Schrödinger

The challenge with pure generative AI in materials discovery is scarcity of training data, failed inference, or non-synthesizable candidates. By combining a physics-based modeling platform with advanced AI/ML architectures, Schrödinger leverages physics at scale for training, atomic scale featurization, and the highest performing inverse design frameworks. This ensures that generated molecules aren't just novel, but realistic, reliable, and optimized for real-world performance. Our multiyear collaborative journey with Panasonic highlights this evolution across multiple application areas, including organic electronics and next-gen battery electrolyte components. Swipe to see the impact of de novo design technologies on Panasonic’s materials development. https://lnkd.in/eJYxPuxa  #Schrödinger #GenerativeAI #MachineLearning #OLED #MaterialsScience #Panasonic

Will you be at the EFMC Medicinal Chemistry 2026 conference from September 6–10 in Basel? Come visit the Schrödinger team at Booth #22 to discuss your R&D challenges and learn about Bunsen, Schrödinger’s new agentic AI co-scientist. Be sure to attend our workshop on September 7th where Schrödinger experts will demonstrate how LiveDesign ML and RetroSynth accelerate drug discovery through automated property prediction and AI-driven synthesis planning.  Learn more: https://hubs.li/Q04sQhvH0 #EFMC2026 #MedicinalChemistry #DrugDiscovery #AI #RetroSynth #LiveDesign #Schrodinger

Attending the 2026 Medicinal Chemistry GRC today? Don't miss Schrödinger's Aleksey Gerasyuto. He will be presenting "In Silico Driven Discovery of SGR-3515: A First-in-Class Wee1/Myt1 Inhibitor for Treatment of Advanced Solid Tumors" during todays evening session on Pivotal Advancements Through Protein Structure. It's a great opportunity to learn how we are integrating physics + AI to accelerate the discovery of new medicines. Details and full program here: https://lnkd.in/ePGDkqi3 #Schrödinger #GRC2026 #ComputationalChemistry #Physics #AI

Schrödinger's Pat Lorton and Shane Brauner we recently sat down with Matt Walters at Supercomputing News to discuss Bunsen, our AI co-scientist. By enabling natural language interaction across our computational platform and informatics enterprise, Bunsen has become a massive force multiplier for our team. Read the full interview below to learn how we are unlocking new possibilities for both expert and non-expert users, and what this means for the future of computational research. Thank you, Matt, for a lively discussion! Check out the conversation below! #Schrödinger #TechInnovation #Supercomputing #HPC #Physics #AI

Schrödinger is excited to be participating in the IUCr2026 conference taking place on August 11th – 18th in Calgary, Canada. Join Shiva Sekharan on August 12th for an in-depth look at Schrödinger’s robust Crystal Structure Prediction (CSP) platform, which integrates machine learning force fields, molecular dynamics, and quantum mechanics to predict stable polymorphs directly from molecular structure. Learn more: https://hubs.li/Q04s12lX0

Great coverage by Brittany Trang, PhD in this week’s STAT AI Prognosis newsletter featuring our CEO, Ramy Farid, on how perspectives around AI in drug discovery are evolving. As conversations around AI continue to shift, we believe it’s helpful to separate two distinct capabilities used in molecular discovery that often get lumped under the same "AI" umbrella: AI/ML for property prediction: AI/ML models rely on training data, and there will never be enough experimental data to navigate the infinite complexity of chemical and protein space. To accurately predict the properties of novel molecules, AI must be paired with synthetic data generated on a massive scale from physics-based calculations. Agentic AI (Workflow & Tool Orchestration): LLM-driven agents such as our new AI co-scientist, Bunsen, are able to understand scientific objectives, develop computational strategies, execute sophisticated molecular discovery workflows and interpret results. As Ramy noted in the piece, earlier skepticism in the industry wasn't about AI as a whole, but about relying solely on predictive models without physics. The need for physics hasn’t shifted. What has shifted is the incredibly rapid maturity of agentic workflows, and the LLMs that power them, which makes advanced physics tools accessible to every scientist. Thanks to Brittany for capturing an important conversation on where AI truly creates value in biotech. Check out Brittany's article in her weekly newsletter here: https://lnkd.in/egDkndkB

Today, we announced a new strategic collaboration and software agreement with Bristol Myers Squibb to deploy Bunsen, our AI co-scientist, within their research organization. Building on our long-standing partnership, we will collaborate with BMS scientists on developing novel functionality within Bunsen in conjunction with our computational technologies designed to enable large-scale chemical exploration as well as with RetroSynth, our AI-driven synthesis planning platform. Our shared goal? To help researchers prioritize the most promising molecules with greater confidence, think differently about how physics-based tools can be used to navigate molecular design, and accelerate the discovery of innovative medicines for patients. Read more about the agreement here: https://hubs.li/Q04r-SgS0 #BMS #Bunsen #MolecularDiscovery #AgenticAI #Physics

We will discuss our second quarter 2026 financial results and review business progress today at 4:30pm ET. Clink here to join: https://hubs.li/Q04rV_N10

We have been named a finalist in the 2026 Fierce AI Innovation Awards under the AI Innovation in Drug Discovery category. We are honored to see our team’s work in combining physics-based modeling and AI recognized alongside so many transformative innovations across the life sciences. Thank you to @FierceLifescienceEvents and the panel of expert judges for this recognition. Winners will be announced at the end of summer in the Fierce AI Innovation Awards Special Report. #FierceAIInnovationAwards #DrugDiscovery #AI #Biotech #ComputationalChemistry #LifeSciences #Pharmaceuticals

Exciting news for scientific computing: Bunsen, our agentic AI co-scientist, is officially in early access! Built specifically for molecular discovery, Bunsen is optimized to execute Schrödinger’s validated computational methods and scale complex workflows. As part of our long-standing collaborations with NVIDIA and Google Cloud, Schrödinger will be using a full stack AI platform to support early Bunsen customers, helping research organizations scale their use of the platform across discovery programs. The collaboration also includes Google Cloud's elastic computing infrastructure and the ability to integrate Schrödinger's platform with the NVIDIA BioNeMo™ Agent Toolkit and the NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. Join the waitlist for priority access: https://lnkd.in/eTkMv4TX. #NVIDIA #GoogleCloud #Bunsen #MolecularDiscovery #AgenticAI #Physics