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首页> 外文期刊>Progress in Artificial Intelligence >Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges
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Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges

机译:用于神经科学药物发现和发展的定量系统药理学:现状,机遇和挑战

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摘要

The substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clinical endpoints, and complex pharmacokinetic/pharmacodynamic relationships, but also the possibility that highly selective drugs in the CNS do not reflect the complex interactions of different brain circuits. Although computational systems pharmacology modeling designed to capture essential components of complex biological systems has been increasingly accepted in pharmaceutical research and development for oncology, inflammation, and metabolic disorders, the uptake in the CNS field has been very modest. In this article, a cross-disciplinary group with representatives from academia, pharma, regulatory, and funding agencies make the case that the identification and exploitation of CNS therapeutic targets for drug discovery and development can benefit greatly from a system and network approach that can span the gap between molecular pathways and the neuronal circuits that ultimately regulate brain activity and behavior. The National Institute of Neurological Disorders and Stroke (NINDS), in collaboration with the National Institute on Aging (NIA), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), and National Center for Advancing Translational Sciences (NCATS), convened a workshop to explore and evaluate the potential of a quantitative systems pharmacology (QSP) approach to CNS drug discovery and development. The objective of the workshop was to identify the challenges and opportunities of QSP as an approach to accelerate drug discovery and development in the field of CNS disorders. In particular, the workshop examined the potential for computational neuroscience to perform QSP-based interrogation of the mechanism of action for CNS diseases, along with a more accurate and comprehensive method for evaluating drug effects and optimizing the design of clinical trials. Following up on an earlier white paper on the use of QSP in general disease mechanism of action and drug discovery, this report focuses on new applications, opportunities, and the accompanying limitations of QSP as an approach to drug development in the CNS therapeutic area based on the discussions in the workshop with various stakeholders.
机译:大脑基本科学的实质性进展尚未被充分转化为成功的临床治疗,以治疗中枢神经系统(CNS)疾病。可能的解释包括缺乏定量和验证的生物标志物,许多临床终点的主观性,以及复杂的药代动力学/药效学相互作用,而且还有可能在CNS中具有高度选择性药物的可能性不反映不同脑电路的复杂相互作用。虽然设计用于捕获复杂生物系统的基本组分的计算系统的药理学建模在药物研究和发育中越来越受到肿瘤,炎症和代谢紊乱的,但CNS领域的摄取已经非常适度。在本文中,具有来自学术界,制药,监管和资助机构的代表的跨学科团体,使CNS治疗目标用于药物发现和发展的识别和开采可以从跨越的系统和网络方法中受益匪浅最终调节脑活动和行为的分子途径与神经元电路之间的间隙。国家神经系统疾病和中风(NINDS)与国家心理健康(NIMH),国家药物滥用学院(NIDA)和国家推进翻译科学中心合作,与国家心理健康研究所(NIMH)合作合作NCATS)召集了一个研讨会来探索和评估定量系统药理学(QSP)探讨CNS药物发现和发展的潜力。研讨会的目标是确定QSP作为加速CNS障碍领域药物发现和发展的方法的挑战和机遇。特别是,研讨会检查了计算神经科学的潜力,以对CNS疾病的作用机制进行基于QSP的审查,以及评估药物效应和优化临床试验设计的更准确和综合的方法。在早期的白皮书上关于使用QSP的一般疾病机制的行动和药物发现,本报告侧重于QSP的新应用,机会和随附的局限性,作为基于CNS治疗区域的药物开发的方法。与各种利益相关者的研讨会讨论。

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