Generative Biologics

Exciting new features are now available with Generative Biologics! Generative Biologics utilizes advanced algorithms and #machinelearning techniques to expedite the #peptidedesign process. However, we understand that the field of peptide design is multifaceted, and we constantly improve our platform. In the latest version we've added advanced model for in-place 3D-based design of peptides and introduced novel AI-based affinity prediction algorithm for an accurate peptide ranking. To generate peptides on our platform you just need to upload the protein structure. All the steps will be handled by the platform automatically. Besides the developed peptide design workflow, recently we introduced our solutions for epitope-specific Antibody and Nanobody generation. That means that now you are able to overcome one of the main limitations of the conventional design methods – receive biologics which bind exactly where you need. As part of our research and development efforts, we are keen to gain insights directly from experts in the field. For more information, head to our new website today and contact our team https://bit.ly/3YukYvS

?? AI-Powered De Novo Generation, from Generative Biologics ?? We're using the power of AI to accelerate de novo biologics discovery—from data exploration to final lead selection. ?? How it works: ?? AI-driven protein modeling to identify binding sites ?? In silico hit generation for rapid molecule screening ?? AI-powered optimization & ranking for wet-lab validation ?? Robotics-assisted testing to confirm breakthrough candidates With AI and automation, we are shortening discovery timelines and enhancing precision in biologics development. ?? Learn more about how we're shaping the future of AI-powered drug discovery! #GenerativeBiologics #AIDrugDiscovery #Biologics #DeNovoDesign

?? Silicon Valley, see you next week! ?? Excited to share that Petrina Kamya, Ph.D., our Global Head of AI Platforms & VP, President of Insilico Medicine Canada, will be speaking at VLAB's Future of Drug Discovery event next week! She’ll be diving into one of the hottest topics in biotech: ?? Is Generative AI the Breakthrough in Drug Development? ?? Thursday, March 20, 2025 ?? Silicon Valley Bank Experience Center ? 6 - 8 PM PST Generative AI is transforming the way we discover and develop new drugs, and Petrina will be sharing insights on how AI-driven platforms are accelerating innovation. If you’re in Silicon Valley, don’t miss this opportunity to explore the future of AI in life sciences! ?? Join the conversation & connect with us there! Email [email protected] and head to the VLAB website here: https://lnkd.in/e8mBmbak #InsilicoMedicine #AIinDrugDiscovery #GenerativeAI #BiotechInnovation #VLAB #AIPlatforms

Great news, my friends - we got $110 million in series E funding led by one of the largest publicly-traded asset management firms in Asia, Value Partners Group . This round follows our announcement of the top line results from our Phase IIa clinical results for Rentosertib (ISM018-055) in IPF and multiple other milestones on the clinical side (TEAD and MAT2A inhibitors are also now in Phase I and PHD1/2 inhibitor for IBD completed two Phase Is). However, the Phase 2a readout is not the only reason for this round. The healthcare partner at Value Partners, Dr Chuen Yan Leung who has a PhD from the University of Cambridge, followed the company since his time in academia and did a lab seminar on experimental validation of our Generative Tensorial Reinforcement Learning (GENTRL) paper in 2019 in Nature Biotechnology. Since then, we have taken both the generative platforms and the reinforcement learning pipeline to a completely new level with over 700 different models. The funding will be used to progress the therapeutic pipeline and to advance and expand our end-to-end generative AI platform. In the comments are links to pieces by the wonderful Saritha Rai of Bloomberg (Exclusive), Conor Hale of Fierce, who knows our company better than anyone for many years, and Kyle LaHucik of Endpoints. Congratulations to the team, to all of the investors and partners who supported us, and to patients who now have the higher chance of seeing the drugs reach the clinic. We are here for the patients and when it comes to Aging, all of us are patients so check out our papers on TNIK and dual purpose aging- and disease-targeting therapeutics.

?? Bridging AI, Automation, and Generative Biologics ?? At Insilico Medicine, we’re leading the Lab-in-the-Loop approach—where AI-driven https://bit.ly/4kKelht meets real-world data generation to accelerate drug discovery. ?? This image showcases how our very own robotics lab seamlessly integrates with our Generative Biologics platform, to optimize workflows from target identification (via PandaOmics) to functional validation. ?? AI-Powered Target Discovery ?? Automated Compound Screening & Validation ?? Generative Biologics for Next-Gen Therapies The synergy of AI, robotics, and automation is unlocking novel therapeutics faster than ever before. Welcome to the future of drug discovery. ?? Learn more: https://bit.ly/3DE0A3o #AIinPharma #LabInTheLoop #GenerativeBiologics #Automation #DrugDiscovery #InsilicoMedicine

?? ????-?????????????? ???????? ?????????????????? ???? ????????????! At #DDIP2025, Petrina Kamya, from Insilico Medicine delivered an insightful presentation on "????????-?????????? ?????????????? ???? ????-???????????? ???????? ?????????????????? ?????? ??????????????????????." ?? She highlighted how AI is accelerating drug discovery by optimizing target identification, reducing development timelines, and enhancing real-world applications in precision medicine. Stay tuned for more updates. #AIinPharma #DrugDiscovery #DDIP2025 #HealthcareInnovation #InsilicoMedicine #Highlights

???? From data exploration to final lead selection, our Generative Biologics platform streamlines #biologicsoptimization using AI-driven insights & robotics-powered validation. Here is the expected timeline: ?? Data Exploration & Model Training (4-5 weeks) ?? Lead Optimization (3-4 weeks/cycle) ? Final Lead Selection (3-5 weeks) With AI-powered analysis, 3D structure modeling, and wet-lab evaluation of the selected binders, we accelerate the journey from variant generation to final candidate validation—helping researchers discover & optimize biologics faster than ever. ?? Learn more about the future of AI in biologics: https://lnkd.in/eeXxqm-G #GenerativeBiologics #AIinBiotech #BiologicsOptimization #AIforDrugDiscovery #PharmaAI

?? Stay Ahead with AI-Powered Drug Discovery! ???? At Insilico Medicine, we’re transforming drug discovery with Pharma.AI. Be sure to follow our Pharma.AI platforms to stay updated on the latest breakthroughs, partnerships, conference presentations, and innovations in AI-driven biologics, small molecule drug design, target discovery, and more. Be sure to follow below ?? ?? Chemistry42 – AI-powered generative chemistry for drug design ?? Generative Biologics – Advancing biologics discovery with AI ?? PandaOmics – AI-driven target discovery and disease insights ?? inClinico – Predicting clinical trial success with AI Follow our platforms to stay informed, connect with experts, and shape the future of AI in pharma! #AIinDrugDiscovery #PharmaAI #GenerativeAI #TargetDiscovery #ClinicalAI #InsilicoMedicine #FollowUs

??? Advancing CNS Therapeutics with Generative AI ???? Insilico And Tenacia Collaborate To Advance CNS Therapeutics With Generative AI The Pharma.AI platform has been instrumental in advancing Insilico’s pipeline of CNS therapeutics, including assets targeting neurodegenerative diseases and other neurological conditions. For instance, the company’s work on ISM001-055, a treatment for idiopathic pulmonary fibrosis, has demonstrated promising results in Phase IIa trials, highlighting the platform’s ability to generate effective drug candidates. Insilico’s focus on CNS therapeutics is driven by the need to address unmet medical needs in neurological disorders. By combining AI-driven innovation with expertise in drug development, Insilico aims to deliver novel treatments that improve outcomes for patients with conditions such as Alzheimer’s disease and epilepsy. Read the latest from Quantum Zeitgeist: https://lnkd.in/eX3qWv8T

?? In case you missed it! Have you seen the new Model Training feature from Generative Biologics? Check out this video here. ??? ?? Users can upload their own experimental data—like affinity values—and train the AI models specifically for their projects. This means you can optimize and screen antibodies and nanobodies more effectively than ever before! Here’s how it works: 1. Upload your experimental data in CSV format. 2. Select the target property (e.g., affinity) for training. 3. Run the model training with just a few clicks! 4. Evaluate the trained model's performance using correlation values and error metrics. If you’re satisfied with the results, deploy the model and use it for future experiments! This feature allows researchers to tailor AI predictions to their specific needs, enhancing biologics development like never before. Check out our screencast to see the feature in action! ?? Get in touch with our team to learn more and book a demo: https://lnkd.in/ewHmSgce