Bradamante Silvia, Barenghi Livia, Beretta Giangiacomo, Bonfa' Maria, Rollini Manuela, Manzoni Matilde
CNR-C.S. Sintesi e Stereochimica di Speciali Sistemi Organici, Milan, Italy.
Biotechnol Bioeng. 2002 Dec 5;80(5):589-93. doi: 10.1002/bit.10418.
Microbial secondary metabolites are one of the sources of therapeutic molecules in the pharmaceutical industry. Product quality and high yields of secondary metabolites are the main goals for the commercial success of a fermentation process. Our novel approach was based on the decision-tree algorithm to determine the key variables correlated with the process outcome and on DOSY-NMR to identify both co-metabolites and impurities, and it improves fermentation systems and speeds up bioprocess development. The approach has been validated in the case of lovastatin production from Aspergillus terreus.
微生物次级代谢产物是制药行业治疗性分子的来源之一。次级代谢产物的产品质量和高产量是发酵过程商业成功的主要目标。我们的新方法基于决策树算法来确定与过程结果相关的关键变量，并基于扩散排序核磁共振（DOSY-NMR）来识别共代谢产物和杂质，它改进了发酵系统并加速了生物工艺开发。该方法已在土曲霉生产洛伐他汀的案例中得到验证。
