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开展临床试验的方法:赖氨酸安非他明与哌甲酯的计算性直接比较

Methods to Develop an Clinical Trial: Computational Head-to-Head Comparison of Lisdexamfetamine and Methylphenidate.

作者信息

Gutiérrez-Casares José Ramón, Quintero Javier, Jorba Guillem, Junet Valentin, Martínez Vicente, Pozo-Rubio Tamara, Oliva Baldomero, Daura Xavier, Mas José Manuel, Montoto Carmen

机构信息

Unidad Ambulatoria de Psiquiatría y Salud Mental de la Infancia, Niñez y Adolescencia, Hospital Perpetuo Socorro, Badajoz, Spain.

Servicio de Psiquiatría, Hospital Universitario Infanta Leonor, Universidad Complutense, Madrid, Spain.

出版信息

Front Psychiatry. 2021 Nov 3;12:741170. doi: 10.3389/fpsyt.2021.741170. eCollection 2021.

Abstract

Regulatory agencies encourage computer modeling and simulation to reduce the time and cost of clinical trials. Although still not classified in formal guidelines, system biology-based models represent a powerful tool for generating hypotheses with great molecular detail. Herein, we have applied a mechanistic head-to-head clinical trial (ISCT) between two treatments for attention-deficit/hyperactivity disorder, to wit lisdexamfetamine (LDX) and methylphenidate (MPH). The ISCT was generated through three phases comprising (i) the molecular characterization of drugs and pathologies, (ii) the generation of adult and children virtual populations (vPOPs) totaling 2,600 individuals and the creation of physiologically based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) models, and (iii) data analysis with artificial intelligence methods. The characteristics of our vPOPs were in close agreement with real reference populations extracted from clinical trials, as did our PBPK models with parameters. The mechanisms of action of LDX and MPH were obtained from QSP models combining PBPK modeling of dosing schemes and systems biology-based modeling technology, i.e., therapeutic performance mapping system. The step-by-step process described here to undertake a head-to-head ISCT would allow obtaining mechanistic conclusions that could be extrapolated or used for predictions to a certain extent at the clinical level. Altogether, these computational techniques are proven an excellent tool for hypothesis-generation and would help reach a personalized medicine.

摘要

监管机构鼓励采用计算机建模和模拟技术,以减少临床试验的时间和成本。尽管基于系统生物学的模型仍未被纳入正式指南,但它是一种强大的工具,能够生成具有高度分子细节的假设。在此,我们对注意力缺陷多动障碍的两种治疗方法,即赖右苯丙胺(LDX)和哌甲酯(MPH),进行了一项机制性的直接对比临床试验(ISCT)。该ISCT通过三个阶段生成,包括:(i)药物和病理的分子特征分析;(ii)生成总计2600名个体的成人和儿童虚拟人群(vPOPs),并创建基于生理的药代动力学(PBPK)和定量系统药理学(QSP)模型;(iii)使用人工智能方法进行数据分析。我们的vPOPs特征与从临床试验中提取的真实参考人群高度一致,我们的PBPK模型参数也是如此。LDX和MPH的作用机制是通过结合给药方案的PBPK建模和基于系统生物学的建模技术(即治疗性能映射系统)的QSP模型获得的。这里描述的进行直接对比ISCT的逐步过程,将能够得出机制性结论,这些结论在一定程度上可以外推或用于临床水平的预测。总之,这些计算技术被证明是一种出色的假设生成工具,有助于实现个性化医疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1aa6/8595241/356469d9cbc7/fpsyt-12-741170-g0001.jpg

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