{"title":"左乙拉西坦的人群药代动力学:系统综述。","authors":"Janthima Methaneethorn, Nattawut Leelakanok","doi":"10.2174/1574884716666210223110658","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The use of levetiracetam (LEV) has been increasing, given its favorable pharmacokinetic profile. Numerous population pharmacokinetic studies for LEV have been conducted. However, there are some discrepancies regarding factors affecting its pharmacokinetic variability. Therefore, this systematic review aimed to summarize significant predictors for LEV pharmacokinetics as well as the need for dosage adjustments.</p><p><strong>Methods: </strong>We performed a systematic search for population pharmacokinetic studies of LEV conducted using a nonlinear-mixed effect approach from PubMed, Scopus, CINAHL Complete, and Science Direct databases from their inception to March 2020. Information on study design, model methodologies, significant covariate-parameter relationships, and model evaluation was extracted. The quality of the reported studies was also assessed.</p><p><strong>Results: </strong>A total of 16 studies were included in this review. Only two studies were conducted with a two-compartment model, while the rest were performed with a one-compartment structure. Bodyweight and creatinine clearance were the two most frequently identified covariates on LEV clearance (CL<sub>LEV</sub>). Additionally, postmenstrual age (PMA) or postnatal age (PNA) were significant predictors for CL<sub>LEV</sub> in neonates. Only three studies externally validated the models. Two studies conducted pharmacodynamic models for LEV with relatively small sample size.</p><p><strong>Conclusion: </strong>Significant predictors for LEV pharmacokinetics are highlighted in this review. For future research, a population pharmacokinetic-pharmacodynamic model using a larger sample size should be conducted. From a clinical perspective, the published models should be externally evaluated before clinical implementation.</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":" ","pages":"122-134"},"PeriodicalIF":16.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Population Pharmacokinetics of Levetiracetam: A Systematic Review.\",\"authors\":\"Janthima Methaneethorn, Nattawut Leelakanok\",\"doi\":\"10.2174/1574884716666210223110658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The use of levetiracetam (LEV) has been increasing, given its favorable pharmacokinetic profile. Numerous population pharmacokinetic studies for LEV have been conducted. However, there are some discrepancies regarding factors affecting its pharmacokinetic variability. Therefore, this systematic review aimed to summarize significant predictors for LEV pharmacokinetics as well as the need for dosage adjustments.</p><p><strong>Methods: </strong>We performed a systematic search for population pharmacokinetic studies of LEV conducted using a nonlinear-mixed effect approach from PubMed, Scopus, CINAHL Complete, and Science Direct databases from their inception to March 2020. Information on study design, model methodologies, significant covariate-parameter relationships, and model evaluation was extracted. The quality of the reported studies was also assessed.</p><p><strong>Results: </strong>A total of 16 studies were included in this review. Only two studies were conducted with a two-compartment model, while the rest were performed with a one-compartment structure. Bodyweight and creatinine clearance were the two most frequently identified covariates on LEV clearance (CL<sub>LEV</sub>). Additionally, postmenstrual age (PMA) or postnatal age (PNA) were significant predictors for CL<sub>LEV</sub> in neonates. Only three studies externally validated the models. Two studies conducted pharmacodynamic models for LEV with relatively small sample size.</p><p><strong>Conclusion: </strong>Significant predictors for LEV pharmacokinetics are highlighted in this review. For future research, a population pharmacokinetic-pharmacodynamic model using a larger sample size should be conducted. From a clinical perspective, the published models should be externally evaluated before clinical implementation.</p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":\" \",\"pages\":\"122-134\"},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1574884716666210223110658\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1574884716666210223110658","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Population Pharmacokinetics of Levetiracetam: A Systematic Review.
Background: The use of levetiracetam (LEV) has been increasing, given its favorable pharmacokinetic profile. Numerous population pharmacokinetic studies for LEV have been conducted. However, there are some discrepancies regarding factors affecting its pharmacokinetic variability. Therefore, this systematic review aimed to summarize significant predictors for LEV pharmacokinetics as well as the need for dosage adjustments.
Methods: We performed a systematic search for population pharmacokinetic studies of LEV conducted using a nonlinear-mixed effect approach from PubMed, Scopus, CINAHL Complete, and Science Direct databases from their inception to March 2020. Information on study design, model methodologies, significant covariate-parameter relationships, and model evaluation was extracted. The quality of the reported studies was also assessed.
Results: A total of 16 studies were included in this review. Only two studies were conducted with a two-compartment model, while the rest were performed with a one-compartment structure. Bodyweight and creatinine clearance were the two most frequently identified covariates on LEV clearance (CLLEV). Additionally, postmenstrual age (PMA) or postnatal age (PNA) were significant predictors for CLLEV in neonates. Only three studies externally validated the models. Two studies conducted pharmacodynamic models for LEV with relatively small sample size.
Conclusion: Significant predictors for LEV pharmacokinetics are highlighted in this review. For future research, a population pharmacokinetic-pharmacodynamic model using a larger sample size should be conducted. From a clinical perspective, the published models should be externally evaluated before clinical implementation.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.