The role of in silico and in vitro models in Parkinson’s disease: Drug discovery and therapy applications

IF 15.5 1区医学 Q1 CELL BIOLOGY

Ageing Research Reviews Pub Date : 2026-01-01 Epub Date: 2025-11-22 DOI:10.1016/j.arr.2025.102953

Munabize Himwaba , Kermue Vasco Jarnda , Maxwell Tarwin Dweh , Xuan Liu , Yuyue Xiang , Xiyan Zou , Hanxiao Lv , Tianjiao Li , Xinya Tu , Jianwu Wang

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引用次数: 0

Abstract

Parkinson's disease is a neurodegenerative condition, marked by a progressive deterioration in both motor and non-motor abilities, which can severely affect the quality of life of the elderly population. With no cure available, innovative tools in treatment development and drug discovery are necessary. For several years, traditional models have been essential; however, they face limitations in replicating the complex setting of Parkinson's disease. In this regard, in silico and in vitro models have become essential tools in advancing Parkinson's disease drug discovery because of the potential they exhibit over traditional models. Here, we comprehensively review the latest innovations in both models and discuss their role in discovering therapeutic targets, optimizing drug candidates, promoting personalized medicine, and identifying biomarkers. While in vitro models better simulate the complicated cell interactions and increase the predictability of therapeutic effects, silico models shine in cost-effectiveness and high-throughput drug screening. Additionally, we discuss how combining advanced technologies with both models can help to overcome current constraints and problems in Parkinson's disease drug discovery, therefore facilitating the development of effective and targeted therapies in a shorter timeframe.

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计算机和体外模型在帕金森病中的作用：药物发现和治疗应用。

帕金森病是一种神经退行性疾病，其特征是运动和非运动能力的进行性恶化，这可能严重影响老年人的生活质量。由于无法治愈，在治疗开发和药物发现方面的创新工具是必要的。多年来，传统模式一直至关重要；然而，他们在复制帕金森病的复杂环境方面面临着局限性。在这方面，计算机和体外模型已经成为推进帕金森病药物发现的重要工具，因为它们比传统模型更具潜力。在这里，我们全面回顾了这两种模型的最新创新，并讨论了它们在发现治疗靶点、优化候选药物、促进个性化医疗和识别生物标志物方面的作用。体外模型能更好地模拟复杂的细胞相互作用，提高治疗效果的可预测性，而硅模型在成本效益和高通量药物筛选方面大放异彩。此外，我们讨论了如何将先进技术与两种模型相结合，以帮助克服当前帕金森病药物发现的限制和问题，从而促进在更短的时间内开发有效的靶向治疗方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ageing Research Reviews 医学-老年医学

CiteScore

19.80

自引率

2.30%

发文量

216

审稿时长

55 days

期刊介绍： With the rise in average human life expectancy, the impact of ageing and age-related diseases on our society has become increasingly significant. Ageing research is now a focal point for numerous laboratories, encompassing leaders in genetics, molecular and cellular biology, biochemistry, and behavior. Ageing Research Reviews (ARR) serves as a cornerstone in this field, addressing emerging trends. ARR aims to fill a substantial gap by providing critical reviews and viewpoints on evolving discoveries concerning the mechanisms of ageing and age-related diseases. The rapid progress in understanding the mechanisms controlling cellular proliferation, differentiation, and survival is unveiling new insights into the regulation of ageing. From telomerase to stem cells, and from energy to oxyradical metabolism, we are witnessing an exciting era in the multidisciplinary field of ageing research. The journal explores the cellular and molecular foundations of interventions that extend lifespan, such as caloric restriction. It identifies the underpinnings of manipulations that extend lifespan, shedding light on novel approaches for preventing age-related diseases. ARR publishes articles on focused topics selected from the expansive field of ageing research, with a particular emphasis on the cellular and molecular mechanisms of the aging process. This includes age-related diseases like cancer, cardiovascular disease, diabetes, and neurodegenerative disorders. The journal also covers applications of basic ageing research to lifespan extension and disease prevention, offering a comprehensive platform for advancing our understanding of this critical field.