Tim Schnabel

Great article by Danielle Joseph Closed Loop Partners.

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If you are here at #JPM2025 or tuning in through the webcast and want to learn more - send me a message. We’re excited to share how our platform is transforming the #regulatorylifecyle, infusing AI thoughtfully throughout traditional processes to drive efficiency. #biotechshowcase #AIinHealth #regulatoryoperations #medicalwriting

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Protein splicing: an intervening protein (intein) is cut out of a protein precursor, producing two proteins. Inteins are mysterious. ↳ Over 200 have been found, and they're typically 100 - 800 amino acids long. ↳ They can be found in bacteria, archaea, and fungi but not in humans or other multi-cellular organisms. ↳ You find them in proteins involved in DNA replication and repair. This makes them an interesting target for antimicrobial drugs, as you could potentially target the microbe's DNA replication and growth without side effects. >>>>>>>>>> mRNA splicing depends on a complex machinery of enzymes. But protein splicing doesn't. Instead, the amino acid sequence controls the cutting and sticking together. So you can place an intein into a human cell line, and it still cuts itself into two. Some RNA structures (aptamers) also have this ability to cut themselves (ribozyme). >>>>>>>>>> I read a paper at the weekend, which led me down the intein rabbit hole. The authors studied inteins in Thermococcus kodakarensis - an archaea that grows at 65 - 100℃. Intein splicing can be temperature-sensitive. Therefore, interfering proteins that control DNA replication is a way to control growth at specific temperatures. (I'll add the paper in the comments). --- ♻️ If you found this helpful or know someone working in biotech, please share it with them! 🧬 Follow me (Steve Harvey) for more biotech content like this.

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Great new MIT technology review article about one of my passion areas: The use of #geneediting tools for #acceleratedbreeding to combat #climatechange via #climateadaptation in #agriculture #agbiologicals #plantgenetics #feed for improved #foodsecurity and #nationalsecurity! We use & #trust these tools in our #pharmaceutical products for #lifesaving therapies. Let’s embrace them for #climate & #food with the same #riskreturn #scientificmindset ! “How a breakthrough gene-editing tool will help the world cope with climate change: Jennifer Doudna, the co-developer of CRISPR, says there’s a “coming revolution” in climate-adapted crops & animals…says the technology will help the world grapple with the growing risks of climate change by delivering crops & animals better suited to hotter, drier, wetter, or weirder conditions. …The grand hope is that CRISPR’s ability to precisely remove specific parts of the DNA within the existing genomes of plants & animals will make it faster & easier to create climate-resilient crops & livestock, avoiding many of the pitfalls of earlier breeding & editing techniques. The added promise is that the resulting products may prove more appealing to the public, since they often won’t carry DNA from other organisms… “It’s very exciting to see these products coming out, because they have real-world impacts that are incredibly important, especially as we’re dealing with the changing climate & with our expanding population,” says Doudna …The USDA has loosened its rules on governing & labeling genetically modified foods in ways that clear the path for many CRISPR alterations… it determined that it will not regulate foods when genome-editing tools like CRISPR are used to make “a single modification that could have otherwise been produced through conventional breeding” over longer time periods. “We’re simply providing a trait that could have occurred naturally,” Doudna says of the regulatory distinction. “It’s just that we accelerated that process with CRISPR.” …Conventional breeding methods—which include cross-breeding varieties of plants & animals or using radiation or chemicals to create mutations—is a messy process. It can create numerous changes throughout the genome that aren’t necessarily beneficial, requiring significant trial & error to tease out improvements… ...“It’s really informed. It really is based on science,” she says. “Rather than looking at how that plant or crop was created, the question is, What is the final product?” She says the IGI has strived to act as a “voice of reason” on these issues, helping to counter fears & misunderstandings by providing scientific information about how CRISPR can be used to treat human diseases, help farmers adapt to climate change, or address other threats in people’s lives.” https://lnkd.in/esJg-7wQ

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Now, there are only 30 days left to invest in Genomic Expression! Genomic Expression's crowdfunding campaign will end on February 6 Genomic Expression is revolutionizing cancer treatment by analyzing tumor RNA and identifying the most effective therapies for patients leveraging proprietary algorithms and AI. Patient Success Stories: The real-world impact is profound, with patients experiencing remarkable outcomes. From metastatic thyroid cancer patients achieving long-term remission to follicular lymphoma patients responding to novel drug combinations identified by OneRNA®, the platform has changed lives. Supported by a team that generated +$80B of value in Biotech: Genomic Expression got to commercial launch of its RNA AI platform, called OneRNA® through $6.5M in grants, $1.7M in seed funding, and $4.5M in lifetime revenue and is supported by a team of investors that collectively generated more than $80B in enterprise value including Jesper Zeuthen, CMO and co-founder of GenMab ($14B market cap) and Dan Adams, founder of Biogen ($22B market cap) and Protein sciences (exit to Sanofi for $740M). In the future, the platform will be able to rapidly translate RNA code into novel and potentially individualized RNA Therapeutics. -> You can jump in with as little as $250. https://lnkd.in/enQ4F4GA?

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🔬 Cell Painting Data Analysis Pipeline in HCS Pipeline 🔬 Today, we're demonstrating how you can analyze your Cell Painting data using the same pipeline we employ internally in the HCS Pipeline platform. With this fully customizable, modular solution, you can simplify and accelerate complex data analysis workflows without needing deep coding expertise. Let’s take a look at the components of the pipeline: 🚀 Step-by-Step Pipeline 🚀 1️⃣ Data Quality Control (QC): Automatically clean your dataset by removing outliers, handling missing values, and applying thresholds for NaNs and zeros. This ensures you're working with high-quality data from the outset. 2️⃣ Feature Reduction: Simplify your dataset by removing highly correlated and non-informative features, keeping only the most important and biologically relevant data to streamline the analysis. 3️⃣ Multiple Levels of Normalization: Apply different normalization methods, including z-score, MAD robustization, and spherizing the data, to remove batch effects and prepare the dataset for accurate downstream analysis. 4️⃣ Aggregation: Aggregate your data across different metadata levels, such as plates or experimental conditions, for seamless comparison and analysis. 5️⃣ UMAP Dimensionality Reduction: Reduce thousands of features to 2D space with UMAP to uncover hidden patterns and similarities between samples. 6️⃣ Interactive Plots: Generate Interactive Distance Matrices and Scatter Plots of UMAP Transformations to visualize relationships and gain insights into your data in just a few clicks. 🔍 Recreate This Pipeline with HCS Pipeline With HCS Pipeline, you can build and customize this analysis pipeline to suit your own research needs. The modular platform makes it easy for anyone to set up powerful workflows without requiring a data scientist. 💬 How are you currently analyzing your Cell Painting data? Let us know in the comments! --- #HCS #CellPainting #DataAnalysis #ResearchTech #Bioinformatics #HCSData #PipelineAutomation

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Single Transcript Unit Surrogate Reporter (STU-SR) systems to enhance the selection of genome-edited plants https://lnkd.in/eevaDBt5

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🚀 New Episode Alert on #GrowEverything! This week, Erum Azeez Khan and I were thrilled to welcome @Michael Fischer from @Waterbear and DeSciNYC to explore Decentralized Science (#DeSci). 🧬 Imagine a future where science is not only more collaborative and transparent but genuinely fun. Thanks to DeSci, integrating blockchain technology, this is quickly becoming a reality. In the interview, we discuss how WaterBear is gamifying science through community-driven research projects, even incorporating meme coins to fuel the excitement! *Meme-ified science, what?* 🔍 Curious about how DeSci is accelerating discoveries and making scientific research more inclusive? Join us as we discuss how this innovative approach is reshaping the landscape of scientific exploration. 🎧 Don't miss this great interview: Spotify: https://lnkd.in/gBH_iksJ Apple: https://lnkd.in/gP7TZHyp YouTube: https://lnkd.in/gJYrAe_6 #DecentralizedScience #BlockchainInScience #InnovativeResearch #ScienceCommunity

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Bharath Ramsundar and his team's work in this space has consistently been amazing, rigorous and detailed. Thanks for democratizing these tools in chemical ML, Bharath! PS: I so want to work with you and your team!

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Interesting technical overview from Ginkgo Bioworks, Inc. that might be the first signs of a strategic pivot: they trained an LLM on 2 billion proteomics sequences. "Here we introduce AA-0, a 650M parameter model following the ESM-2 architecture, trained on public data combined with proprietary sequences from the UMDB. We compare the performance of AA-0 to ESM-2 on popular benchmarks as well as a collection of internal benchmarks relevant to our commercial work in the Ginkgo Bioworks foundry." "AI can make biology easier to engineer. This is the first of many intended releases from the Ginkgo AI team. We are excited to begin peeling back the curtain and enabling bioengineers across the world to access our technologies. As we scale up our training efforts (we are currently training models 10x larger than these and more!), we will be eager to share our findings and plan to make the resultant models available to the community."

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How a pivot from NGS to spatial biology more than doubled Singular Genomics’ value and saved it from bankruptcy. For years, Singular Genomics was struggling. Their flagship sequencing platform, the G4, was up against giants like Illumina and PacBio in a fiercely competitive next-generation sequencing (NGS) market. The company’s stock had been on a steady decline, and rumors swirled about their long-term viability. Then came the pivot. Singular made the bold decision to de-emphasize their sequencing business and focus instead on spatial biology—a fast-growing field that maps the position of RNA and protein expression directly in tissues. They turned their attention to developing the G4X Spatial Sequencer, a cutting-edge platform designed to unlock new possibilities in single-cell and tissue analysis. Investors doubted Singular’s spatial platform and its potential applications in drug development and precision medicine. Then earlier this month, Singular was acquired by Deerfield Management for $20 per share—a staggering 254% premium over its previous closing price. Why did Deerfield bet big? Spatial biology is at the frontier of life sciences, with increasing demand from researchers and biotech companies. Singular’s technology positions Deerfield to capitalize on this high-growth by building better distribution into transformative applications in medicine. Singular’s pivot into spatial biology might have saved the company—and supercharged a new player in the spatial biology market.

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The lack of a publicly available dataset for fermentation/cell culture data is why biomanufacturing is lagging behind other areas of biotech (like DNA & Protein Design) in terms of AI/ML development. Anybody interested in doing some collaborative work to get this done for the greater good of biomanufacturing? We'll offer up our digital resources at BioReact : Bioprocess Meets Ai.

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Do we still need humans to innovate? The most recent episode of our Inside Innovation video podcast series featured my colleagues Amanda McClerren and Jeremy Williams discussing AI, and they left this question for the end of their chat: What do AI tools suggest for the future of climate-smart farming systems? Let me connect two pieces of this brief clip: Amanda's mention of "we still need humans," coupled with Jeremy's suggestion for AI "to automate tasks that, frankly, are boring or that we're not very good at." Scientists' time is best spent not on filling wells on a plate or inspecting lines of code, but instead in making the connections and leaps of logic that only human beings with intuition and creativity can do. A well-governed set of AI tools will make that more possible, not less, and I'm looking forward to seeing that true logic emerge as our tools mature. #AI #AgInnovation #RegenerativeAgriculture

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The GLP1 story illustrates the "academic-industrial valley of death”. What is interesting is how/why the eventual winners (Novo/Lilly) succeed. Ie not through novel target biology but meaningful iterations on delivery, safety, efficacy etc. 2x-daily exenatide to weekly semaglutide to oral semaglutide = masterclass in persistence of development. PCSK9 inhibitors - target ID was some amazing work, but the real change came from solving manufacturing challenges, optimizing dosing schedules, finding right patient populations etc. PD1/PDL1 - Merck wasn't first, but Keytruda dominates through trial design and execution informed by others' stumbles. When the market is so massive coming in 2nd/3rd no longer matters. ☠️ For smaller markets these dynamics reverse = Economics of coming in 2nd look very different, recruitment is a complicated mess, so are the costs, market is 30-60% smaller after the first one; and you just do not recover from suboptimal trial design.

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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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Massive (255 page😱) SEC filing describing the acquisition of Singular Genomics by Deerfield Management (thanks Broomer@Aseq). Adds new meaning to the term "kicking the tires", over 70 companies were contacted; those that dug in for a closer look included 12 public companies (assume included Thermo Fisher Scientific, not Illumina 🤣), 5 private companies (daring, probably wanted the cash), and 13 investment firms. The M&A board committee met 44 times (😱). In the end bidding came down to Deerfield and Tang - which we knew about - and one late player we didn't know about: Medical Excellence Capital, LLC (partner Kim Kamdar sits on Singular's board). Deals often blow up because of executives dissatisfied with the financial outcome. In this case the $24 was withdrawn, the board was forced to then consider liquidating the company (as bad as it sounds: laying everyone off, selling for parts) before a final hail mary save came in at $20 (a $10M oopsie). Must have been a sleepless December for all involved 😳😳😳: 10/30: "Deerfield had improved its offer to $24.00 per share and had again requested exclusivity. [The board informed Deerfield that it] was prepared to enter into an exclusivity arrangement" (Pretty amazing offer given that Singular had been trading at $6 prior to the bidding, seems like the board was doing a great job). 10/31: "[Singular advised Tang that they] would not be moving forward with Tang’s “best and final” offer of $22.50 per share in cash." 12/4: "The CSO reviewed his concerns with the rollover terms proposed by Deerfield and stated that he would not rollover his Singular Common Stock on the terms proposed by Deerfield." 12/8 Tang was re-approached given there was now risk in the Deerfield deal: "Tang indicated that if Tang were to submit a bid, it might be as low as $16.00 per share." 12/14: "Deerfield indicated that [due to] lack of support from the Company’s CSO...and to the Company’s cash position...Deerfield would be willing to proceed...at a reduced price of $18.00 per share" 12/14: "[Bankers advised the board that it] in response to the price reduction, they consider shifting focus to the Company’s other alternatives, including a potential liquidation..." 12/17: "[The Board informed Deerfield of their] willingness to proceed with a transaction at $21.00 per share" 12/20: "Deerfield informed [Singular] that Deerfield would be willing to acquire the Company for $20.00 per share" On December 22nd, the Singular board accepted Deerfield's $20 offer. Talk about negotiating against yourself 🙄🙄🙄 Good news is that it certainly reads as if Deerfield wants to keep the company as a running concern, I thought this might be just a way for them to get some cash back out 👏👏👏 https://lnkd.in/gGKHfuH9

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How does the BioInnovation Institute measure impact? When I started 5 years ago we quickly decided that measuring how much financing our companies raised was the right KPI - it was hard, measurable, and integrated all the effects we wanted to make on the start-ups. (Plus we had a board meeting the next day and we could pull it together pretty quick). We’ve had 5 years to reflect on that choice , and it seems insufficient now. Our startups are advancing to clinical trials (Breye Therapeutics ApS Kariya Pharmaceuticals ) and selling sustainable products (Matr Foods EvodiaBio Sundew ). Most recently BOOST Pharma announced positive clinical data in Brittle Bone Disease showing reduced bone fractures in children. Financing raised showed what our programs could do for start-ups, but its the products they create that are going to improve Human and Planetary Health - and that is the impact we wish to measure and report. The Danish newspaper Børsen featured our CEO Jens Nielsen today and our thoughts on how BII thinks about impact 5 years into this unprecedented experiment. Maybe one day we can tell you about approved medicines, lives saved , and CO2 and water spared ? Stay tuned…. Link below

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As the Chief of Staff at OpenAI, Maddie Hall learned an important lesson firsthand: a small team of mission-driven researchers can turn science fiction into science fact on an extremely short timescale. For decades, AI was a backwater academic discipline thought to be chasing a pipe dream—until it wasn’t. Now it’s a major driver of the economy. Maddie remembers a colleague recommending her Profiles of the Future by Arthur C. Clarke. Written by a prolific science fiction author with an uncanny track record of future predictions—including telecommunication satellites and the Internet, to name a few—the book was an exercise in thinking big. It was also a reminder that even the best futurists didn’t see everything coming. Observing the company’s rapid internal progress, Maddie constructed a new prediction problem for herself. Assume ubiquitous AI. What extremely important problems still wouldn’t be solved? Probably messy problems rooted in the physical world. And which of these problems might have existential consequences if it remains unsolved? Climate change. After exhaustively researching options for making a planetary scale impact on atmospheric carbon levels, Maddie settled on her approach: engineering biology. So in 2019, Maddie left OpenAI and co-founded Living Carbon, Public Benefit Corporation (PBC). In just five years, Living Carbon has developed photosynthesis-enhanced trees using biotechnology, planted hundreds of thousands of trees in four different states in the U.S., built out an experienced carbon project development team, and raised over $36M from leading investors including Temasek, Lowercarbon Capital, Toyota Ventures, Day One Ventures, and Felicis. Let’s explore why they are doing this, how they are doing it, and how the business model of a climate biotech works in practice.

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Interested in seeing what Rocky Balboa, Jeff Spicoli, AI and machine learning have in common, check out this Timmerman Report article on east Coast vs West Coast AI culture clash. We are fortunate to have a network of experienced AI & machine learning professionals available for consulting assignment. Let us know if we can be of help.

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