Characterisation of individual ferritin response in patients receiving chelation therapy

AIM: To develop a drug-disease model describing iron overload and its effect on ferritin response in patients affected by transfusion-dependent haemoglobinopathies and investigate the contribution of interindividual differences in demographic and clinical factors on chelation therapy with deferiprone or deferasirox. METHODS: Individual and mean serum ferritin data were retrieved from 13 published studies in patients affected by hemoglobinopathies receiving deferiprone or deferasirox. A nonlinear mixed effects modelling approach was used to characterise iron homeostasis and serum ferritin production taking into account annual blood consumption, baseline demographic and clinical characteristics. The effect of chelation therapy was parameterised as an increase in the iron elimination rate. Internal and external validation procedures were used to assess model performance across different study populations. RESULTS: An indirect response model was identified, including baseline ferritin concentrations and annual blood consumption as covariates. The effect of chelation on iron elimination rate was characterised by a linear function, with different slopes for each drug [0.0109 (90% CI: 0.0079-0.0131) vs. 0.0013 (90% CI: 0.0008-0.0018) L/mg.month]. In addition to drug-specific differences in the magnitude of the ferritin response, simulation scenarios indicate that ferritin elimination rates depend on ferritin concentrations at baseline. CONCLUSIONS: Modelling of serum ferritin following chronic blood transfusion enabled the characterisation of drug-induced changes in iron elimination rate and ferritin production. The use of a semi-mechanistic parameterisation allowed us to disentangle disease-specific factors from drug-specific properties. Despite comparable chelation mechanisms, deferiprone appears to have a significantly larger effect on the iron elimination rate than deferasirox

Prediction of lung exposure to anti-tubercular drugs using plasma pharmacokinetic data: implications for dose selection

The development of novel candidate molecules for tuberculosis remains challenging, as drug distribution into the target tissue is not fully characterised in preclinical models of infection. Often antitubercular human dose selection is derived from pharmacokinetic data in plasma. Here, we explore whether whole-body physiologically-based pharmacokinetic (PBPK) modelling enables the prediction of lung exposure to anti-tubercular drugs in humans. Whole-body PBPK models were developed for rifampicin, isoniazid, pyrazinamide, and ethambutol using plasma data in mice as basis for the prediction of lung exposure. Model parameters were subsequently used to extrapolate disposition properties from mouse and determine lung:plasma ratio in humans. Model predictions were compared to biopsy data from patients. Predictions were deemed adequate if they fell within two-fold range of the observations. The concentration vs time profiles in lung were adequately predicted in mice. Isoniazid and pyrazinamide lung exposures were predicted to be comparable to plasma levels, whereas ethambutol lung exposure was predicted to be higher than in plasma. Lung:plasma ratio in humans could be reasonably predicted from preclinical data, but was highly dependent on the distribution model. This analysis showed that plasma pharmacokinetics may be used in conjunction with PBPK modelling to derive lung tissue exposure in mice and humans during early lead optimisation phase. However, the impact of uncertainty in predicted tissue exposure due to distribution should be always investigated through a sensitivity analysis when only plasma data is available. Despite these limitations, insight into lung tissue distribution represents a critical step for the dose rationale in tuberculosis patients

Dose rationale for gabapentin and tramadol in pediatric patients with chronic pain

Despite off-label use, the efficacy and safety of gabapentin and tramadol in pediatric patients (3 months to <18 years old) diagnosed with chronic pain has not been characterized. However, generating evidence based on randomized clinical trials in this population has been extremely challenging. The current investigation illustrates the use of clinical trial simulations (CTSs) as a tool for optimizing doses and protocol design for a prospective investigation in pediatric patients with chronic pain. Pharmacokinetic (PK) modeling and CTSs were used to describe the PKs of gabapentin and tramadol in the target population. In the absence of biomarkers of analgesia, systemic exposure (AUC, Css) was used to guide dose selection under the assumption of a comparable exposure-response (PKPD) relationship for either compound between adults and children. Two weight bands were identified for gabapentin, with doses titrated from 5 to 63 mg/kg. This yields gabapentin exposures (AUC0-8 ) of approximately 35 mg/L*h (1200 mg/day adult dose equivalent). For tramadol, median steady state concentrations between 200 and 300 ng/mL were achieved after doses of 2-5 mg/kg, but concentrations showed high interindividual variability. Simulation scenarios showed that titration steps are required to explore therapeutically relevant dose ranges taking into account the safety profile of both drugs. Gabapentin can be used t.i.d. at doses between 7-63 and 5-45 mg/kg for patients receiving gabapentin weighing <15 and ≥15 kg, respectively, whereas a t.i.d. regimen with doses between 1 and 5 mg/kg can be used for tramadol in patients who are not fast metabolisers

A physiologically based pharmacokinetic model of clopidogrel in populations of European and Japanese ancestry: An evaluation of CYP2C19 activity

Treatment response to clopidogrel is associated with CYP2C19 activity through the formation of the active H4 metabolite. The aims of this study were to develop a physiologically based pharmacokinetic (PBPK) model of clopidogrel and its metabolites for populations of European ancestry, to predict the pharmacokinetics in the Japanese population by CYP2C19 phenotype, and to investigate the effect of clinical and demographic factors. A PBPK model was developed and verified to describe the two metabolic pathways of clopidogrel (H4 metabolite, acyl glucuronide metabolite) for a population of European ancestry using plasma data from published studies. Subsequently, model predictions in the Japanese population were evaluated. The effects of CYP2C19 activity, fluvoxamine coadministration (CYP2C19 inhibitor), and population-specific factors (age, sex, BMI, body weight, cancer, hepatic, and renal dysfunction) on the pharmacokinetics of clopidogrel and its metabolites were then characterized. The predicted/observed ratios for clopidogrel and metabolite exposure parameters were acceptable (twofold acceptance criteria). For all CYP2C19 phenotypes, steady-state AUC0-τ of the H4 metabolite was lower for the Japanese (e.g., EM, 7.69 [6.26–9.45] ng·h/ml; geometric mean [95% CI]) than European (EM, 24.8 [20.4–30.1] ng·h/ml, p <.001) population. In addition to CYP2C19-poor metabolizer phenotype, fluvoxamine coadministration, hepatic, and renal dysfunction were found to reduce H4 metabolite but not acyl glucuronide metabolite concentrations. This is the first PBPK model describing the two major metabolic pathways of clopidogrel, which can be applied to populations of European and Japanese ancestry by CYP2C19 phenotype. The differences between the two populations appear to be determined primarily by the effect of varying CYP2C19 liver activity

Dose rationale and pharmacokinetics of dexmedetomidine in mechanically ventilated new-borns : impact of design optimisation

Purpose: There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates. Methods: A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study. Results: Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA. Conclusions: The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population

How to optimise drug study design : pharmacokinetics and pharmacodynamics studies introduced to paediatricians

Objectives In children, there is often lack of sufficient information concerning the pharmacokinetics (PK) and pharmacodynamics (PD) of a study drug to support dose selection and effective evaluation of efficacy in a randomised clinical trial (RCT). Therefore, one should consider the relevance of relatively small PKPD studies, which can provide the appropriate data to optimise the design of an RCT. Methods Based on the experience of experts collaborating in the EU-funded Global Research in Paediatrics consortium, we aimed to inform clinician-scientists working with children on the design of investigator-initiated PKPD studies. Key findings The importance of the identification of an optimal dose for the paediatric population is explained, followed by the differences and similarities of dose-ranging and efficacy studies. The input of clinical pharmacologists with modelling expertise is essential for an efficient dose-finding study. Conclusions The emergence of new laboratory techniques and statistical tools allows for the collection and analysis of sparse and unbalanced data, enabling the implementation of (observational) PKPD studies in the paediatric clinic. Understanding of the principles and methods discussed in this study is essential to improve the quality of paediatric PKPD investigations, and to prevent the conduct of paediatric RCTs that fail because of inadequate dosing.Peer reviewe

Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?

Funding: British Society for Antimicrobial Chemotherapy Research Grant (GA2015-172R). F. K. conducted the research as part of a Medical Research Council fellowship (MR/P014534/1).Objectives : To demonstrate how phenotypic cell viability data can provide insight into antimycobacterial effects for the isoniazid/rifampicin treatment backbone. Methods : Data from a Mycobacterium komossense hollow-fibre infection model comprising a growth control group, rifampicin at three different exposures (Cmax = 0.14, 0.4 and 1.47 mg/L with t½ = 1.57 h and τ = 8 h) and rifampicin plus isoniazid (Cmax rifampicin = 0.4 mg/L and Cmax isoniazid = 1.2 mg/L with t½ = 1.57 h and τ = 8 h) were used for this investigation. A non-linear mixed-effects modelling approach was used to fit conventional cfu data, quantified using solid-agar plating. Phenotypic proportions of respiring (alive), respiring but with damaged cell membrane (injured) and 'not respiring' (dead) cells data were quantified using flow cytometry and Sytox Green™ (Sigma-Aldrich, UK) and resazurin sodium salt staining and fitted using a multinomial logistic regression model. Results : Isoniazid/rifampicin combination therapy displayed a decreasing overall antimicrobial effect with time (θTime1/2 = 438 h) on cfu data, in contrast to rifampicin monotherapy where this trend was absent. In the presence of isoniazid a phenotype associated with cell injury was displayed, whereas with rifampicin monotherapy a pattern of phenotypic cell death was observed. Bacterial killing onset time on cfu data correlated negatively (θTime50 = 28.9 h, θLAGRIF50 = 0.132 mg/L) with rifampicin concentration up to 0.165 mg/L and this coincided with a positive relationship between rifampicin concentration and the probability of phenotypic cell death. Conclusions : Cell viability data provide structured information on the pharmacodynamic interaction between isoniazid and rifampicin that complements the understanding of the antibacillary effects of this mycobacterial treatment backbone.Publisher PDFPeer reviewe