Andrew Beck

🆕New in #JEV 🆕 A novel multiplexed immunoassay for surface-exposed proteins in plasma extracellular vesicles Emma Tordoff, Jillian Allen, Katya Elgart, Ahmed Elsherbini, Vrinda Kalia, Haotian Wu, Erden Eren, Dimitrios Kapogiannis, Olesia Gololobova, Kenneth Witwer, Olga Volpert, Erez Eitan Small membranous extracellular vesicles (EV) incorporate proteins and nucleic acids from the parent cell. Proteins exposed on EV surface are dictated by cellular origin and biogenesis pathway. To better understand the EV origin and function, it is important to develop methods that reveal surface protein composition of heterogeneous EV populations in culture supernatants and in biofluids. Tetraspanins CD9, CD63, and CD81 are common and abundant EV markers. However, their relative enrichment (profile) on EVs of specific cellular origins is not fully elucidated. We introduce LuminEV, a novel version of the Luminex assay for the multiplexed analysis of EV surface proteins. Optimized LuminEV reagents enable direct, specific, and sensitive measurements of EV markers in biofluids and in culture supernatants, bypassing EV isolation step. LuminEV assay for CD9, CD63, and CD81 was validated by comparing simplex and multiplex measurements, establishing linearity, spike-in recovery, inter- and intra-assay precision, and reproducibility between operators. LuminEV measurements of CD9, CD63, and CD81 in conditioned media from 15 cell lines revealed strong variations between cell types and showed high sensitivity, which enabled EV detection without prior concentration. Using tetraspanin levels as a readout, we noted suppression and induction of EV release from the cultured cells by GW6869 and monensin. Measurement of EV CD9, CD63, and CD81 in blood plasma from 70 disease-free donors showed respective abundance of 72, 16, and 12%. CD63 displayed weak, albeit significant, negative correlation with age and was slightly lower in female samples. The assay was then used to detect cell type-specific EV surface markers, including CD235a (erythrocytes), GAP43 (neurons), and CD68 (macrophages), and to detect differences in tetraspanin profiles between healthy and diseased donors. In summary, LuminEV offers robust and sensitive approach for multiplexed assessment of EV surface proteins, to facilitate the research into EV biology, biomarker, and therapeutic applications. https://lnkd.in/eUsJWDZQ

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AI Proteins, a biotechnology company that uses computational de novo protein design to create therapeutic miniproteins, announced last week an agreement with Bristol Myers Squibb (BMS) to discover and develop novel miniprotein-based therapeutics using AI Proteins’ discovery platform. The deal could be worth up to $400M plus royalties on net sales. Miniproteins comprise: a peptide that folds into a highly stable structure, optional disulfide bonds, canonical amino acids without post translational modifications, entirely novel composition of matter designed to be non-immunogenic, and more. Notably, the company says, “because drug-like properties are designed into the miniproteins from the start, every molecule with optimized activity is ready to begin pre-clinical studies.” AI in drug discovery is one of the most active areas of biotech deal-making right now. There has been a steady stream of deals the last two years, but just within the last few months:

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💡 Feature Article 💡 In our latest #BioTuesdays feature, Adi Zuloff-Shani, Ph.D., CEO of Clearmind Medicine (NASDAQ: CMND; FSE: CWY0), discusses how their novel molecule, MEAI, is disrupting binge behaviors by targeting key neural pathways to treat alcohol use disorder (AUD). With FDA-approved clinical trials underway and innovative products like an MEAI-based beverage, Clearmind is poised to revolutionize treatments for AUD and beyond. 🔗 https://lnkd.in/gi4SfYKb Kilmer Lucas Inc.

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I’m excited to kick off The State of AI in Drug Discovery event with a Keynote Fireside Chat and 5,000+ attendees at 8:10am PT / 11:10am ET alongside Fay Lin, PhD. Together, we’ll explore how AI is transforming drug discovery end-to-end—from mapping biology to designing new chemical entities—redefining the future of pharma. I’m honored to serve alongside David Baker, who will share insights from his groundbreaking work using computers to design novel proteins. The advancements from his team at the University of Washington, Institute for Protein Design and the achievements of Demis Hassabis and John Jumper at Google DeepMind—now recognized with The Nobel Prize — have profoundly accelerated the field of protein design. At Recursion, we are leveraging multi-omic datasets—spanning phenomics, genomics, transcriptomics, and increasingly proteomics, and beyond— to create AI-powered Maps of Biology. These maps allow us to uncover novel biological insights and identify new biology and therapeutic targets that were previously out of reach. By combining this biological knowledge with cutting-edge AI-powered molecular design, we are crafting molecules that have the potential to become transformative medicines. In development, we leverage AI-powered solutions to advance predictive trial design, streamline execution, and operationalize workflows. AI helps us make smarter, faster decisions—from optimizing patient recruitment to accelerating evidence generation—improving the probability of success at every stage. Discovery and development remain profoundly humbling endeavors, reminding us of the complexity of biology. But through AI, we are unlocking new possibilities to deliver better medicines faster, ensuring treatments reach patients efficiently, with the highest levels of safety, precision, and impact. The secret to our success lies in our people and culture, who are bilingual in both the art of science and the language of AI. This unique blend allows us to navigate the complexities of biology and technology with creativity, precision, and agility. I look forward to sharing more about these innovations and continuing the conversation at the event! Details on the Oct. 30 The State of AI in Drug Discovery event here: https://lnkd.in/ec5nHGQN Read the full article in GEN here: https://lnkd.in/egEjQvtM #ai #techbio #proteins #chemistry #drugdiscovery #data #biology #maps

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We are running out of human radiologists far faster than anticipated. AI-augmentation has to step it up a notch https://lnkd.in/ejGmQRrK HT @arjunmanrai CC @curtlanglotz

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Excited to share a new publication in the Journal of Molecular Therapy which highlights the eShunt®️ Platform as a CNS gene therapy delivery method. Thanks to the teams at UMass Chan Medical School and Tufts Medical Center for your work on this study. "We're very excited about these promising preclinical results, which suggest that the eShunt System delivery approach could provide biopharmaceutical and biotechnology organizations with a minimally invasive method for delivering gene therapies directly to the cortex and brain." #bbb #CNS #drugdelivery #neurovascular #endovascular https://lnkd.in/eeKCGPm7

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Don’t miss the latest episode of The Bio Report podcast, where our CBO Hilary Eaton, PhD joined Daniel Levine for a wide-ranging conversation about the role of #GenerativeAI in drug development, our OpenCRISPR-1 molecule and why we made it open-source. 👉 https://lnkd.in/gkD4iAEt #AI #CRISPR #OpenCRISPR #ProteinDesign #Podcast

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🔬 Advancing Precision Oncology in Metastatic RCC New findings highlight the potential of longitudinal ctDNA monitoring as a predictive biomarker for treatment response and progression-free survival in metastatic renal cell carcinoma (RCC). This study demonstrates high concordance between ctDNA dynamics and clinical outcomes, paving the way for more personalized approaches to therapy and surveillance. Discover how these insights could impact the future of RCC management. 📖 Read the full study here: https://lnkd.in/ejQhtz6H #RenalCellCarcinoma #ctDNA #PrecisionMedicine #CancerResearch #OncologyInnovation

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Can machine learning outperform PD-L1 as a predictive biomarker for ICI therapy in advanced NSCLC? - Aakash Desai, MD, MPH Ravi B. Parikh American Society of Clinical Oncology (ASCO) https://lnkd.in/er8DdCJY #NSCLC #OncoDaily #Oncology #Cancer #Health #Medicine

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📺 Catch our conversation with Roger Li, MD, of Moffitt Cancer Center, on the final results of #CORE001, which investigated #cretostimogene plus #pembrolizumab for #BCG-unresponsive #NMIBC with #CIS. 👉 Find the Full Video Here:

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We are thrilled to be partnering with Zymo Research Corp on our critical patient-centric programs that are closing the AI loop from patient to effective therapy. Our CEO, Richard Novak, will be presenting together with Keith Booher at PMWC - Precision Medicine World Conference this February to share the power of patient data enabling novel drug target discovery and rapid clinical validation.

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How well can AI (GPT4+RAG) identify patients for clinical trials relative to experts using human-defined queries? @NEJM_AI https://lnkd.in/et5M644A (spoiler: Very well) CODA: Which one of the authors is featured in http://nomenomen.us ?

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Ten Companies to Watch in AI Drug Discovery https://lnkd.in/gCWtSdiZ In AI-based drug discovery—a field benefiting from a cumulative investment of $60 billion—the leaders are making real progress toward approved therapies. The post Ten Companies to Watch in AI Drug Discovery appeared first on GEN [...] #LosAngeles #OrangeCountyCA #Biotech #Lifescience #News

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🚀 Exciting developments in kidney research found check it out at: https://lnkd.in/ebbMqyQQ Check out the CNS team, including Bruce Herr and Katy Börner for their contributions. The Kidney Precision Medicine Project (KPMP) team has expanded the Human Phenotype Ontology with 329 new kidney phenotype terms, enhancing our understanding of acute kidney injury and chronic kidney disease. The Kidney Tissue Atlas Ontology now integrates 259 kidney-related biomarkers from various ontologies. Additionally, a precision medicine metadata ontology (PMMO) was developed for analyzing gene expression profiles in kidney biomarkers. These ontology-based approaches are paving the way for advanced multi-domain data integration in precision medicine! #KidneyResearch #PrecisionMedicine #CNS Learn more about CNS at: https://lnkd.in/emFAUFTE

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We're excited to share a thought-provoking piece by datma CEO Noah Nasser in HIT Consultant Media: "Unlocking Real-World Data to Advance Precision Medicine in 2025." In this article, Noah discusses the transformative potential of real-world data (#RWD) in enhancing patient care and advancing precision medicine. Discovery how federated data models are revolutionizing data sharing and utilization while maintaining stringent privacy standards. Read the full article to explore how these innovations are shaping the future of healthcare: https://lnkd.in/g7Bwfk-Z #RealWorldData #FederatedLearning #DataMonetization #HealthcareInnovation #PrecisionMedicine

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Check out this insightful piece from datma CEO Noah Nasser in HIT Consultant Media: "Unlocking Real-World Data to Advance Precision Medicine in 2025," where he shares how federated data models are not only enhancing patient care but also ensuring stringent privacy standards in healthcare. #RealWorldData #FederatedLearning #DataMonetization #HealthcareInnovation #PrecisionMedicine

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Antibody Affinity & Avidity Compiled from Google AI Antibody affinity & avidity are both measures of how strongly an antibody binds to an antigen, but they differ in what they measure Affinity The strength of a single antibody-antigen interaction at a specific binding site. Affinity is affected by molecular shape, electrostatic interactions, hydrophobic interactions, and environmental factors Avidity The total strength of an antibody's binding to multiple epitopes of an antigen. Avidity is affected by valency, bond strength, and concentration of molecules. Chemical bonds in antibody antigen comple: Formation of the Aby-Agn complex typically proceeds through the following noncovalent interactions such as; hydrophobic bonds, hydrogen bonds, Van der Waals forces, & electrostatic forces Measurement of Antibody Avidity: The antibody avidity can be measured by different methods, such as ammonium sulphate precipitation, solid-phase radioimmunoassay, surface plasmon resonance and modified ELISA. The ELISA is the most common method to analyze the avidity index Method: An IgG ELISA avidity test uses urea as a dissociating agent to measure the binding strength of IgG antibodies to an antigen In an IgG ELISA avidity test, a patient's diluted serum is added to two wells coated with an antigen. One well is washed with a regular wash buffer, while the other well is washed with a wash buffer containing urea. The optical density (OD) value of each well is measured, and the avidity index (AI) is calculated. Avidity Index: A low AI indicates low binding strength, while a high AI indicates high binding strength. A relative avidity index (RAI) is calculated to determine the avidity of a sample. RAIs below 30% indicate low avidity, RAIs between 30% and 40% are equivocal, and RAIs above 40% indicate high avidity Implications: The strength of the interaction between an antibody and an antigen influences the immune response. Antibodies with fewer binding sites tend to have high affinity and low avidity, while those with greater binding sites tend to have low affinity and high avidity. Avidity is defined as the strength of binding between immunoglobulin G (IgG) & its specific target epitope. IgG of high avidity is established during affinity maturation. Failure to achieve high avidity IgG may result in a lack of protective immunity towards infection and disease. Application: IgG avidity assays measure the binding strength between IgG antibodies and virus that can help distinguish a primary CMV infection from a past infection. Rubella IgG avidity testing is most useful in early pregnancy to help rule out a rubella infection in the first trimester, when the risk of congenital defects due to rubella is highest. Toxoplasma & Parvo virus IgG avidity testing is useful in pregnancy Note: IgM antibodies may have low affinity but they have high avidity due to their ten weak binding sites contrary to the two strong binding sites of IgG antibodies.

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AI to the rescue for cancer diagnosis! 🚀 Researchers from the #HarvardInstitutesofMedicine developed a foundation model for cancer imaging biomarker discovery, trained on 11,467 radiographic lesions using self-supervised learning. It outperformed conventional methods, excelling with limited data, and showed robustness and biological relevance, accelerating biomarker translation. This could revolutionize early cancer detection & personalized treatments. Quick Read: https://lnkd.in/gGdGAX5Q #bioinformatics #cancer #biomarker #diagnosis #ai #foundationmodel #personalizedmedicine #healthcare #sciencenews

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