Nate Bremmer

ShiftRx is announcing our $3.5M seed round today (see Axios announcement here: https://lnkd.in/gVqMiGea ) led by Work-Bench, followed on by Opal Ventures, Tau Ventures, Inflect + more. My co-founder Autumn-Kyoko C. and I started this company a little over a year ago as an attempt to fix U.S. Healthcare staffing. You can read her letter here (totally sappy but, very much true): https://lnkd.in/gnFdJy6C When I started my career as a pharmacy technician at CVS Health 10+ years ago, I was working full-time and pursuing the goal of being a PharmD. I chose this path after watching my dad battle colon cancer and being hands-on with his medications and treatment plans. Many pharmacists I worked with tried to talk me out of this goal, and told me “it’s not the same as it used to be”. But for me, this mission was very much personal. I hadn’t initially asked myself, why can’t we be the ones to change it? Around the time I got accepted into a pharmacy school, my dad passed, and I ended up taking a corporate job instead. This was one of the hardest decisions for me to make. I was unsure if the years I had spent working towards this goal had been wasted and if what I had done, had really made an impact. It was then, I committed to making the change I wanted to see. I quit my job and co-founded ShiftRx. I can say with absolute certainty today that the lessons I have taken with me were not lost, and that healthcare was not what it once was. That is why we are on a mission to make it better than before. It starts with us -- as current healthcare providers, former providers, patients, and advocates. #ShiftTogether

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AI and Med Tech in Focus   AI System Developed to Identify Pathology in Tissues Engineers at Washington State University have developed an AI tool that uses images of human and animal tissue to detect abnormalities faster and more accurately than people. The AI algorithm was trained using images from past studies that involved kidney, testes, ovarian, prostate, breast and lymph node abnormalities. The new model detected disease in minutes—current processes take humans several hours and require specialized teams to check each other’s work. It was also found to be more accurate, sometimes detecting instances that humans had missed. The engineers designed the system to handle the processing load of the high-resolution gigapixel images by breaking them down into smaller tiles but still retaining the overall context of the tissue sample—akin to the zoom feature on a microscope or phone camera. Aside from getting diagnostic results more accurately and quickly, the new system also shows promise in epigenetics (the study of molecular processes that change gene behavior without changing underlying DNA). Epigenetic researchers can perform analyses and get results that used to take a year or more in just a couple of weeks. 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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Great article on Biolinq in IEEE Spectrum!

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This is just incredible. Neal Ghosh's demonstration of how #VentureIQ takes deeply technical and complicated content across a range of industrial use cases and ages/stages through an AI-generated conversational podcast (a la #notebookLM) is really mind-blowing. Check out his post, below, and if you haven't seen VentureIQ, yet, let's get you set up to learn more. You can visit VentureIQ.ai or DM any of us over here to book a demo!

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Adam Keating discussing how AI is going to change manufacturing and how CoLab Software is helping them make that transition with ReviewAI

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As an entrepreneur, the journey to product-market fit often feels like walking a tightrope—balancing between speed, learning, and adaptation. Michael Seibel's advice is a powerful reminder: launching ‘something bad’ is not about compromising quality but about accelerating learning. Startups don’t grow in isolation; they grow through real user feedback, hard questions, and rapid iteration. The key is to stay close to your users, listen actively, and hold the solution lightly while embracing the problem fully. This approach not only builds better products but strengthens the resilience of your team and your mission. Remember, feedback isn’t just an input; it’s the foundation of growth. Let’s focus on progress, not perfection.

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We need to 'concretize' aging clocks to accelerate discovery in the biology of aging - Martin Borch Jensen and I just wrote a Norn Group call to action proposing the path for robustly validating aging clocks to the point of replacing lengthy lifespan studies. The vision? Accelerating pivotal experiments 2-10x, by extending preclinical lifespan studies to generate the data needed to benchmark the forecasting power of clocks. Full piece: https://lnkd.in/e97YZGZV Research on the biology of aging is held back by the lengthy timelines of experimental studies involving natural aging. The consequence is that we face an enormous hurdle - time - in developing life-saving therapeutics that target this biology to make a difference in prevalent chronic conditions (neurodegenerative disease, sarcopenia, heart disease, and many more). Biomarkers of the aging process (aging 'clocks') would unlock faster breakthroughs, laying the foundations for surrogate endpoints in human clinical trials, just like cholesterol became adopted as a surrogate endpoint for cardiovascular death. Many clocks have been proposed in the last 13 years, but no definite process for validating their predictive power exists. We envision the Clock Assessment Program (CAP) as a gold standard for benchmarking aging clocks, deployed to accelerate preclinical discovery by reducing the amount of time it takes to identify interventions that meaningfully shift survival curves. Instead of waiting 30 months or more for mouse experiments to finish, CAP-validated clocks will predict eventual endpoints (lifespan, frailty index at a given age, etc.) at earlier timepoints (e.g., 12 and 18 months of age) with sensitivity and specificity that clears a high bar. To no longer wait three years for each preclinical lifespan study, to not take up a decade to validate life-saving therapies that treat universal age-related diseases, we need a rigorous, visionary program to enable progress. Now is the time to concretize. We invite you to join us in tackling or sponsoring this initiative, and reach out to us for further discussion.

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Excited for DCVC portfolio co Alta Resource Technologies to emerge from stealth! The design space of biology is many orders of magnitude larger than inorganic chemistry, and Alta uses it to massively reduce the cost of extracting rare earth metals. https://lnkd.in/g_q5UwRF

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Berkeley SkyDeck is offering cash, resources, and critical introductions for admitted startups to its next cohort. Founders, review Darren Cooke’s great summary for health startups and other multi-stakeholder startups to convey your value proposition to potential investors and partners. I would like to add: Please include the data showing how you have validated your value proposition by talking to many, many decision makers. You must validate the key aspects of your business model with customer data to attract the key resources and partners you need to go from vision to reality. You can do this! 💪🏼 Go Bears 🐻! #startups #venturecapital #innovation #entrepreneurship | University of California, Berkeley | University of California, Berkeley, Haas School of Business | UC Berkeley Innovation & Entrepreneurship

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Come join Marc Bouchet and me at The Drop to discuss the juicy topic of Next Generation #Grid #Hardware We will discuss: ​​What does the utility of the future look like? What are the main barriers preventing the deployment of innovative grid hardware? ​How have startups tackled these barriers? ​How do these startups become venture-style investments? We'd love to hear from you – what other questions should we be discussing?

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Most folks engage with us early in their product development process. Much of the time, we are a great fit for the manufacturing but NOT the product development. Naturally, we look to lean on our network and make introductions to product development firms. The innovators inevitably ask us -- How do we choose the right Product Development firm for our project? (that will be another post for another day. go talk to 3-5 firms, in different places, at different sizes, and see who you like) The NEXT question folks ask is -- How much will this cost? ($100,000 - $1,000,000 is a canned answer) Ok, really though, hourly rates range from $75 to $500+, why the disparity—and how do you decide what’s right for you? Again, SUPER high level. Every project is different. BUT, at a glance... Here’s a quick breakdown: 1️⃣ Hourly Rates Vary by Expertise: Small firms/freelancers: $75–$150/hour Mid-sized firms: $150–$300/hour Large, specialized firms: $300–$500+/hour The differences are often due to experience, location, tools, and risk management. I am also seeing more firms do away with hourly and swap to a monthly retainer or per-project / per-stage fee structure. 2️⃣ How to Decide What Fits Your Needs: Low Budget (<$50k): Startups and simple designs? Freelancers or small firms can work great. Mid-Range Budget ($50k–$150k): For balancing expertise and cost, mid-sized firms are ideal. High Budget ($150k+): Complex, regulated projects? You’ll need a full-service partner. 3️⃣ Find Your Perfect Match: Define your goals: What stage are you in—ideation, prototyping, or scaling? Evaluate portfolios: Look for firms with experience in your product’s niche. Start small: Test with a limited-scope project before committing to the full journey. Maybe toe in the water with a feasibility study. 4️⃣ Domestic vs. Overseas Firms: USA-Based Firms: Offer closer collaboration, reduced communication gaps, and a better understanding of local compliance requirements. Ideal for high-touch projects or when speed to market is critical. Overseas Firms: Typically more cost-effective but may involve longer lead times, language barriers, or timezone challenges. Best suited for well-defined projects with clear deliverables. 💡 Pro Tip: Don’t overlook mid-sized firms for their mix of efficiency and expertise, especially for scaling production or optimizing designs for manufacturing. What questions do you wish you could ask a PD firm? I am toying with the idea of an interview series... Throw some questions in the comments that you'd like to have answered by subject-matter experts.

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ThermoMPNN rapidly predicts point mutations to proteins for changes in stability. This neural network achieves state-of-the art performance on the Fireprot benchmark, and returns predictions in a less than a minute. Try it out on Tamarind Bio: https://lnkd.in/gSCbrpDH Paper:https://lnkd.in/gCXQwUTS

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I've had no time or space (pun intended) to share this, but ... ... recently I had the most fun putting pen to digital paper with Samuel Winnall from Next Sequence® and co-writing the last article in his #SpaceBio article series Biomanufacturing is tough. Drug formulations are more complex than ever, capacity to produce biologics is lagging behind demand, lab to production scale remains poorly predictable. Should we perhaps venture out to space to resolve these challenges? Find out our thoughts here: https://lnkd.in/eMGb9Te4

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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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I worked in a CRISPR lab during my bachelors and this is insane: Profluent, a Berkeley startup, has created AI that generates novel CRISPR gene editors. The AI learns from analyzing vast biological data to create editors that have never existed in nature. And for context prior to this, CRISPR methods used mechanisms found in nature to explore new variations. This breakthrough points to a future of battling disease with greater precision and speed. And even crazier, Profluent literally open-sourced one of these AI-generated editors, OpenCRISPR-1, for free experimentation. While still very early, this technology holds immense potential. And in my personal opinion, could be the potential gateway for personalized medicine. AI is accelerating progress in healthcare and pushing boundaries faster than ever before. And at this point it's inevitable whether you like it or not.. From creating new proteins for vaccines to revolutionizing gene editing, the possibilities are endless. I definitely think we're witnessing a new era of medicine unfold. Does this excite you or worry you we're gonna see something out of the X-men? Follow Scott Caputo - every week I explore AI, innovation & strategy #AI #GeneEditing #Healthcare #Biotech #Innovation

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AI and Med Tech in Focus   AI System Developed to Identify Pathology in Tissues Engineers at Washington State University have developed an AI tool that uses images of human and animal tissue to detect abnormalities faster and more accurately than people. The AI algorithm was trained using images from past studies that involved kidney, testes, ovarian, prostate, breast and lymph node abnormalities. The new model detected disease in minutes—current processes take humans several hours and require specialized teams to check each other’s work. It was also found to be more accurate, sometimes detecting instances that humans had missed. The engineers designed the system to handle the processing load of the high-resolution gigapixel images by breaking them down into smaller tiles but still retaining the overall context of the tissue sample—akin to the zoom feature on a microscope or phone camera. Aside from getting diagnostic results more accurately and quickly, the new system also shows promise in epigenetics (the study of molecular processes that change gene behavior without changing underlying DNA). Epigenetic researchers can perform analyses and get results that used to take a year or more in just a couple of weeks. 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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I spent many weeks researching the story of Robin Zeng and Contemporary Amperex Technology Co., Limited (or CATL) -- the powerful and politically divisive battery maker that commands the largest global market share (and growing) Zeng's story is nothing short of the classic rags to riches narrative we all worship, yet...there are many useful lessons to learn on how/why certain industrial policies succeed via the CATL/Robin Zeng lens These lessons are all the more timely given what is happening to Intel, Stellantis, Northvolt. In my view, CATL could not have existed without China's exclusionary subsidies. Robin Zeng started CATL as a spin out from TDK Corporations, because TDK was Japanese, thus wouldn't qualify for gov't subsidies. Yet, that's not the end of the story. CATL still had to compete with 200+ domestic companies, like BYD etc. Favorable treatment was also removed after a few years, foreign battery companies were invited back into China (LG, Samsung, Panasonic), so CATL had to prove its worth. Yes, it got a leg up initially, but wasn't coddled and protected indefinitely Robin Zeng was also a rare breed...read my story on why. What can we learn from this? Industrial policy works in 3 steps: 1. Subsidize/protect/spur new startups 2. Stop protection, invite competition 3. Hopefully you get a Robin Zeng (or Wang Chuanfu) among your population who is as talented (and paranoid) as Andy Grove to rise above the ashes Agree? Disagree? Either way, I hope you give my telling of the Robin Zeng story a read. It deserves to be told properly. https://lnkd.in/eXXt5mna

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🔬"The promise Decentralized Science [DeSci] holds to change the face of scientific research is immense. DeSci could open up the world of science in a way that gives power to the researchers and speeds up discoveries" - Rebecca Chow, PhD representing ViaBTC Capital. Coming from an academic bakcground, this hits close to home. There are significant gaps and barriers in how we enagage with scientific research - countless months spent scraping for funding, tweaking proposals and research directions to align with potential funders, incredibly long and more often than not unaffordable review and publication processes, and even desperation turning into falsified data... We got some work to do here. Primary avenues of a public-powered infrastructure that must be reformed certainly revolve around funding, creation, review and storage of scientific research. It is time to ditch the "Valley of Death" concept ❌ Decentralized Science sounds futuristic. And in a way, it is. We're still heaps beyond the structure, security and credibility traditional routes have established - all necessary components of science and research. Main revenues for pioneering projects still come from lincenses and sponsorships, the sector lacks exposure and funding, projects are not yet refined or established as trustworthy, and centralization of power and data still remains a concern. I'm incredibly excited to see where DeSci takes us. Although still at infancy stages, the challenges established for traditional research centres and processes are real. And we'll keep moving in the right direction. It is incredible to see well-known personas, companies, and even pharmaceutical giants getting involved and advancing this sector with capital, resources, and awareness, with the likes of Brian Armstrong, Vitalik Buterin, Binance, and Phizer Pharmaceuticals Inc. Massive thanks to Rebecca for a wonderful reminder that intersection of sciences and sectors can bring transformative solutions. I highly suggest taking a deeper dive into the full article 👇

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