering highly developable candidates aiming to expand the therapeutic window. Particularly exciting was their high-throughput polyreactivity screening using the Carterra LSA to assess the behavior of antibody candidates early in discovery. It’s always exciting to see how advanced tools are driving smarter, faster antibody development. At AVS Bio, we’re proud to offer access to the Carterra LSA platform, helping researchers screen, characterize, and subsequently optimize candidates with precision and scale. If you’re interested in exploring how high-throughput kinetic and polyreactivity analyses can accelerate your antibody program, let’s connect. 👋  #FestivalOfBiologics #AntibodyEngineering #Biologics #CarterraLSA #BispecificAntibodies #BEATplatform #Developability #AVSBio 

Invert Just released #InvertAssist, an #AI-powered analysis interface that lets #bioprocess teams analyze #data and run #process modeling using simple #naturallanguage prompts. Bioprocess data is often complex, siloed, and slow to turn into decisions. Invert Assist helps close that analysis → action gap by enabling scientists to: > Spot trends + drivers across runs > Summarize experiments across scales > Build predictive models + simulations > No coding required A meaningful step toward faster development and #manufacturing timelines for #biologics and cell/gene therapies. #bioprocessing #biomanufacturing #biotech #biopharma #celltherapy #genetherapy  #processdevelopment #bioprocessanalytics #digitalbioprocessing #bioprocessautomation https://lnkd.in/eeMuiK4h

⚗️ Nine AI-discovered drugs reached Phase 3 this year-with 31 more lining up. The pipeline just hit fast-forward! These numbers are absolutely mind-blowing! 🤯 AI-discovered drug candidates are showing 80-90% success rates entering Phase 1 trials, compared to just 40-65% for traditional methods. That's a game-changer for the entire pharmaceutical industry. This transformation is completely reshaping how we approach drug development, and I'm here for it! 🚀 ✅ AlphaFold's protein structure predictions earned the 2024 Nobel Prize in Chemistry - proving AI's game-changing impact is real ✅ Specialized models like PharmBERT are extracting pharmacokinetic data with unprecedented accuracy ✅ Multimodal AI is accelerating target identification and clinical trial optimization like never before Here's what really gets me excited - we're talking about cutting both the $2 billion cost AND the decade-long timeline of traditional drug discovery. But the real kicker? The democratization potential! 💡 As someone working in both tech and business development, I'm witnessing firsthand how AI tools are making advanced drug discovery accessible to smaller teams and organizations. This levels the playing field in ways we've never seen before. Oncology is leading the charge with 30% of AI applications in drug discovery, but here's the real breakthrough - we're shifting from reactive to predictive medicine. That's revolutionary! 🌟 The 2025 State of AI in Drug Discovery summit highlighted virtual cells and generative AI as the next frontier. We're not just finding drugs faster - we're finding better drugs, and that's going to change everything. Excited to see where this incredible journey takes us next! The future of healthcare is being written right now. #AI #DrugDiscovery #HealthTech

Innovation in drug discovery is essential for improving healthcare outcomes, and open foundation models have a critical role to play. Learn how the AI Alliance Drug Discovery Working Group brings together experts in clinical practice, open source AI technology, the pharmaceutical industry, and academic research to accelerate life-saving discoveries—and how you can contribute. #redhat #ibm #ai #redhatai

Nabla Bio and Takeda inked a second #drugdiscovery deal which will see Nabla leverage its Joint Atomic Model (JAM) technology for the de novo design of antibodies and multispecifics against several targets. https://lnkd.in/dg62W4Ar #AI #artificialintelligence #biotechnology #digitalhealth #generativeAI #healthtech #licensing

🚀 Improving antibody–antigen affinity with custom AI calculations Wet-lab iterations are slow and expensive. Our platform pinpoints high-impact residue modifications in silico—ranking ΔH, ΔS, ΔG (Kd/IC50-linked) and stability changes—so you enter the lab with a short, high-confidence list of designs. What you’ll see in the figure (p.1): a side-by-side of traditional experimental stages vs. our AI-guided workflow, highlighting fewer cycles and lower costs before arriving at a commercial-grade antibody. antigen ✅ Faster design cycles ✅ Fewer experimental rounds ✅ Transparent, physics-aware ML rankings 🎁 Free pilot project: share a target, we’ll run a focused affinity-optimization sprint and review results with your team. Learn more: https://lnkd.in/dj2c883y #AntibodyEngineering #Biologics #DrugDiscovery #AIinBiotech #ProteinDesign #ComputationalBiology #InSilico #R&D #BiotechInnovation