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The blood–brain barrier (BBB) expresses a high abundance of transporters, particularly P‐glycoprotein (P‐gp), that regulate endogenous and exogenous molecule uptake and removal of waste. This review discusses key drug metabolism and pharmacokinetic considerations for the efflux transporter P‐gp at the BBB in drug discovery and development. We highlight the differences in P‐gp expression and protein levels across species but the limited observations of species‐specific substrates. Given the impact of age and disease on BBB biology, we summarise the modulation of P‐gp for several neurological disorders and ageing and exemplify several disease‐specific hurdles or opportunities for drug exposure in the brain. Furthermore, the review includes observations of CNS‐related drug‐drug interactions due to the inhibition or induction of P‐gp at the BBB in animal studies and humans and the need for continued evaluation especially for compounds with a narrow therapeutic window. This review focusses primarily on small molecules but also considers the impact of new chemical entities, particularly beyond Ro5 molecules and their potential to be recognised as P‐gp substrates as well as advanced drug delivery systems which offer an alternative approach to achieve and sustain central nervous system exposure. [ABSTRACT FROM AUTHOR]

Aims: Develop a population pharmacokinetic model describing propofol pharmacokinetics in (pre)term neonates and infants, that can be used for precision dosing (e.g. during target‐controlled infusion) of propofol in this population. Methods: A nonlinear mixed effects pharmacokinetic analysis (Monolix 2018R2) was performed, based on a pooled study population in 107 (pre)term neonates and infants. Results: In total, 836 blood samples were collected from 66 (pre)term neonates and 41 infants originating from 3 studies. Body weight (BW) of the pooled study population was 3.050 (0.580–11.440) kg, postmenstrual age (PMA) was 36.56 (27.00–43.00) weeks and postnatal age (PNA) was 1.14 (0–104.00) weeks (median and min‐max range). A 3‐compartment structural model was identified and the effect of BW was modelled using fixed allometric exponents. Elimination clearance maturation was modelled accounting for the maturational effect on elimination clearance until birth (by gestational age [GA]) and postpartum (by PNA and GA). The extrapolated adult (70 kg) population propofol elimination clearance (1.64 L min−1, estimated relative standard error = 6.02%) is in line with estimates from previous population pharmacokinetic studies. Empirical scaling of BW on the central distribution volume in function of PNA improved the model fit. Conclusions: It is recommended to describe elimination clearance maturation by GA and PNA instead of PMA on top of size effects when analyzing propofol pharmacokinetics in populations including preterm neonates. Changes in body composition in addition to weight changes or other physio‐anatomical changes may explain the changes in central distribution volume. The developed model may serve as a prior for propofol dose finding and target‐controlled infusion in (preterm) neonates. [ABSTRACT FROM AUTHOR]

On April 24, 2019, a symposium on Pediatric Pharmacokinetics and Dose Predictions was held as a satellite meeting to the 10th Juvenile Toxicity Symposium. This symposium brought together scientists from academia, industry, and clinical research organizations with the aim to update each other on the current knowledge on pediatric drug development. Through more knowledge on specific ontogeny profiles of drug metabolism and transporter proteins, integrated into physiologically‐based pharmacokinetic (PBPK) models, we have gained a more integrated understanding of age‐related differences in pharmacokinetics (PKs), Relevant examples were presented during the meeting. PBPK may be considered the gold standard for pediatric PK prediction, but still it is important to know that simpler methods, such as allometry, allometry combined with maturation function, functions based on the elimination pathway, or linear models, also perform well, depending on the age range or the mechanisms involved. Knowledge from different methods and information sources should be combined (e.g., microdosing can reveal early read‐out of age‐related differences in exposure), and such results can be a value to verify models. To further establish best practices for dose setting in pediatrics, more in vitro and in vivo research is needed on aspects such as age‐related changes in the exposure‐response relationship and the impact of disease on PK. New information coupled with the refining of model‐based drug development approaches will allow faster targeting of intended age groups and allow more efficient design of pediatric clinical trials. [ABSTRACT FROM AUTHOR]

What is known and objective: Sampling volumes of blood from neonates is necessarily limited. However, most of the published propofol analysis assays require a relatively large blood sample volume (typically ≥0.5 mL). Therefore, the aim of the present study was to develop and validate a sensitive method requiring a smaller sample volume (0.2 mL) to fulfill clinically relevant research requirements. Methods: Following simple protein precipitation and centrifugation, the supernatant was injected into the HPLC‐fluorescence system and separated with a reverse phase column. Propofol and the internal standard (thymol) were detected and quantified using fluorescence at excitation and emission wavelengths of 270 nm and 310 nm, respectively. The method was validated with reference to the Food and Drug Administration (FDA) guidance for industry. Accuracy (CV, %) and precision (RSD, %) were evaluated at three quality control concentration levels (0.05, 0.5 and 5 µg/mL). Results and discussion: Calibration curves were linear in the range of 0.005‐20 µg/mL. Intra‐ and interday accuracy (−4.4%‐13.6%) and precision (0.2%‐5.8%) for propofol were below 15%. The calculated LOD (limit of detection) and LLOQ (lower limit of quantification) were 0.0021 µg/mL and 0.0069 µg/mL, respectively. Propofol samples were stable for 4 months at −20°C after the sample preparation. This method was applied for analyzing blood samples from 41 neonates that received propofol, as part of a dose‐finding study. The measured median (range) concentration was 0.14 (0.03‐1.11) µg/mL, which was in the range of the calibration curve. The calculated median (range) propofol half‐life of the gamma elimination phase was 10.4 (4.7‐26.7) hours. What is new and conclusion: A minimal volume (0.2 mL) of blood from neonates is required for the determination of propofol with this method. The method can be used to support the quantification of propofol drug concentrations for pharmacokinetic studies in the neonatal population. [ABSTRACT FROM AUTHOR]

Introduction: The sandwich-cultured hepatocyte (SCH) model has become an invaluable in vitro tool for studying hepatic drug transport, metabolism, biliary excretion and toxicity. The relevant expression of many hepatocyte-specific functions together with the in vivo-like morphology favor SCHs over other preclinical models for evaluating hepatobiliary drug disposition and drug-induced hepatotoxicity., Areas Covered: In this review, the authors highlight recommended procedures required for reproducibly culturing hepatocytes in sandwich configuration. It also provides an overview of the SCH model characteristics as a function of culture time. Lastly, the article presents a summary of the most prominent applications of the SCH model, including hepatic drug clearance prediction, drug-drug interaction potential and drug-induced hepatotoxicity., Expert Opinion: When human (cryopreserved) hepatocytes are used to establish sandwich cultures, the model appears particularly valuable to quantitatively investigate clinically relevant mechanisms related to in vivo hepatobiliary drug disposition and hepatotoxicity. Nonetheless, the SCH model would largely benefit from better insight into the fundamental cell signaling mechanisms that are critical for long-term in vitro maintenance of the hepatocytic phenotype. Studies systematically exploring improved cell culture conditions (e.g., co-cultures or extracellular matrix modifications), as well as in vitro work identifying key transcription factors involved in hepatocyte differentiation are currently emerging.