“I first started working with Geof when I joined his computational biology team in 2018. I was fresh out of grad school, and he helped make the transition from academia to industry very easy for me. Throughout the next several years Geof was an excellent manager. He prioritizes employee development, encourages you to grow and take risks, maintains an open line of communication and runs a very transparent team. Geof is excellent at building new and impactful teams and projects. He is also a great communicator and advocate for people as well as a champion of DE&I in the company.”
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Cambridge, Massachusetts, United States
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Stephen R.
NPC's - #LLM and Chronicling a realm where input signals aren't confined to customary data sources but diffused across disparate computational dimensions, super prompts are conferred dominion over a maelstrom of #information – encompassing both structured datasets and amorphous text corpora. This multidimensional panorama bestows upon them the capacity to harmonize an eclectic assortment of #data, affording outputs that are both recondite in their #wisdom and highly pertinent to their respective contexts.
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Sheng Feng
There is a new paper on DIA global, “The role of RWD & RWE in shaping global regulatory practices“, by Jeffrey Brown from TriNetX. It’s well written. I especially liked the “known unknowns” and “unknown unknowns” discussion, and “matching the expertise of RWE generator & reviewer”suggestion. Two comments: 1. FDA, EMA, PMDA were mentioned, NMPA was left out. In fact, seven RWD/E guidance were published by NMPA during the past years; NMPA has been a strong advocator of RWD/E. 2. RWE for regulatory consideration has a bright future with a rough path forward. So, for everyday practitioners, what are the suggestions between the miserable reality and bright future, especially for service providers, who need to deliver? That reminded me on an External Control Arm study a couple of years ago, where a “perfect” piece of evidence was not available, but we might be able to generate a chain of “good” evidences, combining both primary and secondary data. Is perfect the enemy of good for regulatory RWE studies?
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Eric Merle
Thoughts on the AlphaFold 3 Controversy Nature's editorial today (https://lnkd.in/e4MD5FZB) regarding its decision to publish Google DeepMind and Isomorphic Labs' paper on the AlphaFold 3 release earlier this month, raises interesting points. Read the AlphaFold paper here: https://lnkd.in/eP3CSr3P It is clear that we are in the midst of a true revolution. AlphaFold 3's ability to now predict interactions of biological molecules is an incredible breakthrough. Yet, the lack of immediate code availability nonetheless raises questions about transparency and reproducibility in AI research. I think that Nature's decision, which falls within the guidelines and discretion of their editors also takes into account the interests of all parties. The editorial mentions that the publication will be updated when the code is made available in 6 months. We will surely discuss these topics on the "AI in Healthcare" panel in which I will represent GENOSKIN and participate during the Biotechnology Innovation Organization convention in San Diego. ➡️ Where & When: San Diego Convention Center Corporation Booth #3823 | June 3rd, 2.00-2.45 PM What are your thoughts on the balance between encouraging scientific breakthroughs and ensuring transparency in AI research? I look forward to exchanging on the innovative ways AI is transforming Healthcare. If you're attending, let's connect. ➡️ Schedule a meeting: https://lnkd.in/eW4nXpk9 See you in sunny San Diego! ☀️ #BIO2024 #AI #AlphaFold3 #OpenScience #Innovation #Revolution Business France SoCal French-American Chamber of Commerce ▶ Stephane Richard Bettina ExpertonSteve LevineJean-Frederic Petit-Nivard Brian Atwood Sylvie ALMERI Camille Risso Jerome Revole Nam-Hee LEE
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Kirk Sudheimer, MBA
Founded by senior Google and GRAIL executives, Betteromics are solving the unstructured data problems plaguing HC/LS and specifically leveraging Regulatory Grade GenAI for the creation of structured data (i.e. cancer staging, pharmacovigilance, etc.) from unstructured text. Dramatically faster / Traceable and verifiable / Easier, and more agile, than traditional methods
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Hung Trinh
Regeneron's blockbuster eye drug posts weaker sales due to inventory impact May 2 (Reuters) - U.S. drugmaker Regeneron Pharmaceuticals Inc (REGN.O), opens new tab missed Wall Street estimates for quarterly profit on Thursday, hurt by softer sales of its blockbuster eye drug Eylea due to reduction in wholesaler inventory. Apart from an impact of about $40 million cut in inventory, Regeneron said changing market dynamics that resulted in lower volumes and lower selling price also hurt Eylea sales. Total sales of the drug, jointly developed with Bayer AG (BAYGn.DE), opens new tab, fell 2% to $1.40 billion in the January-to-March quarter, missing estimates of $1.86 billion, according to LSEG estimates. The higher 8 milligram dose version contributed $200 million to Eylea's total sales, compared to consensus estimates of $196 million. Regeneron said it continues to see strong uptake of the higher dose version of Eylea. Analysts have high hopes for the high dose. They expect the high-dose version to gain market share over the standard dose largely over the next year. https://lnkd.in/eZ-NqKDH
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Raymond J. Kelleher, MD, PhD
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Michael Mietzner🧫🧬🔬💊💉🏭
What a fantastic event held by AWS and supporting companies. 2 big takeaways: 1) AI is rapidly changing to address issues and drive reliability with new tools from AWS and others. 2) Like any tool, you can't let this happen to you, you need to plan and apply it systematically for the benefit of your company. It was great to hear of the planned implementation and strategic alignment some companies are taking to best poise them for success.
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Russ Belden
Sharing an article on the 12 hottest biotechs in #Boston. Indeed all are innovative and well-funded, yet there are three that I find intriguing. Life Biosciences, MOMA Therapeutics, and Orna Therapeutics are leading the way in biotech innovation. Life Biosciences is redefining aging with programs for optic neuropathies and neurodegenerative disease. MOMA Therapeutics is discovering the next generation of precision medicines by targeting molecular machines that underlie human disease. Orna Therapeutics has developed circular RNA (oRNA) with applications across multiple disease areas, including cancer, regenerative medicine, protein replacement, infectious diseases, and autoimmunity. Their lead program is an in situ CAR therapy that combines oRNA™ molecules and proprietary lipid nanoparticles (LNPs) to deliver chimeric antigen receptors (CARs) directly to patient’s immune cells within the body (isCAR™ therapy). If you need help with your biotech commercialization, contact Russ at russ@bridge1.net or call 415-307-0774. #biotech #emergingbiotech #CEO #therapeutics #commercialization #funding #aging Read more about these innovative biotechs and others in Boston in this article: https://lnkd.in/eza6aPA4
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Mike Clements
Looking to add neural #organoids 🧠 to your research but need help getting started? Check out this new publication in Nature Protocols: https://lnkd.in/ejRp9WuQ The use of neural #organoid models to study neural activity has rocketed 🚀over the last 5 years. In this paper, Michael Fitzgerald and Tiffany Chu in Alysson Muotri’s lab, share their methods for characterizing the electrophysiology of neural organoids with their Maestro Pro MEA system. #Neuroscience, #StemCells, #BrainOrganoids, #DiseaseModelling, #AxionBio
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Ljubomir Buturovic
Reality check regarding the AI/ML-based early cancer detection: https://lnkd.in/ghQt_MsA The great news is that NIH is launching a "Vanguard" study to evaluate the new technologies this year. But it'll take ~15 years to get the results (the two trials mentioned below will run in sequence): "The Vanguard study is expected to take 4 years, according to Neslund-Dudas. The larger randomized controlled trial likely will have a 10-year to 12-year timeline." Thus, it takes an extremely long time to determine if these innovations improve public health (as I explained in a prior article: https://lnkd.in/gjSzUrbM). This is a fundamental challenge for early cancer detection, independent of technology Bottom line: whenever you read an article about new AI tech for cancer screening, think ~10-15 years to prove public health benefit (and remember the outcome could be negative)
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Amrutesh Puranik, Ph.D.
🔬 Discovering Biomarkers for Better Outcomes in Melanoma Treatment 🔬 Exciting news from ASCO 2024! Led by Jeffrey Weber, our team is proud to present pioneering findings on the role of predictive and pharmacodynamic biomarkers for response and toxicity in melanoma treatment. Our phase II trial combined tocilizumab (TOCI) with immune checkpoint inhibitors, reducing toxicity and revealing new biomarkers. Initiated in 2020-21, this work involved multiple high parametric flow cytometry panels to identify various myeloid, NK and functional CD4 and CD8 T cell populations linked to treatment outcomes. Our insights are paving the way for more personalized, effective melanoma management. 🔥 Hot Take: Inflammation Modulators are Here to Stay in Immuno-Oncology!🔥 📍 Check out our findings at ASCO Poster Abstract #9538; Poster Board #322. #ASCO2024 #MelanomaAwareness #TranslationalBiomarkers #TranslationalResearch
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Susan B. Nichols
After a turbulent few years, 2024 has given the biotechnology industry some signs of a return to normalcy. For one, venture investment appears to have stabilized at levels seen prior to a pandemic-era spike. Data presented by the Biotechnology Innovation Organization at the group’s annual meeting this week in San Diego showed private drug companies in the U.S. raised $3.8 billion during the first quarter.... Venture capital firms are also active in raising cash, reloading for new investment in the sector. Several new groups have launched this year, including Regeneron’s venture arm and Goldman Sachs’ first life sciences fund, which raised $650 million. Established investors are busy, too: ARCH Venture Partners outlined plans in February to raise $3 billion, while Canaan Partners X LLC recently added $100 million to its 13th fund.... #investing #investment #IPO #MergersandAcquisitions #funding #financing #biotech #biotechnology #returningtonormal #capitaldeployment Biotechnology Innovation Organization #celltherapy #genetherapy #cellandgenetherapy #advancedtherapies #regenerativemedicine #lifesciences #lifescience #BIO2024
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Kendalle Burlin O'Connell, Esq.
Jonathan Montagu, CEO of MassBio member HotSpot Therapeutics, Inc., writes on the #LifeSCiVC blog about hopes around an immuno-oncology spring this year, aligning with the emergence of #biotech from its own long winter. Jonathan points out that after the #lifesciences industry dove headfirst into I-O “to address the substantial need that still persists for many cancer patients with a range of tumor types,” much of the second-generation agents fell short. He writes about why he’s optimistic that new approaches have started to turn the tide. What are your thoughts on the I-O space right now? https://lnkd.in/eMh62Z8j #immunooncology #oncology #patientdriven
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Drug Discovery Biology Strategy Meeting
The Drug Discovery Biology & Bioinformatics Strategy Meeting on May 21st in San Diego brings Philip Cheung, Philip, Founder and CEO of Refactor BioSciences, to the center stage. Philip tackles the critical issue of data democratization – making complex bioinformatics data accessible and usable for a wider audience. This session dives into the fundamental considerations for making data democratization a reality. We'll explore strategies for presenting complex data in a way that's comprehensible and useful to researchers across various backgrounds, even those without specialized training. We'll discuss Philip's insights on ensuring data democratization doesn't compromise patient privacy or data security and on implementing rigorous standards that ensure data integrity and allow for comparisons across different datasets and sources. The session will also delve into the technological infrastructure needed to handle large-scale data sharing and analysis and explore the challenges and considerations for building robust systems that can support this transformation. See you in San Diego! #DrugDiscovery #DataScience #Bioinformatics #WestCoastScience #PhilipCheung #RefactorBiosciences
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Jeff Bissen
If you're not using iPSC-based models in drug discovery, you should be 💡 Immortalized lines are very common research tools, and they really are quite appealing in the sense that they're easy to work with. However, can you really trust them in drug discovery programs? It's hard to say yes because they have pretty messed up karyotypes (massive chromosomal abnormalities). Not exactly what I would call therapeutically relevant cell models ❌ On the other end of the spectrum, you've got primary cells, which are much more indicative of actual patient outcomes. In exchange for this therapeutic relevance though, they die off in culture pretty quickly, so your assay windows are quite short. Plus, primary cells are difficult to source and aren't amenable to larger scale culture. In an ideal world, we want cell models that balance the ease of immortalized lines and the relevance of primary cells ⚖ Enter induced pluripotent stem cells (iPSCs)! This basic workflow is as follows: (1) Start with relevant patient or healthy donor samples (often easily accessible skin or blood) (2) Reprogram these somatic cells into iPSCs (super important to use non-integrating methods!) (3) Perform CRISPR editing if needed (creating a disease-causing mutation, or reverting a mutated line back to wild-type) (4) Differentiate these iPSCs into desired cells types (cardiomyocytes, astrocytes, etc.) (5) Scale up production, depending on the required cell number (could be in the billions) (6) Use these iPSC-derived cell models for high throughput screening (assays customized to the modality and indication) Much more therapeutically relevant than immortalized lines, but also compatible with longer assay windows and larger culture volumes! iPSC-based models really are super powerful in drug discovery 💪 Maybe you want to implement such models but don't know where to start. Maybe you're using them to some extent but are already at capacity in terms of staff or lab space. Maybe you have expertise in the downstream assays but need a good supply of cells. In any case, this is exactly what I work on every day, so don't be shy about reaching out for help 😊 #drugdiscovery #neuroscience #biotechnology Hi, I'm Jeff Bissen (pronounced BEE-sen) 👋 In my current role as Senior Director of Business Development at Ncardia, I help with applications of iPSCs in drug discovery - and also in cell therapy (see the sister company Cellistic). 🧬 Send a message to discuss your project! I also post almost every weekday about the science and business of biotech. 🔔 Follow my profile, and subscribe to my weekly newsletter: https://lnkd.in/e8r_WBP8 *** Views expressed on LinkedIn are entirely my own and not necessarily held by any past, present, or future employer***
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Ana Jimenez Pastor
The CHAIMELEON Project aims to build an EU-wide cloud-based infrastructure for health imaging data to facilitate and contribute to developing and validating AI tools for improved cancer management. Key points: 💡 We have built a pan-cancer repository guaranteeing data standardization and image harmonization of patient data from different European hospitals to facilitate the development of reproducible and generalizable AI models. 🔏 We apply the European data privacy standards to avoid patient re-identification. 📈 We have built an infrastructure that combines storage and processing capabilities to train and validate AI solutions to accelerate lab-to-market transition. 🏆 We have organized an Open Challenge to open the developed infrastructure to the research community. More info: https://lnkd.in/dudFz-Kn 🎥 Do not miss the following video if you want more details of the project 👇 👇 👇
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Hung Trinh
Umoja Biopharma Announces Publication in Blood Highlighting Successful Generation of In Vivo CAR T-cells in Non-Human Primate Modeling First landmark, peer-reviewed publication of successful in vivo CAR T-cell data in an immune competent NHP model Data validate the VivoVec™ platform in a translationally relevant model and support its transition into human clinical testing, offering a potential paradigm shift in the field of CAR T-cell therapies Key Study Findings VivoVec particles (VVPs) incorporating CD80 and CD58 costimulation proteins exhibit enhanced capacity for in vivo CAR T-cell generation and produce CAR T-cells with increased antitumor functionality compared to those produced from VVPs displaying anti-CD3 scFvs alone. Combining the anti-CD3 scFv together with the ligand binding domains of CD80 and CD58 into a single multi-domain fusion (MDF) protein markedly augments the particles’ ability to bind, activate, and transduce T-cells. VVPs incorporating MDF compatible with NHP T-cell activation and costimulation potently generate anti-CD20 CAR T-cells in vivo, comprising up to 65% https://lnkd.in/eqsSTKjf
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Alex Dickinson
Wow, this is a big one - $1B to leverage GenAI for drug molecule design. Two links to Illumina: - Funding lead is Bob Nelson, who seed-funded Illumina, and - "teams and technologies from the genetic sequencing giant Illumina" "Drug R&D is an endeavor rife with failure — commonly cited figures estimate that only about 10% of drugs that make it to human testing are ever approved, and a far greater share fail before ever being tested in a person." "Xaira and several other new biotechs believe they can change that with new generative AI methods that can design complex molecules from scratch, find new targets, and cut months or even years from the process." Great example of the potential for GenAI to disrupt the entire drug development process. At Ryght we're applying GenAI to another major bottleneck - getting drugs through clinical trials (you can try the preview version at ryght.ai).
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