Development and adaptation of mathematical methodologies for drug evaluation and use

目前，正规当局将基于模型的药物研究和开发作为一种重要方法加以颁布，这种方法大大有助于药物管理和决策。学术界通过开展一些基础研究活动和开设专门课程，也接受了同样的观点。我们观察到，与药物有关的研究已逐步发展成为一个精确的科学学科，可以受益于巨大的数学灵感和兴趣。本研究计划的目标是通过引入适当的数学方法，为药物开发和评价建立一个坚实的理论框架。我们研究的这一方向只是回应了对治疗评估和预测的更准确指标的日益增长的需求。不可否认的是，基于微分方程的确定性数学表示为生物制药领域带来了巨大的洞察力，并追溯了其定量时代的道路。然而，越来越多的报告，通过先进的测量技术，沿着在药物相关知识的进步，新获得的数据支持的变化，挑战这一领域的许多方面的确定性的看法。 由于这种变异性通常不包括在传统的指标中，并且由于越来越多的报告证据表明其影响，因此基于理论的药理学指标的提议成为不可避免的步骤，以便提供药物性能的公平评价并减少不适当药物使用的后果。概率特征无疑是这种变异性的内在组成部分，应该为这种新的调查分配足够的权重。 使用各种数学方法，我们将在不同的水平上工作，这些水平有助于治疗的可变性，从药物摄入到药物吸收和体内处置，然后到药物作用。

Model-based drug research and development is now promulgated by regular authorities as an important approach that substantially contributes to drug management and decision-making. The same vision has been embraced by academia through launching of several fundamental research activities and specialized curricula. We observe that drug-related research has been progressively evolving towards an exact science discipline that can benefit from great mathematical inspiration and interest. The objective of the present research program is to build a solid theoretical framework for drug development and evaluation by introducing appropriate mathematical methodologies. This direction in our research simply echoes the increasing need for more accurate metrics for therapeutic evaluation and prediction. It is undeniable that the deterministic mathematical representation based on differential equations has brought great insights to the biopharmaceutical field and traced the path towards its quantitative era. However, the increasingly reported variability, supported by newly acquired data through advanced measurement techniques, along with the progress in drug-related knowledge, challenges this deterministic vision for many aspects of the field. Since this variability is not generally included into traditional metrics, and because of the increasingly reported evidence for its impact, proposition of theoretically-based pharmacological metrics becomes an unavoidable step in order to provide a fair evaluation of drug performance and reduce consequences of inappropriate drug use. The probabilistic features, which undoubtedly are intrinsic part of this variability, should be allocated a sufficient weight for this new investigation. Using various mathematical approaches, we will work at different levels that contribute to therapeutic variability, going from the drug intake, to drug absorption and disposition within the body and then to drug action.