Establishment of a Disease-Drug Trial Model for Postmenopausal Osteoporosis: A Zoledronic Acid Case Study.

Costly and lengthy clinical trials hinder the development of safe and effective treatments for postmenopausal osteoporosis. To reduce the expense associated with these trials, we established a mechanistic disease-drug trial model for postmenopausal osteoporosis that can predict phase 3 trial outcome based on short-term bone turnover marker data. To this end, we applied a previously developed model for tibolone to bisphosphonates using zoledronic acid as paradigm compound by (1) linking the mechanistic bone cell interaction model to bone turnover markers as well as bone mineral density in lumbar spine and total hip, (2) employing a mechanistic disease progression function, and (3) accounting for zoledronic acid's mechanism of action. Once developed, we fitted the model to clinical trial data of 581 postmenopausal women receiving (1) 5-mg zoledronic acid in year 1 and saline in year 2, (2) 5-mg zoledronic acid in year 1 and year 2, or (3) placebo (saline), calcium (500 mg), and vitamin D (400 IU). All biomarker data was fitted reasonably well, with no apparent bias or model misspecification. Age, years since menopause, and body mass index at baseline were identified as significant covariates. In the future, the model can be modified to explore the link between short-term biomarkers and fracture risk.

Regulatory Perspectives in Pharmacometric Models of Osteoporosis.

Osteoporosis is a disorder of the bones in which they are weakened to the extent that they become more prone to fracture. There are various forms of osteoporosis: some of them are induced by drugs, and others occur as a chronic progressive disorder as an individual gets older. As the median age of the population rises across the world, the chronic form of the bone disease is drawing attention as an important worldwide health issue. Developing new treatments for osteoporosis and comparing them with existing treatments are complicated processes due to current acceptance by regulatory authorities of bone mineral density (BMD) and fracture risk as clinical end points, which require clinical trials to be large, prolonged, and expensive to determine clinically significant impacts in BMD and fracture risk. Moreover, changes in BMD and fracture risk are not always correlated, with some clinical trials showing BMD improvement without a reduction in fractures. More recently, bone turnover markers specific to bone formation and resorption have been recognized that reflect bone physiology at a cellular level. These bone turnover markers change faster than BMD and fracture risk, and mathematically linking the biomarkers via a computational model to BMD and/or fracture risk may help in predicting BMD and fracture risk changes over time during the progression of a disease or when under treatment. Here, we discuss important concepts of bone physiology, osteoporosis, treatment options, mathematical modeling of osteoporosis, and the use of these models by the pharmaceutical industry and the Food and Drug Administration.

Development of a physiology-directed population pharmacokinetic and pharmacodynamic model for characterizing the impact of genetic and demographic factors on clopidogrel response in healthy adults.

Clopidogrel (Plavix®), is a widely used antiplatelet agent, which shows high inter-individual variability in treatment response in patients following the standard dosing regimen. In this study, a physiology-directed population pharmacokinetic/pharmacodynamic (PK/PD) model was developed based on clopidogrel and clopidogrel active metabolite (clop-AM) data from the PAPI and the PGXB2B studies using a step-wise approach in NONMEM (version 7.2). The developed model characterized the in vivo disposition of clopidogrel, its bioactivation into clop-AM in the liver and subsequent platelet aggregation inhibition in the systemic circulation reasonably well. It further allowed the identification of covariates that significantly impact clopidogrel's dose-concentration-response relationship. In particular, CYP2C19 intermediate and poor metabolizers converted 26.2% and 39.5% less clopidogrel to clop-AM, respectively, compared to extensive metabolizers. In addition, CES1 G143E mutation carriers have a reduced CES1 activity (82.9%) compared to wild-type subjects, which results in a significant increase in clop-AM formation. An increase in BMI was found to significantly decrease clopidogrel's bioactivation, whereas increased age was associated with increased platelet reactivity. Our PK/PD model analysis suggests that, in order to optimize clopidogrel dosing on a patient-by-patient basis, all of these factors have to be considered simultaneously, e.g. by using quantitative clinical pharmacology tools.

Clinical pharmacokinetics and pharmacodynamics of clopidogrel.

Acute coronary syndromes (ACS) remain life-threatening disorders, which are associated with high morbidity and mortality. Dual antiplatelet therapy with aspirin and clopidogrel has been shown to reduce cardiovascular events in patients with ACS. However, there is substantial inter-individual variability in the response to clopidogrel treatment, in addition to prolonged recovery of platelet reactivity as a result of irreversible binding to P2Y12 receptors. This high inter-individual variability in treatment response has primarily been associated with genetic polymorphisms in the genes encoding for cytochrome (CYP) 2C19, which affect the pharmacokinetics of clopidogrel. While the US Food and Drug Administration has issued a boxed warning for CYP2C19 poor metabolizers because of potentially reduced efficacy in these patients, results from multivariate analyses suggest that additional factors, including age, sex, obesity, concurrent diseases and drug-drug interactions, may all contribute to the overall between-subject variability in treatment response. However, the extent to which each of these factors contributes to the overall variability, and how they are interrelated, is currently unclear. The objective of this review article is to provide a comprehensive update on the different factors that influence the pharmacokinetics and pharmacodynamics of clopidogrel and how they mechanistically contribute to inter-individual differences in the response to clopidogrel treatment.

Population pharmacokinetics of tranexamic acid in paediatric patients undergoing craniosynostosis surgery.

BACKGROUND: Tranexamic acid (TXA) effectively reduces blood loss and transfusion requirements during craniofacial surgery. The pharmacokinetics of TXA have not been fully characterized in paediatric patients and dosing regimens remain diverse in practice. A mixed-effects population analysis would characterize patient variability and guide dosing practices. OBJECTIVE: The objective of this study was to conduct a population pharmacokinetic analysis and develop a model to predict an effective TXA dosing regimen for children with craniosynostosis undergoing cranial remodelling procedures. METHODS: The treatment arm of a previously reported placebo-controlled efficacy trial was analysed. Twenty-three patients with a mean age 23 ± 19 months received a TXA loading dose of 50 mg/kg over 15 min at a constant rate, followed by a 5 mg/kg/h maintenance infusion during surgery. TXA plasma concentrations were measured and modelled with a non-linear mixed-effects strategy using Monolix 4.1 and NONMEM(®) 7.2. RESULTS: TXA pharmacokinetics were adequately described by a two-compartment open model with systemic clearance (CL) depending on bodyweight (WT) and age. The apparent volume of distribution of the central compartment (V1) was also dependent on bodyweight. Both the inter-compartmental clearance (Q) and the apparent volume of distribution of the peripheral compartment (V2) were independent of any covariate. The final model may be summarized as: CL (L/h) = [2.3 × (WT/12)(1.59) × AGE(-0.0934)] × e(η1), V1 (L) = [2.34 × (WT/12)(1.4)] × e(η2), Q (L/h) = 2.77 × e(η3) and V2 (L) = 1.53 × e(η4), where each η corresponds to the inter-patient variability for each parameter. No significant correlation was found between blood volume loss and steady-state TXA concentrations. Based on this model and simulations, lower loading doses than used in the clinical study should produce significantly lower peak concentrations while maintaining similar steady-state concentrations. CONCLUSIONS: A two-compartment model with covariates bodyweight and age adequately characterized the disposition of TXA. A loading dose of 10 mg/kg over 15 min followed by a 5 mg/kg/h maintenance infusion was simulated to produce steady-state TXA plasma concentrations above the 16 µg/mL threshold. This dosing scheme reduces the initial high peaks observed with the larger dose of 50 mg/kg over 15 min used in our previous clinical study.