Skin pharmacokinetics of miltefosine in the treatment of post-kala-azar dermal leishmaniasis in South Asia.

INTRODUCTION: Post-kala-azar dermal leishmaniasis (PKDL) arises as a dermal complication following a visceral leishmaniasis (VL) infection. Current treatment options for PKDL are unsatisfactory, and there is a knowledge gap regarding the distribution of antileishmanial compounds within human skin. The present study investigated the skin distribution of miltefosine in PKDL patients, with the aim to improve the understanding of the pharmacokinetics at the skin target site in PKDL. METHODS: Fifty-two PKDL patients underwent treatment with liposomal amphotericin B (20 mg/kg) plus miltefosine (allometric dosing) for 21 days. Plasma concentrations of miltefosine were measured on study days 8, 15, 22 and 30, while a punch skin biopsy was taken on day 22. A physiologically based pharmacokinetic (PBPK) model was developed to evaluate the distribution of miltefosine into the skin. RESULTS: Following the allometric weight-based dosing regimen, median miltefosine concentrations on day 22 were 43.73 µg/g (IQR: 21.94-60.65 µg/g) in skin and 33.29 µg/mL (IQR: 25.9-42.58 µg/mL) in plasma. The median individual concentration ratio of skin to plasma was 1.19 (IQR: 0.79-1.9). In 87% (45/52) of patients, skin exposure was above the suggested EC90 PK target of 10.6 mg/L associated with in vitro susceptibility. Simulations indicated that the residence time of miltefosine in the skin would be more than 2-fold longer than in plasma, estimated by a mean residence time of 604 versus 266 hours, respectively. CONCLUSION: This study provides the first accurate measurements of miltefosine penetration into the skin, demonstrating substantial exposure and prolonged retention of miltefosine within the skin. These findings support the use of miltefosine in cutaneous manifestations of leishmaniasis. In combination with parasitological and clinical data, these results are critical for the future optimization of combination therapies with miltefosine in the treatment of PKDL.

Instructor-Blinded Study of Pharmacy Student Learning When a Flipped Online Classroom Was Implemented during the COVID-19 Pandemic.

A multi-cohort instructor-blinded research study was completed at the School of Pharmacy, University of Waterloo, to test the impact on study learning endpoints when an online flipped classroom teaching style was implemented during the COVID-19 pandemic. The learning endpoints were gain in factual knowledge and gain in self-confidence in clinical skills (assessing a patient, developing a care plan for a minor ailment, and implementing the care plan by counselling patients on the condition). Gain in factual knowledge was assessed with an instructor-blinded multiple-choice test administered before and after the course. Gain in self-confidence in clinical skills was assessed with a survey asking students to report their self-confidence in completing 10 clinical tasks on a 5-item Likert scale. Students being taught in an online flipped classroom cohort during the COVID-19 pandemic trended toward having a higher gain in self-confidence throughout the course but a lower gain in factual knowledge when compared with a traditional classroom cohort in the previous year.

Model-Based Assessment of the Contribution of Monocytes and Macrophages to the Pharmacokinetics of Monoclonal Antibodies.

PURPOSE: We have hypothesized that a high concentration of circulating monocytes and macrophages may contribute to the fast weight-based clearance of monoclonal antibodies (mAbs) in young children. Exploring this hypothesis, this work uses modeling to clarify the role of monocytes and macrophages in the elimination of mAbs. METHODS: Leveraging pre-clinical data from mice, a minimal physiologically-based pharmacokinetic model was developed to characterize mAb uptake and FcRn-mediated recycling in circulating monocytes, macrophages, and endothelial cells. The model characterized IgG disposition in complex scenarios of site-specific FcRn deletion and variable endogenous IgG levels. Evaluation was performed for predicting IgG disposition with co-administration of high dose IVIG. A one-at-a-time sensitivity analysis quantified the role of relevant cellular parameters on IgG elimination in various scenarios. RESULTS: The plasma AUC of mAbs was highly sensitive to endothelial cell parameters, but had near-nil sensitivity to monocyte and macrophage parameters, even in scenarios with 90% loss of FcRn expression/activity. In mice with normal FcRn expression, simulations suggest that less than 2% of an IV dose is eliminated in macrophages, while endothelial cells are predicted to dominate mAb elimination. CONCLUSIONS: The model suggests that the role of monocytes and macrophages in IgG homeostasis includes extensive uptake and highly efficient FcRn-mediated protection, but not appreciable degradation when FcRn is present. Therefore, it is very unlikely that a high concentration of circulating monocytes can contribute to explaining the fast weight-based clearance of mAbs in very young children, even if FcRn expression/activity was 90% lower in children than in adults.

Pediatric Dose Selection for Therapeutic Proteins.

In selecting optimal dosing regimens in support of the clinical use of monoclonal antibodies and other therapeutic proteins in pediatric indications, the unique pharmacokinetic properties of this class of biologics, as well as the underlying physiologic and pathophysiologic processes and their modulation by childhood growth and development, needs to be appreciated. During drug development, first-in-pediatric dose selection is a capstone event in the pediatric investigation plan that relies heavily on extrapolation of pharmacokinetic and pharmacodynamic data from adult to pediatric populations. It is facilitated by combinations of pharmacometric approaches, including allometry, physiologically based pharmacokinetic modeling, and population pharmacokinetic analyses, although data on reliability and qualification of some of these tools in the context of therapeutic proteins are still limited but emerging. Presented data suggest nonlinear relationships between body weight and both clearance and volume of distribution for therapeutic proteins in pediatric populations, with allometric exponents of 0.75 and 0.8, respectively. For newborns and infants (<1 year), even higher nonlinearity seems to occur. Translation of the quantitative characterization of the pediatric pharmacokinetics of therapeutic proteins into dosing regimens for the drug label requires compromising between precision dosing and clinical practicability, with tiered dosing algorithms based on size or age strata being the currently most frequently applied methodology.

A Physiological Approach to Pharmacokinetics in Chronic Kidney Disease.

The conventional approach to approximating the pharmacokinetics of drugs in patients with chronic kidney disease (CKD) only accounts for changes in the estimated glomerular filtration rate. However, CKD is a systemic and multifaceted disease that alters many body systems. Therefore, the objective of this exercise was to develop and evaluate a whole-body mechanistic approach to predicting pharmacokinetics in patients with CKD. Physiologically based pharmacokinetic models were developed in PK-Sim v8.0 (www.open-systems-pharmacology.org) to mechanistically represent the disposition of 7 compounds in healthy human adults. The 7 compounds selected were eliminated by glomerular filtration and active tubular secretion by the organic cation transport system to varying degrees. After a literature search, the healthy adult models were adapted to patients with CKD by numerically accounting for changes in glomerular filtration rate, kidney volume, renal perfusion, hematocrit, plasma protein concentrations, and gastrointestinal transit. Literature-informed interindividual variability was applied to the physiological parameters to facilitate a population approach. Model performance in CKD was evaluated against pharmacokinetic data from 8 clinical trials in the literature. Overall, integration of the CKD parameterization enabled exposure predictions that were within 1.5-fold error across all compounds and patients with varying stages of renal impairment. Notable improvement was observed over the conventional approach to scaling exposure, which failed in all but 1 scenario in patients with advanced CKD. Further research is required to qualify its use for first-in-CKD dose selection and clinical trial planning for a wider selection of renally eliminated compounds, including those subject to anion transport.

Quantifying breast milk intake by term and preterm infants for input into paediatric physiologically based pharmacokinetic models.

Despite the many benefits of breast milk, mothers taking medication are often uncertain about the risks of drug exposure to their infants and decide not to breastfeed. Physiologically based pharmacokinetic models can contribute to drug-in-milk safety assessments by predicting the infant exposure and subsequently, risk for toxic effects that would result from continuous breastfeeding. This review aimed to quantify breast milk intake feeding parameters in term and preterm infants using literature data for input into paediatric physiologically based pharmacokinetic models designed for drug-in-milk risk assessment. Ovid MEDLINE and Embase were searched up to July 2, 2019. Key study reference lists and grey literature were reviewed. Title, abstract and full text were screened in nonduplicate. Daily weight-normalized human milk intake (WHMI) and feeding frequency by age were extracted. The review process retrieved 52 studies. A nonlinear regression equation was constructed to describe the WHMI of exclusively breastfed term infants from birth to 1 year of age. In all cases, preterm infants fed with similar feeding parameters to term infants on a weight-normalized basis. Maximum WHMI was 152.6 ml/kg/day at 19.7 days, and weighted mean feeding frequency was 7.7 feeds/day. Existing methods for approximating breast milk intake were refined by using a comprehensive set of literature data to describe WHMI and feeding frequency. Milk feeding parameters were quantified for preterm infants, a vulnerable population at risk for high drug exposure and toxic effects. A high-risk period of exposure at 2-4 weeks of age was identified and can inform future drug-in-milk risk assessments.

Integration of Ontogeny Into a Physiologically Based Pharmacokinetic Model for Monoclonal Antibodies in Premature Infants.

An understanding of pediatric pharmacokinetics (PK) is essential for first-in-pediatric dose selection and clinical trial design. At present, there is no reliable way to scale the PK of monoclonal antibodies and immunoglobulin G drug products from adults to young children or to premature infants-a vulnerable population with a rapidly growing drug development pipeline. In this work, pediatric physiologically based PK models are constructed in PK-Sim and Mobi to explore the PK of pagibaximab, palivizumab, MEDI8897, and intravenous immunoglobulin in preterm infants. In addition to considering ontogeny in pediatric organ volumes, organ composition, blood flow rates, and hematocrit, advanced ontogeny is applied for 3 key parameters: capillary surface area, hematopoietic cell concentration, and lymph flow rate. The role and importance of each parameter for determining pediatric clearance (CL) and volume of distribution at steady state (VSS ) are quantitatively assessed with a local sensitivity analysis. In addition, the uncertainty around parameters with limited information in pediatrics is addressed (eg, free neonatal Fc receptor concentration). The full ontogeny parameterization yields pediatric PK predictions that are within 1.5-fold prediction error >90% of the time for preterm infants, with an absolute average fold error of 1.05. This result suggests that many of the key factors related to ontogeny are appropriately addressed. Overall, this study makes a first step toward developing a platform pediatric physiologically based PK model for monoclonal antibodies and immunoglobulin G drug products by solidifying existing parameterizations, integrating new concepts, and drawing attention to unmet needs for physiologic knowledge in children.

Physiologically-Based Pharmacokinetic Modeling vs. Allometric Scaling for the Prediction of Infliximab Pharmacokinetics in Pediatric Patients.

The comparative performances of physiologically-based pharmacokinetic (PBPK) modeling and allometric scaling for predicting the pharmacokinetics (PKs) of large molecules in pediatrics are unknown. Therefore, both methods were evaluated for accuracy in translating knowledge of infliximab PKs from adults to children. PBPK modeling was performed using the base model for large molecules in PK-Sim version 7.4 with modifications in Mobi. Eight population PK models from literature were reconstructed and scaled by allometry to pediatrics. Evaluation data included seven pediatric studies (~4-18 years). Both methods performed comparably with 66.7% and 68.6% of model-predicted concentrations falling within twofold of the observed concentrations for PBPK modeling and allometry, respectively. Considerable variability was noted among the allometric models. Therefore, pediatric clinical trial planning would benefit from using approaches that require predictions depending on the specific question i.e., PBPK modeling and allometry.

Biodistribution and Physiologically-Based Pharmacokinetic Modeling of Gold Nanoparticles in Mice with Interspecies Extrapolation.

Gold nanoparticles (AuNPs) are a focus of growing medical research applications due to their unique chemical, electrical and optical properties. Because of uncertain toxicity, "green" synthesis methods are emerging, using plant extracts to improve biological and environmental compatibility. Here we explore the biodistribution of green AuNPs in mice and prepare a physiologically-based pharmacokinetic (PBPK) model to guide interspecies extrapolation. Monodisperse AuNPs were synthesized and capped with epigallocatechin gallate (EGCG) and curcumin. 64 CD-1 mice received the AuNPs by intraperitoneal injection. To assess biodistribution, groups of six mice were sacrificed at 1, 7, 14, 28 and 56 days, and their organs were analyzed for gold content using inductively coupled plasma mass spectrometry (ICP-MS). A physiologically-based pharmacokinetic (PBPK) model was developed to describe the biodistribution data in mice. To assess the potential for interspecies extrapolation, organism-specific parameters in the model were adapted to represent rats, and the rat PBPK model was subsequently evaluated with PK data for citrate-capped AuNPs from literature. The liver and spleen displayed strong uptake, and the PBPK model suggested that extravasation and phagocytosis were key drivers. Organ predictions following interspecies extrapolation were successful for rats receiving citrate-capped AuNPs. This work lays the foundation for the pre-clinical extrapolation of the pharmacokinetics of AuNPs from mice to larger species.

Predicting Escitalopram Exposure to Breastfeeding Infants: Integrating Analytical and In Silico Techniques.

BACKGROUND: Escitalopram is used for post-partum depression; however, there are limited pharmacokinetic data of escitalopram in milk and plasma of infants breastfed by women taking the drug. OBJECTIVE: The objective of this study was to apply physiologically-based pharmacokinetic (PBPK) modelling to predict infant drug exposure (plasma area under the curve from time zero to infinity [AUC∞]) based on drug monitoring data of escitalopram in breast milk. METHODS: Using a newly developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method, we quantified escitalopram concentrations in milk samples of 18 breastfeeding women with escitalopram therapy at steady state, collected at three to five time points. The escitalopram concentrations in breast milk were used with infant feeding parameters from the literature to simulate infant daily dose. We used PK-Sim® to develop an adult PBPK model for escitalopram and extrapolated it to a population of 1600 infants up to 12 months of age. An integration of the simulated infant daily dose and the virtual infants with variable physiological-pharmacological parameters was used to predict drug exposure (plasma AUC∞) distribution in the population of infants breastfed by women receiving escitalopram 20 mg/day. RESULTS: Escitalopram concentrations in milk were 50 ± 17 ng/mL (mean ± standard deviation). The simulated infant plasma AUC∞ following escitalopram exposure through breast milk was low, with a median of 1.7% (range 0.5-5.9%) of the corresponding maternal plasma AUC∞, indicating no substantial exposure. CONCLUSIONS: Infant exposure levels to escitalopram in breast milk are low. A PBPK modeling approach can be used to translate data on drug monitoring in milk into a population distribution of infant plasma levels for drug safety assessment.

Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability.

In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 ([Formula: see text]), the convective flow rate of mAb through vascular pores ([Formula: see text]), the endocytic transport rate of mAb through vascular endothelium ([Formula: see text]), the degradation rate of mAb-HER2 complexes ([Formula: see text]) and the concentration of shed HER2 extracellular domain in circulation ([Formula: see text]). [Formula: see text] was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. [Formula: see text] was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability.