Andy Hickl

From drug design to protein modeling, the future of biomedical discovery depends on solving quantum systems we can’t touch with classical computation. Phasecraft co-founder and CTO Toby Cubitt spoke with Marianne Guenot, Ph.D., for her Nature Medicine piece on our partnership with Wellcome Leap. Together, they are exploring how #quantum computing could transform biochemistry, with a focus on drug discovery for myotonic dystrophy, and what it’ll take to reach practical quantum advantage in this field. https://lnkd.in/d622N444

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I’m excited to share a landmark step forward for the University of Chicago and for Chicago’s growing quantum ecosystem. Today we announced a new partnership with IonQ that will bring a production-grade trapped ion quantum system and quantum networking capabilities directly to our campus—supporting world-class research, hands-on opportunities for our students, and deeper collaboration across academia, industry, and national labs. The future IonQ Center for Engineering and Science will strengthen UChicago’s leadership in quantum science and engineering and help accelerate real-world applications in security, health, energy, and beyond, right here in Illinois. Proud of our colleagues at UChicago Pritzker School of Molecular Engineering and the Chicago Quantum Exchange whose vision and work made this possible. Read more: UChicago launches landmark initiative with IonQ to advance quantum research and collaboration. https://lnkd.in/gJwcJmjZ

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The Biological Computing Co. (TBC), a San Francisco, CA-based biological computing and brain-inspired #AI company, has raised $25M in Seed funding. The round was led by Primary and coincided with the opening of TBC’s flagship laboratory in Mission Bay, San Francisco, supporting early customer deployments. TBC plans to use the new capital to expand operations and accelerate platform development, advancing a new compute layer that combines living neurons with advanced AI systems. The company’s platform integrates neural-based intelligence directly with foundation models, improving performance while reducing compute costs. Its neuroscience and engineering teams encode real-world data—such as images and video—into living neurons, then decode neural activity into richer representations mapped to AI models via modular adapters. In parallel, TBC’s Algorithm Discovery platform applies biologically derived principles to design AI systems beyond transformers, strengthening existing architectures rather than replacing them. 🧠 A bold step forward at the intersection of neuroscience, biological computing, and artificial intelligence. Alexander Ksendzovsky MD, PhD CEO & Co-Founder Jonathan Pomeraniec MD, MBA COO & Co-Founder Cristina Florio, PhD Director of Laboratory Operations Ex-NIH #FundingAnnouncement #SeedFunding #BiologicalComputing #BrainInspiredAI #ArtificialIntelligence #Neuroscience #DeepTech #ComputeInnovation #SanFrancisco #StartupFunding #VentureCapital

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🚀 Exciting news for the UC San Diego research community! UCSD’s Institute for Genomic Medicine (IGM) has partnered with us as an to bring researchers access to Ultima Genomics's high-throughput sequencing platform. Through this collaboration, UCSD network members can take advantage of: 🔬 Comprehensive applications on the UG100 with Solaris™ (WGS, RNA sequencing, single-cell MRD assays, and more) 💡 Expert support from sample prep to data delivery 💰 Exclusive UCSD pricing This partnership ensures high-quality sequencing services and seamless logistics... all right here in San Diego. We're proud to be an Ultima certified service provider. #Genomics #Sequencing #Innovation #ResearchCollaboration #UCSD #Inocras #UltimaGenomics

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🚀 Welcome to the Biostatistics Symposium of Southern California (BSSC) LinkedIn Group We’re excited to launch this community for professionals across biostatistics, data science, and the broader life sciences ecosystem in Southern California. Biostatistics Symposium of Southern California (BSSC) is a non-profit organization with 501(c)(3) tax-exempt status, created to bring together professionals from academia, biopharmaceutical companies, and the wider life sciences industry. What makes BSSC unique is that many of our committee members started out as attendees themselves. That perspective helps us design events and discussions that genuinely reflect the interests and needs of the community. Our mission is simple: 🔬 Prepare Through our flagship annual symposium, we bring together statisticians, data scientists, and industry leaders to share knowledge, ideas, and innovation across the Southern California life sciences ecosystem. 📈 Promote We highlight the critical impact statisticians and data scientists have across biopharmaceutical and life science industries, showcasing new methodologies and insights that are advancing the field. 🤝 Collaborate BSSC works closely with the three local chapters of the American Statistical Association (ASA): • Southern California Chapter (SCASA) • Orange County & Long Beach Chapter (OCLBASA) • San Diego Chapter (SDASA) Together, we aim to support the next generation of statisticians and data scientists driving innovation across biotech, pharma, and medical devices. This group will be a space to share: • Industry insights • Event updates • Career opportunities • Thought leadership in biostatistics and data science • Collaboration across the Southern California life sciences community If you work in biostatistics, statistical programming, data science, clinical research, or related life sciences fields, we’re glad you’re here. Welcome to the community. 📩 For any questions or inquiries, please feel free to contact us at BSSC.information@gmail.com

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Read about the mission and the purpose for the startup of the Institute for Infrastructure and Interoperable Data in Learning in our first white paper. "The institute will assume stewardship and maintenance of essential TLA-related open source technologies and conformance systems. It will also reconstitute elements of the research capacity previously led by ADL." #Interoperability #DataStandards #LearningTechnology https://lnkd.in/exNYjsYj

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Major news for AI in Healthcare! We’re excited about our new collaboration with the UCSF UC Berkeley Joint Program in Computational Precision Health and UC Berkeley College of Computing, Data Science, and Society—a unique academic partnership that will host and manage the Nightingale Open Science Dataset. This is what meaningful change in health technology looks like, and we’re thrilled to be part of a team working towards a better future. The collaboration will expand access to a key resource that addresses some of the most persistent challenges in health AI research and deployment. Learn more about Nightingale Open Science: https://lnkd.in/eZwegzae

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🎤 Did you catch Esha Joshi's talk on scaling with Seqera? Turning a research project into a robust, real-world solution requires tools that support both early ideation and mega-scale computation. In this talk, Esha shared how Seqera empowers scientists to scale code, compute, projects, and teams—from early experimentation to enterprise-level deployments. 🔗 Watch the full talk here: https://hubs.la/Q03pHh220 🎥 Check out the #NextflowSummit playlist: https://hubs.la/Q03pHl7q0

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🚀 Accelerating discovery with AIxBio starts with data 📈 Last week, NSCEB Chair Senator Todd Young, Senator Ben Ray Luján, NSCEB Commissioner Rep. Ro Khanna, and Rep. Jay Obernolte introduced the AI-Ready Bio-Standards Act of 2026. The legislation reflects recommendations made in the April 2025 biotech action plan from the NSCEB. By directing the National Institute of Standards and Technology (NIST) to develop standards that make biological data more interoperable, structured, and machine-readable, this legislation will help ensure that researchers and innovators can fully harness AI to drive new breakthroughs. From new medicines to advanced materials, the future of biotechnology will be increasingly powered by AI. This legislation is an important step toward building the data infrastructure needed to fuel that future. 🧬🤖 Learn more about the bill here: https://lnkd.in/e9JMRyZy 

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We report new work from our group in collaboration with Google's genomics team. A challenge with genetic discovery for heart failure is that its classification within large scale biobanks is extremely vague. This has led to the surprising situation where, in 2026, there are only 2 validated GWAS loci for heart failure with preserved ejection fraction, a sub-group that accounts for HALF of the total heart failure patients, heart failure being the single most common admitting diagnosis in patients over the age of 65 (more than 30 million people globally). We need to do better. One approach is to use machine learning to develop a precision phenotype (for this you need rich health care system data from many patients, not biobank data). Then, you can take that probabilistic framework and apply it to biobanks which, while less enriched for patients, provide the power of large scale and deep genomics and proteomics. This was the idea that Jack W O'Sullivan MD, PhD and a large collaborating team sought to pursue in this work. The findings went beyond all our expectations. First, the team increased the number of loci confidently associated with HFpEF almost 50 fold! We report 99 loci, up from 2. Second, by integrating multi-omics in a causal inference framework, we prioritize gene-protein pathways as candidates for therapeutic development while de-prioritizing non-causal targets, reclassifying them as biomarkers. How could we tell we were on track? We noted first that three clinical trials for one of our deprioritized targets (MPO) were negative (genomics really can save money in drug discovery). We also validated one of our prioritized targets in a novel clinical study. In conclusion, we hope this work accelerates our understanding of heart failure. We believe this approach to precision phenotyping can extend the reach of our global biobanks in many directions. Finally, we believe incorporating causal inference in a multiomic framework can directly inform investment decisions in drug discovery pipelines. Congratulations to the entire team and special thanks to our Google collaborators who are the co-leaders of this work. Taedong (Ted) Yun Cory McLean Andrew Carroll Paper: https://lnkd.in/gamstJQM

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