scholarly journals Combining Therapeutic Drug Monitoring and Pharmacokinetic Modelling Deconvolutes Physiological and Environmental Sources of Variability in Clozapine Exposure

Pharmaceutics ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 47
Author(s):  
Kenneth H. Wills ◽  
Stephen J. Behan ◽  
Michael J. Nance ◽  
Jessica L. Dawson ◽  
Thomas M. Polasek ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Smoking Status ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Modelling ◽  
Environmental Covariates ◽  
Poppk Model ◽  
Post Hoc ◽  
The Impact

Background: Clozapine is a key antipsychotic drug for treatment-resistant schizophrenia but exhibits highly variable pharmacokinetics and a propensity for serious adverse effects. Currently, these challenges are addressed using therapeutic drug monitoring (TDM). This study primarily sought to (i) verify the importance of covariates identified in a prior clozapine population pharmacokinetic (popPK) model in the absence of environmental covariates using physiologically based pharmacokinetic (PBPK) modelling, and then to (ii) evaluate the performance of the popPK model as an adjunct or alternative to TDM-guided dosing in an active TDM population. Methods: A popPK model incorporating age, metabolic activity, sex, smoking status and weight was applied to predict clozapine trough concentrations (Cmin) in a PBPK-simulated population and an active TDM population comprising 142 patients dosed to steady state at Flinders Medical Centre in Adelaide, South Australia. Post hoc analyses were performed to deconvolute the impact of physiological and environmental covariates in the TDM population. Results: Analysis of PBPK simulations confirmed age, cytochrome P450 1A2 activity, sex and weight as physiological covariates associated with variability in clozapine Cmin (R2 = 0.7698; p = 0.0002). Prediction of clozapine Cmin using a popPK model based on these covariates accounted for <5% of inter-individual variability in the TDM population. Post hoc analyses confirmed that environmental covariates accounted for a greater proportion of the variability in clozapine Cmin in the TDM population. Conclusions: Variability in clozapine exposure was primarily driven by environmental covariates in an active TDM population. Pharmacokinetic modelling can be used as an adjunct to TDM to deconvolute sources of variability in clozapine exposure.

The impact of an electronic hospital system on therapeutic drug monitoring

2021 ◽  
Author(s):  
Paul Firman ◽  
Karen Whitfield ◽  
Ken‐Soon Tan ◽  
Alexandra Clavarino ◽  
Karen Hay
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Therapeutic Drug ◽  
Hospital System ◽  
The Impact ◽  
Electronic Hospital

Population Pharmacokinetics of Meropenem in Preterm Infants

2021 ◽  
Vol 76 (5) ◽  
pp. 497-505
Author(s):  
Irina B. Bondareva ◽  
Sergey K. Zyryanov ◽  
Aleksandra M. Kazanova
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Pharmacokinetic Parameter ◽  
Gestational Age ◽  
Drug Monitoring ◽  
Pharmacokinetic Parameters ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Variability ◽  
Older Children ◽  
Term Neonates

Background. Meropenem, a broad spectrum carbapenem antibiotic, is often used for newborns despite of limited data available on neonatal pharmacokinetics. Due to pharmacokinetic and pharmacodynamic differences as well as to significant changes in the human body related to growth and maturation of organs and systems, direct scaling and dosing extrapolation from adults or older children with adjustment on patients weight can result in increased risk of toxicity or treatment failures. Aims to evaluate the pharmacokinetics of meropenem in premature neonates based on therapeutic drug monitoring data in real clinical settings. Materials. Of 53 pre-term neonates included in the pharmacokinetic/pharmacodynamic analysis, in 39 (73.6%) patients, gestational age ranged from 23 to 30 weeks. Population and individual pharmacokinetic parameter values were estimated by the NPAG program from the Pmetrics package based on peak-trough therapeutic drug monitoring. Samples were assayed by high-performance liquid chromatography. One-compartment pharmacokinetic model with zero-order input and first-order elimination was used to fit concentration data and to predict pharmacokinetic parameter (%T MIC of free drug) for virtual patients with simulated fast, moderate and slow meropenem elimination received different dosage by minimum inhibitory concentration (MIC) level. Univariate and multivariate regression analysis was used to evaluate the influence of patients covariates (gestational age, postnatal age, postconceptual age, body weight, creatinine clearance calculated by Schwartz formula, etc) on estimated meropenem pharmacokinetic parameters. Results. The identified population pharmacokinetic parameters of meropenem in pre-term newborns (elimination half-lives T1/2 = 1.93 0.341 h; clearance CL = 0.26 0.085 L/h/ kg; volume of distribution V = 0.71 0.22 L/h) were in good agreement with those published in the literature for adults, neonates and older children. Pharmacokinetic/pharmacodynamic modeling demonstrated that a meropenem dosage regimen of 90 mg/kg/day administered using prolonged 3-hour infusion every 8 hours should be considered as potentially effective therapy if nosocomial infections with resistant organisms (MIC 8 mg/L) are treated. Conclusions. Neonates and especially pre-term neonates have a great pharmacokinetic variability. Meropenem dosing in premature newborns derived from population pharmacokinetic/pharmacodynamic model can partly overcome the variability, but not all pharmacokinetic variability can be explained by covariates in a model. Further personalizing based on Bayesian forecasting approach and a patients therapeutic drug monitoring data can help to achieve desired pharmacodynamic target.

scholarly journals P99 Clinical validation of published vancomycin population PK models in critically ill neonates

2019 ◽  
Vol 104 (6) ◽  
pp. e58.2-e59
Author(s):  
A van der Veen ◽  
RJ Keizer ◽  
W de Boode ◽  
A Somers ◽  
R Brüggemann ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
A Priori ◽  
Predictive Performance ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Suitable Model ◽  
List Type ◽  
A Posteriori ◽  
Target Attainment

BackgroundVancomycin is commonly used for treatment of severe Gram+ neonatal infections. Currently, even with the use of optimized dosing regimens and therapeutic drug monitoring (TDM), target attainment rates are abominable, leaving patients at risk for therapeutic failure and toxicity. Model-informed precision dosing (MIPD) offers a large potential to improve therapy in the individual patient.The aim of this study was to identify a suitable model for bedside MIPD by assessing the predictive performance of published population pharmacokinetic (popPK) models.MethodsA literature search was conducted to identify parametric popPK models. PK vancomycin data were retrospectively collected from NICU patients at the Radboud University Hospital, Nijmegen, The Netherlands. The model predictive performance was assessed by comparison of predictions to observations, calculation of bias (Mean Percentage Errors, MPE) and imprecision (Normalized Root Mean Squared Errors, NRMSE). Evaluations included both a priori (model covariate input) and a posteriori (model covariate and TDM concentration input) scenarios.Results265 TDM measurements from 65 neonates (median postmenstrual age:32 weeks [range:25–45 weeks]; median weight:1281g [range:597–5360g]; median serum creatinine:0,48 mg/dL [range:0,15–1,28 mg/dL]) were used for model evaluation. Six popPK models were evaluated1–6. A posteriori predictions of all models were consistently more accurate and precise compared to the a priori (starting dose) predictions. PopPK models of Frymoyer et al. and Capparelli et al. consistently performed best through all evaluations in both the a priori and a posteriori scenario (MPE ranging from -18 to 6,4% in a priori scenario and -6,5 to -3,8% in a posteriori scenario; NRMSE ranging from 34 to 40% in a priori scenario and 23 to 24% in a posteriori scenario).ConclusionLarge differences in predictive performance of popPK models were observed. Repeated therapeutic drug monitoring remains necessary to increase target attainment rate. Best performing models for bedside MIPD were identified in our patient population.ReferencesZhao W, Lopez E, Biran V, et al. ( 2013). Vancomycin continuous infusion in neonates: Dosing optimisation and therapeutic drug monitoring. Arch Dis Child;98(6):449–453.Capparelli EV, Lane JR, Romanowski GL, et al. ( 2001). The influences of renal function and maturation on vancomycin elimination in newborns and infants. J Clin Pharmacol, 41:927–934.De Cock RFW, Allegaert K, Brussee JM, et al. ( 2014). Simultaneous pharmacokinetic modeling of gentamicin, tobramycin and vancomycin clearance from neonates to adults: towards a semi-physiological function for maturation in glomerular filtration. Pharm Res;31(10):2642–2654.Frymoyer A, Hersh AL, El-Komy MH, et al. ( 2014). Association between vancomycin trough concentration and area under the concentration-time curve in neonates. Antimicrob Agents Chemother, 58(11):6454–6461.Anderson BJ, Allegaert K, Van Den Anker JN, Cossey V, Holford NHG. ( 2006). Vancomycin pharmacokinetics in preterm neonates and the prediction of adult clearance. Br J Clin Pharmacol;63(1):75–84.Germovsek E, Osborne L, Gunaratnam F, Lounis SA, Busquets FB, Sinha AK. ( 2019). Development and external evaluation of a population pharmacokinetic model for continuous and intermittent administration of vancomycin in neonates and infants using prospectively collected data. J Antimicrob Chemother, 1–9.Disclosure(s)R. Keizer is an employee and stockholder of InsightRX.

scholarly journals Preanalytical considerations in therapeutic drug monitoring of immunosuppressants with dried blood spots

Diagnosis ◽  
2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Adrian Klak ◽  
Steven Pauwels ◽  
Pieter Vermeersch
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Current Knowledge ◽  
Dried Blood Spots ◽  
Therapeutic Drug ◽  
Drying Time ◽  
Blood Spots ◽  
Home Based ◽  
The Impact ◽  
Blood Spot

Abstract Background Dried blood spots (DBSs) could allow patients to prepare their own samples at home and send them to the laboratory for therapeutic drug monitoring (TDM) of immunosuppressants. The purpose of this review is to provide an overview of the current knowledge about the impact of DBS-related preanalytical factors on TDM of tacrolimus, sirolimus and everolimus. Content Blood spot volume, blood spot inhomogeneity, stability of analytes in DBS and hematocrit (Hct) effects are considered important DBS-related preanalytical factors. In addition, the influence of drying time has recently been identified as a noteworthy preanalytical factor. Tacrolimus is not significantly influenced by these factors. Sirolimus and everolimus are more prone to heat degradation and exhibited variations in recovery which were dependent on Hct and drying time. Summary and outlook DBS-related preanalytical factors can have a significant impact on TDM for immunosuppressants. Tacrolimus is not significantly influenced by the studied preanalytical factors and is a viable candidate for DBS sampling. For sirolimus and everolimus more validation of preanalytical factors is needed. In particular, drying conditions need to be examined further, as current protocols may mask Hct-dependent effects on recovery. Further validation is also necessary for home-based self-sampling of immunosuppressants as the sampling quality is variable.

scholarly journals 1737. Impact of Therapeutic Drug Monitoring (TDM) of Azole Prophylaxis in Lung Transplant Recipients on the Development of Positive Fungal Events

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S636-S636
Author(s):  
Anooj Shah ◽  
Carly D’Agostino ◽  
Kathleen Cunningham ◽  
Clare Kane ◽  
Michael G Ison ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Lung Transplant ◽  
Study Groups ◽  
Fungal Species ◽  
Therapeutic Drug ◽  
Transplant Recipients ◽  
Lung Transplant Recipients ◽  
Index Value ◽  
The Impact

Abstract Background The utility and clinical impact of therapeutic drug monitoring (TDM) of prophylactic azole antifungals in lung transplant recipients is not well described. The objective of this study was to investigate the impact of TDM of azole prophylaxis in lung transplant recipients on the development of positive fungal events. Methods A retrospective analysis was performed on 47 lung transplant recipients between 2013 and 2018 at Northwestern Memorial Hospital. A positive fungal event was defined as fungal species on BAL culture and/or positive BAL Aspergillus galactomannan (GM) with an index value ≥1.0. Study groups were defined based on attainment of therapeutic trough levels after initiation of oral therapy (therapeutic if posaconazole level ≥0.7 μg/mL or voriconazole ≥1–5.5 μg/mL, subtherapeutic if ≥2 consecutive levels of posaconazole <0.7 μg/mL or voriconazole <1 μg/mL after initial dose increase). Results There were no differences in baseline characteristics (Figure 1). There were a total of 11 fungal events with 3 (12.0%) occurring in the therapeutic cohort and 8 (36.4%) in those subtherapeutic (P = 0.08). In the 5 patients with a positive GM, the mean index was 2.02 ± 0.95. 7/30 (23.3%) of patients on posaconazole had a fungal event, with 2/7 (28.6%) requiring treatment at the time of event. For patients on voriconazole, 4/17 (23.5%) had a fungal event, with 1/4 (25.0%) requiring treatment. Mean time to fungal event was 164.5 ± 8.9 days vs. 135.9 ± 13.7 days in the therapeutic and subtherapeutic group, respectively (P = 0.05). All patients on posaconazole suspension who experienced a fungal event were subtherapeutic (3/3, 100%) compared with the majority of patients on posaconazole delayed release (DR) tablets who achieved therapeutic levels (17/22, 77.3%). Mean posaconazole trough level observed in the patients receiving DR tablet was 2.15 ± 0.95 μg/mL. Conclusion There was an association between two consecutive subtherapeutic azole prophylaxis levels and positive fungal events indicating a role for TDM in lung transplant recipients. Time to fungal event post-transplant was shorter in subtherapeutic patients. As anticipated, the use of posaconazole suspension resulted in subtherapeutic levels. This study presents an opportunity for further research of the impact of TDM on clinical outcomes to optimize patient care. Disclosures All authors: No reported disclosures.

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