Novo Nordisk Partners with Anthropic, Anew Labs Raises $290M

London has always been at the forefront of biotech innovation, which can be shown by two events, nearly 70 years apart. 1952. A basement lab at King's College London, Rosalind Franklin and her PhD student Raymond Gosling captured Photo 51, the X-ray image that gave the key evidence for DNA's helical structure. 2020. A short tube ride away in King's Cross, DeepMind's London team built AlphaFold 2, which predicts a protein's 3D structure from its amino acid sequence. It won Demis Hassabis and John Jumper a share of the 2024 Nobel Prize in Chemistry. With these as the benchmark, it's no surprise that London has built a formidable ecosystem. Here's some I've been following: → Isomorphic Labs is the drug design company DeepMind spun out in 2021, led by Demis Hassabis and Max Jaderberg. They raised $2.1 billion in May. → Simon Kohl is building Latent Labs. He was on the core AlphaFold 2 team and set up DeepMind's wet lab at the Francis Crick Institute before starting it. In March they launched Latent-Y, their drug design agent. → Glen Gowers and Oliver Vince are building Basecamp Research, AI models that design DNA and proteins, trained on genetic data they collect with partners in over 30 countries. They raised a $140 million Series C in September. → James Field is building LabGenius Therapeutics in Bermondsey, using machine learning and robotics to design antibodies for solid tumors. → Jake Taylor-King co-founded Relation, where Rosie Rodriguez is President of Growth. They train AI on human cell data to find new drug targets, and GSK expanded its partnership with them in July. → Kerstin Papenfuss is building Big Picture Bio, using AI to design cancer drug combinations. → Pedro Correa de Sampaio is building Neobe Therapeutics, engineering bacteria that colonize solid tumors and break down the fibrotic barrier around them, enabling immune infiltration. → Max Jamilly is building Hoxton Farms, growing real animal fat from cells in their own bioreactors. → Kevin Walton and the team at Baseimmune design antigens computationally so the body builds its own immune response. They are now taking that into lung fibrosis. → Myricx Bio came out of Ed Tate's lab at Imperial, working with the Crick, in 2019. Novartis completed its acquisition in August, paying $1.1 billion upfront. Carolyn Corbet and I will be in London on October 14 and 15 for ELRIG Drug Discovery 2026. Would love to meet people building there. Feel free to reach out!

BioAI Weekly | TechBio & Healthcare AI A weekly snapshot of the biggest funding rounds, partnerships, platform moves and leadership changes shaping TechBio and Healthcare AI - powered by ARTO Week of 21 to 27 September 2026 🔴 Biggest Story Enveda raised a $311M Series E led by Catalio Capital Management at a $2B valuation, double where it stood a year ago, to push three AI-discovered medicines into later-phase trials. Total raised now tops $845M. Congratulations Viswa Colluru, PhD and the team (and for hiring great people like my good friend Dr Douglas Maslin!) 💰 Funding of the Week Basecamp Research closed a $140M Series C led by S32, with Anthropic's Anthology Fund and NVIDIA, to train its next EDEN models and build an AI-designed in vivo cell therapy pipeline. BigHat Biosciences raised a $75M Series C co-led by DFJ Growth and Premji Invest - US, taking total funding to $223M. 🤝 Partnership of the Week Genentech signed a bispecific antibody collaboration with Earendil Labs in oncology: $55M upfront and more than $1.5B in total value. Boehringer Ingelheim signed a multi-target deal worth over $1B with Envisagenics, built on its SpliceCore platform for RNA splicing-derived cancer targets. 🤖 AI / Platform Move Anthropic said Claude found a previously unknown enzyme system in bacteriophage DNA, with a CRISPR-like repeat array, after a 21.5-hour autonomous search of 1.9 billion protein clusters. It is the first result from Anthropic's new biology lab. 🧪 Science Milestone XtalPi Inc. submitted a US FDA IND for KQTD-126, a gut-restricted pan-TRK inhibitor for chronic intestinal pain in IBS and IBD, designed with its AI models and robotic chemistry . 📈 Scale-Up of the Week @Biolevate raised a €30M Series A co-led by RAISE France and @Orange Ventures, with MSD's Global Health Innovation Fund, and opened a Boston office to build its US business. 👤 Leadership Move ProQR Therapeutics appointed Chris Hart as Chief Data and AI Officer and added Hugging Face co-founder Thomas Wolf to its board as strategic AI advisor. ImmunoScape named Peter Olagunju as CEO as its cancer T cell therapy platform moves toward the clinic. 🔥 Company to Watch Azulene Labs. The Berkeley startup raised a $3.4M pre-seed led by Ground State Ventures to build physics-based foundation models for drug and materials simulation, trained on quantum-mechanical data. “Chemistry should work the way aerospace engineering already works, where you design the thing in a computer, you believe the answer, and the physical object behaves as predicted the first time you build it.” Nicolas Sawaya, Co-founder If you want the full monthly report (BioAI Monthly), send me a message and I will send it to you directly. #TechBio #HealthAI #biotech

BioAI Weekly | TechBio & Healthcare AI Week of 5 to 11 October 2026 🔴 Biggest Story: Biohub Virtual Biology Initiative reached $1.8B in commitments. Google DeepMind, Isomorphic Labs and Meta put in $300M between them, alongside more than $500M each from the US Department of Energy and NIH, to build open cell data for predictive AI models of biology. 💰 Funding of the Week: Iambic Therapeutic set terms for a $150M Nasdaq IPO under the ticker IAM, at up to an $806M valuation, and submitted an IND for IAM217, its second AI-designed cancer candidate. WhiteLab Genomics raised a $26M Series B led by @AVP, with Debiopharm and Omnes returning, for its AI-designed genomic medicines. 🤝 Partnership of the Week: GSK expanded its work with Chai Discovery into a collaboration after its own wet-lab tests found binders to every target it tested from Chais zero-shot designs. 🤖 AI / Platform Move: Danaher will open its first autonomous AI lab at Abcam in early 2027, with robotics and orchestration built with Automata, aiming to cut the time from concept to validated antibody reagent by up to eight times. 🧪 Science Milestone: CHARM Therapeutics dosed the first patient with CHM-029, a menin inhibitor for AML designed on its DragonFold co-folding model, under 24 months from first synthesis. 📈 Scale-Up of the Week: Multiply Labs raised a $75M Series B led by Patrick Soon-Shiongs NantWorks, with AstraZeneca joining, to scale robotic manufacturing of cell and gene therapies and grow its engineering, regulatory and commercial teams. 👤 Leadership Move: Formation Bio hired Anirvan Ghosh as SVP, Head of Translational Sciences. He was CEO of UNITY Biotechnology and led research and early development at Biogen. 🔥 Company to Watch Lila Bio. The Seattle spinout from David Bakers lab designs miniprotein radioligand therapies for cancer, and has hired Kimberly Ma, formerly of RayzeBio, as Chief Development Officer. "That's exactly the experience we need as we take our innovative radioligand therapy programs into the clinic." Jake Kraft, Ph.D., CEO If you want the full monthly report (BioAI Monthly), send me a message and I will send it to you directly. #TechBio #HealthAI #biotech

Basecamp Research Raises $140M to Advance AI-Designed In Vivo Cell Therapies - https://lnkd.in/euEtXpbU Basecamp Research, a frontier AI company developing AI-designed medicines, today announced a $140M Series C financing to train a new generation of EDEN models and advance a pipeline of AI-designed therapeutics towards clinical development. Basecamp’s ambition is to develop cures for diseases that remain incurable by designing medicines that reprogram the body to repair itself. The company combines frontier AI models trained on proprietary biological data with technology for writing DNA sequences into cells. “We believe the future of medicine lies in reprogramming the body to repair itself. We design the models and the medicines to teach it how,” said Glen Gowers, co-founder and CEO of Basecamp Research. “AI-based approaches promise to change what’s possible for patients who currently have few alternatives. This funding brings this technology closer to those who need it most.” Andy Conrad, General Partner at S32 and former CEO of Google’s Verily, who joins the Board of Directors, said: “AI is opening up new possibilities across every part of society, but perhaps nowhere is the potential more meaningful than in human health. The ability to combine AI, biological data and scientific insight could transform how we understand disease, discover medicines and ultimately improve and extend people’s lives. Basecamp Research is building an important technology platform at the center of that opportunity.” At the centre of Basecamp Research’s AI platform is the Trillion Gene Atlas, the world’s largest proprietary biological AI training dataset. Built with partners including NVIDIA, Anthropic, PacBio and Ultima Genomics, the Atlas draws on biological data collected through access and benefit-sharing partnerships in more than 30 countries across all seven continents. Read more at: https://lnkd.in/euEtXpbU #ai #celltherapy #stemcell

Basecamp Research Raises $140M to Advance AI-Designed In Vivo Cell Therapies - https://lnkd.in/eQf7f7YK Basecamp Research, a frontier AI company developing AI-designed medicines, today announced a $140M Series C financing to train a new generation of EDEN models and advance a pipeline of AI-designed therapeutics towards clinical development. Basecamp’s ambition is to develop cures for diseases that remain incurable by designing medicines that reprogram the body to repair itself. The company combines frontier AI models trained on proprietary biological data with technology for writing DNA sequences into cells. “We believe the future of medicine lies in reprogramming the body to repair itself. We design the models and the medicines to teach it how,” said Glen Gowers, co-founder and CEO of Basecamp Research. “AI-based approaches promise to change what’s possible for patients who currently have few alternatives. This funding brings this technology closer to those who need it most.” Andy Conrad, General Partner at S32 and former CEO of Google’s Verily, who joins the Board of Directors, said: “AI is opening up new possibilities across every part of society, but perhaps nowhere is the potential more meaningful than in human health. The ability to combine AI, biological data and scientific insight could transform how we understand disease, discover medicines and ultimately improve and extend people’s lives. Basecamp Research is building an important technology platform at the center of that opportunity.” At the centre of Basecamp Research’s AI platform is the Trillion Gene Atlas, the world’s largest proprietary biological AI training dataset. Built with partners including NVIDIA, Anthropic, PacBio and Ultima Genomics, the Atlas draws on biological data collected through access and benefit-sharing partnerships in more than 30 countries across all seven continents. Read more at: https://lnkd.in/eQf7f7YK #ai #celltherapy #stemcell

🧬 What if AI could help researchers know sooner whether a cancer treatment is actually working? Developing a new cancer treatment can take years. And one of the biggest challenges isn't simply discovering a potential therapy — it's determining as early and reliably as possible whether that therapy is producing meaningful outcomes. Could AI help reduce the time between a clinical trial beginning and researchers understanding whether a treatment is working? Toronto-based Altis Labs has raised US$25 million in Series A funding to expand its AI-powered platform for clinical trials across additional cancer types and increase deployments with global biopharmaceutical partners. Its AI model, IPRO, analyzes radiology scans and generates survival predictions. In a post-hoc analysis of Johnson & Johnson's Phase 3 MARIPOSA lung-cancer trial, Altis reported that its AI endpoint detected a treatment effect 11 months before the trial's primary progression-free-survival result and 26 months before the final overall-survival result. These are reported study findings, not a guarantee that AI will improve every trial. AI in healthcare shouldn't simply be about replacing an existing process with an algorithm. The real opportunity is to make existing data more useful while keeping clinicians, researchers and regulators in the loop. That means: 🔹 Turn existing medical data into actionable insights Healthcare organizations already generate enormous amounts of imaging, clinical and outcomes data. AI can potentially help extract patterns that are difficult to identify manually. 🔹 Move from reactive to predictive Instead of waiting until the end of a long process to understand outcomes, AI can help identify meaningful signals earlier. 🔹 Protect sensitive patient data The more healthcare organizations use AI, the more important privacy, cybersecurity, data governance and secure infrastructure become. 🚀 Industries That Could Benefit 🏥 Healthcare & Hospitals 🧬 Biotechnology 💊 Pharmaceuticals 🔬 Medical Research 🩻 Medical Imaging 🧪 Diagnostics 💻 HealthTech & AI Software 🛡️ Healthcare Cybersecurity What if the next major healthcare breakthrough isn't only a new drug — but a better way to understand whether that drug is working? AI could potentially help researchers move faster. But the real challenge is building systems where: AI + Clinical Evidence + Human Expertise + Secure Data = Better Healthcare Decisions Where do you think AI could make the biggest difference in healthcare over the next 5 years? Clinical trials? Medical imaging? Drug discovery? Diagnostics? Patient care? I'd be interested to hear what you think. 👇 Follow NorthTech Daily for insights on Canadian AI, startups, healthcare technology and emerging innovation. #AI #ArtificialIntelligence #HealthTech #HealthcareAI #CancerResearch #Biotech #Pharma #ClinicalTrials #MedicalAI #CanadianTech #TorontoTech #Innovation #NorthTechDaily

OXFORD IS BUILDING AN AI SCIENTIST TO HELP DEVELOP PERSONALISED CANCER VACCINES AI in life sciences is moving beyond analysing data and supporting individual tasks. Researchers at Oxford are developing Ciara, an AI scientist designed to work alongside human researchers and potentially accelerate the development of personalised cancer vaccines. The project is backed by the UK’s Advanced Research and Invention Agency (ARIA). (The Times⁠) KEY FACTS Ciara is being developed to: • Read and interpret scientific literature • Generate scientific hypotheses • Design experiments • Direct robotic laboratory equipment • Learn from experimental results • Help identify and rank neoantigens for personalised cancer vaccines The ambition is significant. The Oxford team hopes the technology could ultimately contribute to personalised cancer vaccines reaching clinical trials for prostate cancer, melanoma and glioblastoma within four years. (The Times⁠) Human oversight remains important. Changes to robotic laboratory instructions require approval from two scientists and experimental actions are logged and reviewed. (The Times⁠) WHY IT MATTERS This is an important example of where Agentic AI could take life sciences. We are moving from AI that answers questions and analyses datasets towards systems capable of participating across the scientific workflow: LITERATURE → HYPOTHESIS → EXPERIMENT → DATA → LEARNING → NEXT EXPERIMENT ARIA describes the wider concept as AI Scientists, autonomous systems capable of reasoning, planning and executing experiments with reduced continuous human intervention. (Aria⁠) THE BIGGER PICTURE If these approaches prove scientifically reliable, safe and capable of operating within appropriate regulatory frameworks, the implications could extend well beyond cancer vaccines. Drug discovery and development could increasingly combine: SCIENTISTS + AI AGENTS + ROBOTICS + AUTOMATED LABS + HIGH-QUALITY DATA The opportunity is not about removing scientists. It is about potentially increasing the speed and scale at which scientists can test hypotheses and generate evidence. That could become one of the most important applications of Agentic AI across life sciences. Source: ARIA – AI in Science / AI Scientists https://lnkd.in/eijPyHu7 Follow Graham Sanders for global updates across Pharma, Biotech, CRO & AI This post is provided for informational and educational purposes only and is based on publicly available information. It does not constitute financial, investment, medical or legal advice, nor an endorsement of any company or product. Company names, trademarks and logos remain the property of their respective owners. #ArtificialIntelligence #AgenticAI #LifeSciences #Biotech #Oncology #CancerResearch #DrugDiscovery #PersonalisedMedicine

Issue 94 of the Cambridge Biocapital newsletter is out. Last Tuesday, the government accepted all 44 recommendations of the National Commission into the Regulation of AI in Healthcare. Its central call is for AI medical devices to be assessed and monitored throughout their working life, rather than once. The same day, Skin Analytics announced that DERM will go live in all 18 NHS South East trusts, extending AI skin cancer triage to a further 9 million people. DERM is certified for autonomous use, so patients with benign lesions can be discharged at triage while higher-risk cases go to a specialist. According to Skin Analytics this is the largest deployment of autonomous medical AI in NHS history. More in this week’s Cambridge Biocapital newsletter: https://lnkd.in/eYZZJBQQ Featured this week: Sensible Biotechnologies, Sava, RoslinCT, MintNeuro, Cori Clinical, MiAlgae, The University of Manchester, Imperial College London, University of Warwick, STFC, RQ Biotechnology Ltd., Advanced Research + Invention Agency (ARIA), Oak Hill Bio, Ochre Bio, Skin Analytics, AviadoBio, Oxford Brain Diagnostics Ltd, CHARM Therapeutics, Aide Health, Bitfount, OncoBayes, Shift Bioscience, ViiV Healthcare, AstraZeneca, Cancer Research UK (CRUK), NHS Blood and Transplant, GSK, Theramex, OKYO Pharma, Bio-Techne, UCL

🇫🇷 Paris-based genomic medicine firm WhiteLab Genomics has raised c.€23m in Series B financing to scale its artificial intelligence platform for drug delivery design. ⠀ Founded in 2019 by David Del Bourgo, Lucia Cinque, and Julien Cottineau, the BioTech venture utilises its proprietary ALFRED platform to engineer viral and non-viral delivery vehicles for targeted therapies. ⠀ The technology helps genetic treatments navigate complex biological barriers, having demonstrated successful brain-targeting capabilities in collaboration with the Paris Brain Institute. ⠀ The funding round was led by global platform AVP, which manages over €2.5bn in assets, with participation from new backers Yaday Health and Blast Club alongside existing investors Omnes Capital and Debiopharm Innovation Fund. ⠀ Following the transaction, François Robinet of AVP and Dr Daniel Teper of Yaday Health will take seats on the board of directors. ⠀ The capital will support the expansion of in vivo validation work across non-viral technologies, while accelerating international growth across Boston, the West Coast, Japan, and South Korea. ⠀ 🚀 €23.2m Series B round led by AVP to advance AI-driven genomic medicine design. ⠀ 🚀 Proprietary ALFRED platform optimises adeno-associated viruses, lipid nanoparticles, and programmable payloads. ⠀ 🚀 Research partnerships established with biopharma leaders including Sanofi, Cytiva, and Institut Imagine. ⠀ 🚀 Expansion plans focused on scaling North American operations and entering Asian markets. ⠀ WhiteLab Genomics is well positioned to unlock new treatment possibilities for complex neurological and genetic conditions through precision molecular design.

🔬 What if you could see what a drug does to a cell, and predict whether it will kill a tumor, from images alone? I built PhenoScreen Viewers, an AI imaging tool for drug discovery that turns microscope images into answers scientists can see, check and act on. 🧫 CELL VIEWER (Cell Painting) • Automatic segmentation of every cell and nucleus → no manual outlining; thousands of cells measured in minutes • Cells colored by abnormality vs untreated (DMSO) cells → spot active compounds at a glance • 5-stain toggles (DNA, ER, RNA, actin/Golgi, mitochondria) → see which organelle a drug affects • Click a cell for its per-stain view and top changed measurements → turns an AI score into biology 🎞️ TIME-LAPSE VIEWER (tumour organoids) • Every organoid tracked across the whole movie → follow each ones fate, not just well averages • Death predicted from the first 24 h of brightfield, with no stain → earlier answers and less destructive assays (cross-validated AUROC 0.75 on a published pancreatic cancer dataset) • Death-stain overlay → check every prediction against ground truth • Per-organoid growth and death curves → separate drugs that slow growth from drugs that kill • Contact sheet of all wells by dose → dose-response visible across the plate at once • Option to train on your own organoids → adapts to new cell lines and assays • Vision Transformer attention maps → shows where and on which stain the AI looked, so results can be trusted • Treated vs untreated cells side by side → instant visual confirmation of a hit ⚙️ BUILT FOR THE LAB • Single image or whole-plate upload (files, folders, .zip) → from one quick check to a full screen • Wells, stains, time points and doses read from file names, plus plate-map import → minimal setup • Models trained once and re-used → every new experiment gets faster • Runs locally in the browser → sensitive data stays in-house 💡 REAL-WORLD USES 💊 Phenotypic screening and hit triage ⚠️ Early toxicity flags before animal studies 🧬 Patient-derived organoid testing for personalised oncology 🔁 Mechanism-of-action and drug-repurposing studies 🏥 High-content imaging for pharma, biotech, CROs and academic labs Stack: Python, PyTorch (DINO self-supervised ViT), Cellpose, multi-object tracking, gradient boosting, Flask. This continues my work in medical imaging AI, from radiology and pathology to drug discovery. Id value feedback from teams doing Cell Painting and organoid work, including Biohub, Pfizer, AstraZeneca, Novartis, Roche, Recursion and Broad Institute of MIT and Harvard What would make this most useful in your workflow?