冷链
背景(考古学)
理论(学习稳定性)
动力学
抗原性
环境科学
强制降级
化学
降级(电信)
生物系统
热力学
色谱法
计算机科学
食品科学
医学
物理
免疫学
抗原
生物
机器学习
甲酸铵
高效液相色谱法
古生物学
量子力学
电信
标识
DOI:10.1016/j.ejpb.2018.01.005
摘要
Due to their thermosensitivity, most vaccines must be kept refrigerated from production to use. To successfully carry out global immunization programs, ensuring the stability of vaccines is crucial. In this context, two important issues are critical, namely: (i) predicting vaccine stability and (ii) preventing product damage due to excessive temperature excursions outside of the recommended storage conditions (cold chain break). We applied a combination of advanced kinetics and statistical analyses on vaccine forced degradation data to accurately describe the loss of antigenicity for a multivalent freeze-dried inactivated virus vaccine containing three variants. The screening of large amounts of kinetic models combined with a statistical model selection approach resulted in the identification of two-step kinetic models. Predictions based on kinetic analysis and experimental stability data were in agreement, with approximately five percentage points difference from real values for long-term stability storage conditions, after excursions of temperature and during experimental shipments of freeze-dried products. Results showed that modeling a few months of forced degradation can be used to predict various time and temperature profiles endured by vaccines, i.e. long-term stability, short time excursions outside the labeled storage conditions or shipments at ambient temperature, with high accuracy. Pharmaceutical applications of the presented kinetics-based approach are discussed.
科研通智能强力驱动
Strongly Powered by AbleSci AI