Respiratory Disease and Lung Function Unit, Department of Medicine and Surgery, University of Parma, Parma, Italy (L.C.); Pulmonary Pharmacology Unit, Institute of Pharmaceutical Science, King's College London, United Kingdom (C.P.); Unit of Pharmacology, Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy (M.G.-M.); and Respiratory Medicine Unit, Department of Experimental Medicine, University of Rome "Tor Vergata", Rome, Italy (M.C., P.R.)
Respiratory Disease and Lung Function Unit, Department of Medicine and Surgery, University of Parma, Parma, Italy (L.C.); Pulmonary Pharmacology Unit, Institute of Pharmaceutical Science, King's College London, United Kingdom (C.P.); Unit of Pharmacology, Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy (M.G.-M.); and Respiratory Medicine Unit, Department of Experimental Medicine, University of Rome "Tor Vergata", Rome, Italy (M.C., P.R.).
Pharmacol Rev. 2024 Oct 16;76(6):1159-1220. doi: 10.1124/pharmrev.124.000951.
This review explores the concept of synergy in pharmacology, emphasizing its importance in optimizing treatment outcomes through the combination of drugs with different mechanisms of action. Synergy, defined as an effect greater than the expected additive effect elicited by individual agents according to specific predictive models, offers a promising approach to enhance therapeutic efficacy while minimizing adverse events. The historical evolution of synergy research, from ancient civilizations to modern pharmacology, highlights the ongoing quest to understand and harness synergistic interactions. Key concepts, such as concentration-response curves, additive effects, and predictive models, are discussed in detail, emphasizing the need for accurate assessment methods throughout translational drug development. Although various mathematical models exist for synergy analysis, selecting the appropriate model and software tools remains a challenge, necessitating careful consideration of experimental design and data interpretation. Furthermore, this review addresses practical considerations in synergy assessment, including preclinical and clinical approaches, mechanism of action, and statistical analysis. Optimizing synergy requires attention to concentration/dose ratios, target site localization, and timing of drug administration, ensuring that the benefits of combination therapy detected bench-side are translatable into clinical practice. Overall, the review advocates for a systematic approach to synergy assessment, incorporating robust statistical analysis, effective and simplified predictive models, and collaborative efforts across pivotal sectors, such as academic institutions, pharmaceutical companies, and regulatory agencies. By overcoming critical challenges and maximizing therapeutic potential, effective synergy assessment in drug development holds promise for advancing patient care. SIGNIFICANCE STATEMENT: Combining drugs with different mechanisms of action for synergistic interactions optimizes treatment efficacy and safety. Accurate interpretation of synergy requires the identification of the expected additive effect. Despite innovative models to predict the additive effect, consensus in drug-drug interactions research is lacking, hindering the bench-to-bedside development of combination therapies. Collaboration among science, industry, and regulation is crucial for advancing combination therapy development, ensuring rigorous application of predictive models in clinical settings.
本文综述了药理学协同作用的概念,强调了通过具有不同作用机制的药物联合使用来优化治疗效果的重要性。协同作用是指根据特定的预测模型,个体药物的预期相加作用之外的效果,它为提高治疗效果同时最小化不良反应提供了一种很有前途的方法。协同作用研究的历史演变,从古至今的药理学,突出了人们对理解和利用协同相互作用的持续探索。重点讨论了关键概念,如浓度-反应曲线、相加作用和预测模型,强调了在整个药物开发过程中需要准确的评估方法。虽然存在各种用于协同作用分析的数学模型,但选择合适的模型和软件工具仍然是一个挑战,需要仔细考虑实验设计和数据解释。此外,本文还探讨了协同作用评估中的实际考虑因素,包括临床前和临床方法、作用机制和统计分析。优化协同作用需要注意浓度/剂量比、靶位定位和药物给药时间,确保在实验室检测到的联合治疗的益处能够转化为临床实践。总的来说,该综述主张采用系统的协同作用评估方法,结合强大的统计分析、有效的简化预测模型以及学术机构、制药公司和监管机构等关键领域的合作,克服关键挑战并最大化治疗潜力,为药物开发中的协同作用评估提供了前进的方向,有望改善患者的治疗效果。