Mohammad Fallahi

Please join us in the webinar next Monday to learn the latest update for our AAV manufacturing platforms, using transient transfection and stable producer cell lines, and advanced analytics in genome integrity that can support your path to IND and beyond. "Current AAV manufacturing often suffers from low productivity and scalability, high cost of raw materials, supply chain complexity, and high batch-to-batch variation. To overcome these limitations and industrialize AAV manufacturing, Lonza has developed two high-performing Xcite® AAV manufacturing platforms, using transient transfection and stable producer cell lines (PCL) technologies. Lonza’s AAV transient transfection platform consistently delivers industry leading AAV titers (E11 to E12 vg/mL), high full/empty capsid ratio and overall yield (20-40% recovery). Lonza’s proprietary suspension HEK293 cell line and plasmids, optimized manufacturing processes and innovative AAV analytics have been integrated to generate a robust and scalable platform (3L to 250L) with proven performance using multiple serotypes (AAV2, 5, 6, 8, 9 and novel capsids) and transgenes. The streamlined transient transfection platform de-risks your path to IND and reduces complexity and timeline for lengthy process and analytical development. Building upon the proprietary HEK293 cells, Lonza further developed a high-producing, helper virus-free AAV stable PCL technology. AAV production is tightly regulated and is chemically induced using doxycycline. Selected PCL clones have been identified with higher AAV titer (> 1E12 vg/mL) than transient transfection process with comparable full/empty capsid ratio (> 30% full capsids at harvest). These stable clonal cells maintain long-term stability (> 30 passages) for AAV productivity and packaging efficiency. Helper-virus free AAV PCL eliminates the need for costly plasmids, reduces supply chain and manufacturing complexities and can be easily scaled to 2000L+. Taken together, our Xcite® AAV platforms can enable high quantity and quality of commercial AAV manufacturing at a scale you need for your valuable therapies."

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🌟 𝐄𝐱𝐜𝐢𝐭𝐞𝐝 𝐭𝐨 𝐒𝐡𝐚𝐫𝐞 NyBerMan Bioinformatics Europe 𝐋𝐚𝐭𝐞𝐬𝐭 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐯𝐞 𝐏𝐮𝐛𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧! In collaboration with Sri Balaji Vidyapeeth University contributed to the bioinformatics analysis particularly to find conserved protein domains in the target protein, showcasing our expertise in structural bioinformatics. ✴️ 𝐓𝐢𝐭𝐥𝐞: Helicobacter pylori biofilm interference by N-acyl homoserine lactonases: in vitro and in silico approaches ✴️ 𝐃𝐎𝐈: https://lnkd.in/eF2Pp642 We extend our congratulations to the entire research team and a special thanks to Vaijayanthi Saravanan for initiating this collaboration and to our structural bioinformatics consultant, Dr. Madhana Priya Vikram, for her exceptional contributions. At NyBerMan, we provide end-to-end bioinformatics solutions, 𝐜𝐨𝐯𝐞𝐫𝐢𝐧𝐠 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐟𝐫𝐨𝐦 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞 𝐭𝐨 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐭𝐨 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧 𝐈𝐥𝐥𝐮𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧𝐬. 📩 𝐈𝐧𝐭𝐞𝐫𝐞𝐬𝐭𝐞𝐝 𝐢𝐧 𝐜𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐧𝐠? 🔻 For Structual & Cheminfo services, sbcteam@nyberman.com 🔻 For Multi-omics services, omicsteam@nyberman.com. 🔻 For other queries at m.velusamy@nyberman.eu 🌐 𝐋𝐞𝐚𝐫𝐧 𝐦𝐨𝐫𝐞 𝐚𝐛𝐨𝐮𝐭 𝐨𝐮𝐫 𝐛𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬 𝐞𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐚𝐧𝐝 𝐨𝐟𝐟𝐞𝐫𝐞𝐝 𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 at https://lnkd.in/eXPsdk67. #Bioinformatics #Research #Collaboration Sudharsana Sundarrajan, PhD Aiswarya P S Nair Bhavani Sridharan #Bioinformatics #Research #Collaboration #StructuralBiology #Proteomics #ConservedDomains #ComputationalBiology #MultiOmics #ScientificInnovation #DrugDiscovery #FunctionalGenomics #Genomics #Teamwork #CuttingEdgeResearch

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Latest PTCR work on Ascend (BioPharma version) from Prof. Fornelli and others. This time PTCR was combined with MS3 to localize payload on ADC using MD mass spectrometry. Interesting, we expected UVPD may slove this issue dependently, but it not. Still need the help form PTCR-MS3 to get enough and high S/N support ions~.

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Unlock the secrets of gene regulation! This exciting article, https://lnkd.in/gPe6AUKY, demonstrates single-cell multiplex profiling of gene expression and RNA–chromatin associations within individual nuclei. It uncovers cellular heterogeneity in chromatin architecture and its correlation with gene regulation, aging, and disease pathology in the human brain. Explore how chromatin-associated RNA influences gene expression spatially with our advanced Multiomic assay. You can jointly visualize RNA and chromatin-associated proteins in the same section. #multiomics #spatial #ageing #generegulation Learn more here: https://lnkd.in/gB9GVuJb

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Their abstract: We demonstrated a novel approach for protein–protein interaction (PPI) profiling of histone H3 using intracellular photocatalytic-proximity labeling (iPPL). This approach identified that the combination of acriflavine as a photocatalyst and 1-methyl-4-arylurazol (MAUra) as a protein labeling agent was the most efficient strategy to proceed the protein proximity labeling reaction. Furthermore, the identification of the labeled amino acids in histone H3 interacting proteins, histone lysine N-methyltransferase EZH2, showed that the amino acid in EZH2 within a few nanometers from histone H3 is labeled by iPPL. This restricted labeling radius allows for more-focused PPI profiling, compared to conventional proximity labeling methods.

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I wanted to congratulate my coauthors Rashmi Madda, Haichuan Liu and Zoe Zhang on a great technote about multilevel analysis of MMAE conjugated Trastuzumab using Genovis' GlyCLICK® chemistry. Combining the ZenoTOF 7600 with both the Intabio ZT and EAD peptide mapping, comprehensive intact and localized characterization of modifications were achieved. Comparisons between pre and post derivatized Trastuzumab samples identified natural and synthetic modifications allowing for highly accurate monitoring of the payload conjugation reactions. For those interested follow the link below for a PDF copy of the technote https://lnkd.in/eSreFYCz

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Last week, my team at Aganitha and I participated in an industry roundtable on "Accelerating drug discovery and development". A question that came our way was: How is generative AI powered drug design different from traditional drug design? There are of course, many differences, and a key one our team emphasized is the ability to factor-in safety and developability concerns upfront during design and not as an afterthought. There was a second key difference our team emphasized. When embarking on generative AI powered drug design exercises, or for that matter, any in silico drug design exercise, prior understanding of target structure and function becomes very important. Given that we are in the era of AlphaFold-like AI powered structure prediction models, this prerequisite does not seem too onerous but like for any step in drug discovery - nothing is as simple as it first seems. 🔗 We wrote more about this topic in a blog. Check it out at

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Assessing Technical Expertise: Choosing the Right CDMO for Advanced Therapy Medicinal Products (ATMPs) Recently, reflecting on a panel discussion I participated in with industry experts Louis Garguilo, Praveen Prasanna, and Vibhav Patel, I've developed a comprehensive framework for evaluating a Contract Development and Manufacturing Organization's (CDMO) technical capabilities. https://lnkd.in/dFWSrtcg Selecting the Right CDMO: 10 Critical Evaluation Criteria 1.    On-Site Due Diligence Conduct comprehensive on-site visits to assess capabilities. Immerse yourself in process development, QC labs, and GMP manufacturing suites to gain direct insights into the team's expertise and culture. 2.    Talent Assessment Evaluate the organization's talent approach: ·      Retention of top-tier professionals ·      Team interaction and communication dynamics ·      Leadership's commitment to technical excellence ·      Evidence of continuous learning 3.    Project-Specific Expertise Verify the CDMO's ability to demonstrate: ·      Specific ATMP methodologies ·      GxP compliance ·      Successful technology transfer ·      Regulatory understanding 4.    Analytical Capabilities Scrutinize analytical expertise: ·      Safety and purity testing ·      Identity verification ·      Quantitative analysis ·      ATMP-specific potency testing 5.    Industry Reputation ·      Leverage professional network insights ·      Seek candid colleague feedback ·      Treat CDMO selection like a critical review 6.    Problem-Solving Skills Assess their approach to challenges: ·      Deviation handling ·      Root cause analysis ·      Innovative problem-solving 7.    Talent Pool Considerations ·      Local talent availability ·      Recruitment strategies ·      Ability to attract top talent 8.    Subject Matter Expert Access Ensure direct communication with: ·      Project-specific SMEs ·      Technical experts ·      Professionals with nuanced insights 9.    Regulatory Track Record Verify: ·      Post-approval inspection performance ·      Patient-ready product history ·      Comprehensive Drug Master File 10. Technological Infrastructure Evaluate: ·      State-of-the-art facilities ·      Cutting-edge equipment ·      Novel ATMP technology expertise Final Insight Selecting the right CDMO requires systematic assessment of these critical aspects to align with your ATMP development goals. #ATMP #Biotechnology #CDMOSelection #RegulatoryCompliance #IndustryInsights

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Check out this cool blog post on virtual screening in drug discovery authored by Natalie Ma, PhD and myself!

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2025 is off to good start! Check out our recently published Proof-Of-Principle paper that describes an SPR-based assay for estimation of all fundamental kinetics parameters for irreversible covalent inhibitors of KRAS G12C. With this method, you can determine kon, koff, as well as kinact, unlocking new possibilities for improving compound prioritization through a deeper mechanistic understanding.

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So happy to share that our latest work is out in Molecular Therapy (Cell Press) 📝 ▪️In this work, we demonstrate that cell-specific re-targeting of IL-12 to PD-1+ cells (CD8 and CD4) using VHHs enhances the antitumor effect of this cytokine, and outperforms a more popular approach involving targeting cytokines to highly expressed molecules in the TME, like PD-L1. Despite the latter strategy being very effective at anchoring the cytokine to the TME, our findings suggest that specific delivery to the target cell is more effective and allows to lower treatment doses. These observations may also have implications for other cytokine-based therapies. ▪️Access the full text here 👇🏼 https://lnkd.in/dkJ2EDM5 ▪️Thank you all co-authors for their dedicated work! Uxue Beloki Eguzkiza, Patricia Apaolaza Insagurbe, Ana Igea Sucunza, Laura Salaberry, Laura Prats Mari, Eric Rovira Barreira, PhD, Juan José Lasarte, Lucía Vanrell, Cristian Smerdou Picazo. Nanogrow Biotech

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Thoughtful and insightful podcast on H5N1 and related topics, Arnab Chatterjee. Thanks for taking the time to share your wisdom, especially the part about needing more and better antivirals. https://lnkd.in/eMB-mta8

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Check out our recent talk, "The best end-to-end deep-learning practices" at statgen 2024 authored by Jake Gagnon, Hangyu Liu, Lira Pi, and Himanshu Pandya https://lnkd.in/e3_D7Esh #DeepLearning #MachineLearning

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Less than a month and counting . . . The growing demand for recombinant proteins requires simultaneous strategic development, application, and adoption of tools for the efficient expression and production of these valuable biomolecules. The Expression Stream at #PEGSEurope tackles these issues head on. https://lnkd.in/eaVu6nnZ ◼ SHORT COURSE: Tools for Cell Line Engineering and Development – what are the future tools for CLE and CLD? ◼ TRAINING SEMINAR: Current Applications of Host Expression Systems and Optimisation of the CEPA Workflow to Support Therapeutic Generation and Structural Biology – applying CEPA (Cloning, Expression, Purification, Analytics) to your workflow process? ◼ CONFERENCE: Using Data Science to Maximise Protein Production – how are you using data and engineering to evaluate expression hosts? ◼ CONFERENCE: Optimising Expression Platforms - what is the best expression system for producing your recombinant protein of choice? ◼ CONFERENCE: Protein Process Development - what are your throughput goals? These strategic back-to-back meetings investigate the newest data, innovations, and strategies to make the expression of therapeutic proteins more efficient, effective and trouble-free. #biopharmaceuticals #proteinexpression #proteinpurification #Barcelona

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Explore the #Illumina PIPseq #singlecell assay and gain an overview of how to explore it with Illumina #bioinformatics tools including DRAGEN, Partek Flow, and Correlation Engine. You will learn the basic steps in tertiary scRNA-Seq analysis. Register at: https://lnkd.in/dNnarDcR

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AI informed antibody design feels like such a near-term, high-upside application of AI in drug discovery. Antibody structures are constrained, tons of good training data, relatively small antigen recognition regions, lots of genetically validated targets, understood delivery and application vs de novo protein design a la Generate (which I also think is radical and am bullish on). This looks cool. https://lnkd.in/eQkgDXbP

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"San Diago... which of course in German means..." (you can fill in the blank in your head if you know the reference 😂) But I AM in gorgeous San Diego! Please reach out if you've been curious about base editing and would like to have an in person seminar in the So Cal region this month! Why base editing for your therapeutic cell engineering pipelines? ⏲️ SAVE TIME- reduce timelines on multiplex edited cell products by up to 90% 💰 SAVE ON COSTS of manufacturing when less steps are required to reach the end product 💪 HEALTHIER CELL PRODUCTS - gene editing with our platform avoids double strand DNA breaks, reducing the risk of genomic translocations, reducing cytotoxicity, and supporting normal growth rates

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We have an immediate opening for an experienced Medicinal Chemist (Staff or Senior Postdoc depending on experience) to design, synthesize and optimize novel compounds to modulate Nuclear Receptors and Drug-metabolizing Enzymes, using our current chemical scaffolds, ligand-protein co-crystals, and SAR data as starting points. This is an exciting opportunity to collaborate with a team of experienced biologists and structural biologists and bring our research to the next levels. If interested (or known someone who are interested), please forward CVs to me (taosheng.chen@stjude.org). Research Summary: Drug toxicity and resistance are the leading causes of therapeutic failures. The Chen Lab (https://lnkd.in/dWMm_-am) studies: (1) the chemical regulation of nuclear xenobiotic receptors, (2) the molecular basis of signal crosstalk among nuclear receptors, and (3) the mechanism of selective modulation of highly homologous drug-metabolizing enzymes. We are taking a hypothesis-driven and technology-enabled multidisciplinary approach to develop chemical probes and investigate biological mechanisms. In particular we use the promiscuous pregnane X receptor (PXR) and constitutive androstane receptor (CAR) as models. PXR and CAR transcriptionally regulate cytochrome P450 3A4 (CYP3A4) and CYP3A5—drug-metabolizing enzymes that metabolize more than 50% of clinical drugs, the dysregulation of which contributes to drug toxicity and drug resistance. We have developed the first selective PXR antagonist (Nat Commun 8:741, 2017; Nat Commun 15:4054, 2024); established that PXR and CAR form an unexpected heterodimer (Nucleic Acids Res 50:3254, 2022); revealed a mechanism that expands PXR’s ligand binding pocket to reduce ligand’s binding affinity (Proc Natl Acad Sci U S A. 120: e2217804120, 2023); and discovered the first CYP3A5-selective inhibitor and its structural basis (J Am Chem Soc 143:18467, 2021). Our goal is to understand nuclear receptor-regulated transcription networks, enzyme-drug interactions, and design therapeutic approaches to overcome drug resistance and toxicity in cellular and animal models.

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