Janssen Mart P, Over Jan, van der Poel Cees L, Cuijpers H Theo M, van Hout Ben A
University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands.
Transfusion. 2008 Jan;48(1):153-62. doi: 10.1111/j.1537-2995.2007.01493.x. Epub 2007 Sep 24.
The prevention of transmission of viral infections by plasma-derived medicinal products is of concern to manufacturers, legislators, and patient representative groups. Recent European legislation requires a viral risk assessment for all new marketing applications of such products.
A discrete event Monte Carlo model was developed to determine the viral transmission risks of the plasma-derived medicinal products. The model incorporates donor epidemiology, donation intervals, efficiency of screening tests for viral markers, inventory hold period, size and composition of the manufacturing pool, production time, process virus reduction capacity, and product yield. With the model, the human immunodeficiency virus (HIV) and hepatitis C virus (HCV) contamination risks of a typical hypothetical plasma product were calculated, and the sensitivity of the risk to various model variables was analyzed.
The residual HIV and HCV risks of the finished products are linear in change with viral incidence rate and inversely linear with product yield and process virus reduction capacity. For the product analyzed in this article, the residual risk is less sensitive to changes in screening test pool size, donation frequency, and inventory hold period. There is only a limited dependency on the donation type (apheresis or whole-blood donations) and a negligible dependency on the manufacturing pool size.
The use of probabilistic model simulation techniques is indispensable when estimating realistic residual viral risks of plasma-derived medicinal products. In contrast to conventional deterministic residual risk estimations, the probabilistic approach allows incorporation of specific manufacturing decisions and therefore provides the only feasible alternative for a correct assessment of residual risks.
血浆衍生药物产品的病毒感染传播预防是制造商、立法者和患者代表团体所关注的问题。欧洲近期的立法要求对此类产品的所有新上市申请进行病毒风险评估。
开发了一个离散事件蒙特卡罗模型来确定血浆衍生药物产品的病毒传播风险。该模型纳入了献血者流行病学、献血间隔、病毒标志物筛查测试的效率、库存保存期、生产池的规模和组成、生产时间、工艺病毒去除能力以及产品产量。利用该模型，计算了一种典型假设血浆产品的人类免疫缺陷病毒（HIV）和丙型肝炎病毒（HCV）污染风险，并分析了风险对各种模型变量的敏感性。
成品的残留HIV和HCV风险随病毒发病率呈线性变化，与产品产量和工艺病毒去除能力呈反线性关系。对于本文分析的产品，残留风险对筛查测试池规模、献血频率和库存保存期变化的敏感性较低。对献血类型（单采或全血献血）的依赖性有限，对生产池规模的依赖性可忽略不计。
在估计血浆衍生药物产品实际的残留病毒风险时，使用概率模型模拟技术是必不可少的。与传统的确定性残留风险估计不同，概率方法允许纳入特定的生产决策，因此为正确评估残留风险提供了唯一可行的选择。
