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Bioprocess decision support tool for scalable manufacture of extracellular vesicles |
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| Authors: | Kelvin S Ng James A Smith Matthew P McAteer Benjamin E Mead Jamie Ware Felix O Jackson Alison Carter Lino Ferreira Kim Bure Jon A Rowley Brock Reeve David A Brindley Jeffrey M Karp |
| Institution: | 1. Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts
Division of Engineering in Medicine, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA Harvard Stem Cell Institute, Cambridge, Massachusetts RoosterBio, Frederick, Maryland These authors contributed equally to this study.;2. Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK;3. Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts These authors contributed equally to this study.;4. Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts Division of Engineering in Medicine, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA Harvard Stem Cell Institute, Cambridge, Massachusetts Broad Institute of Harvard and MIT, Cambridge, Massachusetts Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts;5. The Oxford-UCL Centre for the Advancement of Sustainable Medical Innovation, University of Oxford, Oxford, UK;6. Department of Paediatrics, University of Oxford, Oxford, UK;7. University of Coimbra, Center for Neuroscience and Cell Biology, Portugal;8. RoosterBio, Frederick, Maryland;9. Harvard Stem Cell Institute, Cambridge, Massachusetts;10. Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts |
| Abstract: | Newly recognized as natural nanocarriers that deliver biological information between cells, extracellular vesicles (EVs), including exosomes and microvesicles, provide unprecedented therapeutic opportunities. Large-scale and cost-effective manufacturing is imperative for EV products to meet commercial and clinical demands; successful translation requires careful decisions that minimize financial and technological risks. Here, we develop a decision support tool (DST) that computes the most cost-effective technologies for manufacturing EVs at different scales, by examining the costs of goods associated with using published protocols. The DST identifies costs of labor and consumables during EV harvest as key cost drivers, substantiating a need for larger-scale, higher-throughput, and automated technologies for harvesting EVs. Importantly, we highlight a lack of appropriate technologies for meeting clinical demands, and propose a potentially cost-effective solution. This DST can facilitate decision-making very early on in development and be used to predict, and better manage, the risk of process changes when commercializing EV products. |
| Keywords: | costs economics exosomes extracellular vesicles manufacturing scale-up |