In a typical course of drug development, thorough pharmacokinetic (PK) studies are essential for the determination of drug biodistribution, dosage and efficacy without toxicity. For vaccines, however, unless a new formulation component is used, most regulatory agencies rule out the need for studying the biodistribution of the vaccine antigenic material per se, and only dose-immunogenicity studies are performed. This is because traditional vaccines are meant to directly induce immunogenicity by locally recruiting immunocytes that will carry on with the pursuing immunogenic processes. Thus, the clinical outcome from traditional vaccines is determined mainly by an immunological response phase. Yet, the case is significantly different for the emergent genetic vaccines (vectorised DNA or mRNA vaccines), where the clinical outcome is dependent on a combination of two major response phases: a pharmacological phase that involves biodistribution, assimilation, gene translation and epitope(s) presentation, followed by an immunological phase, which is similar to that of traditional vaccines. From a mathematical perspective, processes involved in drug administration are typically subject to inter- and intra-patient statistical distributions like most physiological processes. Therefore, the clinical outcome after administering genetic vaccines obeys a statistical probability distribution combined of the sum of two major response probability distributions, pharmacological and immunological. This implies that the variance coefficient of the summed response probability distributions has a larger value than the variance of each underlying distribution. In other words, due to the multi-phased mode of action of genetic vaccines, their clinical outcome has more variability than that of traditional vaccines. This observation points toward the necessity for regulating genetic vaccines in a similar manner to bio-therapeutics to ensure better efficacy and safety. A structural PK model is provided to predict the sources of variability, biodistribution and dose optimisation.

在药物开发的典型过程中，彻底的药代动力学 (PK) 研究对于确定无毒性的药物生物分布、剂量和功效至关重要。然而，对于疫苗，除非使用新的配方成分，否则大多数监管机构都排除了研究疫苗抗原材料本身的生物分布的需要，并且只进行了剂量免疫原性研究。这是因为传统疫苗旨在通过局部招募免疫细胞来直接诱导免疫原性，这些免疫细胞将继续进行免疫原性过程。因此，传统疫苗的临床结果主要由免疫反应阶段决定。然而，对于新兴的基因疫苗（矢量化 DNA 或 mRNA 疫苗），情况却大不相同，其中临床结果取决于两个主要反应阶段的组合：一个涉及生物分布、同化、基因翻译和表位呈递的药理学阶段，然后是类似于传统疫苗的免疫学阶段。从数学的角度来看，与大多数生理过程一样，涉及药物管理的过程通常会受到患者间和患者内的统计分布的影响。因此，接种基因疫苗后的临床结果服从药理学和免疫学两种主要反应概率分布之和的统计概率分布。这意味着总和响应概率分布的方差系数具有比每个基础分布的方差更大的值。换言之，由于基因疫苗的多阶段作用方式，其临床结果比传统疫苗具有更大的变异性。这一观察结果表明有必要以与生物疗法类似的方式调节基因疫苗，以确保更好的疗效和安全性。提供结构 PK 模型来预测变异性、生物分布和剂量优化的来源。