Jonah Kallenbach

What do bio and health applications mean for the next wave of AI -- specifically about compute? (I'm talking to you NVDA longs!) LifeX Ventures is hosting a super roundtable with some serious techbio leaders tomorrow along with Analog Century Management's Val Zlatev -- come hear Thomas Clozel Sean McClain Chetan Patel at 11am ET For the survey results based on asking 100 techbio CTOs and CEOs, join the call. Here, my own speculations after wrapping up the report: -- Amazon needs to have a GPU program on warp drive right now -- Nvidia needs to have a data center / cloud business in the works -- Edge AI chips are about to be everywhere -- in your watch, car, sneakers, thermostats, gene sequencers, spectroscopes -- All this compute needs way more data: expect a boom in sensors of all types -- Remember human genome moonshot that sequenced one person once? Now you can sequence your every cell one by one. Expect that for protein folding (AlphaFold was that moonshot) and other simulation uses, a full "twin" model of you, cell by cell -- Google has no angle here -- worse chips, worse cloud, worse models, worse phones / edge devices -- Specialty silicon for unique use-cases, lower-power, lower-memory are surely coming fast - like back in the day for mobile phones when Qualcomm, Broadcomm, Infineon, Mediatek, etc duked it out.

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“Folks have moved the goalpost on earlier stage companies and are requiring clinical data and are requiring you to go longer with less,” says Cain McClary, MD of KdT Ventures. Who's paying attention to those earlier stage companies? The smaller, more focused #venturecapital firms. Just like we see in #clinicalresearch technology, pioneering, early-stage #biotechs, #medicaldevice, and other #lifesciences companies are best served by an entirely separate ecosystem of funders.

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On the latest Vital Signs, Nikhil Krishnan and I had a ton of fun chatting with Dr. Atul Butte. Dr. Butte is a professor at UCSF, Chief Data Scientist of the UC Health System, and a co-founder of numerous healthcare startups. In our conversation, Dr. Butte shared his takes on healthcare AI opportunities, challenges, hype, and more. A few highlights: ⚡LLM use cases, data, and growth LLMs are already helping to solve the “drudgery” aspects of medicine, such as automatically drafting SOAP notes and patient messages. Dr. Butte is excited about future applications of LLMs that can help with the “cognitive” aspects: with difficult medical problems an LLM might be able to stitch together disparate pieces of information to generate a potentially novel solution. He also highlights that prompt engineering will become the next “coding language” as so much of leveraging LLMs is knowing how to ask them the right questions. Additionally, Dr. Butte discusses how since 2016, UCSF has been working to deidentify its patient notes so that it can query them to answer clinical questions and ultimately enhance patient care. ⚡The need for patient-facing AI As patients are increasingly able to access their own personal health data in nicely structured formats (e.g., EHRs, wearables), they desperately need more tools to help them interpret and make decisions using that data. Dr. Butte understands that these patient-facing solutions are challenging to get funded but he emphasizes that patients need to receive the benefits of AI sooner. ⚡Evaluating healthcare AI solutions In order to evaluate AI solutions, we often put human specialists – such as medical professionals – on the same tasks. Understanding that specialists often disagree with each other, a significant challenge arises in figuring out how we can evaluate AI considering we can’t just “average” all the specialist opinions. Dr. Butte points out that there still remains a massive gap in AI evaluation tools. Additionally, there are so many organizations that want to have a say in how healthcare AI is regulated that the landscape is uncertain. An awesome conversation with an expert on all things AI meets healthcare. Listen to the full episode below: Spotify: https://spoti.fi/3Wr3643 Apple: https://apple.co/4acwgan

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Excited for this one. Congrats to Alex Cohen and Hello Patient on their seed round announcement. Hello Patient stands to change the communication paradigm between patients and providers forever. Their generative AI call agent technology is tackling the tremendous admin burden of patient facing comms (scheduling, follow ups, referrals, prescription refills, etc). Massive opportunity and we think Alex and his team are expertly positioned to become market leaders. Max Ventures is thrilled to co-lead the seed round with 8VC and Bling Capital A great quote below from Alex highlighting the concept of "service as a software". Healthcare is a heavily service oriented industry - so the opportunity for step change is even more profound. The startup's approach is part of a paradigm shift where AI companies are offering service as software. "I'm a big believer that the right way to do this is through a managed services business. We're not building SaaS. I believe we can do this services as software where what was traditionally a services business now has software margins because I don't have to go employ a whole bunch of people to do the services under the hood," Cohen noted. https://lnkd.in/ehNN2AmW

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Excited to share what Nithin Parsan and I have been working on at YC! At Reticular (YC F24), we're pioneering the future of explainable AI for biology. Check out the post and our first technical blogpost linked in the comments to learn more about what we're focused on.

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Good Q&A with Dash Bio co-founders on their story going from Moderna to a startup and how they intend to use AI and robotics to transform clinical bioanalysis https://lnkd.in/gmmiq4dQ

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I'm so excited to continue supporting Prolific Machines, Inc., and the incredible Deniz Kent, PhD ,Max Huisman, and Declan Jones. Today's cellular biology processes are incredibly expensive, inefficient, imprecise, and sometimes purely ineffective. These processes are used from everything from making antibodies to treat diseases, to fermentation used to make high-value nutritional proteins in baby formula, to whole cuts of cultured meat. Prolific has developed a biology platform that leverages light to guide cell behavior and optimize performance over time using AI. By combining light, bioengineering, hardware, and AI in fundamentally new ways, Prolific can help pharmaceutical, nutritional, and therapeutics companies get to market faster, less expensively, and more efficiently — ultimately in hopes of helping improve outcomes — a mission any of us can get behind. Mark Cuban Peter T. Frederick Blackford Cooper Rinzler David Adelman Darco Capital Breakthrough Energy Michael Schulson Kevin Love Tobias Harris Breyer Capital Charles Besser Brennan Besser Lettuce Entertain You Restaurants https://lnkd.in/ea2TqdQk

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Sometimes investors unintentionally become jerks. I really believe most investors are good people and mean well. But over time with an endless email pile, heartbreak, constantly saying no....they can get jaded. We have to be aware of our own mindsets. Or it can be too easy to go down the wrong path. One of the things I value the most about the NFX team is that we always give honest feedback to each other. We want to be the investors we wish we had when we were running our companies. This might be spicy, but this is what investors owe founders (and when you can call them out): https://lnkd.in/dUPuwJvg 

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At the annual Decoding Bio summit, I sat down with Brad Loncar of BiotechTV to discuss how we at Bessemer Venture Partners are thinking about where value accrues for AI in biotech. The short answer: Ultimate value accrues at the therapeutic level. Longer answer: If AI improves drug discovery along any axis (speed, efficiency, cost, new biology, novel chemistry), and becomes a near-ubiquitous tool in the discovery process, value will accrue up the stack. Vertical integration of discovery and development will be essential to capture this value, and the greatest moats will (still) be built in clinical development – trial design, biomarker identification, indication selection, and raw execution.

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NYC is undisputedly the best place to build in healthcare AI 🏥 , sitting at the intersection of exploding tech/AI momentum + matured healthcare/life sciences economy, with all-time-high venture + gov funding + R&D scientists Had a ton of fun hosting an intimate healthcare-centric dinner tonight with researchers, engineers, founders, health system operators, and physicians from Tandem, Tennr, Mount Sinai Health System, Google DeepMind, Counsel Health, EliseAI, Neo, Weill Cornell Graduate School of Medical Sciences, Inductive Bio, NYC Health + Hospitals with John Bryson (Banc of California) Lots of excitement all around, coupled with some frustration with the deeply brokenness of U.S. healthcare - some of the hot takes / promising areas we talked about: - If your healthcare AI startup’s product is on Epic’s roadmap, you have no chance of winning, as health systems would much rather adopt an okay solution from Epic ⏳ - AI scribing tools have not meaningfully evolved since v1 📑 - Healthcare will get much worse before it gets better - the U.S. society is totally unprepared for the silver tsunami / rapidly aging population 👵 (Visible Ventures portco Grayce is tackling this problem!) - Better retrieval of medical records with precision on what part of a patient’s records is relevant to diagnostics will unlock huge time savings for doctors (and correct their human errors) 🔬 - Improving scientific reasoning abilities of frontier models will lead to better reasoning in diagnostic workflows, which is currently under-explored due to difficulty of finding high-quality benchmarks 🧠 - Startup founders can’t build a durable, venture-scale company on the sole basis of prior auth 🛣 - Machine learning models are speeding up DFT calculations significantly, enabling improved analysis and understanding of biomarker systems 👩‍🔬 - We will live in a future where pharmacy benefit manager (PBM) is obsolete 💊

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📈 ‘Founder mode’ -  This has suddenly become the buzziest buzz term in the tech world, coined by @Paul Graham, co-founder of Y Combinator. It’s about running a company like a founder would, vs. ‘manager mode,’ where professional managers take over. Graham argues founder mode is far superior, especially in early-stage startups. He criticizes VCs and MBA graduates for mismanaging companies. 🧠 “Hire good people and give them room to do their jobs. Sounds great when it’s described that way, doesn’t it? Except in practice, judging from the report of founder after founder, what this often turns out to mean is: hire professional fakers and let them drive the company into the ground.” https://lnkd.in/eyWtgWEH 📍The piece reminds me of an interview with Vinod Khosla, then at Khosla Ventures, where he castigated venture capitalists for sitting on boards and attempting to manage companies without any real understanding of how to grow a business. 🤔I agree—founder mode is crucial in the early days, but once a company hits 100+ employees, the balance between founder and manager modes may begin to shift. And the transition can be hard. ❓Fellow agrifoodtech entrepreneurs, do you think this applies to our sector as well?

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I’m excited to share my recent conversation with Joel Beasley | Modern CTO on the Modern CTO Podcast. We discussed my pivot from clinical medicine to the founding of Northpond Ventures, focusing on practical lessons from career transitions and the real-world impact of biotechnology innovations. Here are some of the highlights:  1. How I managed to reshape my career around personal strengths and market needs 2. The importance of support systems in overcoming professional challenges 3. How venture capital can drive scientific innovation into marketable solutions 4. An overview of Northpond Ventures’ strategy in fostering partnerships with leading academic institutions You can listen to the full episode here: https://lnkd.in/eGDzY98h #Biotechnology #Tech #Leadership #CareerChange #VentureCapital #Entrepreneurship

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“I was super attracted to math because I really loved going into questions I didn't know exactly how to solve. Figuring out new ways and being creative with solutions.” In Part 1 of The Biotech Startups Podcast conversation with Immunai CEO, Noam Solomon, a big theme is the love for problem-solving and creativity in mathematics. In this episode we talk about: – Noam’s early passion for mathematics and his unique educational journey, starting university at age 14 – The importance of critical thinking and creativity, and how these skills are foundational for both academic and entrepreneurial success – The solitude and resilience required during his PhD studies, and how these experiences prepared him for the challenges of entrepreneurship – Transitioning from academia to the biotech industry, and the realization that making a real-world impact often requires stepping outside of academic circles It’s another fascinating journey into the mind of a biotech leader, packed with insights and valuable lessons. Head over to Apple Podcasts or Spotify for this episode and more stories only a biotech exec can tell! #biotechnology #lifesciences #podcast

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At Innosphere Ventures, we’ve assessed 50+ Life Sciences startups, and we’ve noticed a trend among founders: to successfully solicit funding from investors, they need to create balance in their go-to-market strategies to be investor ready. This isn’t a surprising finding, given the majority of our founders’ status as first-time founders and academic entrepreneurs. We have amazing university partners, so the companies that they refer to us are excellent at their product and the science, they often have the foundation of a really great team, and they are on their way to a strong intellectual property strategy. But they tend to underbake the less academic parts of their investor-ready story. That’s where our Incubator comes in: to help founders balance their commercial model and story so that they’re ready to approach potential investors with an airtight business plan. With the right development, regulatory, clinical, and financial plans in hand, they’ll be able to convincingly pitch to investors how they plan to get revenue and traction, how they plan to get investors’ money back, and how they’ll generate growth… all music to investors’ ears. Our Incubator takes talented, knowledgeable founders, identifies any investor-readiness needs in their skill sets, and fills them in with critical go-to-market knowledge. That way, when they approach investors, they’ll have the full suite of product, science, and GTM know-how to successfully win funding.

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AI and Med Tech in Focus   AI Used to Assess IVF Embryo Quality Researchers at Weill Cornell Medicine have developed a novel machine learning system called BELA that can accurately assess the chromosomal quality of IVF embryos using time lapsed images and maternal age. The system distinguishes whether an embryo has normal or abnormal numbers of chromosomes and is not based on subjective interpretation. Currently, IVF embryos are manually examined under a microscope and if a problem is suspected, a more risky biopsy-like procedure is done. BELA uses machine learning algorithms to analyze nine time-lapsed video images taken over five days to generate an objective score. That score is coupled with maternal age to predict whether the chromosomes are normal or abnormal. BELA results have been shown to be more objective, accurate, efficient and predictive. It is hoped that the system could be used to expand the availability of IVF to areas that don’t have access to current high-end testing and have efficacy to assess more general embryonic development. VC Investors are always adjusting their "Play Book" with a variety of options for investing. Mikal Ventures is one of those alternatives, offering curated solutions to real world problems. Reach out if you have questions on how we can be of assistance and bookmark https://mikalventures.com/ for additional insights and information.

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Hot off the pre-print server – an important publication authored by the Atropos Health team exploring the performance of LLMs in answering real-world clinical questions. LLMs excel at summarizing and contextualizing existing literature, but cannot generate de novo medical evidence today. The results of the study highlight performance gains attributable to injecting novel, relevant, and up-to-date medical evidence into LLM-powered clinical decision support systems. Brigham Hyde Nigam Shah Saurabh Gombar Read the study here: https://lnkd.in/ecuU25Pq

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We are poised for a revolution in biotech that will be uniquely enabled by computers. Across the market, we are seeing biotechs and biopharma restructure research roadmaps and strategies around computing due to a perfect storm of developing trends: 1. The tooling is getting better. Assays are able to measure a broad array of molecules at a falling cost and increasing throughput. Look to Scale Biosciences, Curio Bioscience, AtlasXomics Inc. for inspiration. We are sequencing millions of single cells and building spatial maps of the molecular state of tumors. After two generations of "next-generation sequencing", and stagnating DNA read costs under the monopoly of Illumina, this wave of the new assays will have a profound impact on the iteration speed and scale of experimentation. 2. Biotechs are using data to guide decisions and are incorporating domain informed machine learning as a core part of the molecular design process. There is great synergy here with better tooling as a means of abundant, cheap data. Look to Recursion, Manifold Bio, Dyno Therapeutics, Asimov. Models are starting to do useful things, like generate functional gene editing proteins and entire prokaryotic organisms. Look to ESM (Arc Institute), AlphaFold3 (Google DeepMind), RFdiffusion. 3. New classes of therapies - genetic medicines and engineered immune cells - are having real success in the clinic. One dose cures for cardiovascular disease (Verve Therapeutics w PCSK9), vaccines for cancer (Moderna w mRNA 4157), in-vivo gene editing proteins (Ensoma, CRISPR Therapeutics, Beam Therapeutics), metabolic disease (Novartis, Eli Lilly and Company w GLP-1/GIP modulators) are being dosed in real people right now. 4. The AI craze is commoditizing accelerated hardware (NVIDIA), fast storage devices like NVMes and maturing the systems tooling for moving around lots of data between computers. One happy accident of this bubble will be the reuse of these components to build a new systems stack for the large scale processing of molecular data. This will be very important to construct a 1 billion single cell atlas and beyond. 5. Language models might be the perfect tool to distill the unstructured corpus of public data and literature sitting around on the Internet into real biological insights for scientist asking questions in natural language. 6. There is an appetite from the market for new applications of biotech beyond drug development. Bacteria driven lithium mining (Maverick BioMetals), cell agriculture (Aleph Farms, Hoxton Farms), early signs of consumer biologics (Geltor) and biofoundries (Ginkgo Bioworks, Inc.). Some of the greatest minds of our generation will want to do more than perturb the human body with therapies. One of the great joys of building LatchBio is working with many of these companies and watching these trends unfold each day in real time. We are doing our part to incubate and disseminate a new class of software tools to the industry.

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Thanks for the interview Connie Loizos. More to come about investments yet to be announced and the founders who are working every day to build in these spaces. Excited to have shared the gamut across where we invest from Earth to TimberEye to Monaire. We're investing out of $440m under management across 3 funds and are thankful every day that we started this focused fund to partner with entrepreneurs who are ready to turn the last bastion of old world industries into tech sectors. The physical world is driven by huge industries that need to change...and not simply by completing work incrementally better or by fitting into existing buying cycles and budgets. Many of our companies are totally reinventing how products are made or services are delivered and their customers win. We want to see more of this in every sector including industrial, transportation, energy, defense, space, manufacturing to name a few. https://lnkd.in/e-TqpvFh

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