Goonaseelan Pillai

Pharmacokinetics/Pharmacodynamics of Bisphosphonates: Use for Optimisation of Intermittent Therapy for Osteoporosis

Bisphosphonates suppress osteoclast-mediated bone resorption and are widely used in the management of osteoporosis. Daily oral administration of alendronic acid and risedronic acid have been shown to reduce the risk of vertebral and non-vertebral fractures. Once-weekly regimens with these bisphosphonates are pharmacologically equivalent to daily regimens. Regimens with treatment-free intervals longer than 1 week present an attractive therapeutic option as they may offer additional patient convenience and long-term adherence to treatment. However, until recently, such regimens, usually referred to as intermittent or cyclical, have not shown any convincing antifracture efficacy in clinical trials, probably because of the empirical manner in which the design of these regimens has been approached. Investigation of pharmacokinetics/pharmacodynamics of bisphosphonates may help in the design of effective intermittent dosage regimens.Bisphosphonates are poorly absorbed from the gastrointestinal tract and about 50% of the absorbed drug is taken up selectively by the skeleton, while the rest is excreted unaltered in urine. Bisphosphonates exert their action at the bone surface, where they are taken up by the osteoclasts during bone resorption. Therefore, when describing the pharmacokinetics of bisphosphonates in relation to the pharmacodynamics, the amount of bisphosphonate at the skeleton should be accounted for. Few of the reported clinical pharmacokinetic studies addressed this issue. This is partly due to the absence of study design elements to account for skeletal binding of the drugs. Pharmacokinetic studies have also been hampered by technical difficulties in determining the concentration of bisphosphonates in serum and urine. Moreover, most clinical pharmacokinetic (but also pharmacokinetic/pharmacodynamic) studies have primarily used noncompartmental analysis, leaving out the distinct advantages of modelling and simulation techniques.Clinically, the primary action of bisphosphonates can be assessed by the measurement of biochemical markers of bone resorption. Recent studies indicate that the pattern of these markers during bisphosphonate treatment may be predictive of antifracture efficacy; however, only limited data are available for the development of pharmacokinetic/pharmacodynamic models that are able to predict the response of these markers to different treatment regimens with bisphosphonates. Recently, pharmacokinetic/pharmacodynamic models for response to bisphosphonates have been described and, at present, some of them are being used in the design of bisphosphonate regimens with long drug-free intervals.

Pharmacokinetic Evaluation of the Penetration of Antituberculosis Agents in Rabbit Pulmonary Lesions

ABSTRACT Standard antituberculosis (anti-TB) therapy requires the use of multiple drugs for a minimum of 6 months, with variable outcomes that are influenced by a number of microbiological, pathological, and clinical factors. This is despite the availability of antibiotics that have good activity against Mycobacterium tuberculosis in vitro and favorable pharmacokinetic profiles in plasma. However, little is known about the distribution of widely used antituberculous agents in the pulmonary lesions where the pathogen resides. The rabbit model of TB infection was used to explore the hypothesis that standard drugs have various abilities to penetrate lung tissue and lesions and that adequate drug levels are not consistently reached at the site of infection. Using noncompartmental and population pharmacokinetic approaches, we modeled the rate and extent of distribution of isoniazid, rifampin, pyrazinamide, and moxifloxacin in rabbit lung and lesions. Moxifloxacin reproducibly showed favorable partitioning into lung and granulomas, while the exposure of isoniazid, rifampin, and pyrazinamide in lesions was markedly lower than in plasma. The extent of penetration in lung and lesions followed different trends for each drug. All four agents distributed rapidly from plasma to tissue with equilibration half-lives of less than 1 min to an hour. The models adequately described the plasma concentrations and reasonably captured actual lesion concentrations. Though further refinement is needed to accurately predict the behavior of these drugs in human subjects, our results enable the integration of lesion-specific pharmacokinetic-pharmacodynamic (PK-PD) indices in clinical trial simulations and in in vitro PK-PD studies with M. tuberculosis.

Population pharmacokinetics of rifampin in pulmonary tuberculosis patients, including a semimechanistic model to describe variable absorption.

ABSTRACT This article describes the population pharmacokinetics of rifampin in South African pulmonary tuberculosis patients. Three datasets containing 2,913 rifampin plasma concentration-time data points, collected from 261 South African pulmonary tuberculosis patients aged 18 to 72 years and weighing 28.5 to 85.5 kg and receiving regular daily treatment that included administration of rifampin (450 to 600 mg) for at least 10 days, were pooled. A compartmental pharmacokinetic model was developed using nonlinear mixed-effects modeling. Variability in the shape of the absorption curve was described using a flexible transit compartment model, in which a delay in the onset of absorption and a gradually changing absorption rate were modeled as the passage of drug through a chain of hypothetical compartments, ultimately reaching the absorption compartment. A previously described implementation was extended to allow its application to multiple-dosing data. The typical population estimate of oral clearance was 19.2 liters·h−1, while the volume of distribution was estimated to be 53.2 liters. Interindividual variability was estimated to be 52.8% for clearance and 43.4% for volume of distribution. Interoccasional variability was estimated for CL/F (22.5%) and mean transit time during absorption (67.9%). The use of single-drug formulations was found to increase both the mean transit time (by 104%) and clearance (by 23.6%) relative to fixed-dose-combination use. A strong correlation between clearance and volume of distribution suggested substantial variability in bioavailability, which could have clinical implications, given the dependence of treatment effectiveness on exposure. The final model successfully described rifampin pharmacokinetics in the population studied and is suitable for simulation in this context.

Non-Linear Mixed Effects Modeling – From Methodology and Software Development to Driving Implementation in Drug Development Science

Few scientific contributions have made significant impact unless there was a champion who had the vision to see the potential for its use in seemingly disparate areas—and who then drove active implementation. In this paper, we present a historical summary of the development of non-linear mixed effects (NLME) modeling up to the more recent extensions of this statistical methodology. The paper places strong emphasis on the pivotal role played by Lewis B. Sheiner (1940–2004), who used this statistical methodology to elucidate solutions to real problems identified in clinical practice and in medical research and on how he drove implementation of the proposed solutions. A succinct overview of the evolution of the NLME modeling methodology is presented as well as ideas on how its expansion helped to provide guidance for a more scientific view of (model-based) drug development that reduces empiricism in favor of critical quantitative thinking and decision making

Variability in the population pharmacokinetics of isoniazid in South African tuberculosis patients

AIM This study was designed to characterize the population pharmacokinetics of isoniazid in South African pulmonary tuberculosis patients. METHODS Concentration-time measurements obtained from 235 patients receiving oral doses of isoniazid as part of routine tuberculosis chemotherapy in two clinical studies were pooled and subjected to nonlinear mixed-effects analysis. RESULTS A two-compartmental model, including first-order absorption and elimination with allometric scaling, was found to describe the observed dose-exposure relationship for oral isoniazid adequately. A mixture model was used to characterize dual rates of isoniazid elimination. Estimates of apparent clearance in slow and fast eliminators were 9.70 and 21.6 l h(-1) , respectively. The proportion of fast eliminators in the population was estimated to be 13.2%. Central volume of distribution was estimated to be 10% smaller in female patients and clearance was found to be 17% lower in patients with HIV. Variability in absorption rate (90%) was completely interoccasional in nature, whereas in relative bioavailability, interoccasional variability (8.4%) was lower than interindividual variability (26%). Oral doses, given once daily according to dosing policies at the time, were sufficient to reach therapeutic concentrations in the majority of the studied population, regardless of eliminator phenotype. Simulations suggested that current treatment guidelines (5 mg kg(-1) ) may be suboptimal in fast eliminators with low body weight. CONCLUSIONS A population pharmacokinetic model was developed to characterize the highly variable pharmacokinetics of isoniazid in a South African pulmonary tuberculosis patient population. Current treatment guidelines may lead to underexposure in rapid isoniazid eliminators.

Longitudinal Model-Based Meta-Analysis in Rheumatoid Arthritis: An Application Toward Model-Based Drug Development

Summary‐level longitudinal data on the clinical efficacy of drugs for rheumatoid arthritis (RA) are available in the literature. This information can be used to optimize the clinical development of new drugs for RA. The aim of this study was twofold: first, to quantify the time course of the ACR20 score across approved drugs and patient populations, and second, to apply this knowledge in the decision‐making process for a specific compound, canakinumab. The integrated analysis included data from 37 phase II–III studies describing 13,474 patients. It showed that, with the tested doses/regimens of canakinumab, there was only a low probability that this drug would be better than the most effective current treatments. This finding supported the decision not to continue with clinical development of canakinumab in RA. This paper presents the first longitudinal model‐based meta‐analysis of ACR20. The framework can be applied to any other compound targeting RA, thereby supporting internal and external decision making at all clinical development stages.

Pharmacokinetic Similarity of Biologics: Analysis Using Nonlinear Mixed‐Effects Modeling

Our objective was to show, using two examples, that a pharmacokinetic (PK) similarity analysis can be performed using nonlinear mixed‐effects models (NLMEM). We used two studies that compared different biosimilars: a three‐way crossover trial with somatropin and a parallel‐group trial with epoetin‐α. For both data sets, the results of NLMEM‐based analysis were compared with those of noncompartmental analysis (NCA). For the latter analysis, we performed an NLMEM‐based equivalence Wald test on secondary parameters of the model: the area under the curve and the maximal concentration. Somatropin PK was described by a one‐compartment model and epoetin‐α PK by a two‐compartment model with linear and Michaelis–Menten elimination. For both studies, similarity of PK was demonstrated by means of both NCA and NLMEM, and both methods led to similar results. Therefore, for establishing similarity, PK data can be analyzed by either of the methods. NCA is an easier approach because it does not require data modeling; however, NLMEM leads to a better understanding of the underlying biological system.

Open-source mobile digital platform for clinical trial data collection in low-resource settings.

Background Governments, universities and pan-African research networks are building durable infrastructure and capabilities for biomedical research in Africa. This offers the opportunity to adopt from the outset innovative approaches and technologies that would be challenging to retrofit into fully established research infrastructures such as those regularly found in high-income countries. In this context we piloted the use of a novel mobile digital health platform, designed specifically for low-resource environments, to support high-quality data collection in a clinical research study. Objective Our primary aim was to assess the feasibility of a using a mobile digital platform for clinical trial data collection in a low-resource setting. Secondarily, we sought to explore the potential benefits of such an approach. Methods The investigative site was a research institute in Nairobi, Kenya. We integrated an open-source platform for mobile data collection commonly used in the developing world with an open-source, standard platform for electronic data capture in clinical trials. The integration was developed using common data standards (Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model), maximising the potential to extend the approach to other platforms. The system was deployed in a pharmacokinetic study involving healthy human volunteers. Results The electronic data collection platform successfully supported conduct of the study. Multidisciplinary users reported high levels of satisfaction with the mobile application and highlighted substantial advantages when compared with traditional paper record systems. The new system also demonstrated a potential for expediting data quality review. Discussion and Conclusions This pilot study demonstrated the feasibility of using a mobile digital platform for clinical research data collection in low-resource settings. Sustainable scientific capabilities and infrastructure are essential to attract and support clinical research studies. Since many research structures in Africa are being developed anew, stakeholders should consider implementing innovative technologies and approaches.

Building capability for clinical pharmacology research in sub-Saharan Africa

A strong scientific rationale exists for conducting clinical pharmacology studies in target populations because local factors such as genetics, environment, comorbidities, and diet can affect variability in drug responses. However, clinical pharmacology studies are not widely conducted in sub‐Saharan Africa, in part due to limitations in technical expertise and infrastructure. Since 2012, a novel public‐private partnership model involving research institutions and a pharmaceutical company has been applied to developing increased capability for clinical pharmacology research in multiple African countries.

Population pharmacokinetic modeling of glibenclamide in poorly controlled South African type 2 diabetic subjects

Aim The aim of this study was to describe the pharmacokinetics (PK) of glibenclamide in poorly controlled South African type 2 diabetic subjects using noncompartmental and model-based methods. Methods A total of 24 subjects with type 2 diabetes were administered increasing doses (0 mg/d, 2.5 mg/d, 5 mg/d, 10 mg/d, and 20 mg/d) of glibenclamide daily at 2-week intervals. Plasma glibenclamide, glucose, and insulin determinations were performed. Blood sampling times were 0 minute, 30 minutes, 60 minutes, 90 minutes, and 120 minutes (post breakfast sampling) and 240 minutes, 270 minutes, 300 minutes, 330 minutes, 360 minutes, and 420 minutes (post lunch sampling) on days 14, 28, 42, 56, and 70 for doses of 0 mg, 2.5 mg, 5.0 mg, 10 mg, and 20 mg, respectively. Blood sampling was performed after the steady state was reached. A total of 24 individuals in the data set contributed to a total of 841 observation records. The PK was analyzed using noncompartmental analysis methods, which were implemented in WinNonLin®, and population PK analysis using NONMEM®. Glibenclamide concentration data were log transformed prior to fitting. Results A two-compartmental disposition model was selected after evaluating one-, two-, and three-compartmental models to describe the time course of glibenclamide plasma concentration data. The one-compartment model adequately described the data; however, the two-compartment model provided a better fit. The three-compartment model failed to achieve successful convergence. A more complex model, to account for enterohepatic recirculation that was observed in the data, was unsuccessful. Conclusion In South African diabetic subjects, glibenclamide demonstrates linear PK and was best described by a two-compartmental model. Except for the absorption rate constant, the other PK parameters reported in this study are comparable to those reported in the scientific literature. The study is limited by the small study sample size and inclusion of poorly controlled type 2 diabetic subjects.