A comprehensive understanding of coral reproduction and development is needed because corals are threatened in many ways by human activity. Major threats include the loss of their photosynthetic symbionts (Symbiodinium) caused by rising temperatures (bleaching), reduced ability to calcify caused by ocean acidification, increased storm severity associated with global climate change and an increase in predators caused by runoff from human agricultural activity. In spite of these threats, detailed descriptions of embryonic development are not available for many coral species. The current consensus is that there are two major groups of stony corals, the "complex" and the "robust". In this paper we describe the embryonic development of four "complex" species, Pseudosiderastrea tayamai, Galaxea fascicularis, Montipora hispida, and Pavona Decussata, and seven "robust" species, Oulastrea crispata, Platygyra contorta, Favites abdita, Echinophyllia aspera, Goniastrea favulus, Dipsastraea speciosa (previously Favia speciosa), and Phymastrea valenciennesi (previously Montastrea valenciennesi). Data from both histologically sectioned embryos and whole mounts are presented. One apparent difference between these two major groups is that before gastrulation the cells of the complex corals thus far described (mainly Acropora species) spread and flatten to produce the so-called prawn chip, which lacks a blastocoel. Our present broad survey of robust and complex corals reveals that prawn chip formation is not a synapomorphy of complex corals, as Pavona Decussata does not form a prawn chip and has a well-developed blastocoel. Although prawn chip formation cannot be used to separate the two clades, none of the robust corals which we surveyed has such a stage. Many robust coral embryos pass through two periods of invagination, separated by a return to a spherical shape. However, only the second of these periods is associated with endoderm formation. We have therefore termed the first invagination a pseudo-blastopore.

Physiologically based pharmacokinetic (PBPK) models are increasingly used to support pediatric dose selection for small molecule drugs. In contrast, only a few pediatric PBPK models for therapeutic antibodies have been published recently, and the knowledge on the maturation of the processes relevant for antibody pharmacokinetics (PK) is limited compared to small molecules. The aim of this study was, thus, to evaluate predictions from antibody PBPK models for children which were scaled from PBPK models for adults in order to identify respective knowledge gaps. For this, we used the generic PBPK model implemented in PK-Sim without further modifications. Focusing on general clearance and distribution mechanisms, we selected palivizumab and bevacizumab as examples for this evaluation since they show simple, linear PK which is not governed by drug-specific target mediated disposition at usual therapeutic dosages, and their PK has been studied in pediatric populations after intravenous application. The evaluation showed that the PK of palivizumab was overall reasonably well predicted, while the clearance for bevacizumab seems to be underestimated. Without implementing additional ontogeny for antibody PKspecific processes into the PBPK model, bodyweight normalized clearance increases only moderately in young children compared to adults. If growth during aging at the time of the simulation was considered, the apparent clearance is approximately 20% higher compared to simulations for which growth was not considered for newborns due to the long half-life of antibodies. To fully understand the differences and similarities in the PK of antibodies between adults and children, further research is needed. By integrating available information and data, PBPK modeling can contribute to reveal the relevance of involved processes as well as to generate and test hypothesis.

Intraperitoneal vancomycin is the first-line therapy in the management of peritoneal dialysis (PD)-related peritonitis. However, due to the paucity of data, vancomycin dosing for peritonitis in patients on automated peritoneal dialysis (APD) is empiric and based on clinical experience rather than evidence. Studies in continuous ambulatory peritoneal dialysis (CAPD) patients have been used to provide guidelines for dosing and are often extrapolated for APD use, but it is unclear whether this is appropriate. This review summarizes the available pharmacokinetic data used to inform optimal dosing in patients on CAPD or APD. The determinants of vancomycin disposition and pharmacodynamic effects are critically summarized, knowledge gaps explored, and a vancomycin dosing algorithm in PD patients is proposed.

Immuno‐oncology (IO) is a fast‐expanding field due to recent success using IO therapies in treating cancer. As IO therapies do not directly kill tumor cells but rather act upon the patients’ own immune cells either systemically or in the tumor microenvironment, new and innovative approaches are required to inform IO therapy research and development. Quantitative systems pharmacology (QSP) modeling describes the biological mechanisms of disease and the mode of action of drugs with mathematical equations, which has significant potential to address the big challenges in the IO field, from identifying patient populations that respond to different therapies to guiding the selection, dosing, and scheduling of combination therapy. To assess the perspectives of the community on the impact of QSP modeling in IO drug development and to understand current applications and challenges, the IO QSP working group—under the QSP Special Interest Group (SIG) of the International Society of Pharmacometrics (ISoP)—conducted a survey among QSP modelers, non‐QSP modelers, and non‐modeling IO program stakeholders. The survey results are presented here with discussions on how to address some of the findings. One of the findings is the differences in perception among these groups. To help bridge this perception gap, we present several case studies demonstrating the impact of QSP modeling in IO and suggest actions that can be taken in the future to increase the real and perceived impact of QSP modeling in IO drug research and development.

Availability of lower-dose oseltamivir capsules, an increased pharmacokinetic database, and a desire to align drug exposure across the spectrum of renal function prompted reassessment of oral dosing in patients with renal impairment. The data set comprised 128 subjects (71 with varying degrees of renal impairment) from 8 studies, which included single and multiple doses of 20-1000 mg. Pharmacokinetic profiles of oseltamivir phosphate (OP) and oseltamivir carboxylate (OC) were modeled simultaneously in NONMEM. Exposure metrics of OP and OC (AUC48  h , Cmax , Cmin ) after administration of various dosing regimens were simulated for renal impairment subgroups and compared with exposures in patients with normal renal function receiving approved regimens. For influenza treatment, 30 mg once-daily and twice-daily regimens were selected for severe and moderate impairment, respectively. These regimens provided OC exposures similar or above those of the approved 75-mg twice-daily treatment regimen in subjects with normal renal function. For influenza prophylaxis, 30 mg once every other day and once-daily regimens were selected for severe and moderate impairment, respectively. No dosing adjustments were required for mild impairment. This analysis supported revised labeling in the United States and Europe for oral oseltamivir dosing in patients with moderate and severe renal impairment.

It is unclear if the pharmacokinetics of vancomycin are the same during automated peritoneal dialysis (APD), where cycler exchanges may affect the systemic, peritoneal, and urinary disposition of drug. We conducted a prospective pharmacokinetic study evaluating the pharmacokinetics of vancomycin in plasma, dialysis fluid, and urine in peritonitis-negative patients on APD. Patients underwent four drug-free exchanges with 1.5% or 2.5% dextrose following the initial dwell period. Plasma, dialysis fluid, and urine was collected over the course of 7 days for pharmacokinetic analysis. Four patients completed the study with no adverse events. Following a median (range) dwell of 14.6 (14.2-17.6 h), the mean (±SD) observed maximum plasma concentration was 28.7 ± 4.9 mg/L with a mean bioavailability of 98.5 ± 1.4% prior to starting the cycler. The overall mean total plasma clearance estimated from study start to completion was 7.6 ± 1.2 ml/min. Mean total clearance during the dialytic exchange was 13.6 ± 4.9 ml/min. In patients with residual renal function, the mean vancomycin renal clearance was 3.1 ± 1.5 ml/min, representing 21.4%-58.9% of the overall total plasma clearance during the study period. Despite the small sample size, this pilot study suggests that the dwell time has important implications for systemic vancomycin exposure, time to therapeutic plasma concentration, and dosing. Dose is driven by dwell time, whereas the cycler determines the dosing interval. Rapid exchanges from APD will determine the frequency of dosing rather than the adequacy of absorption when vancomycin is given in the peritoneum. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?Vancomycin dosing in patients with peritonitis during automated peritoneal dialysis (APD) is empiric and extrapolated from studies in patients on continuous ambulatory peritoneal dialysis (CAPD). Extrapolation of pharmacokinetic data from CAPD to APD may result in substantial under-or overdosing due to rapid exchanges and longer dwell times. The impact of residual renal function on vancomycin pharmacokinetics is also unknown.

Costly and lengthy clinical trials hinder the development of safe and effective treatments for postmenopausal osteoporosis. To reduce the expense associated with these trials, we established a mechanistic disease‐drug trial model for postmenopausal osteoporosis that can predict phase 3 trial outcome based on short‐term bone turnover marker data. To this end, we applied a previously developed model for tibolone to bisphosphonates using zoledronic acid as paradigm compound by (1) linking the mechanistic bone cell interaction model to bone turnover markers as well as bone mineral density in lumbar spine and total hip, (2) employing a mechanistic disease progression function, and (3) accounting for zoledronic acid's mechanism of action. Once developed, we fitted the model to clinical trial data of 581 postmenopausal women receiving (1) 5‐mg zoledronic acid in year 1 and saline in year 2, (2) 5‐mg zoledronic acid in year 1 and year 2, or (3) placebo (saline), calcium (500 mg), and vitamin D (400 IU). All biomarker data was fitted reasonably well, with no apparent bias or model misspecification. Age, years since menopause, and body mass index at baseline were identified as significant covariates. In the future, the model can be modified to explore the link between short‐term biomarkers and fracture risk.

The main objective of this tutorial is to provide the readers with a roadmap of how to establish increasingly complex target‐mediated drug disposition (TMDD) models for monoclonal antibodies. To this end, we built mathematical models, each with a detailed visualization, starting from the basic TMDD model by Mager and Jusko to the well‐established, physiologically based model by Li et al. in a step‐wise fashion to highlight the relative importance of key physiological processes that impact mAb kinetics and system dynamics. As the models become more complex, the question of structural and parameter identifiability arises. To address this question, we work through a trastuzumab case example to guide the modeler's choice for model and parameter optimization in light of the context of use. We leave the readers of this tutorial with a brief summary of the advantages and limitations of each model expansion, as well as the model source codes for further self‐guided exploration and hands‐on analysis.