Clinical Pharmacokinetics最新文献

{"title":"Population Pharmacokinetics and Pharmacodynamics of Dalbavancin and C-Reactive Protein in Patients with Staphylococcal Osteoarticular Infections.","authors":"Pier Giorgio Cojutti, Sara Tedeschi, Eleonora Zamparini, Pierluigi Viale, Federico Pea","doi":"10.1007/s40262-024-01410-2","DOIUrl":"10.1007/s40262-024-01410-2","url":null,"abstract":"<p><strong>Background and objective: </strong>Dalbavancin is increasingly used for the long-term treatment of chronic osteoarticular infections. A population pharmacokinetic/pharmacodynamic (PK/PD) analysis for assessing the relationship between dalbavancin exposure and C-reactive protein (C-RP) over time was conducted.</p><p><strong>Methods: </strong>Non-linear mixed-effect modeling was fitted to dalbavancin and C-RP concentrations. Monte Carlo simulations assessed the weekly percentage of C-RP reduction associated with different dosing regimens, starting from baseline to < 1 mg/dL.</p><p><strong>Results: </strong>A total of 45 patients were retrospectively included in the analysis. The PK of dalbavancin was described by a two-compartment model, and the PD of C-RP was described by an indirect turnover maximum inhibition model. The total dalbavancin concentration model estimate producing 50% of maximum C-RP production inhibition (IC₅₀) was 0.70 mg/L. Monte Carlo simulations showed that in patients with staphylococcal osteoarticular infections targeting total dalbavancin concentrations at > 14.5 mg/L at any time point may achieve C-RP production inhibition over time in > 95% of patients. Based on this, the findings showed that a cumulative dose of 3000 mg administered in the first 3 weeks may lead to a > 90% C-RP decrease versus baseline in approximately 5-6 weeks. In patients needing treatment prolongation, an additional 1500 mg dose after this period may maintain C-RP concentrations < 1 mg/dL for other 3 weeks.</p><p><strong>Conclusions: </strong>A decrease in C-RP is related to dalbavancin exposure in osteoarticular infections. Targeting dalbavancin plasma concentrations above the efficacy threshold may be associated with effective treatment.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1271-1282"},"PeriodicalIF":4.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11449996/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142016512","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":"Development and Application of a Physiologically Based Pharmacokinetic Model for Elagolix in the Adult and Adolescent Population.","authors":"Xinghai Zhang, Xuanxuan Wang, Rui Li, Chenning Zhang, Jianmin Du, Hengli Zhao, Qing Wen","doi":"10.1007/s40262-024-01402-2","DOIUrl":"10.1007/s40262-024-01402-2","url":null,"abstract":"<p><strong>Introduction: </strong>Endometriosis, a common and distressing gynecological condition, affects fertility and causes pain, is often managed with medications such as Elagolix. The present study aimed to construct a physiologically based pharmacokinetic (PBPK) model for elagolix to predict its pharmacokinetics in different populations, including those with special conditions, to enhance treatment strategies for endometriosis.</p><p><strong>Methods: </strong>The PBPK model was optimized using observational data based on the oral administration of elagolix in a healthy Chinese population under fasting conditions. Model accuracy was further verified by comparing the predicted postprandial elagolix concentration data for healthy Chinese individuals with observed data and by comparing these values with the predicted values in a US population model with renal injury or following multiple-dose administration.</p><p><strong>Results: </strong>Elagolix pharmacokinetic (PK) profiles in the Chinese and American populations exhibited no differences that were attributable to ethnicity. The model predicted in vivo PK in adolescents aged 14-18 years, revealing no clinically significant differences in the effects of elagolix between adolescents and adults. In addition, no predicted PK differences in individuals with overweight were observed. However, notable variations emerged in those classified as obesity class 2 and above compared to healthy individuals.</p><p><strong>Conclusion: </strong>Our study presents a novel PBPK model for elagolix in healthy Chinese women, addressing a clinical data gap for its use in adolescents and obese patients. By validating the model with real-world factors, including diet and renal impairment, we provide initial pharmacokinetic predictions for these populations, contributing to a more informed clinical approach.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1357-1370"},"PeriodicalIF":4.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141765692","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":"Dose Justification for Asciminib in Patients with Philadelphia Chromosome-Positive Chronic Myeloid Leukemia with and Without the T315I Mutation.","authors":"Francois Pierre Combes, Sherwin K B Sy, Ying Fei Li, Sebastien Lorenzo, Kohinoor Dasgupta, Shruti Kapoor, Matthias Hoch, Yu-Yun Ho","doi":"10.1007/s40262-024-01411-1","DOIUrl":"10.1007/s40262-024-01411-1","url":null,"abstract":"<p><strong>Background and objective: </strong>Asciminib is approved in patients with Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase (Ph+ CML-CP) treated with ≥ 2 prior tyrosine kinase inhibitors. Here, we aimed to demonstrate similarity in efficacy/safety of asciminib 80 mg once daily (q.d.) versus 40 mg twice daily (b.i.d.) in patients with CML-CP without T315I mutation and support the use of the 200-mg b.i.d. dosage in patients harboring T315I, using model-informed drug development.</p><p><strong>Methods: </strong>Data were collected from 199 patients in the phase I (NCT02081378; 10-200 mg b.i.d. or 10-400 mg q.d.) and 154 patients in the phase III (NCT03106779; 40 mg b.i.d.) studies. Evaluations were based on population pharmacokinetics (PopPK) and exposure-response (efficacy/safety) analyses.</p><p><strong>Results: </strong>PopPK showed comparable exposure (area under the curve, AUC_0-24h) for 40 mg b.i.d. and 80 mg q.d. (12,638 vs 12,646 ng*h/mL); average maximum and minimum plasma concentrations for 80 mg q.d. were 1.61- and 0.72-fold those of 40 mg b.i.d., respectively. Exposure-response analyses predicted similar major molecular response rates for 40 mg b.i.d. and 80 mg q.d. (Week 24: 27.6% vs 24.8%; Week 48: 32.3% vs 30.6%). Results also established adequacy of 200 mg b.i.d. in patients with T315I mutation (Week 24: 20.7%; Week 48: 23.7%), along with a similar safety profile for all dose regimens.</p><p><strong>Conclusions: </strong>Similarity between 40 mg b.i.d. and 80 mg q.d. regimens was investigated, demonstrating similar and substantial efficacy with well-tolerated safety in patients without T315I mutation. The 200-mg b.i.d. dose was deemed safe and effective for patients with T315I mutation.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1301-1312"},"PeriodicalIF":4.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450061/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142145322","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":"Correction to: Development and Application of a Physiologically Based Pharmacokinetic Model for Elagolix in the Adult and Adolescent Population.","authors":"Xinghai Zhang, Xuanxuan Wang, Rui Li, Chenning Zhang, Jianmin Du, Hengli Zhao, Qing Wen","doi":"10.1007/s40262-024-01415-x","DOIUrl":"10.1007/s40262-024-01415-x","url":null,"abstract":"","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1371"},"PeriodicalIF":4.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142104953","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":"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":"10.1007/s40262-024-01398-9","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background and objectives: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;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&lt;sup&gt;2&lt;/sup&gt; = 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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;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 f","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1067-1087"},"PeriodicalIF":4.6,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343830/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141616020","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":"Dosing Adjustments in Cases of Altered Plasma Protein Binding are Most Needed for Drugs with a Volume of Distribution Below 1.3 L/kg.","authors":"Florin M Musteata","doi":"10.1007/s40262-024-01403-1","DOIUrl":"10.1007/s40262-024-01403-1","url":null,"abstract":"<p><strong>Background: </strong>The present literature offers conflicting views on the importance of changes in plasma protein binding in clinical therapeutics. Furthermore, there are no methods to calculate a new dosing regimen when such changes occur.</p><p><strong>Methods: </strong>Previous models developed by Balaz et al. and Greenblat et al. were used to calculate a plasma protein binding (PPB) score for individual drugs based on the volume of distribution for total concentration and the bound fraction of drug. The models were further used to calculate a new drug dosing interval for cases of altered plasma protein binding. The equations apply best for drugs with fast absorption and fast distribution; they can be used as approximations for drugs with slow distribution by using the volume of distribution at steady state and the rate constant of the elimination phase.</p><p><strong>Results: </strong>The newly developed equations show that changes in plasma protein binding are relevant only for drugs with a positive PPB score; such drugs must have a volume of distribution for total concentration below 1.3 L/kg and high protein binding. It is further shown that the drug dosing interval should be reduced when the remaining fraction of plasma protein binding is below the PPB score.</p><p><strong>Conclusion: </strong>A new method to rank drugs according to the impact of changes in plasma protein binding on their pharmacokinetic profile was developed. The new method was applied to show that drugs with high PPB scores need reductions in their dosing interval when the level of protein binding decreases.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1111-1119"},"PeriodicalIF":4.6,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141751295","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":"Clinical Trial Data-Driven Risk Assessment of Drug-Drug Interactions: A Rapid and Accurate Decision-Making Tool.","authors":"Tong Yuan, Fulin Bi, Kuan Hu, Yuqi Zhu, Yan Lin, Jin Yang","doi":"10.1007/s40262-024-01404-0","DOIUrl":"10.1007/s40262-024-01404-0","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;In clinical practice, the vast array of potential drug combinations necessitates swift and accurate assessments of pharmacokinetic drug-drug interactions (DDIs), along with recommendations for adjustments. Current methodologies for clinical DDI evaluations primarily rely on basic extrapolations from clinical trial data. However, these methods are limited in accuracy owing to their lack of a comprehensive consideration of various critical factors, including the inhibitory potency, dosage, and type of the inhibitor, as well as the metabolic fraction and intestinal availability of the substrate.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to propose an efficient and accurate clinical pharmacokinetic-mediated DDI assessment tool, which comprehensively considers the effects of inhibitory potency and dosage of inhibitors, intestinal availability and fraction metabolized of substrates on DDI outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study focuses on DDIs caused by cytochrome P450 3A4 enzyme inhibition, utilizing extensive clinical trial data to establish a methodology to calculate the metabolic fraction and intestinal availability for substrates, as well as the concentration and inhibitory potency for inhibitors ( &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mtext&gt;i&lt;/mtext&gt;&lt;/msub&gt; &lt;/math&gt; or &lt;math&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;k&lt;/mi&gt; &lt;mtext&gt;inact&lt;/mtext&gt;&lt;/msub&gt; &lt;mo&gt;/&lt;/mo&gt; &lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mtext&gt;I&lt;/mtext&gt;&lt;/msub&gt; &lt;/mrow&gt; &lt;/math&gt; ). These parameters were then used to predict the outcomes of DDIs involving 33 substrates and 20 inhibitors. We also defined the risk index for substrates and the potency index for inhibitors to establish a clinical DDI risk scale. The training set for parameter calculation consisted of 73 clinical trials. The validation set comprised 89 clinical DDI trials involving 53 drugs. which was used to evaluate the reliability of in vivo values of &lt;math&gt;&lt;msub&gt;&lt;mtext&gt;K&lt;/mtext&gt; &lt;mtext&gt;i&lt;/mtext&gt;&lt;/msub&gt; &lt;/math&gt; and &lt;math&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;k&lt;/mi&gt; &lt;mtext&gt;inact&lt;/mtext&gt;&lt;/msub&gt; &lt;mo&gt;/&lt;/mo&gt; &lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mtext&gt;I&lt;/mtext&gt;&lt;/msub&gt; &lt;/mrow&gt; &lt;/math&gt; , the accuracy of DDI predictions, and the false-negative rate of risk scale.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;First, the reliability of the in vivo &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mtext&gt;i&lt;/mtext&gt;&lt;/msub&gt; &lt;/math&gt; and &lt;math&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;k&lt;/mi&gt; &lt;mtext&gt;inact&lt;/mtext&gt;&lt;/msub&gt; &lt;mo&gt;/&lt;/mo&gt; &lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mtext&gt;I&lt;/mtext&gt;&lt;/msub&gt; &lt;/mrow&gt; &lt;/math&gt; values calculated in this study was assessed using a basic static model. Compared with values obtained from other methods, this study values showed a lower geometric mean fold error and root mean square error. Additionally, incorporating these values into the physiologically based pharmacokinetic-DDI model facilitated a good fitting of the C-t curves when the substrate's metabolic enzymes are inhibited. Second, area under the curve ratio predictions of studied drugs were within a 1.5 × margin of error in 81% of cases compared with clinical observations in the validation ","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1147-1165"},"PeriodicalIF":4.6,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141888605","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":"Population Pharmacokinetics of Capivasertib in Patients with Advanced or Metastatic Solid Tumours.","authors":"Carlos Fernandez-Teruel, Marie Cullberg, Cath Eberlein, Simon T Barry, Diansong Zhou","doi":"10.1007/s40262-024-01407-x","DOIUrl":"10.1007/s40262-024-01407-x","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background and objective: &lt;/strong&gt;Overactivation of the PI3K/AKT pathway can occur in many cancers. Capivasertib is a potent, selective pan-AKT inhibitor. The objectives of this analysis were to develop a population pharmacokinetic model for capivasertib and to quantitatively assess the impact of intrinsic and extrinsic factors on the pharmacokinetics of capivasertib.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Pharmacokinetic data from four phase I and II studies were combined. Capivasertib was administered orally at a dose range of 80-800 mg twice daily over 28-day and 21-day cycles as monotherapy or in combination with paclitaxel or fulvestrant, using continuous dosing or one of two intermittent dosing schedules: either 4 days on, 3 days off (4/3) or 2 days on, 5 days off (2/5). Several models and approaches were tested for their ability to describe capivasertib disposition. The covariates assessed included dose, schedule, age, body weight, race, sex, creatinine clearance, hepatic function, renal function, smoking status, food effect, formulation, and concomitant use with paclitaxel, fulvestrant, cytochrome P450, family 3, subfamily A (CYP3A) inducers, CYP3A inhibitors and acid-reducing agents.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 3963 capivasertib plasma concentrations from 441 patients were included. Capivasertib pharmacokinetics was adequately described by a three-compartment model where the apparent clearance (CL/F) presented a moderate time-dependent and dose-dependent clearance. Following oral administration of multiple doses of capivasertib (400 mg twice daily; [4/3]), the initial CL/F was 62.2 L/h (between-subject variability 39.3%), and after approximately 120 hours, CL/F decreased by 18%. The effective half-life was 8.34 h. Steady state was predicted to be reached on every third and fourth dosing day each week from the second week with exposure levels that produced robust inhibition of AKT but not of other related kinases. The area under the plasma concentration-time curve and maximum plasma concentration of capivasertib were proportional between the dose levels of 80-480 mg after multiple doses but more than proportional beyond 480 mg. Schedule, age, race, sex, creatinine clearance, hepatic function, renal function, smoking status and concomitant use with fulvestrant, CYP3A inducers, CYP3A inhibitors or acid-reducing agents were not significant covariates for capivasertib pharmacokinetics. Concomitant use of paclitaxel, food effect and formulation statistically significantly affected capivasertib pharmacokinetics, but the effect was low. Body weight was statistically significantly related to capivasertib CL/F, with a 12% reduction in CL/F at steady state and a 14% increase in the area under the curve for 12 hours at steady state and maximum concentration at steady state at a lower body weight (47 kg vs 67 kg reference).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Capivasertib pharmacokinetics showed moderate between-subject variabilit","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1191-1204"},"PeriodicalIF":4.6,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343776/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141912058","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":"Innovating Thiopurine Therapeutic Drug Monitoring: A Systematic Review and Meta-Analysis on DNA-Thioguanine Nucleotides (DNA-TG) as an Inclusive Biomarker in Thiopurine Therapy.","authors":"Ahmed B Bayoumy, A R Ansari, C J J Mulder, K Schmiegelow, Timothy Florin, N K H De Boer","doi":"10.1007/s40262-024-01393-0","DOIUrl":"10.1007/s40262-024-01393-0","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background and objective: &lt;/strong&gt;Thioguanine (TG), azathioprine (AZA), and mercaptopurine (MP) are thiopurine prodrugs commonly used to treat diseases, such as leukemia and inflammatory bowel disease (IBD). 6-thioguanine nucleotides (6-TGNs) have been commonly used for monitoring treatment. High levels of 6-TGNs in red blood cells (RBCs) have been associated with leukopenia, the cutoff levels that predict this side effect remain uncertain. Thiopurines are metabolized and incorporated into leukocyte DNA. Measuring levels of DNA-incorporated thioguanine (DNA-TG) may be a more suitable method for predicting clinical response and toxicities such as leukopenia. Unfortunately, most methodologies to assay 6-TGNs are unable to identify the impact of NUDT15 variants, effecting mostly ethnic populations (e.g., Chinese, Indian, Malay, Japanese, and Hispanics). DNA-TG tackles this problem by directly measuring thioguanine in the DNA, which can be influenced by both TPMT and NUDT15 variants. While RBC 6-TGN concentrations have traditionally been used to optimize thiopurine therapy due to their ease and affordability of measurement, recent developments in liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have made measuring DNA-TG concentrations in lymphocytes accurate, reproducible, and affordable. The objective of this systematic review was to assess the current evidence of DNA-TG levels as marker for thiopurine therapy, especially with regards to NUDT15 variants.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A systematic review and meta-analysis were performed on the current evidence for DNA-TG as a marker for monitoring thiopurine therapy, including methods for measurement and the illustrative relationship between DNA-TG and various gene variants (such as TPMT, NUDT15, ITPA, NT5C2, and MRP4). PubMed and Embase were systematically searched up to April 2024 for published studies, using the keyword \"DNA-TG\" with MeSH terms and synonyms. The electronic search strategy was augmented by a manual examination of references cited in articles, recent reviews, editorials, and meta-analyses. A meta-analysis was performed using R studio 4.1.3. to investigate the difference between the coefficients (Fisher's z-transformed correlation coefficient) of DNA-TG and 6-TGNs levels. A meta-analysis was performed using RevMan version 5.4 to investigate the difference in DNA-TG levels between patients with or without leukopenia using randomized effect size model. The risk of bias was assessed using the Newcastle-Ottowa quality assessment scale.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In this systematic review, 21 studies were included that measured DNA-TG levels in white blood cells for either patients with ALL (n = 16) or IBD (n = 5). In our meta-analysis, the overall mean difference between patients with leukopenia (ALL + IBD) versus no leukopenia was 134.15 fmol TG/µg DNA [95% confidence interval (CI) (83.78-184.35), P &lt; 0.00001; heterogeneity chi squared of 5.62, I&lt;","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1089-1109"},"PeriodicalIF":4.6,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343975/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141731054","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":"A Machine Learning Algorithm to Predict the Starting Dose of Daptomycin.","authors":"Florence Rivals, Sylvain Goutelle, Cyrielle Codde, Romain Garreau, Laure Ponthier, Pierre Marquet, Tristan Ferry, Marc Labriffe, Alexandre Destere, Jean-Baptiste Woillard","doi":"10.1007/s40262-024-01405-z","DOIUrl":"10.1007/s40262-024-01405-z","url":null,"abstract":"<p><strong>Background and objective: </strong>The dosage of daptomycin is usually based on body weight. However, it has been shown that this approach yields too high an exposure in obese patients. Pharmacokinetic and pharmacodynamic indexes (PK/PD) have been proposed for daptomycin's antibacterial effect (AUC/CMI >666) and toxicity (C0 > 24.3 mg/L). We previously developed machine learning (ML) algorithms to predict starting doses based on Monte Carlo simulations. We propose a new way to perform probability of target attainment based on an ML algorithm to predict the daptomycin starting dose.</p><p><strong>Methods: </strong>The Dvorchik model of daptomycin was implemented in the mrgsolve R package and 4950 pharmacokinetic profiles were simulated with doses ranging from 4 to 12 mg/kg. We trained and benchmarked four machine learning algorithms and selected the best to iteratively search for the optimal dose of daptomycin maximizing the event (AUC/CMI > 666 and C0 < 24.3 mg/L). The ML algorithm was evaluated in simulations and an external database of real patients in comparison with population pharmacokinetics.</p><p><strong>Results: </strong>The performance of the Xgboost algorithms developed to predict the event (ROC AUC) in the training and test set were 0.762 and 0.761, respectively. The most important prediction variables were dose, creatinine clearance, body weight and sex. In the external database of real patients, the starting dose administered based on the ML algorithm significantly improved the target attainment by 7.9% (p-value = 0.02929) in comparison with the dose administered based on body weight.</p><p><strong>Conclusion: </strong>The developed algorithm improved the target attainment for daptomycin in comparison with weight-based dosing. We built a Shiny app to calculate the optimal starting dose.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1137-1146"},"PeriodicalIF":4.6,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141859216","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}