Clinical Pharmacokinetics最新文献

{"title":"Dose-Response Study of Norepinephrine Infusion for Maternal Hypotension in Preeclamptic Patients Undergoing Cesarean Delivery Under Spinal Anesthesia.","authors":"Yi Chen, Lei Guo, Rui Qin, Nan Xi, Shengfu Wang, Yujie Ma, Xinli Ni","doi":"10.1007/s40262-024-01381-4","DOIUrl":"10.1007/s40262-024-01381-4","url":null,"abstract":"<p><strong>Background and objective: </strong>Spinal anesthesia remains the preferred mode of anesthesia for preeclamptic patients during cesarean delivery. We investigated the incidence of maternal hypotension under spinal anesthesia during cesarean delivery, by comparing different prophylactic infusion rates of norepinephrine with normal saline.</p><p><strong>Methods: </strong>We randomly allocated 180 preeclamptic patients (45 in each groups) aged 18-45 scheduled for cesarean delivery to receive one of four prophylactic norepinephrine infusions at doses of 0 (normal saline group), 0.025 (0.025 group), 0.05 (0.05 group), or 0.075 (0.075 group) µg/kg/min following spinal anesthesia. The primary endpoint was the incidence of maternal hypotension (systolic blood pressure < 80% of baseline).</p><p><strong>Results: </strong>The incidence of maternal hypotension was reduced with different prophylactic infusion rates of norepinephrine (26.7%, 15.6%, and 6.7%) compared with normal saline (37.8%) with a significant decreasing trend (p = 0.002). As the infusion doses of norepinephrine increased, there is a significant decreasing trend in deviation of systolic blood pressure control (median performance error; median absolute performance error) from baseline (p < 0.001; p < 0.001) and need for rescue norepinephrine boluses (p = 0.020). The effective dose 50 and effective dose 90 of prophylactic norepinephrine infusion were - 0.018 (95% confidence interval - 0.074, 0.002) µg/kg/min and 0.065 (95% confidence interval 0.048, 0.108) µg/kg/min, respectively.</p><p><strong>Conclusions: </strong>Prophylactic infusion of norepinephrine, as compared to no preventive measures, can effectively reduce the incidence of maternal hypotension in preeclamptic patients under spinal anesthesia during cesarean delivery, without increasing other adverse events for either the mother or neonate.</p><p><strong>Registration: </strong>Clinical trials.gov identifier number NCT04556370.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"847-856"},"PeriodicalIF":4.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141310168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pharmacogenetic Testing or Therapeutic Drug Monitoring: A Quantitative Framework.","authors":"Maddalena Centanni, Niels Reijnhout, Abel Thijs, Mats O Karlsson, Lena E Friberg","doi":"10.1007/s40262-024-01382-3","DOIUrl":"10.1007/s40262-024-01382-3","url":null,"abstract":"<p><strong>Background: </strong>Pharmacogenetic profiling and therapeutic drug monitoring (TDM) have both been proposed to manage inter-individual variability (IIV) in drug exposure. However, determining the most effective approach for estimating exposure for a particular drug remains a challenge. This study aimed to quantitatively assess the circumstances in which pharmacogenetic profiling may outperform TDM in estimating drug exposure, under three sources of variability (IIV, inter-occasion variability [IOV], and residual unexplained variability [RUV]).</p><p><strong>Methods: </strong>Pharmacokinetic models were selected from the literature corresponding to drugs for which pharmacogenetic profiling and TDM are both clinically considered approaches for dose individualization. The models were used to simulate relevant drug exposures (trough concentration or area under the curve [AUC]) under varying degrees of IIV, IOV, and RUV.</p><p><strong>Results: </strong>Six drug cases were selected from the literature. Model-based simulations demonstrated that the percentage of patients for whom pharmacogenetic exposure prediction is superior to TDM differs for each drug case: tacrolimus (11.0%), tamoxifen (12.7%), efavirenz (49.2%), vincristine (49.6%), risperidone (48.1%), and 5-fluorouracil (5-FU) (100%). Generally, in the presence of higher unexplained IIV in combination with lower RUV and IOV, exposure was best estimated by TDM, whereas, under lower unexplained IIV in combination with higher IOV or RUV, pharmacogenetic profiling was preferred.</p><p><strong>Conclusions: </strong>For the drugs with relatively low RUV and IOV (e.g., tamoxifen and tacrolimus), TDM estimated true exposure the best. Conversely, for drugs with similar or lower unexplained IIV (e.g., efavirenz or 5-FU, respectively) combined with relatively high RUV, pharmacogenetic profiling provided the most accurate estimate for most patients. However, genotype prevalence and the relative influence of genotypes on the PK, as well as the ability of TDM to accurately estimate AUC with a limited number of samples, had an impact. The results could be used to support clinical decision making when considering other factors, such as the probability for severe side effects.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"871-884"},"PeriodicalIF":4.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141261243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Various Degrees of Renal or Hepatic Impairment on the Pharmacokinetic Properties of Once-Weekly Insulin Icodec.","authors":"Hanne Haahr, Blanka Cieslarová, Janne R Hingst, Shan Jiang, Niels R Kristensen, Viera Kupčová, Lea Nørgreen, Frank-Dietrich H Wagner, Stanislav Ignatenko","doi":"10.1007/s40262-024-01375-2","DOIUrl":"10.1007/s40262-024-01375-2","url":null,"abstract":"<p><strong>Background and objective: </strong>Icodec is a once-weekly insulin being developed to provide basal insulin coverage in diabetes mellitus. This study evaluated the effects of renal or hepatic impairment on icodec pharmacokinetics.</p><p><strong>Methods: </strong>Two open-label, parallel-group, single-dose (1.5 U/kg subcutaneously) trials were conducted. In a renal impairment trial, 58 individuals were allocated to normal renal function (measured glomerular filtration rate ≥ 90 mL/min), mild (60 to < 90 mL/min), moderate (30 to < 60 mL/min) or severe (< 30 mL/min) renal impairment or end-stage renal disease. In a hepatic impairment trial, 25 individuals were allocated to normal hepatic function or mild (Child-Pugh Classification grade A), moderate (grade B) or severe (grade C) hepatic impairment. Blood was sampled frequently for a pharmacokinetic analysis until 35 days post-dose.</p><p><strong>Results: </strong>The shape of the icodec pharmacokinetic profile was not affected by renal or hepatic impairment. Total icodec exposure was greater for mild (estimated ratio [95% confidence interval]: 1.12 [1.01; 1.24]), moderate (1.24 [1.12; 1.37]) and severe (1.28 [1.16; 1.42]) renal impairment, and for end-stage renal disease (1.14 [1.03; 1.28]), compared with normal renal function. It was also greater for mild (1.13 [1.00; 1.28]) and moderate (1.15 [1.02; 1.29]) hepatic impairment versus normal hepatic function. There was no statistically significant difference between severe hepatic impairment and normal hepatic function. Serum albumin levels (range 2.7-5.1 g/dL) did not statistically significantly influence icodec exposure.</p><p><strong>Conclusions: </strong>The clinical relevance of the slightly higher icodec exposure with renal or hepatic impairment is limited as icodec should be dosed according to individual need. No specific icodec dose adjustment is required in renal or hepatic impairment.</p><p><strong>Clinical trial registration: </strong>ClinicalTrials.gov identifiers: NCT03723785 and NCT04597697.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"819-830"},"PeriodicalIF":4.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140897536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Physiologically Based Pharmacokinetic Modeling to Characterize the Effects of Age and Obesity on the Disposition of Levetiracetam in the Pediatric Population.","authors":"Patricia D Maglalang, Jaydeep Sinha, Kanecia Zimmerman, Sean McCann, Andrea Edginton, Christoph P Hornik, Chi D Hornik, William J Muller, Amira Al-Uzri, Marisa Meyer, Jia-Yuh Chen, Ravinder Anand, Eliana M Perrin, Daniel Gonzalez","doi":"10.1007/s40262-024-01367-2","DOIUrl":"10.1007/s40262-024-01367-2","url":null,"abstract":"<p><strong>Background: </strong>Levetiracetam is an antiseizure medication used for several seizure types in adults and children aged 1 month and older; however, due to a lack of data, pharmacokinetic (PK) variability of levetiracetam is not adequately characterized in certain populations, particularly neonates, children younger than 2 years of age, and children older than 2 years of age with obesity.</p><p><strong>Objective: </strong>This study aimed to address the gap by leveraging PK data from two prospective standard-of-care pediatric trials (n = 88) covering an age range from 1 month to 19 years, including those with obesity (64%), and applying a physiologically based PK (PBPK) modeling framework.</p><p><strong>Methods: </strong>A published PBPK model of levetiracetam for children aged 2 years and older was extended to pediatric patients younger than 2 years of age and patients older than 2 years of age with obesity by accounting for the obesity and age-related changes in PK using PK-Sim^® software. The prospective pediatric data, along with the literature data for neonates and children younger than 2 years of age, were used to evaluate the extended PBPK models.</p><p><strong>Results: </strong>Overall, 82.4% of data fell within the 90% interval of model-predicted concentrations, with an average fold error within twofold of the accepted criteria. PBPK modeling revealed that children with obesity had lower weight-normalized clearances (0.053 L/h/kg) on average than children without obesity (0.063 L/h/kg). The effect of maturation was well-characterized, resulting in comparable PBPK-simulated, weight-normalized clearances for neonates and children younger than 2 years of age reported from the literature.</p><p><strong>Conclusions: </strong>PBPK modeling simulations revealed that the current US FDA-labeled pediatric dosing regimen listed in the prescribing information can produce the required exposure of levetiracetam in these target populations with dose adjustments for children with obesity aged 4 years to younger than 16 years.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"885-899"},"PeriodicalIF":4.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11225543/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141174558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilising Endogenous Biomarkers in Drug Development to Streamline the Assessment of Drug-Drug Interactions Mediated by Renal Transporters: A Pharmaceutical Industry Perspective.","authors":"Hee Jae Choi, Shilpa Madari, Fenglei Huang","doi":"10.1007/s40262-024-01385-0","DOIUrl":"10.1007/s40262-024-01385-0","url":null,"abstract":"<p><p>The renal secretion of many drugs is facilitated by membrane transporters, including organic cation transporter 2, multidrug and toxin extrusion protein 1/2-K and organic anion transporters 1 and 3. Inhibition of these transporters can reduce renal excretion of drugs and thereby pose a safety risk. Assessing the risk of inhibition of these membrane transporters by investigational drugs remains a key focus in the evaluation of drug-drug interactions (DDIs). Current methods to predict DDI risk are based on generating in vitro data followed by a clinical assessment using a recommended exogenous probe substrate for the individual drug transporter. More recently, monitoring plasma-based and urine-based endogenous biomarkers to predict transporter-mediated DDIs in early phase I studies represents a promising approach to facilitate, improve and potentially avoid conventional clinical DDI studies. This perspective reviews the evidence for use of these endogenous biomarkers in the assessment of renal transporter-mediated DDI, evaluates how endogenous biomarkers may help to expand the DDI assessment toolkit and offers some potential knowledge gaps. A conceptual framework for assessment that may complement the current paradigm of predicting the potential for renal transporter-mediated DDIs is outlined.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"735-749"},"PeriodicalIF":4.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222257/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141310222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Together or Apart? Revealing the Impact of Dietary Interventions on Bioavailability of Quinolones: A Systematic Review with Meta-analyses.","authors":"Agnieszka Wiesner, Paweł Zagrodzki, Alicja Gawalska, Paweł Paśko","doi":"10.1007/s40262-024-01377-0","DOIUrl":"10.1007/s40262-024-01377-0","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background and objective: &lt;/strong&gt;Managing drug-food interactions is essential for optimizing the effectiveness and safety profile of quinolones. Following PRISMA guidelines, we systematically reviewed the influence of dietary interventions on the bioavailability of 22 quinolones.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;All studies describing or investigating the impact of food, beverages, antacids, and mineral supplements on pharmacokinetic parameters or pharmacokinetic/pharmacodynamic indices of orally taken quinolones were considered for inclusion. We excluded reviews, in vitro and in silico studies, studies performed on animals, and those involving alcohol. We performed the search in Medline (via PubMed), Embase, and Cochrane Library, covering reports from database inception to December 2022. We used the following tools to assess the risk of bias: version 2 of the Cochrane risk-of-bias tool for parallel trials, the Cochrane risk-of-bias tool for cross-over studies, and the NIH quality assessment tool for before-after studies. We performed quantitative analyses for each quinolone if two or more food-effect studies with specified and comparable study designs were available. If meta-analyses were not applicable, we qualitatively summarized the results.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;We included 109 studies from 101 reports. Meta-analyses were conducted for 12 antibiotics and qualitative synthesis was employed for the remaining drugs. Of the studies, 60.5% were open-label, cross-over, as recommended by FDA. We judged 46% of studies as having a high risk of bias and only 4% of having a low risk of bias. Among 19 quinolones with available food impact data, 14 (74%) had potentially clinically important interactions. For nalidixic acid, oxolinic acid, and tosufloxacin, food exerted a high positive impact on bioavailability (AUC or C&lt;sub&gt;max&lt;/sub&gt; increased by &gt; 45%), whereas, for all the remaining drugs, postprandial absorption was lower. The most significant negative influence of food (AUC or C&lt;sub&gt;max&lt;/sub&gt; decreased by &gt; 40%) occurred for delafloxacin capsules and norfloxacin, whereas the moderate influence (AUC or C&lt;sub&gt;max&lt;/sub&gt; decreased by 30-40%) occurred for nemonoxacin and rufloxacin. All 14 analysed quinolones showed a substantial reduction in bioavailability when co-administered with antacids and mineral supplements, except for calcium preparations. The impact of beverages was evaluated for 10 quinolones, with 50% experiencing significantly reduced absorption in the presence of milk (the highest negative impact for ciprofloxacin). Moreover, both ciprofloxacin and levofloxacin demonstrated compromised bioavailability when consumed with orange juice, particularly calcium-fortified.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Discussion: &lt;/strong&gt;Several factors may influence interactions, including the physicochemical characteristics of quinolones, the type of intervention, drug formulation, and the patient's health status. We assessed the quality of evidence as lo","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"773-818"},"PeriodicalIF":4.6,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222276/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141161166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Pharmacokinetics of Intravenous Lidocaine in Adults: A Systematic Review.","authors":"Keng Wah Foong, Sook Hui Chaw, Yoke Lin Lo, Pui San Loh","doi":"10.1007/s40262-024-01373-4","DOIUrl":"10.1007/s40262-024-01373-4","url":null,"abstract":"<p><strong>Background: </strong>The establishment of optimal dosing regimens for intravenous (IV) lidocaine in the perioperative setting, aiming to balance effective pain relief with minimisation of potential side effects, is a topic of ongoing debate. This discussion stems from the significant variability in lidocaine's pharmacokinetic (PK) parameters and its relatively narrow safety margin. Population pharmacokinetic (popPK) modelling has emerged as a valuable tool for understanding the factors contributing to this observed variability in drug kinetics.</p><p><strong>Objectives: </strong>This systematic review compiles the existing knowledge on lidocaine's PK properties and published popPK models, with a focus on significant covariates.</p><p><strong>Methods: </strong>A systematic search on Cochrane CENTRAL, Medline, and EMBASE was performed from inception to June 2023. Original clinical studies that administered IV lidocaine to adults and performed PK analyses using a nonlinear mixed effects modelling approach were included. The quality of the included studies was assessed by compliance with the Clinical Pharmacokinetics (ClinPK) statement checklist.</p><p><strong>Results: </strong>Seven studies were included, which involved a diverse adult population, including both volunteers and patients with various comorbidities. Lidocaine PK was primarily characterised by a two- or three-compartment model. The volume of distribution at steady state ranged from 66 to 194 L, and the total clearance ranged from 22 to 49 L/h. Despite adjusting for significant covariates like heart failure status, alpha-1-acid glycoprotein, duration of lidocaine infusion, and body weight, each study revealed substantial variability in PK parameters. The potential impact of hepatic or renal function biomarkers on these PK parameters calls for further investigation. Incomplete reporting of key aspects of developed models may hinder the models' reliability and clinical application.</p><p><strong>Conclusion: </strong>The findings emphasise the importance of tailoring drug dosage to ensure the safe and effective use of intravenous lidocaine. Optimal design methodologies may be incorporated for a more efficient identification of important covariates. Utilising contemporary model evaluation methods like visual predictive checks and bootstrapping would enhance the robustness of popPK models and the reliability of their predictions. This comprehensive review advances our understanding of lidocaine's pharmacokinetics and lays the groundwork for further research in this critical area of perioperative pain management. Review protocol registered on 25 August 2023 in PROSPERO (CRD42023441113). This work was supported by the Fundamental Research Grant Scheme, the Ministry of Higher Education, Malaysia (FRGS/1/2020/SKK01/UM/02/2).</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"623-643"},"PeriodicalIF":4.5,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140849701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Relative Bioavailability of Dolutegravir (DTG) and Emtricitabine/Tenofovir Alafenamide Fumarate (F/TAF) Administered as Paediatric Tablet Formulations in Healthy Volunteers.","authors":"Lisanne A H Bevers, Anne E M Kamphuis, L C Wendy van der Wekken-Pas, Rory Leisegang, David M Burger, Angela Colbers","doi":"10.1007/s40262-024-01378-z","DOIUrl":"10.1007/s40262-024-01378-z","url":null,"abstract":"","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"729-730"},"PeriodicalIF":4.5,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11106176/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140849700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drugs in Human Milk Part 1: Practical and Analytical Considerations in Measuring Drugs and Metabolites in Human Milk.","authors":"Osama Y Alshogran, Prerna Dodeja, Hamdan Albukhaytan, Taylor Laffey, Nupur Chaphekar, Steve Caritis, Imam H Shaik, Raman Venkataramanan","doi":"10.1007/s40262-024-01374-3","DOIUrl":"10.1007/s40262-024-01374-3","url":null,"abstract":"<p><p>Human milk is a remarkable biofluid that provides essential nutrients and immune protection to newborns. Breastfeeding women consuming medications could pass the drug through their milk to neonates. Drugs can be transferred to human milk by passive diffusion or active transport. The physicochemical properties of the drug largely impact the extent of drug transfer into human milk. A comprehensive understanding of the physiology of human milk formation, composition of milk, mechanisms of drug transfer, and factors influencing drug transfer into human milk is critical for appropriate selection and use of medications in lactating women. Quantification of drugs in the milk is essential for assessing the safety of pharmacotherapy during lactation. This can be achieved by developing specific, sensitive, and reproducible analytical methods using techniques such as liquid chromatography coupled with mass spectrometry. The present review briefly discusses the physiology of human milk formation, composition of human milk, mechanisms of drug transfer into human milk, and factors influencing transfer of drugs from blood to milk. We further expand upon and critically evaluate the existing analytical approaches/assays used for the quantification of drugs in human milk.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"561-588"},"PeriodicalIF":4.5,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140921116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalized Antifungal Therapy Through Model-Informed Precision Dosing of Posaconazole.","authors":"Anouk M E Jansen, Kim Snijdelaar, Ron J Keizer, Isabel Spriet, Erwin Dreesen, Roger J M Brüggemann, Rob Ter Heine","doi":"10.1007/s40262-024-01361-8","DOIUrl":"10.1007/s40262-024-01361-8","url":null,"abstract":"<p><strong>Background and objective: </strong>Posaconazole is a pharmacotherapeutic pillar for prophylaxis and treatment of invasive fungal diseases. Dose individualization is of utmost importance as achieving adequate antifungal exposure is associated with improved outcome. This study aimed to select and evaluate a model-informed precision dosing strategy for posaconazole.</p><p><strong>Methods: </strong>Available population pharmacokinetic models for posaconazole administered as a solid oral tablet were extracted from the literature and evaluated using data from a previously published prospective study combined with data collected during routine clinical practice. External evaluation and selection of the most accurate and precise model was based on graphical goodness-of-fit and predictive performance. Measures for bias and imprecision included mean percentage error (MPE) and normalized relative root mean squared error (NRMSE), respectively. Subsequently, the best-performing model was evaluated for its a posteriori fit-for-purpose and its suitability in a limited sampling strategy.</p><p><strong>Results: </strong>Seven posaconazole models were evaluated using 764 posaconazole plasma concentrations from 143 patients. Multiple models showed adequate predictive performance illustrated by acceptable goodness-of-fit and MPE and NRMSE below ± 10% and ± 25%, respectively. In the fit-for-purpose analysis, the selected model showed adequate a posteriori predictive performance. Bias and imprecision were lowest in the presence of two prior measurements. Additionally, this model showed to be useful in a limited sampling strategy as it adequately predicted total posaconazole exposure from one (non-)trough concentration.</p><p><strong>Conclusion: </strong>We validated an MIPD strategy for posaconazole for its fit-for-purpose. Thereby, this study is an important first step towards MIPD-supported posaconazole dosage optimization with the goal to improve antifungal treatment in clinical practice.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"645-656"},"PeriodicalIF":4.5,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11106146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140293036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}