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.
Biotechnol Bioeng. 2019 Feb;116(2):307-319. doi: 10.1002/bit.26809. Epub 2018 Nov 8.
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.
新发现的细胞间生物信息传递的天然纳米载体——细胞外囊泡（EVs），包括外泌体和微囊泡，为治疗提供了前所未有的机会。大规模且具有成本效益的制造对于满足商业和临床需求的 EV 产品至关重要；成功的转化需要仔细决策，以最小化财务和技术风险。在这里，我们开发了一个决策支持工具（DST），通过检查使用已发表方案相关的商品成本，计算不同规模制造 EV 的最具成本效益的技术。DST 确定了 EV 收获过程中劳动和耗材的成本是关键成本驱动因素，这证明需要更大规模、更高通量和自动化的 EV 收获技术。重要的是，我们强调了缺乏满足临床需求的适当技术，并提出了一种潜在的具有成本效益的解决方案。该 DST 可以在开发的早期阶段协助决策，并用于预测和更好地管理 EV 产品商业化过程中工艺变化的风险。
