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Robotically handled whole-tissue culture system for the screening of oral drug formulations.
Nature Biomedical Engineering ( IF 26.8 ) Pub Date : 2020-04-27 , DOI: 10.1038/s41551-020-0545-6
Thomas von Erlach 1 , Sarah Saxton 1 , Yunhua Shi 1 , Daniel Minahan 1 , Daniel Reker 1, 2 , Farhad Javid 1 , Young-Ah Lucy Lee 1 , Carl Schoellhammer 1 , Tina Esfandiary 1 , Cody Cleveland 1, 2 , Lucas Booth 1 , Jiaqi Lin 1 , Hannah Levy 1 , Sophie Blackburn 1 , Alison Hayward 3 , Robert Langer 1, 4, 5 , Giovanni Traverso 1, 2, 6
Affiliation  

Monolayers of cancer-derived cell lines are widely used in the modelling of the gastrointestinal (GI) absorption of drugs and in oral drug development. However, they do not generally predict drug absorption in vivo. Here, we report a robotically handled system that uses large porcine GI tissue explants that are functionally maintained for an extended period in culture for the high-throughput interrogation (several thousand samples per day) of whole segments of the GI tract. The automated culture system provided higher predictability of drug absorption in the human GI tract than a Caco-2 Transwell system (Spearman's correlation coefficients of 0.906 and 0.302, respectively). By using the culture system to analyse the intestinal absorption of 2,930 formulations of the peptide drug oxytocin, we discovered an absorption enhancer that resulted in a 11.3-fold increase in the oral bioavailability of oxytocin in pigs in the absence of cellular disruption of the intestinal tissue. The robotically handled whole-tissue culture system should help advance the development of oral drug formulations and might also be useful for drug screening applications.

中文翻译:

用于筛选口服药物制剂的机器人处理的全组织培养系统。

癌症衍生细胞系的单层被广泛用于药物胃肠道 (GI) 吸收的建模和口服药物开发。然而,它们通常不能预测药物在体内的吸收。在这里,我们报告了一个机器人处理的系统,该系统使用大型猪 GI 组织外植体,这些外植体在培养过程中保持较长时间的功能,用于对 GI 道的整个部分进行高通量检查(每天数千个样本)。与 Caco-2 Transwell 系统相比,自动培养系统提供了更高的人体胃肠道药物吸收可预测性(Spearman 相关系数分别为 0.906 和 0.302)。通过使用培养系统分析2930个多肽类药物催产素制剂的肠道吸收情况,我们发现了一种吸收促进剂,它可以在没有肠道组织细胞破坏的情况下使猪的催产素口服生物利用度增加 11.3 倍。机器人处理的全组织培养系统应该有助于推进口服药物制剂的开发,也可能对药物筛选应用有用。
更新日期:2020-04-27
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