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Erica Del Monaco reposted thisErica Del Monaco reposted thisSchrödinger employees, Magdalene Romero and Erica Del Monaco, attended NVIDIA GTC, where NVIDIA CEO Jensen Huang and other industry leaders spoke about the next frontiers of AI innovation and technologies reshaping the world. Our participation included a panel featuring Schrödinger's Shane Brauner as well as Perry Nightingale, Jason Monden, and Sony Mohapatra. Panelists revealed insights on building production-grade AI stacks. Shane shared how we use Google Cloud Services to accelerate the discovery of novel therapeutics and materials. We are grateful for the opportunity to share our work alongside the brightest minds in the industry! #GTC2026
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Erica Del Monaco shared thisExciting to see the acceleration of domain specific applications of AI. With the recent advances in agentic AI and lab automation, the transition from traditional drug discovery to the “digital dry lab” is quickly becoming a reality. #NVIDIAGTC #healthcareinnovations #digitaldrugdiscoveryErica Del Monaco shared thisDay 2 at NVIDIA GTC! Really enjoyed Jensen Huang’s keynote yesterday, great to see such a clear focus on scaling AI infrastructure, full-stack systems, and real-world impact. The talks and networking have been fantastic, all centered around how quickly this is moving into production. #NVIDIAGTC #AI
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Erica Del Monaco shared thisThis article highlights how AI is accelerating drug discovery. The increased adoption of AI technologies, combined with the FDA's push to reduce the reliance on animal testing, could dramatically reduce the timelines and costs of drug development.AI-driven drug discovery picks up as FDA pushes to reduce animal testingAI-driven drug discovery picks up as FDA pushes to reduce animal testing
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Erica Del Monaco reposted thisErica Del Monaco reposted thisWhat if the “rules” in drug discovery were meant to be rewritten? Mutations in the KRAS protein are among the most common drivers of many cancers, and SOS1 has emerged as a compelling upstream target to indirectly inhibit KRAS activity. At Schrödinger, we set out to design a truly differentiated SOS1 inhibitor. Most existing inhibitors looked highly similar chemically and structurally. We asked a bold question: could the solvent-exposed amino acids at the edge of the SOS1 pocket — long considered “off limits” in medicinal chemistry — become an opportunity rather than a liability? This is where Schrödinger's platform gave us a competitive advantage. In our latest Extrapolations blog, Abba Leffler shares how FEP+ provided the computational foresight to explore what traditional approaches would have missed. Read the full blog post here: https://lnkd.in/dh6Y27pG #DrugDiscovery #ComputationalChemistry #Schrodinger #MedicinalChemistry #KRAS #SOS1
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Erica Del Monaco reposted thisErica Del Monaco reposted thisSchrödinger is excited to host the US User Group Meeting at the Newport Harbor Island Resort in Newport, Rhode Island, from September 15-17, 2025. This in-person event will bring together a dedicated group of Schrödinger users and team members from across the United States. The event will feature scientific presentations, hands-on workshops, panel discussions, and networking opportunities. Preliminary agenda announced! View agenda and register here: https://hubs.li/Q03rszGp0
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Erica Del Monaco shared thisSchrödinger is hosting an in-person event in San Diego next week on Wednesday, October 25: Advancing Drug Discovery with Digital Chemistry Seminar & Design Challenge Workshop. Join us from 12 PM - 3 PM, followed by a networking happy hour. Click the link below for more details and link to register. #Schrödinger #SanDiego #DrugDiscovery #CompChem #MedChem https://lnkd.in/gdTtbREzAdvancing Drug Discovery with Digital Chemistry Seminar & WorkshopAdvancing Drug Discovery with Digital Chemistry Seminar & Workshop
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Erica Del Monaco shared thisErica Del Monaco shared thisThere’s some big things cooking in our Enterprise product management team, and we’re #hiring a senior member to help drive the future of large scale modeling and experimental data and in our integrated technology platform, LiveDesign!
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Erica Del Monaco shared thisKids Day at the Schrödinger San Diego office! We made slime, extracted DNA from strawberries, learned that you can write code to model DNA on the computer, and had a pizza party! 🧫👩🏼🔬🧬👩🏼💻🍕
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Erica Del Monaco shared thisErica Del Monaco shared thisThe Antibody Society is offering several free registrations to the April session of Schrödinger’s online course, Introduction to Computational Antibody Engineering to our student and post-doc members. This is an awesome opportunity to learn about computational antibody engineering! The session opens on April 18th. If you would like to attend for free, send a message via LinkedIn to Janice Reichert. More information about the course is here: https://lnkd.in/eK8cPdpE
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Erica Del Monaco liked thisErica Del Monaco liked thisI volunteered with the Fleet Science Center tonight for their “Two Scientists Walk Into a Bar” program, which is exactly what it sounds like: Scientists + bar + open Q&A. There’s no script, no deck, no agenda. Just people asking whatever’s on their mind. Some questions were deep, some were career-focused, and some were just fun. Having casual conversations about science outside of work is incredibly rewarding and it’s programs like this can help build science literacy in an organic way.
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Erica Del Monaco liked thisErica Del Monaco liked thisFor years, Schrödinger didn’t just operate the largest supercomputer in the pharma industry—we operated a supercomputer larger than all of pharma combined. We have been championing a computationally driven, "predict first" paradigm for over 30 years. I remember building our very first GPU cluster back in 2012. At the time, betting that heavily on compute was a novel concept in this space. Today, it is the bedrock of modern drug discovery. The energy and announcements surrounding NVIDIA's GTC last week served as massive validation for this technology-driven approach. Following Eli Lilly’s recent LillyPod supercomputer announcement, Roche announced their own massive new system during the week of GTC. It is incredibly exciting to see the world's largest pharma companies investing at this scale. Our partners at NVIDIA and Google Cloud clearly recognize this fundamental paradigm shift as well. (It was also fantastic to see Schrödinger featured directly in Jensen Huang's keynote!) But for us, this isn't just a theoretical compute arms race. We have demonstrated the real-world impact, and our customers are seeing it too. Take our MALT-1 inhibitor program as an example. Iteratively developing our lead series computationally, we only had to synthesize 78 compounds over 10 months, compared to an industry average synthesizing 2,500 compounds over 2-3 years. That is what "predict first" means in reality. It means drastically reducing physical waste in the lab, cutting years off timelines, and ultimately designing better, safer medicines. The rest of the industry is catching up to a Physics+AI approach, and patients will be the ultimate winners. #AI #Supercomputing #GTC2026 #DrugDiscovery #Schrodinger #CIO
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Erica Del Monaco liked thisAt the recent NVIDIA GTC event, I had the opportunity to co-lead a session on “Accelerating Antibody Design with Generative Science on NVIDIA Platforms,” alongside Kris Kersten, medb corcoran, Kailash Swarna, and Emily Rose Miller, with participation from industry experts. The discussion centered on a challenge we see across Life Sciences today relating to bridging the gap between rapid advances in AI models and scientific workflows used in drug discovery. Generative AI is transforming protein engineering, antibody discovery, and biologics development by enabling researchers to explore vast regions of the protein sequence and structural design space. However, moving from promising models to production grade discovery pipelines remains difficult. Many organizations encounter similar bottlenecks: • Code heavy pipelines requiring significant engineering to connect sequence generation, structure prediction, docking, and molecular simulation tools • Rapid model evolution across protein folding and biomolecular foundation models • Research grade models that lack APIs, scalability, and operational robustness • Infrastructure scaling challenges as workflows combine AI inference, structural modeling, and large scale candidate evaluation During the session we walked through a generative science pipeline for antibody design. The workflow starts with generative models that design antibody sequences targeting a specific antigen. These candidates are evaluated using protein structure prediction models to estimate folding and binding compatibility. Promising candidates then move through docking and interaction analysis to evaluate antibody–antigen binding affinity. Additional biophysical filtering and simulation based analysis help assess stability and developability. Running these stages iteratively allows researchers to generate and evaluate thousands to millions of antibody candidates, dramatically accelerating exploration of the molecular design space. A key theme from the discussion is that these pipelines are increasingly built as modular workflows composed of GPU accelerated libraries such as #NVIDIA BioNeMo, and model microservices. They provide optimized components for protein language models, structure prediction, and biomolecular Generative AI, while containerized microservices help operationalize these capabilities in scalable discovery pipelines. Enabling this type of generative science requires purpose built AI infrastructure including GPU accelerated compute, high-performance networking, data architectures, and orchestration layers that support complex scientific workflows. The convergence of Generative AI, structural biology, and advanced AI infrastructure is beginning to reshape how therapeutics are discovered. It is great to see how quickly generative biology is moving from research into real discovery pipelines. #LifeSciences #AIInfrastructure David Wood Adeline Cheam Lyndi Wu Gali Halpern Wienerman Tunc Yorulmaz Tom Stuermer
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Erica Del Monaco liked thisEach of these students has the potential to positively impact the world; hopefully we helped inspire them to do so!Erica Del Monaco liked thisReflecting on a standout morning from a couple of weeks ago when we hosted the 2026 New York Tiger Trek cohort at our Manhattan headquarters! It was an absolute pleasure to welcome 17 of Princeton University’s student leaders for an immersive look at how software is revolutionizing the life sciences. From a deep dive with Abba Leffler to a dynamic dialogue on our "predict-first" discovery paradigm, the energy and curiosity in the room were truly inspiring. One of the visiting students shared their reflections on the session in a fantastic article, and we’re proud to highlight their perspective on how leadership and scientific rigor can coexist at scale. Read the student’s full recap of the visit here: https://hubs.li/Q048b69B0 A big thanks to the #NYTT cohort for the fresh perspectives and the thoughtful questions that are still sparking conversations among our team. #Schrödinger #PrincetonUniversity #NYTT2026 #FutureOfScience #StudentLeadership #Innovation #LifeSciences
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Erica Del Monaco liked thisErica Del Monaco liked thisLast week at NVIDIA's GTC conference, I had the privilege of speaking as a panelist. During our session, "Blueprint for AI Scale: How Industry Architects Succeed with NVIDIA" (presented by Google Cloud), my co-panelists Sony Mohapatra , Perry Nightingale , moderator Jason Monden, and I dug into the actual mechanics of making computation cost-effective. The standout for us right now is the GCP G4 Blackwell instance. The ability to do a 4-way MIG (multi-instance GPU) split on each physical card is a major shift for price-to-performance. Agentic AI is driving increased utilization of underlying toolsets like Schrödinger's Predictive Toxicology solution. Architecting cost-conscious and performant compute is vital to address the needs of these new workflows. It was great to share the stage with fellow industry architects who are actually building the infrastructure that makes next-gen science possible. #GTC2026 #GoogleCloud #NVIDIA #AgenticAI #CIO #Schrodinger
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Erica Del Monaco liked thisErica Del Monaco liked thisSee you all tomorrow at #ACSSpring2026 for the well anticipated MEDI First Time Disclosures session. This session celebrates the creativity and scientific rigor behind bringing a compound from the bench to humans. The unveiling of these active clinical assets for the very first time is a moment that always energizes our community. A huge thank you to CAS for their generous support and sponsorship of our networking reception immediately following the session. Come join us for conversation and connection to spark the next wave of innovation. Looking forward to seeing you there tomorrow! 2PM - 7PM Sidney Marcus Auditorium ACS Division of Medicinal Chemistry Arnaud Marchand Emily Cherney Wenge Zhong Laurent Gomez David Myles Ulrich Luecking https://www.cas.org
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Erica Del Monaco liked thisNo dull moment at Protagonist Therapeutics. Let’s hope that the best is yet to come. Cheers!Erica Del Monaco liked thisWhat a week for all of us at Protagonist! After celebrating the FDA Approval of ICOTYDE, we are thrilled to be recognized on the Nasdaq Tower in Times Square as a Fast 500 company. Ranking among the fastest-growing innovative companies in North America is a powerful validation of our innovation platform. To our customers, partners, and every member of the Protagonist family: This moment belongs to you. We’re just getting started. Looking forward to what's yet to come. #PTGX #NASDAQ #BayAreaFast500 #Biotech #Innovation
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Erica Del Monaco liked thisTake a tour of Lilly's new AI Factory with Brittany Trang, PhD from STAT!Erica Del Monaco liked thisYesterday, I went to pharma company Eli Lilly and Company's headquarters in Indianapolis to see its new NVIDIA-powered supercomputer, the biggest in pharma. Both companies think this will help the U.S. win the AI arms race. The two companies also announced a deal at the J.P. Morgan Healthcare Conference where they will invest up to $1 billion in robotic AI labs. Learn more in my story at STAT: https://lnkd.in/g34pEAnn #health #healthcare #medicine #pharma #AI #artificialintelligence
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Erica Del Monaco liked thisErica Del Monaco liked thisNVIDIA Ignites the Next Industrial Revolution in Knowledge Work With Open Agent Development PlatformNVIDIA Ignites the Next Industrial Revolution in Knowledge Work With Open Agent Development Platform
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LF Energy, an initiative of The Linux Foundation, provides a neutral, collaborative environment for the open source digital foundations that will enable the electrification of everything to scale. Our mission is to accelerate and transform the world’s relationship with energy. The Power of Together.
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