Posaconazole in paediatric malignancy and haematopoietic stem cell transplant: dosing to achieve therapeutic concentration.

OBJECTIVES: Posaconazole is increasingly used for the treatment and prophylaxis of invasive fungal infections in immunocompromised children. We aimed to review evidence for paediatric posaconazole dosing regimens focusing on attainment of target concentrations and frequency of adverse effects. METHODS: In May 2023, the Cochrane, Embase, MEDLINE and PubMed databases were searched for articles reporting posaconazole dosing in children with malignancy or post-haematopoietic stem cell transplantation. Studies reporting the attainment of target serum concentrations were included. RESULTS: Overall, 24 studies were included. Eighteen studies of the oral suspension consistently reported poor attainment of target concentrations for prophylaxis (≥0.7 µg/mL, 12%-78%) despite high daily doses of 14-23 mg/kg/day (max. 1200 mg/day). Target attainment was significantly affected by gastric pH and food intake. Six studies of the delayed-release tablet (DRT) reported 58%-94% achieved concentrations ≥0.7 µg/mL, with the majority using lower doses of 4-12 mg/kg/day (max. 300 mg/day). Similarly, one study of powder for oral suspension found 67%-100% achieved target concentrations with a dose of 6 mg/kg/day (max. 300 mg/day). As expected, the IV formulation had high attainment of prophylaxis targets (81%-90%) with 6-10 mg/kg/day (max. 400 mg/day). All formulations were well tolerated, and no relationship between adverse effects and posaconazole concentrations was identified. CONCLUSIONS: The required posaconazole dose in immunocompromised children varies depending on the formulation. The IV infusion had the highest attainment of therapeutic concentration followed by the DRT and powder for suspension. By contrast, the oral suspension had low attainment of target concentrations despite higher daily doses.

Optimal sample selection applied to information rich, dense data.

Dense data can be classified into superdense information-poor data (type 1 dense data) and dense information-rich data (type 2 dense data). Arbitrary, random, or optimal thinning may be applied to type 1 dense data to minimise computational burden and statistical issues (such as autocorrelation). In contrast, a prospective or retrospective optimal design can be applied to type 2 dense data to maximise information gain from limited resources (capital and/or time). Here we describe a retrospective optimal selection strategy for quantification of unbound drug concentration from a discrete set of plasma samples where the total drug concentration has been measured.

Oral docetaxel plus encequidar - A pharmacokinetic model and evaluation against IV docetaxel.

The development of optimized dosing regimens plays a crucial role in oncology drug development. This study focused on the population pharmacokinetic modelling and simulation of docetaxel, comparing the pharmacokinetic exposure of oral docetaxel plus encequidar (oDox + E) with the standard of care intravenous (IV) docetaxel regimen. The aim was to evaluate the feasibility of oDox + E as a potential alternative to IV docetaxel. The article demonstrates an approach which aligns with the FDA's Project Optimus which aims to improve oncology drug development through model informed drug development (MIDD). The key question answered by this study was whether a feasible regimen of oDox + E existed. The purpose of this question was to provide an early GO / NO-GO decision point to guide drug development and improve development efficiency. METHODS:  A stepwise approach was employed to develop a population pharmacokinetic model for total and unbound docetaxel plasma concentrations after IV docetaxel and oDox + E administration. Simulations were performed from the final model to assess the probability of target attainment (PTA) for different oDox + E dose regimens (including multiple dose regimens) in relation to IV docetaxel using AUC over effective concentration (AUCOEC) metric across a range of effective concentrations (EC). A Go / No-Go framework was defined-the first part of the framework assessed whether a feasible oDox + E regimen existed (i.e., a PTA ≥ 80%), and the second part defined the conditions to proceed with a Go decision. RESULTS:  The overall population pharmacokinetic model consisted of a 3-compartment model with linear elimination, constant bioavailability, constant binding mechanics, and a combined error model. Simulations revealed that single dose oDox + E regimens did not achieve a PTA greater than 80%. However, two- and three-dose regimens at 600 mg achieved PTAs exceeding 80% for certain EC levels. CONCLUSION:  The study demonstrates the benefits of MIDD using oDox + E as a motivating example. A population pharmacokinetic model was developed for the total and unbound concentration in plasma of docetaxel after administration of IV docetaxel and oDox + E. The model was used to simulate oDox + E dose regimens which were compared to the current standard of care IV docetaxel regimen. A GO / NO-GO framework was applied to determine whether oDox + E should progress to the next phase of drug development and whether any conditions should apply. A two or three-dose regimen of oDox + E at 600 mg was able to achieve non-inferior pharmacokinetic exposure to current standard of care IV docetaxel in simulations. A Conditional GO decision was made based on this result and further quantification of the "effective concentration" would improve the ability to optimise the dose regimen.

Training the next generation of pharmacometric modelers: a multisector perspective.

The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing. The field largely started when Lewis Sheiner and Stuart Beal published their seminal papers on population pharmacokinetics in the late 1970's and early 1980's and has continued to grow in impact and use since its inception. Physiological-based pharmacokinetics and systems pharmacology have grown rapidly in scope and impact in the last decade and machine learning is just on the horizon. While all these methodologies are categorized as pharmacometrics, no one person can be an expert in everything. So how do you train future pharmacometricians? Leading experts in academia, industry, contract research organizations, clinical medicine, and regulatory gave their opinions on how to best train future pharmacometricians. Their opinions were collected and synthesized to create some general recommendations.

Identifying a therapeutic target for vancomycin against staphylococci in young infants.

OBJECTIVES: To determine the therapeutic target of vancomycin in young infants with staphylococcal infections. METHODS: Retrospective data were collected for infants aged 0 to 90 days with CoNS or MRSA bacteraemia over a 4 year period at the Royal Children's Hospital Melbourne, Australia. Vancomycin broth microdilution MICs were determined. A published pharmacokinetic model was externally validated using the study dataset and a time-to-event (TTE) pharmacodynamic model developed to link the AUC of vancomycin with the event being the first negative blood culture. Simulations were performed to determine the trough vancomycin concentration that correlates with a 90% PTA of the target AUC24. RESULTS: Thirty infants, 28 with CoNS and 2 with MRSA bacteraemia, who had 165 vancomycin concentrations determined were included. The vancomycin broth microdilution MIC was determined for 24 CoNS and 1 MRSA isolate, both with a median MIC of 1 mg/L (CoNS range = 0.5-4.0). An AUC0-24 target of ≥300 mg/L·h or AUC24-48 of ≥424 mg/L·h. increased the chance of bacteriological cure by 7.8- and 7.3-fold, respectively. However, AUC0-24 performed best in the pharmacokinetic-pharmacodynamic model. This correlates with 24 to 48 h trough concentrations of >15-18 mg/L and >10-15 mg/L for 6- and 12-hourly dosing, respectively, and can be used to guide vancomycin therapy in this population. CONCLUSIONS: An AUC0-24 ≥300 mg/L·h or AUC24-48 ≥424 mg/L·h was associated with an increase in bacteriological cure in young infants with staphylococcal bloodstream infections.

Dose banding - Weighing up benefits, risks and therapeutic failure.

AIMS: Dose banding is a method of dose individualisation in which all patients with similar characteristics are allocated to the same dose. Dose banding results in some patients receiving less intensive treatment which risks a reduction in therapeutic benefit (iatrogenic therapeutic failure) because of variability not predicted by dose banding. This study aims to explore the effects of dose banding on therapeutic success and failure. METHODS: This was a simulation study. Virtual patients were simulated under a simple pharmacokinetic model where the response of interest is the steady-state average concentration. Clearance was correlated with a covariate used for dose banding. Dose individualisation was based on: one-dose-fits-all, covariate-based dosing, empirical dose banding, dose banding optimised for net therapeutic benefit and optimised for both benefit and minimising iatrogenic therapeutic failure. RESULTS: The lowest and highest probability of target attainment (PTA) were 44% for one-dose-fits-all and 72% for covariate-based dosing. Neither dosing approach would result in iatrogenic therapeutic failure as lower dose intensities do not occur. Empirical dose banding performed better than one-dose-fits-all with 59% PTA but not as good as either optimised method (64-69% PTA) while carrying a risk of iatrogenic therapeutic failure in 25% of patients. Optimising for benefit (only) improved PTA but carried a risk of iatrogenic therapeutic failure of up to 10%. Optimising for benefit and minimising iatrogenic therapeutic failure provided the best balance. CONCLUSION: Future application of dose banding needs to consider both the probability of benefit as well the risk of causing iatrogenic therapeutic failure.

A framework for simplification of quantitative systems pharmacology models in clinical pharmacology.

Quantitative systems pharmacology (QSP) is a relatively new discipline within modelling and simulation that has gained wide attention over the past few years. The application of QSP models spans drug-target identification and validation, through all drug development phases as well as clinical applications. Due to their detailed mechanistic nature, QSP models are capable of extrapolating knowledge to predict outcomes in scenarios that have not been tested experimentally, making them an important resource in experimental and clinical pharmacology. However, these models are complicated to work with due to their size and inherent complexity. This makes many applications of QSP models for simulation, parameter estimation and trial design computationally intractable. A number of techniques have been developed to simplify QSP models into smaller models that are more amenable to further analyses while retaining their accurate predictive capabilities. Different simplification techniques have different strengths and weaknesses and hence different utilities. Understanding the utilities of different methods is essential for selection of the best method for a particular situation. In this paper, we have created an overall framework for model simplification techniques that allows a natural categorisation of methods based on their utility. We provide a brief description of the concept underpinning the different methods and example applications. A summary of the utilities of methods is intended to provide a guide to modellers in their model endeavours to simplify these complicated models.

Optimal dosing of enoxaparin in overweight and obese children.

AIM: Current enoxaparin dosing guidelines in children are based on total body weight. This is potentially inappropriate in obese children as it may overestimate the drug clearance. Current evidence suggests that obese children may require lower initial doses of enoxaparin, therefore the aim of this work was to characterise the pharmacokinetics of enoxaparin in obese children and to propose a more appropriate dosing regimen. METHODS: Data from 196 unique encounters of 160 children who received enoxaparin treatment doses were analysed. Enoxaparin concentration was quantified using the chromogenic anti factor Xa (anti-Xa) assay. Patients provided a total of 552 anti-Xa samples. Existing published pharmacokinetic (PK) models were fitted and evaluated against our dataset using prediction-corrected visual predictive check plots (pcVPCs). A PK model was fitted using a nonlinear mixed-effects modelling approach. The fitted model was used to evaluate the current standard dosing and identify an optimal dosing regimen for obese children. RESULTS: Published models of enoxaparin pharmacokinetics in children did not capture the pharmacokinetics of enoxaparin in obese children as shown by pcVPCs. A one-compartment model with linear elimination best described the pharmacokinetics of enoxaparin. Allometrically scaled fat-free mass with an estimated exponent of 0.712 (CI 0.66-0.76) was the most influential covariate on clearance while linear fat-free mass was selected as the covariate on volume. Simulations from the model showed that fat-free mass-based dosing could achieve the target anti-Xa activity at steady state in 77.5% and 78.2% of obese and normal-weight children, respectively, compared to 65.2% and 75.5% for standard total body weight-based dosing. CONCLUSIONS: A population PK model that describes the time course of anti-Xa activity of enoxaparin was developed in a paediatric population. Based on this model, a unified dosing regimen was proposed that will potentially improve the success rate of target attainment in overweight/obese patients without the need for patient body size categorisation. Therefore, prospective validation of the proposed approach is warranted.

Exploring Inductive Linearization for simulation and estimation with an application to the Michaelis-Menten model.

Nonlinear ordinary differential equations (ODEs) are common in pharmacokinetic-pharmacodynamic systems. Although their exact solutions cannot generally be determined via algebraic methods, their rapid and accurate solutions are desirable. Thus, numerical methods have a critical role. Inductive Linearization was proposed as a method to solve systems of nonlinear ODEs. It is an iterative approach that converts a nonlinear ODE into a linear time-varying (LTV) ODE, for which a range of standard integration techniques can then be used to solve (e.g., eigenvalue decomposition [EVD]). This study explores the properties of Inductive Linearization when coupled with EVD for integration of the LTV ODE and illustrates how the efficiency of the method can be improved. Improvements were based on three approaches, (1) incorporation of a convergence criterion for the iterative linearization process (for simulation and estimation), (2) creating more efficient step sizes for EVD (for simulation and estimation), and (3) updating the initial conditions of the Inductive Linearization (for estimation). The performance of these improvements were evaluated using single subject stochastic simulation-estimation with an application to a simple pharmacokinetic model with Michaelis-Menten elimination. The reference comparison was a standard non-stiff Runge-Kutta method with variable step size (ode45, MATLAB). Each of the approaches improved the speed of the Inductive Linearization technique without diminishing accuracy which, in this simple case, was faster than ode45 with comparable accuracy in the parameter estimates. The methods described here can easily be implemented in standard software programme such as R or MATLAB. Further work is needed to explore this technique for estimation in a population approach setting.

A minimal model to describe short-term haemodynamic changes of the cardiovascular system.

AIMS: Current pharmacokinetic-pharmacodynamic models describing the haemodynamic changes often do not include necessary feedback mechanisms. These models provide adequate description of current data but may fail to adequately extrapolate to additional scenarios. This study aims to develop a minimal model to describe the short-term changes of haemodynamics that can be used as the basis for model development by future researchers. METHODS: A minimal haemodynamic model was developed to describe the influence of drugs on blood pressure components. The model structure was defined based on known mechanisms and previously published models. The model was evaluated under 2 different simulation settings. The model parameters were calibrated to describe (without estimation) the haemodynamics of 2 antihypertensive drugs with data extracted from the literature. Structural identifiability analysis was done using various combinations of the observed variable. RESULTS: The proposed model structure includes mean arterial pressure, heart rate and stroke volume and is composed of 4 states described by differential equations. Model evaluation showed flexibility in describing the haemodynamics at different target perturbations. Overlay plots of model predictions and literature data showed a good description without data fitting. The structural identifiability analysis revealed all model parameters and initial conditions were identifiable only when heart rate, mean arterial pressure and cardiac output were measured together. CONCLUSIONS: A minimal model of the haemodynamic system was developed and evaluated. The model accounted for short-term haemodynamic feedback processes. We propose that this model can be used as the basis for future pharmacometric analyses of drugs acting on the haemodynamic system.

Evaluation of designs for renal drug studies based on the European Medicines Agency and Food and Drug Administration guidelines for drugs that are predominantly secreted.

AIMS: Dose adjustment for drugs eliminated by the kidneys generally assume a linear relationship between renal drug clearance (CLR ) and glomerular filtration rate (GFR). This assumption may not hold for drugs that undergo extensive tubular secretion where nonlinearity in drug handling is expected. The aim of this study is to determine if renal drug study designs recommended by the European Medicines Agency (EMA) and Food and Drug Administration (FDA) could distinguish linear from nonlinear renal drug handling. METHODS: In this simulation and estimation study, the study designs based on the EMA and FDA guidelines for Phase I renal drug studies were evaluated for their ability to discriminate a linear from a nonlinear relationship between CLR and GFR. The number of subjects for each simulated study ranged from 4 to 960. Power, relative standard error and bias were calculated. RESULTS: Study designs under the EMA and FDA guidelines required ≥8 and ≥48 subjects, respectively, to achieve ≥80% power to discriminate a linear from nonlinear relationship between CLR and GFR. The relative standard error of estimated parameters were 13-37 and 17-44% for the designs with 24 subjects under the EMA and FDA guidelines, respectively. The bias in parameter estimates under the EMA designs were not evident, however, they were biased (13-21%) under the FDA designs. CONCLUSION: The EMA design was found to require fewer subjects (n = 8) compared to the FDA (n = 48) to discriminate linear from nonlinear drug renal handling at ≥80% study power while both the designs perform poorly for the parameter precision.

Sulfate conjugation may be the key to hepatotoxicity in paracetamol overdose.

Paracetamol-induced hepatotoxicity is the leading cause of acute liver failure in many countries, including North America and the United Kingdom. Among the three dominant paracetamol metabolism pathways (i.e. glucuronidation, sulfation and oxidation), the importance of sulfation is often underestimated because of the general thinking that the sulfation pathway is saturated at therapeutic doses and ultimately accounts for a limited proportion of the fate of a paracetamol dose. We illustrate that insufficient sulfation leads to a shift in biotransformation of paracetamol to toxic oxidation pathways and patients with low sulfate reserves are at higher risk of paracetamol toxicity. Here, we propose that sulfation is of critical importance in understanding the risk of liver toxicity secondary to paracetamol overdose. Serum inorganic sulfate, a measurable substrate on the causal path of paracetamol-induced liver toxicity, should be considered a biomarker for potential toxicity as well as a target for treatment.

Does the intact nephron hypothesis provide a reasonable model for metformin dosing in chronic kidney disease?

This research explored the intact nephron hypothesis (INH) as a model for metformin dosing in patients with chronic kidney disease (CKD). The INH assumes that glomerular filtration rate (GFR) will account for all kidney drug handling even for drugs eliminated by tubular secretion like metformin. We conducted two studies: (1) a regression analysis to explore the relationship between metformin clearance and eGFR metrics, and (2) a joint population pharmacokinetic analysis to test the relationship between metformin renal clearance and gentamicin clearance. The relationship between metformin renal clearance and eGFR metrics and gentamicin clearance was found to be linear, suggesting that a proportional dose reduction based on GFR in patients with CKD is reasonable.

Reduction of quantitative systems pharmacology models using artificial neural networks.

Quantitative systems pharmacology models are often highly complex and not amenable to further simulation and/or estimation analyses. Model-order reduction can be used to derive a mechanistically sound yet simpler model of the desired input-output relationship. In this study, we explore the use of artificial neural networks for approximating an input-output relationship within highly dimensional systems models. We illustrate this approach using a model of blood coagulation. The model consists of two components linked together through a highly dimensional discontinuous interface, which creates a difficulty for model reduction techniques. The proposed approach enables the development of an efficient approximation to complex models with the desired level of accuracy. The technique is applicable to a wide variety of models and provides substantial speed boost for use of such models in simulation and control purposes.

A general model for cell death and biomarker release from injured tissues.

Cellular response to insults may result in the initiation of different cell death processes. For many cases the cell death process will result in an acute release of cellular material that in some circumstances provides valuable information about the process (i.e. may represent a biomarker). The characteristics of the biomarker release is often informative and plays critical roles in clinical practice and toxicology research. The aim of this study is to develop a general, semi-mechanistic model to describe cell turnover and biomarker release by injured tissue that can be used for estimation in pharmacokinetic and (toxicokinetic)-pharmacodynamic studies. The model included three components: (1) natural tissue turnover, (2) biomarker release from cell death and its movement from the cell through the tissue into the blood, (3) different target insult mechanisms of cell death. We applied the general model to biomarker release profiles for four different cell insult causes. Our model simulations showed good agreements with reported data under both delayed release and rapid release cases. Additionally, we illustrate the use of the model to provide different biomarker profiles. We also provided details on interpreting parameters and their values for other researchers to customize its use. In conclusion, our general model provides a basic structure to study the kinetic behaviour of biomarker release and disposition after cellular insult.

Lack of effect of tart cherry concentrate dose on serum urate in people with gout.

OBJECTIVES: Cherry concentrate has been suggested to reduce serum urate (SU) and gout flares. The aims of this study were to determine the magnitude of the effect of tart cherry concentrate on SU in people with gout, the most effective dose of tart cherry concentrate for lowering SU, and adverse effects. METHODS: Fifty people with gout and SU > 0.36 mmol/l were recruited. Half were on allopurinol and half were on no urate-lowering therapy. Participants were randomized to receive tart cherry juice concentrate: placebo, 7.5 ml, 15 ml, 22.5 ml or 30 ml twice daily for 28 days. Blood samples were taken at baseline, then at 1, 3 and 5 h post cherry and then on days 1, 3, 7, 14, 21 and 28. The area under the curve for SU was calculated over the 28-day study period. RESULTS: Cherry concentrate dose had no significant effect on reduction in SU area under the curve, urine urate excretion, change in urinary anthocyanin between day 0 and day 28, or frequency of gout flares over the 28-day study period (P = 0.76). There were 24 reported adverse events, with only one (hyperglycaemia) considered possibly to be related to cherry concentrate. Allopurinol use did not modify the effect of cherry on SU or urine urate excretion. CONCLUSION: Tart cherry concentrate had no effect on SU or urine urate excretion. If there is an effect of cherry concentrate on gout flares over a longer time period, it is not likely to be mediated by reduction in SU. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR), https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=368887, ANZCTR 12615000741583).

The pharmacokinetics of meropenem and piperacillin-tazobactam during sustained low efficiency haemodiafiltration (SLED-HDF).

OBJECTIVE: We analysed the pharmacokinetics of meropenem and piperacillin-tazobactam in patients undergoing a standardised session of sustained low efficiency haemodiafiltration (SLED-HDF) to inform the dosing of these drugs in an acute setting. PARTICIPANTS: Six stable patients with end-stage kidney disease. METHODS: An open-label pilot pharmacokinetic study of meropenem and piperacillin-tazobactam. SLED-HDF was undertaken for 4 h. Plasma drug concentrations were measured pre- and post-filter and in the effluent at multiple time points. The pharmacokinetic data was analysed using non-compartmental methods. The fraction of time that individual plasma concentration profiles were predicted to remain above the MIC break-points for commonly isolated gram-negative pathogens during a prolonged SLED-HDF session was assessed using two targets; fT > MIC (fraction of time above the MIC) and the more aggressive fT > 4 × MIC (fraction of time above 4 × MIC). RESULTS: Meropenem total and SLED-HDF clearance ranged from 141 to 180 mL/min and 126-205 mL/min, respectively. Piperacillin total and SLED-HDF clearance values ranged from 131 to 252 mL/min and 135-162 mL/min, respectively. Our results suggest that prolonged SLED-HDF (12 h) will only maintain a sufficient meropenem and piperacillin-tazobactam plasma concentration to achieve a target of fT > MIC for gram-negative pathogens (MIC 2 mg/L-meropenem, 8 mg/L-piperacillin-tazobactam) for less than 40% of the time. Plasma concentrations would be inadequate to achieve the more aggressive target of 100 % fT > 4xMIC target recommended for critically unwell patients. CONCLUSIONS: The pharmacokinetic data obtained from this pilot study demonstrate significant quantities of meropenem and piperacillin are removed during a SLED-HDF session. This may lead to subtherapeutic concentrations of piperacillin and meropenem over the duration of HDF session. TRIAL REGISTRATION: Australasian Clinical Trials Registry Network (ACTRN12616000078459).

The intact nephron hypothesis as a model for renal drug handling.

PURPOSE: The intact nephron hypothesis (INH) states that impaired renal function results from a reduction in the number of complete (intact) nephrons. Under this model, renal drug clearance is assumed to be a linear function of glomerular filtration while tubular handling is ignored. The aims of this study were to systematically review published studies designed to test the INH and to assess the strength of the study designs used. METHODS: A systematic literature search was conducted in MEDLINE, EMBASE and Google Scholar. Studies specifically designed to understand the relationship between glomerular and tubular function across different levels of renal function were included. Studies that found a linear relationship between GFR and tubular clearance were deemed to support the INH while studies that found a non-linear relationship did not support the INH. Study design was accessed using a bespoke strength of evidence score. RESULTS: Thirty studies met the criteria for inclusion. Of these, 24 did not support the INH. Studies that did not support the INH used methods for measuring tubular clearance that were more robust and included subjects with a wider range of GFR values than studies that supported the INH. DISCUSSION: Our results suggest that the INH may not be a suitable general model for renal drug handling, particularly for drugs that are eliminated by tubular mechanisms. Further studies to assess the clinical importance of a non-linear relationship between drug clearance and GFR are warranted.

Automated proper lumping for simplification of linear physiologically based pharmacokinetic systems.

Physiologically based pharmacokinetic (PBPK) models are an important type of systems model used commonly in drug development before commencement of first-in-human studies. Due to structural complexity, these models are not easily utilised for future data-driven population pharmacokinetic (PK) analyses that require simpler models. In the current study we aimed to explore and automate methods of simplifying PBPK models using a proper lumping technique. A linear 17-state PBPK model for fentanyl was identified from the literature. Four methods were developed to search the optimal lumped model, including full enumeration (the reference method), non-adaptive random search (NARS), scree plot plus NARS, and simulated annealing (SA). For exploratory purposes, it was required that the total area under the fentanyl arterial concentration-time curve (AUC) between the lumped and original models differ by 0.002% at maximum. In full enumeration, a 4-state lumped model satisfying the exploratory criterion was found. In NARS, a lumped model with the same number of lumped states was found, requiring a large number of random samples. The scree plot provided a starting lumped model to NARS and the search completed within a short time. In SA, a 4-state lumped model was consistently delivered. In simplify an existing linear fentanyl PBPK model, SA was found to be robust and the most efficient and may be suitable for general application to other larger-scale linear systems. Ultimately, simplified PBPK systems with fundamental mechanisms may be readily used for data-driven PK analyses.

Development of a nonlinear hierarchical model to describe the disposition of deuterium in mother-infant pairs to assess exclusive breastfeeding practice.

The World Health Organization recommends exclusive breastfeeding (EBF) for the first 6 months after birth. The deuterium oxide dose-to-the-mother (DTM) technique is used to distinguish EBF based on a cut-off (< 25 g/day) of water intake from sources other than breastmilk. This value is based on a theoretical threshold and has not been verified in field studies. The aim of this study was to estimate the water intake cut-off value that can be used to define EBF practice. One hundred and twenty-one healthy infants, aged 2.5-5.5 months who were deemed to be EBF were recruited. After administration of deuterium to the mothers, saliva was sampled from mother and infant pairs over a 14-day period. Validation of infant feeding practices was conducted via home observation over six non-consecutive days with caregiver recall. A fully Bayesian framework using a gradient-based Markov chain Monte Carlo approach implemented in Stan was used to estimate the cut-off of non-milk water intake of EBF infants. From the original data set, 113 infants were determined to be EBF and provided 1500 paired mother-infant observations. The deuterium saliva concentrations were best described by two linked 1-compartment models (mother and infant), with body weight as a covariate on the mother's volume of distribution and infant's body weight on infant's water clearance rate. The cut-off value was based on the 90th percentile of the posterior distribution of non-milk water intake and was 86.6 g/day. This cut-off value can be used in future field studies in other geographic regions to determine exclusivity of breast feeding practices in order to determine their potential public health needs.