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| This Advancing RNA discussion will be a deep dive into the world of plasmid sourcing and quality considerations. What quality attributes matter the most for producing the desired quality of mRNA? What are the current gaps in our knowledge of plasmid quality, and how are we as an industry striving to close these gaps? Register today and find out. |
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By Anna Rose Welch, Advancing RNA | The transition from RNA vaccines to therapeutics is an “expansion” all on its own; but to do this successfully, we need to expand our science, our products’ deliverability, and our patient access. In the following article, I highlight a few of the best practices and/or innovations that came up in conversation during this event that will play a significant role in helping us expand mRNA’s reach, both scientifically and therapeutically. | |
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Decoding How HNRNPD Shapes circRNA Biogenesis And RNA Fate | By Chen Liang, Ph.D., Researcher, University of Science and Technology of China | How do cells decide between circular and linear RNA? New insights into HNRNPD reveal mechanisms that could improve the design of future circRNA therapeutics. |
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| Optimizing Large-Scale mRNA Processes In A cGMP Environment | Poster | By Clemens Jakobi, Michal Domański, and Telmo Graça, Lonza | Commercial production requires validated, highly reproducible workflows. Examine emerging technologies designed to streamline process development in regulated environments. |
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| Nucleic Acid-LNP Ultrafiltration And Diafiltration | White Paper | Recipharm Advanced Bio | Downstream filtration can make or break LNPs at scale. See how membrane format, loading, and shear affect recovery and stability — and how alternative TFF lowers scale‑up risk. |
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| Webinar: Autonomous Impinging Jet Mixing for LNP Process Development | Lipid nanoparticle (LNP) development can be slow and resource-intensive. Discover how impinging jet mixing, automation, inline analytics, and data-driven optimization can accelerate process development and enable more predictive manufacturing. This Knauer webinar will explore closed-loop experimentation, automated design of experiments, self-optimization, and modeling approaches that can help identify robust conditions faster and support scalable, reproducible LNP production. Click here to learn more. |
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