Li Na, Yang Harry
MedImmune LLC, One MedImmune Way, Gaithersburg, MD 20878, United States.
Biologicals. 2012 Nov;40(6):439-44. doi: 10.1016/j.biologicals.2012.07.016. Epub 2012 Sep 25.
Since most biological products are derived from living cell culture, it is possible that viral contaminants be transmitted to the final product. Regulatory guidance requires that viral clearance studies be conducted to demonstrate the capacity of the production process in viral removal and inactivation. The key is accurate estimation of viral titer and reduction factor (RF), defined as the difference in log(10) virus titers before and after each step of purification. Darling et al. (1998) [1] suggested a method for analysis of clearance studies. However it is unable to establish an estimate of RF when the post-process viral counts are zero. In this paper, we provide theoretical justification of the method based on normal distribution and discuss the caveats regarding the degrees of freedom. We propose two alternative methods under the assumption that the number of plaques follows a Poisson distribution. Through simulation studies, the Poisson-based methods are shown to provide better estimates of viral titers. Under the Poisson model, we also derive a method to calculate the exact confidence limits for the viral titer and reduction factor even if the post-process viral counts are zero. The use of the methods is illustrated through numerical examples.
由于大多数生物制品来源于活细胞培养，病毒污染物有可能被传递到最终产品中。监管指南要求进行病毒清除研究，以证明生产过程去除和灭活病毒的能力。关键在于准确估计病毒滴度和清除因子（RF），清除因子定义为纯化各步骤前后病毒滴度的对数（10）之差。达林等人（1998年）[1]提出了一种分析清除研究的方法。然而，当处理后病毒计数为零时，它无法建立清除因子的估计值。在本文中，我们基于正态分布提供了该方法的理论依据，并讨论了关于自由度的注意事项。在噬斑数量服从泊松分布的假设下，我们提出了两种替代方法。通过模拟研究，基于泊松分布的方法显示能更好地估计病毒滴度。在泊松模型下，我们还推导了一种方法，即使处理后病毒计数为零，也能计算病毒滴度和清除因子的精确置信限。通过数值示例说明了这些方法的应用。
