目的:对肠道病毒71型灭活疫苗生产工艺中氢氧化铝佐剂的制备工艺进行优化。方法:采用氨水法制备氢氧化铝佐剂,取优化前3批及优化后3批,对制备过程中氨水的滴加方式以及透析方式进行优化;检测优化前后的氢氧化铝佐剂的粒径、沉降率、铵...目的:对肠道病毒71型灭活疫苗生产工艺中氢氧化铝佐剂的制备工艺进行优化。方法:采用氨水法制备氢氧化铝佐剂,取优化前3批及优化后3批,对制备过程中氨水的滴加方式以及透析方式进行优化;检测优化前后的氢氧化铝佐剂的粒径、沉降率、铵离子及铝含量,同时检测优化前后各3批氢氧化铝对肠道病毒71型灭活疫苗的吸附效果。结果:优化后的氢氧化铝佐剂平均粒径显著小于优化前(P<0.05),且平均粒径变异系数小于优化前3批,优化后3批氢氧化铝佐剂的沉降率均为0 m L,铵离子检测合格率100%,铝含量及氢氧化铝含量显著大于优化前(P<0.05)、分别提高了24.7%和26.1%;优化前后6批氢氧化铝佐剂所配制的半成品,其上清液抗原百分含量均≤1.25%,优化前后的氢氧化铝佐剂对EV71抗原的吸附效果比较,差异无统计学意义(P>0.05)。结论:本部分的优化方式提高了自配氢氧化铝佐剂的质量和安全性,减少了批间差异,提高了生产效率,并且其有效性没有因为优化而受到影响。展开更多
A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses...A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses. The significance of variables and their interactions were tested by means of the ANOVA with 95% confidence limits; the standardized effects were investigated by Pareto chart, the optimum values of the selected variables were obtained by analyzing the response surface contour plots. The optimized Mw value of 1. 217 × 10^5 g/mol was very close to the industrial value （ （ 1.22 ±0. 004） ×10^6 g/tool） at the optimum values.展开更多
文摘目的:对肠道病毒71型灭活疫苗生产工艺中氢氧化铝佐剂的制备工艺进行优化。方法:采用氨水法制备氢氧化铝佐剂,取优化前3批及优化后3批,对制备过程中氨水的滴加方式以及透析方式进行优化;检测优化前后的氢氧化铝佐剂的粒径、沉降率、铵离子及铝含量,同时检测优化前后各3批氢氧化铝对肠道病毒71型灭活疫苗的吸附效果。结果:优化后的氢氧化铝佐剂平均粒径显著小于优化前(P<0.05),且平均粒径变异系数小于优化前3批,优化后3批氢氧化铝佐剂的沉降率均为0 m L,铵离子检测合格率100%,铝含量及氢氧化铝含量显著大于优化前(P<0.05)、分别提高了24.7%和26.1%;优化前后6批氢氧化铝佐剂所配制的半成品,其上清液抗原百分含量均≤1.25%,优化前后的氢氧化铝佐剂对EV71抗原的吸附效果比较,差异无统计学意义(P>0.05)。结论:本部分的优化方式提高了自配氢氧化铝佐剂的质量和安全性,减少了批间差异,提高了生产效率,并且其有效性没有因为优化而受到影响。
基金Supported by the R&D Program of Catalyst Company,SINOPEC(G8101-11-ZS-0016*)
文摘A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses. The significance of variables and their interactions were tested by means of the ANOVA with 95% confidence limits; the standardized effects were investigated by Pareto chart, the optimum values of the selected variables were obtained by analyzing the response surface contour plots. The optimized Mw value of 1. 217 × 10^5 g/mol was very close to the industrial value （ （ 1.22 ±0. 004） ×10^6 g/tool） at the optimum values.
