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BioMed Research International
Volume 2014 (2014), Article ID 269305, 7 pages
Research Article

Serum-Free Medium Optimization Based on Trial Design and Support Vector Regression

1State Key Laboratory of Natural Medicines, School of Life Science and Technology, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009, China
2College of Science, China Pharmaceutical University, 24 TongJia Xiang, Nanjing 210009, China
3Research Center of Biostatistics and Computational Pharmacy, 24 Tong Jia Xiang, Nanjing 210009, China

Received 17 March 2014; Revised 26 July 2014; Accepted 27 July 2014; Published 14 October 2014

Academic Editor: Metin Guru

Copyright © 2014 Jian Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The Plackett-Burman design and support vector machine (SVM) were reported to be used on many fields such as some feature selections, protein structure prediction, or forecasting of other situations. Here, with suspension adapted Chinese hamster ovary (CHO) cells as the object of study, a serum-free medium for the culture of CHO cells in suspension was optimized by this method. Support vector machine based on genetic algorithm was used to predict the growth rate of CHO and prove the results from the trial designs. Experimental results indicated that ZnSO4, transferrin, and bovine serum albumin (BSA) were important ones. The same conclusion was arrived at when the support vector regression model analyzed the experimental results. With the methods mentioned, the influence of 7 medium supplements on the growth of CHO cells in suspension was evaluated efficiently.