Becky Pferdehirt, PhD

#data #biology #biotech #food #ai #ML This is such an important issue! First, if you’re not already subscribed to Jesse's newsletter Jesse Johnson, you should be! It’s packed with extremely interesting and educational content, especially for #data and #R&D managers and users (which means all of us, right?). This specific post is incredibly relevant in our company too, especially with teams that aren't traditionally data-oriented. Our solution in my data team along with Omer Genkin? We co-create internal tools with our users, leveraging ML and other cutting-edge techniques to solve real day-to-day challenges. Our mission is to make these tools as intuitive and accessible as possible – with the simplest UI/UX (if any at all) and ensuring the insights are crystal clear. It's all about #empowering everyone, not just the data scientists, to harness the power of #data and #AI.

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I’m thrilled to announce the launch of Radar Therapeutics, dedicated to making programmable, safe, "smart" #mRNA-based therapies that only get activated in the right cells, at the right time. Working with Katherine Jones, Sarah Chesemore, and others at the Bill & Melinda Gates Foundation, we witnessed how Moderna and BioNTech SE/Pfizer catapulted mRNA therapies onto the world stage with unprecedented speed, saving millions of lives.   At Radar, we want to bring this promise beyond vaccines into the most complex therapeutic compartments by solving one of the biggest problems for these therapies: making sure these mRNAs only reprogram the right cells in the body, avoiding potentially toxic off-target effects. We are committed to making therapies with the highest bar of safety, and widely accessible to patients that need them. I was incredibly lucky to meet my co-founder Eerik Kaseniit (thank you Anna-Julia Storch), while at Stanford University Graduate School of Business. Eerik was obsessed with the problem of precisely targeted, timely and controlled regulation of mRNA translation. Alongside Stanford Prof Xiaojing Gao and MIT Prof Jim Collins, we decided to direct those efforts towards saving lives by starting Radar Therapeutics. We attracted the brilliant minds Svetlana Lucas, David Schaffer, and Eric Klein along the way. We are grateful to NFX, Eli Lilly and Company, Biovision Ventures, and KdT Ventures for taking the lead on this round, alongside BEVC, Pear VC, ARTIS Ventures, Ten VC, Elementum Ventures, Emcure Pharmaceuticals Limited, SALT, Conscience VC, and more. Here’s to a future where we can program therapies to rewrite any disease with utmost safety and accuracy. I’ll be at #BIO2024 for anyone looking to connect! Sharing some information about the company here: Endpoints News - https://lnkd.in/g4MQT245 Firstword Pharma - https://lnkd.in/gq3heWsE Genetic Engineering News - https://lnkd.in/gNPDfHEs Chemical & Engineering News - https://lnkd.in/gUx8ijmY Longevity Technology - https://lnkd.in/gRwdtiKx PBR- https://lnkd.in/gvUG_c5M Businesswire - https://lnkd.in/gcv88QAM Alix Marduel Vasudev Bailey Asset Abdualiyev Shan-Lyn Ma Wesley Barrow Pioneer Fund Jackie Benson Shannon Dahl Jackie Papkoff, Ph.D. Nat Kolber Jon Levin Ilya Strebulaev StartX Ron Boger Howard Rosen

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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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I'm delighted to share news of this new AI-focused drug discovery company, Xaira, built on foundational technology from David Baker and led by Marc Tessier-Lavigne. The company applies AI tools to unlock opportunities in drug discovery for aspects of biology that we believe are not readily obtainable with conventional methods. I co-led NEA's investment in Xaira, along with my NEA partner and the firm’s co-CEO Mohamad Makhzoumi, and I will be joining Xaira’s board. Our enthusiasm for Xaira based on our belief that applying AI and large language models to biology holds immense promise and is still in its early stages. Currently, the application of AI to biology relies on model architectures borrowed from the tech world. A lack of well-curated clinical training sets hinders building and training these models effectively. This limits the advancement of AI in solving biological problems compared to other fields. Xaira aims to bridge this gap. We now have a clear understanding of the data needed to answer fundamental biological questions. By iterating on leading life science models and using focused perturbation data generated through our large-scale experiments, Xaira will generate data specifically suited to building advanced model architectures that are optimized for biology -- and hopefully, unlock therapeutic opportunities for patients who are not being optimally served by existing therapeutics.

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Very much agree: we use multiple models, each having their own “view” or features they interpret, in order to make candidate selections. This effectively creates an ensemble that outperforms one single model. Selecting #enzyme or #antibody candidates to take to the lab is best done this way. A single model has a narrow view of the world. #techbio #ml #biotech

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To date, Erum Azeez Khan and I have published more than 80 episodes dissecting all things biotech on the #GrowEverything podcast. We’ve covered everything from biomaterials revolutionizing everyday products to microbes paving the way for interstellar exploration. Whether you're a seasoned biotech pro or a curious newcomer, there's always something new to learn. If you’re a synthetic biology enthusiast, we’ve selected some episodes just for you: Forget jargon, Ginkgo Bioworks, Inc.'s Cas Smith makes synthetic biology (synbio) fun and easy to understand. We explore how innovative synbio solutions are transforming multiple industries. Listen here: https://lnkd.in/ewPnMtkX What’s the latest in the world of synbio? Paul Freemont of Imperial College London tracked synbio’s progress and impact over the past five years. We talked about how universities are making biotech knowledge accessible worldwide, how rural and urban areas are collaborating on revolutionary manufacturing systems, and the surprising role of art and design in fueling bio breakthroughs. Listen here: https://lnkd.in/eGHFNAG5 How is synthetic biology shaping the future? In our conversation with SynBioBeta founder John Cumbers, we discuss bacteria for tasks like cleaning teeth, explore subscription-based revenue models, and the importance of innovation in a field threatened by monopolies. Listen here: https://lnkd.in/eZ7z9SiT When you listen, be sure to hit the subscribe button to join our growing community of bio-enthusiasts! Let’s Grow Everything!

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Versant Ventures debuts Santa Ana Bio, Inc. (Alameda) with $168 million and a trio of programs that riff in new ways on existing ideas like targeting mast cells and stimulating the PD-1 pathway. One of Santa Ana’s drugs, dubbed SAB01, is a so-called bispecific #antibody. It is designed to mute the mast cells that drive allergic disease by blocking a protein called c-Kit. But the drug will only do so when it detects another target that’s found on those cells. Foresite Capital (Larkspur) an investment firm that backs life sciences and healthcare companies, has raised a $900 million fund. The fund, Foresite’s sixth, will invest in companies focused on precision medicine, healthcare delivery and life sciences infrastructure. In drug developers, specifically, the firm is looking for those using #genetics and #machinelearning to identify potential therapies. Actio Biosciences, Inc. (San Diego) announces $55 Million Series A financing to deploy a suite of proprietary tools and deep #genetics expertise to develop #therapeutics against targets shared between rare and more prevalent diseases. They have a lead small molecule program targeting TRPV4 mutations advancing toward clinic for treatment of Charcot-Marie-Tooth disease type 2C and other serious bone diseases. Actio also announced an innovative partnership with The Jackson Laboratory to develop and implement new transgenic models of rare disease pathways. M&A, Deals, Partnerships: Johnson & Johnson is handing back a bispecific T cell engager program designed to target both CD20 and CD3 to its partner Xencor, ending a significant piece of an agreement between the companies that started in 2021. Xencor completed enrollment for a Phase 1 trial of plamotamab last year. The biotech said the drug is now Phase 2-ready, adding it will review its potential to address unmet needs. The original collaboration and license deal saw Xencor get $100 million upfront for global development and commercialization rights to plamotamab. Other Interesting News: The failure of a Pfizer medicine for #Duchenne muscular dystrophy adds new uncertainty around the effectiveness of #genetherapy for the muscle-wasting condition. Pfizer said the treatment missed its mark in a definitive Phase 3 study of boys between 4 and 7 years of age with DMD. Pfizer said the therapy didn’t lead to a significant difference versus placebo on a measure of motor function, or on key secondary measures such as timed tests for how quickly study participants could stand or walk. Avidity Biosciences, Inc. (San Diego) drug for muscular dystrophy shows promise. Shares in Avidity rose by nearly one-third as the company revealed new clinical trial data for its drug del-brax in a form of #musculardystrophy.  Among eight patients treated with del-brax, Avidity reported greater than 50% average reduction in a panel of genes regulated by another gene called DUX4. Avidity also said participants showed signs of increased strength.

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I’ve said it and I mean it: The longevity drug won’t be a molecule but an algorithm. Technically, it won’t be solely a molecule, but an algorithm personalizing various molecules, depending on the context. At Ani Biome we’ve already built such a system and are about to validate it clinically in three independent studies. Once we do, we’ll become a Nvidia of longevity. Mark this post. #longevity #techbio #disruption #innovation #gutmicrobiome #nvidiaoflongevity #ai

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Wow - 2 ex-Meta employees launch EvolutionaryScale landing $142m to advance AI in biology. EvolutionaryScale has introduced ESM3, a cutting-edge language model for biology that predicts protein sequences, structures, and functions. This model can simulate millions of years of evolution, generating new proteins with potential applications in medicine, research, and sustainability. ESM3 represents a significant advancement in AI's ability to design and engineer biological systems. There will be comparisons with AlphaFold3, intrigued where this goes... https://lnkd.in/dhtQDtsA #AIinDrugDiscovery #genomics #proteomics

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Investment, therapeutic viability, and next-gen. technologies... That's what the cell therapy field needs. I had the pleasure of sitting down with Jason C. Foster of Ori Biotech recently on their podcast to talk all things cell therapy, the enabling technologies that support this modality, and the need for more investment. What did we touch on (and link to full podcast below)? Investors needing to see a return when investing in cell therapies. Need to bring manufacturing costs down to expand access. Next-gen. tools to create better, more robust therapies. Purpose-built therapies require purpose-built tools! Our consulting practice, how we help our clients, and how we view the field of advanced therapies. We take a differentiated approach to tracking, following, and mapping key trends across advanced therapies to bring novel, business-impacting insights to our clients. Want to discuss any of the above? Where the field of cell therapies are going? What it means for your own development pipeline? Reach out and let me know what you think in the comments! #celltherapy #venturecapital #consulting https://lnkd.in/g7SH9FAU

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I wonder if change in a mature industry is incremental or disruptive? I've been on the road last 3 weeks. One of my realizations is that the pharma/biotech industry is having a really hard time understanding the implications of AI in their field. Our conversations are centered on how AI might augment our old way of doing things. Not so much on will there be newer ways of doing things? Biological research is a complex balancing exercise between mechanistic understanding and pure empirical evidence. We are progressively better at understanding - or as I would say hypothesising - about how a disease works and how a drug might 'cure' it. A submission of mechanism of action is more common in IND applications but as far as I can tell it's not a pre-requisite. The greatest successes of drug research are solid empirical hit and trial. Very successful ones at that. The hay day of drug research in the 60s to 90s was because big pharma figured out how to do compound screening effectively at scale. Will AI give us new ways to do this in more effective ways? I would be extremely surprised if that were not to be the case. a. we have never had access to the kind of data that we do now b. we have never had a tool like modern AI to sift through data Those two combined will give us ways to do empirical research like we haven't done before. That much is clear. Will it change the relative dearth of blockbuster drugs? That is a whole another subject. What is clear to me is that the current focus on mechanistic understanding will have to evolve to incorporate AI. We will have newer ways to do things - not necessarily change or abandon old ways. Link to a blog that Abhishek wrote in 2020 which seems truer than ever before.

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Reposting to increase the number of people who see this and could answer my question: Can someone share the peer reviewed source of work described in the Ted Talk below? If it’s in the Ted talk, can you tell me where approximately? I’d like to read the paper(s) and understand better what “predicted the structures of all 200 million proteins known to nature means”. My knowledge of protein structure prediction is limited primarily to x-ray crystallography, NMR and homology models based on those structural models that are stored in the protein database (PDB). I’d like to have a sense of how accurate the structures are predicted to be and how that accuracy was determined. My major concern is that predicting the protein structures of every proteins that is even remotely related to a solved structure is exciting but not necessarily new given that it was frequently done 18+ years ago. If the prediction is accurate for proteins that have no similarity to previously solved proteins, how do we know it’s right without first solving some of those sequences. Even if you used a subset of the PDB to train a model and another subset to test those predictions, I would think there’d be a big level of uncertainty of the predictions that are for protein with no practical similarity in the PDB. Update: Thanks to Daniel Hickmore for the DM it got me to the Nature paper that has been accepted but is not yet published. I'm reading it now to see if my questions get answered: https://lnkd.in/ei3pyCax

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We're moving from an age of scientific discovery to an age of scientific engineering. And software is playing a defining role. I got a glimpse at the future of genetic engineering and our incredible ability to program life thanks to Colossal Biosciences CEO Ben Lamm. Can you believe CRISPR is already 12 years old?! We've come such a long way since and its time to check-in on the cutting edge. My three key takeaways from chatting to Ben of what's to come: 1. Humans will defeat death 2. All drugs will be created in software 3. Genetic engineering is inescapable Curious? I unpack each of those in my write up: https://lnkd.in/gzK-Hui9?

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Excited to share that Waypoint Bio has emerged from stealth to turbocharge drug discovery using *in vivo* spatial pooled screening tech with $14.5 million in financing, led by Hummingbird Ventures, with participation from other investors, including Recode Ventures and pre-seed lead Fifty Years. Pooled screening is an incredibly powerful technology for drug discovery, but it’s historically been limited to measuring simple cell phenotypes, such as growth or drug resistance. This limits the technology’s value in more complex diseases where interactions between cells and their environment are key, including T cell interactions with solid tumor cancers, such as pancreatic and gastric cancer. Our platform turbocharges traditional pooled screening by leveraging #spatialbiology to generate complex, multivariate and spatial readouts for every perturbation, and quickly generate novel drug candidates with a greater probability of clinical success. We will use the financing toward first designing CAR T-cell therapies with superior efficacy against the tumor microenvironment, and later, Treg therapies for autoimmune diseases, and advance them in partnership with biotech and pharma and on our own. Thanks to Ryan Cross for speaking with me and David Phizicky for Endpoints News about our platform, the first to combine pooled screening and spatial biology for drug discovery, and to our awesome investors for supporting our work to bring new therapies to the underserved! https://lnkd.in/eV_hc3Y9

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I have all 3 top LLMs, Google Gemini 1.5, Claude Opus and ChatGPT4o, and I have a great understanding of all their nuanced differences, but it's often shocking how similar their output is. I don't know what to make of it. I know they have a lot of overlapping training data, but one imagines they process it in significantly different ways, have a lot of their own propriety data, and have significantly different transformer architectures. How are they producing a nearly identical list of abstract suggestions in response to a complex query?

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Reactosome graduated from the IndieBio SF Batch 15! 🧬 We’ve learned so much and met amazing fellow companies disrupting standards—harnessing the power of the dark proteome, squeezing DNA out of rocks, reversing climate change with cold plasma, achieving the fastest sequencing, and so much more! We are beyond grateful to every IndieBio and SOSV team member for making all of this possible. Just five months ago, Giorgio Fracasso and I had just a crazy idea and determination. Today, we are officially Reactosome, the world’s first synthetic nucleus company. Behind this achievement were countless hours in the lab—from assembling prototypes to witnessing the first glow of RNA expression in cells; calls spanning 9,099 km, filled with business wisdom and human support—late at night and during morning rides to work; challenges that pushed us beyond our comfort zones; negotiating deals; and making endless improvements to ensure our message is clear, loud, and bold. We are now confident that our Synthetic Nucleus will enable a whole new class of genomic medicine—safer, continuous and controllable, with the largest cargo capacity, and suitable for specific cell delivery! Our next goal is to accelerate the R&D up to the preclinical stage and engage with biopharma. Interested in a sneak peek? Check out the video the IndieBio team produced: https://lnkd.in/enKybc7B Feel free to reach out to learn more. We are fundraising and looking for more partners! Loud shoutout to IndieBio SF Batch 15, you are the best: Hypercell Technologies, RyboDyn Inc., BryoSphere Biotechnologies, SpiralWave, AquaLith, Stream Genomics, Farm Minerals, Jolly Mazumdar & Thimmaiah Chendrimada, and Nutrition from Water™ (NXW) #IndieBio #GenomicMedicine #genetherapy #RNA #DNA #Biotech #Fundraising #SyntheticNucleus #Reactosome 

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Integrating lab instruments with cloud infra is so much fun. Working with some of the customers who were struggling to upload files manually to network-attached storage, and then moving the CSV manually to Benchling. Some of the questions that I keep hearing: After successfully getting the data from Mass Spec to Scispot Labsheets, how do I connect with my notebook entries? Can I use the same configuration for one instrument to another? We invested some engineering resources to build a universal agent for lab instruments. One agent, 100s of instruments supporting various protocols. Connect. Transform. Forget. The goal is to help our customers easily connect any lab instrument with a few clicks using a universal agent. Once connected, wet lab folks can easily search and discover the processed data in Scispot Labsheets. Computational folks can either use the API or connectors to push the data to relevant destinations or use it for downstream AI work. We at Scispot love making videos. So here is a quick video on our universal agent. Pardon the music but my taste of music is eclectic. More details here: https://lnkd.in/gKd2ateV

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Had to miss today's #BiotechHangout but will be listening on X to make sure that I don't miss the thoughtful discussion and insights shared earlier. I invite you to do the same ICYMI.

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Regeneron is expanding its genetic medicine efforts and will work with California startup Mammoth Biosciences on gene-editing programs reaching parts of the human body beyond the liver, the companies announced Thursday.... ...Under the deal terms, Regeneron will pay $5 million and make a $95 million upfront equity investment in Mammoth, with the startup eligible for up to $370 million in milestone payments and potential royalties for each target.... #CRISPR #geneediting #cellandgenetherapy #advancedtherapies #lifesciences #biotech #biotechnology #equityinvestment #investment #funding #financing #milestonepayments Jennifer Doudna Lucas Harrington Christos Kyratsous Trevor Martin #delivery #royalties #innovation #advancingmedicine

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