Assessment of the nlmixr R-package for population pharmacokinetic modeling: A metformin case study

Aim: nlmixr offers first-order conditional estimation with or without interaction (FOCE or FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin’s population pharmacokinetics with flip-flop characteristics within nlmixr framework and investigated SAEM and FOCEi’s performance with respect to bias, precision, and robustness. Method: Compartmental pharmacokinetic models were fitted. The final model was determined based on the lowest objective function value and visual inspection of goodness-of-fit plots. To examine flip-flop pharmacokinetics, k_a values of a typical concentration-time profile based on the final model were perturbed and changes in the steepness of the terminal elimination phase were evaluated. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100-times and resultant changes evaluated. Results: A one-compartment model with transit compartment for absorption best described the data. At low n, Stirling’s approximation of n! over-approximated plasma concentration unlike the log-gamma function. Flip-flop pharmacokinetics were evident as the steepness of the terminal elimination phase changed with k_a. Mean rRMSE for fixed-effect parameters was 0.932. When initial estimates were perturbed, FOCEi estimates of k_a and food effect on k_a appeared bimodal and were upward biased. Discussion: nlmixr is reliable for NLMEM even if flip-flop is present but caution should be exercised when using Stirling’s approximation for n! in the transit compartment model. SAEM was marginally superior to FOCEi in bias and precision, but SAEM was superior against initial estimate perturbations.

Pharmacokinetics and Drug-Drug Interactions of Abacavir and Lamuvudine Co-administered With Antituberculosis Drugs in HIV-Positive Children Treated for Multidrug-Resistant Tuberculosis

Given the high prevalence of multidrug-resistant (MDR)-TB in high HIV burden settings, it is important to identify potential drug-drug interactions between MDR-TB treatment and widely used nucleoside reverse transcriptase inhibitors (NRTIs) in HIV-positive children. Population pharmacokinetic models were developed for lamivudine (n = 54) and abacavir (n = 50) in 54 HIV-positive children established on NRTIs; 27 with MDR-TB (combinations of high-dose isoniazid, pyrazinamide, ethambutol, ethionamide, terizidone, fluoroquinolones, and amikacin), and 27 controls without TB. Two-compartment models with first-order elimination and transit compartment absorption described both lamivudine and abacavir pharmacokinetics, respectively. Allometric scaling with body weight adjusted for the effect of body size. Clearance was predicted to reach half its mature value ∼2 (lamivudine) and ∼3 (abacavir) months after birth, with completion of maturation for both drugs at ∼2 years. No significant difference was found in key pharmacokinetic parameters of lamivudine and abacavir when co-administered with routine drugs used for MDR-TB in HIV-positive children.

Dolutegravir pharmacokinetics during co-administration with either artemether/lumefantrine or artesunate/amodiaquine

Background In sub-Saharan Africa, artemisinin-containing therapies for malaria treatment are regularly co-administered with ART. Currently, dolutegravir-based regimens are recommended as first-line therapy for HIV across most of Africa. Objectives To investigate the population pharmacokinetics of dolutegravir during co-administration with artemether/lumefantrine or artesunate/amodiaquine, two commonly used antimalarial therapies. Methods We developed a population pharmacokinetic model of dolutegravir with data from 26 healthy volunteers in two Phase 2 studies with a total of 403 dolutegravir plasma concentrations at steady state. Volunteers received 50 mg of dolutegravir once daily alone or in combination with standard treatment doses of artemether/lumefantrine (80/480 mg) or artesunate/amodiaquine (200/540 mg). Results A two-compartment model with first-order elimination and transit compartment absorption best described the concentration–time data of dolutegravir. Typical population estimates for clearance, absorption rate constant, central volume, peripheral volume and mean absorption transit time were 0.713 L/h, 1.68 h−1, 13.2 L, 5.73 L and 1.18 h, respectively. Co-administration of artemether/lumefantrine or artesunate/amodiaquine increased dolutegravir clearance by 10.6% (95% CI 4.09%–34.5%) and 26.4% (95% CI 14.3%–51.4%), respectively. Simulations showed that simulated trough concentrations of dolutegravir alone or in combination with artemether/lumefantrine or artesunate/amodiaquine are maintained above the dolutegravir protein-adjusted IC90 of 0.064 mg/L for more than 99% of the individuals. Conclusions Dolutegravir dose adjustments are not necessary for patients who are taking standard 3 day treatment doses of artemether/lumefantrine or artesunate/amodiaquine.

COVIDStrategyCalculator: A standalone software to assess testing- and quarantine strategies for incoming travelers, contact person management and de-isolation

In early 2020 COVID-19 turned into a global pandemic. Non-pharmaceutical interventions (NPIs), including the isolation of infected individuals, tracing and quarantine of exposed individuals are decisive tools to prevent onwards transmission and curb fatalities. Strategies that combine NPIs with SARS-CoV-2 testing may help to shorten quarantine durations while being non-inferior with respect to infection prevention. Thus, combined strategies can help reducing the socio-economic burden of SARS-CoV-2 and increase public acceptance.We developed a software that enables policy makers to calculate the reduction in transmissibility through quarantine or isolation in combination with arbitrary testing strategies. The user chooses between three different modi [(i) isolation of infected individuals, (ii) management of potentially infected contacts and (iii) quarantine of incoming travelers], while having flexibility in customizing testing strategies and model parameters. The software enables decision makers to tailor calculations specifically to their questions and perform an assessment ‘on the fly’, based on current evidence on infection dynamics.Underneath, we analytically solve a stochastic transit compartment model of the infection time course, which captures temporal changes in test sensitivities, incubation- and infectious periods, as well as times to symptom onset using its default parameters.Using default parameters, we estimated that testing travelers at the point of entry reduces the risk about 4.69 (4.19,4.83) fold for PCR vs. 3.59 (3.22, 3.69) fold for rapid diagnostic tests (RDT, 87% relative sensitivity) when combined with symptom screening. In comparison to 14 days of pure quarantine, 8 (PCR) vs. 10 (RDT) days of pre-test quarantine would be noninferior for incoming travelers as well as for contact person management. De-isolation of infected individuals 11 days after symptom onset reduces the risk by >99fold (7.68,>1012). This tool is freely available from: https://github.com/CovidStrategyCalculator/CovidStrategyCalculator

Exact solutions and equi-dosing regimen regions for multi-dose pharmacokinetics models with transit compartments

Compartmental models which yield linear ordinary differential equations (ODEs) provide common tools for pharmacokinetics (PK) analysis, with exact solutions for drug levels or concentrations readily obtainable for low-dimensional compartment models. Exact solutions enable valuable insights and further analysis of these systems. Transit compartment models are a popular semi-mechanistic approach for generalising simple PK models to allow for delayed kinetics, but computing exact solutions for multi-dosing inputs to transit compartment systems leading to different final compartments is nontrivial. Here, we find exact solutions for drug levels as functions of time throughout a linear transit compartment cascade followed by an absorption compartment and a central blood compartment, for the general case of n transit compartments and M equi-bolus doses to the first compartment. We further show the utility of exact solutions to PK ODE models in finding constraints on equi-dosing regimen parameters imposed by a prescribed therapeutic range. This leads to the construction of equi-dosing regimen regions (EDRRs), providing new, novel visualisations which summarise the safe and effective dosing parameter space. EDRRs are computed for classical and transit compartment models with two- and three-dimensional parameter spaces, and are proposed as useful graphical tools for informing drug dosing regimen design.

Pharmacokinetic Models to Characterize the Absorption Phase and the Influence of a Proton Pump Inhibitor on the Overall Exposure of Dacomitinib

Introduction: Dacomitinib is an epidermal growth factor receptor (EGFR) inhibitor approved for the treatment of metastatic non-small cell lung cancer (NSCLC) in the first line in patients with EGFR activating mutations. Dacomitinib is taken orally once daily at 45 mg with or without food, until disease progression or unacceptable toxicity occurs. Oncology patients often can develop gastroesophageal reflux disease (GERD), which may require management with an acid-reducing agent. Proton pump inhibitors (PPIs), such as rabeprazole, inhibit sodium-potassium adenosine triphosphatase (H+/K+-ATPase) pumps that stimulate acid secretion in the stomach and have a prolonged pharmacodynamic effect that extends beyond 24 h post-administration. The aim of this work was to characterize the absorption of dacomitinib via modeling with a particular interest in quantifying the impact of rabeprazole on the pharmacokinetics (PK) of dacomitinib. Materials and Methods: The pooled dataset consisted of five clinical pharmacology healthy volunteer studies, which collected serial pharmacokinetic concentration-time profiles of dacomitinib. Non-linear mixed effects modeling was carried out to characterize dacomitinib pharmacokinetics in the presence and absence of the concomitant use of a PPI, rabeprazole. Several absorption models, some more empirical, and some more physiologically based, were tested: transit compartment, first-order absorption with and without lag time, and variations of combined zero- and first-order absorption kinetics models. Results: The presence of a PPI was a significant covariate affecting the extent (F) and rate (ka) of dacomitinib absorption, as previously reported in the dedicated clinical study. A transit compartment model was able to best describe the absorption phase of dacomitinib.

Abacavir Exposure in Children Cotreated for Tuberculosis with Rifampin and Superboosted Lopinavir-Ritonavir

ABSTRACT In children requiring lopinavir coformulated with ritonavir in a 4:1 ratio (lopinavir-ritonavir-4:1) and rifampin, adding ritonavir to achieve a 4:4 ratio with lopinavir (LPV/r-4:4) overcomes the drug-drug interaction. Possible drug-drug interactions within this regimen may affect abacavir concentrations, but this has never been studied. Children weighing <15 kg needing rifampin and LPV/r-4:4 were enrolled in a pharmacokinetic study and underwent intensive pharmacokinetic sampling on 3 visits: (i) during the intensive and (ii) continuation phases of antituberculosis treatment with LPV/r-4:4 and (iii) 1 month after antituberculosis treatment completion on LPV/r-4:1. Pharmacometric modeling and simulation were used to compare exposures across weight bands with adult target exposures. Eighty-seven children with a median (interquartile range) age and weight of 19 (4 to 64) months and 8.7 (3.9 to 14.9) kg, respectively, were included in the abacavir analysis. Abacavir pharmacokinetics were best described by a two-compartment model with first-order elimination and transit compartment absorption. After allometric scaling adjusted for the effect of body size, maturation could be identified: clearance was predicted to be fully mature at about 2 years of age and to reach half of this mature value at about 2 months of age. Abacavir bioavailability decreased 36% during treatment with rifampin and LPV/r-4:4 but remained within the median adult recommended exposure, except for children in the 3- to 4.9-kg weight band, in which the exposures were higher. The observed predose morning trough concentrations were higher than the evening values. Though abacavir exposure significantly decreased during concomitant administration of rifampin and LPV/r-4:4, it remained within acceptable ranges. (This study is registered in ClinicalTrials.gov under identifier NCT02348177.)

Semi-Mechanism-Based Pharmacokinetic-Toxicodynamic Model of Oxaliplatin-Induced Acute and Chronic Neuropathy

Oxaliplatin (L-OHP) is widely prescribed for treating gastroenterological cancer. L-OHP-induced peripheral neuropathy is a critical toxic effect that limits the dosage of L-OHP. An ideal chemotherapeutic strategy that does not result in severe peripheral neuropathy but confers high anticancer efficacy has not been established. To establish an optimal evidence-based dosing regimen, a pharmacokinetic-toxicodynamic (PK-TD) model that can characterize the relationship between drug administration regimen and L-OHP-induced peripheral neuropathy is required. We developed a PK-TD model of L-OHP for peripheral neuropathy using Phoenix® NLME™ Version 8.1. Plasma concentration of L-OHP, the number of withdrawal responses in the acetone test, and the threshold value in the von Frey test following 3, 5, or 8 mg/kg L-OHP administration were used. The PK-TD model consisting of an indirect response model and a transit compartment model adequately described and simulated time-course alterations of onset and grade of L-OHP-induced cold and mechanical allodynia. The results of model analysis suggested that individual fluctuation of plasma L-OHP concentration might be a more important factor for individual variability of neuropathy than cell sensitivity to L-OHP. The current PK-TD model might contribute to investigation and establishment of an optimal dosing strategy that can reduce L-OHP-induced neuropathy.

Model-Based Evaluation of Higher Doses of Rifampin Using a Semimechanistic Model Incorporating Autoinduction and Saturation of Hepatic Extraction

ABSTRACTRifampin is a key sterilizing drug in the treatment of tuberculosis (TB). It induces its own metabolism, but neither the onset nor the extent of autoinduction has been adequately described. Currently, the World Health Organization recommends a rifampin dose of 8 to 12 mg/kg of body weight, which is believed to be suboptimal, and higher doses may potentially improve treatment outcomes. However, a nonlinear increase in exposure may be observed because of saturation of hepatic extraction and hence this should be taken into consideration when a dose increase is implemented. Intensive pharmacokinetic (PK) data from 61 HIV-TB-coinfected patients in South Africa were collected at four visits, on days 1, 8, 15, and 29, after initiation of treatment. Data were analyzed by population nonlinear mixed-effects modeling. Rifampin PKs were best described by using a transit compartment absorption and a well-stirred liver model with saturation of hepatic extraction, including a first-pass effect. Autoinduction was characterized by using an exponential-maturation model: hepatic clearance almost doubled from the baseline to steady state, with a half-life of around 4.5 days. The model predicts that increases in the dose of rifampin result in more-than-linear drug exposure increases as measured by the 24-h area under the concentration-time curve. Simulations with doses of up to 35 mg/kg produced results closely in line with those of clinical trials.