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）研究对于确定药物的生物分布、剂量和功效（无毒性）至关重要。然而，对于疫苗来说，除非使用新的配方成分，否则大多数监管机构都不需要研究疫苗抗原材料本身的生物分布，而只进行剂量免疫原性研究。这是因为传统疫苗旨在通过局部募集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，新兴基因疫苗（载体化 DNA 或 mRNA 疫苗）的情况却截然不同，其临床结果取决于两个主要反应阶段的组合：药理学阶段，涉及生物分布、同化、基因翻译和表位）呈现，然后是免疫阶段，这与传统疫苗的阶段类似。从数学角度来看，与大多数生理过程一样，药物给药过程通常受到患者间和患者内部的统计分布的影响。因此，施用基因疫苗后的临床结果服从药理学和免疫学两个主要反应概率分布之和的统计概率分布。这意味着总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。 换句话说，由于基因疫苗的多阶段作用模式，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，有必要以与生物治疗类似的方式监管基因疫苗，以确保更好的功效和安全性。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。