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
{"title":"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","authors":"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","doi":"10.1007/s40262-024-01398-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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: R<sup>2</sup> = 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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1067-1087"},"PeriodicalIF":4.6000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343830/pdf/","citationCount":"0","resultStr":"{\"title\":\"Can we Predict Drug Excretion into Saliva? A Systematic Review and Analysis of Physicochemical Properties.\",\"authors\":\"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\",\"doi\":\"10.1007/s40262-024-01398-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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: R<sup>2</sup> = 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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":10405,\"journal\":{\"name\":\"Clinical Pharmacokinetics\",\"volume\":\" \",\"pages\":\"1067-1087\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343830/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Pharmacokinetics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s40262-024-01398-9\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Pharmacokinetics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40262-024-01398-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Can we Predict Drug Excretion into Saliva? A Systematic Review and Analysis of Physicochemical Properties.
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.
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.