Can we Predict Drug Excretion into Saliva? A Systematic Review and Analysis of Physicochemical Properties.

IF 4.6 2区 医学 Q1 PHARMACOLOGY & PHARMACY Clinical Pharmacokinetics Pub Date : 2024-08-01 Epub Date: 2024-07-15 DOI:10.1007/s40262-024-01398-9
Thi A Nguyen, Ricky H Chen, Bryson A Hawkins, David E Hibbs, Hannah Y Kim, Nial J Wheate, Paul W Groundwater, Sophie L Stocker, Jan-Willem C Alffenaar
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Abstract

Background and objectives: Saliva is a patient-friendly matrix for therapeutic drug monitoring (TDM) but is infrequently used in routine care. This is due to the uncertainty of saliva-based TDM results to inform dosing. This study aimed to retrieve data on saliva-plasma concentration and subsequently determine the physicochemical properties that influence the excretion of drugs into saliva to increase the foundational knowledge underpinning saliva-based TDM.

Methods: Medline, Web of Science and Embase (1974-2023) were searched for human clinical studies, which determined drug pharmacokinetics in both saliva and plasma. Studies with at least ten subjects and five paired saliva-plasma concentrations per subject were included. For each study, the ratio of the area under the concentration-time curve between saliva and plasma was determined to assess excretion into saliva. Physicochemical properties of each drug (e.g. pKa, lipophilicity, molecular weight, polar surface area, rotatable bonds and fraction of drug unbound to plasma proteins) were obtained from PubChem and Drugbank. Drugs were categorised by their ionisability, after which saliva-to-plasma ratios were predicted with adjustment for protein binding and physiological pH via the Henderson-Hasselbalch equation. Spearman correlation analyses were performed for each drug category to identify factors predicting saliva excretion (α = 5%). Study quality was assessed by the risk of bias in non-randomised studies of interventions tool.

Results: Overall, 42 studies including 40 drugs (anti-psychotics, anti-microbials, immunosuppressants, anti-thrombotic, anti-cancer and cardiac drugs) were included. The median saliva-to-plasma ratios were similar for drugs in the amphoteric (0.59), basic (0.43) and acidic (0.41) groups and lowest for drugs in the neutral group (0.21). Higher excretion of acidic drugs (n = 5) into saliva was associated with lower ionisation and protein binding (correlation between predicted versus observed saliva-to-plasma ratios: R2 = 0.85, p = 0.02). For basic drugs (n = 21), pKa predicted saliva excretion (Spearman correlation coefficient: R = 0.53, p = 0.02). For amphoteric drugs (n = 10), hydrogen bond donor (R = - 0.76, p = 0.01) and polar surface area (R = - 0.69, p = 0.02) were predictors. For neutral drugs (n = 10), protein binding (R = 0.84, p = 0.004), lipophilicity (R = - 0.65, p = 0.04) and hydrogen bond donor count (R = - 0.68, p = 0.03) were predictors. Drugs considered potentially suitable for saliva-based TDM are phenytoin, tacrolimus, voriconazole and lamotrigine. The studies had a low-to-moderate risk of bias.

Conclusions: Many commonly used drugs are excreted into saliva, which can be partly predicted by a drug's ionisation state, protein binding, lipophilicity, hydrogen bond donor count and polar surface area. The contribution of drug transporters and physiological factors to the excretion needs to be evaluated. Continued research on drugs potentially suitable for saliva-based TDM will aid in adopting this person-centred TDM approach to improve patient outcomes.

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我们能否预测药物在唾液中的排泄量?系统回顾与理化特性分析
背景和目的:唾液是治疗药物监测(TDM)中对患者友好的基质,但在常规护理中却很少使用。这是由于基于唾液的 TDM 结果在指导用药方面存在不确定性。本研究旨在检索唾液-血浆浓度数据,随后确定影响唾液中药物排泄的理化性质,以增加基于唾液的 TDM 的基础知识:方法:在 Medline、Web of Science 和 Embase(1974-2023 年)中检索了确定唾液和血浆中药物药代动力学的人类临床研究。研究中至少有 10 名受试者,且每名受试者的唾液和血浆浓度有 5 个配对值。每项研究都测定了唾液和血浆浓度-时间曲线下面积的比值,以评估药物在唾液中的排泄情况。每种药物的理化性质(如 pKa、亲油性、分子量、极性表面积、可旋转键和未与血浆蛋白结合的药物比例)均来自 PubChem 和 Drugbank。药物按其离子性进行分类,然后通过亨德森-哈塞尔巴赫方程对蛋白质结合力和生理 pH 值进行调整,预测唾液与血浆的比率。对每个药物类别进行斯皮尔曼相关性分析,以确定预测唾液排泄的因素(α = 5%)。研究质量通过干预工具的非随机研究偏倚风险进行评估:共纳入42项研究,包括40种药物(抗精神病药、抗微生物药、免疫抑制剂、抗血栓药、抗癌药和心脏病药)。两性组(0.59)、碱性组(0.43)和酸性组(0.41)药物的唾液与血浆比率中值相似,中性组药物的唾液与血浆比率中值最低(0.21)。酸性药物(n = 5)在唾液中的排泄量较高,与较低的离子化和蛋白质结合率有关(唾液与血浆的预测比值与观察比值之间的相关性:R2 = 0.85,p = 0.05):R2 = 0.85,p = 0.02)。对于碱性药物(n = 21),pKa 预测了唾液排泄量(斯皮尔曼相关系数:R = 0.53,p = 0.02)。对于两性药物(n = 10),氢键供体(R = - 0.76,p = 0.01)和极性表面积(R = - 0.69,p = 0.02)是预测因子。对于中性药物(n = 10),蛋白质结合力(R = 0.84,p = 0.004)、亲油性(R = - 0.65,p = 0.04)和氢键供体数量(R = - 0.68,p = 0.03)是预测因素。苯妥英、他克莫司、伏立康唑和拉莫三嗪被认为可能适用于基于唾液的 TDM。这些研究的偏倚风险为低至中度:许多常用药物都会排泄到唾液中,这可以通过药物的电离状态、蛋白质结合力、亲脂性、氢键供体数量和极性表面积进行部分预测。还需要评估药物转运体和生理因素对排泄的影响。继续研究可能适合基于唾液的 TDM 的药物将有助于采用这种以人为本的 TDM 方法来改善患者的治疗效果。
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来源期刊
CiteScore
8.80
自引率
4.40%
发文量
86
审稿时长
6-12 weeks
期刊介绍: Clinical Pharmacokinetics promotes the continuing development of clinical pharmacokinetics and pharmacodynamics for the improvement of drug therapy, and for furthering postgraduate education in clinical pharmacology and therapeutics. Pharmacokinetics, the study of drug disposition in the body, is an integral part of drug development and rational use. Knowledge and application of pharmacokinetic principles leads to accelerated drug development, cost effective drug use and a reduced frequency of adverse effects and drug interactions.
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