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ObjectivesGraves' disease (GD) with onset in childhood or adolescence is a rare disease (ORPHA:525731). Current pharmacotherapeutic approaches use antithyroid drugs, such as carbimazole, as monotherapy or in combination with thyroxine hormone substitutes, such as levothyroxine, as block-and-replace therapy to normalize thyroid function and improve patients' quality of life. However, in the context of fluctuating disease activity, especially during puberty, a considerable proportion of pediatric patients with GD is suffering from thyroid hormone concentrations outside the therapeutic reference ranges. Our main goal was to develop a clinically practical pharmacometrics computer model that characterizes and predicts individual disease activity in children with various severity of GD under pharmacotherapy.MethodsRetrospectively collected clinical data from children and adolescents with GD under up to two years of treatment at four different pediatric hospitals in Switzerland were analyzed. Development of the pharmacometrics computer model is based on the non-linear mixed effects approach accounting for inter-individual variability and incorporating individual patient characteristics. Disease severity groups were defined based on free thyroxine (FT4) measurements at diagnosis.ResultsData from 44 children with GD (75% female, median age 11 years, 62% receiving monotherapy) were analyzed. FT4 measurements were collected in 13, 15, and 16 pediatric patients with mild, moderate, or severe GD, with a median FT4 at diagnosis of 59.9 pmol/l (IQR 48.4, 76.8), and a total of 494 FT4 measurements during a median follow-up of 1.89 years (IQR 1.69, 1.97). We observed no notable difference between severity groups in terms of patient characteristics, daily carbimazole starting doses, and patient years. The final pharmacometrics computer model was developed based on FT4 measurements and on carbimazole or on carbimazole and levothyroxine doses involving two clinically relevant covariate effects: age at diagnosis and disease severity.DiscussionWe present a tailored pharmacometrics computer model that is able to describe individual FT4 dynamics under both, carbimazole monotherapy and carbimazole/levothyroxine block-and-replace therapy accounting for inter-individual disease progression and treatment response in children and adolescents with GD. Such clinically practical and predictive computer model has the potential to facilitate and enhance personalized pharmacotherapy in pediatric GD, reducing over- and underdosing and avoiding negative short- and long-term consequences. Prospective randomized validation trials are warranted to further validate and fine-tune computer-supported personalized dosing in pediatric GD and other rare pediatric diseases.

BackgroundJuvenile idiopathic arthritis (JIA) is one of the most common pediatric inflammatory rheumatic diseases (PiRDs). Uncontrolled disease activity is associated with decreased quality of life and chronic morbidity. Biologic disease-modifying antirheumatic drugs (bDMARDs) and Janus kinase inhibitors (JAKi) have considerably improved clinical outcomes. For optimized patient care, understanding the efficacy-safety profile of biologics in subgroups of JIA is crucial. This systematic review based on published randomized controlled trials (RCTs) aims to assess efficacy and safety data for bDMARDs and JAKi with various JIA subgroups after 3 months of treatment.MethodsData for American College of Rheumatology (ACR) pediatric (Pedi) 30, 50, and/or 70 responses after 3 months of treatment were selected from RCTs investigating bDMARDs or JAKi in JIA according to predefined inclusion/exclusion criteria. Treatment and control arms were compared by calculating risk ratios (RRs) with 95% confidence intervals (CIs), and proportions of overall, serious adverse events (AEs) and infections were analyzed. Forest plots were generated to summarize efficacy and safety endpoints across studies, JIA subgroups, and type of biologics.ResultsTwenty-eight out of 41 PiRD RCTs investigated bDMARD or JAKi treatments in JIA. 9 parallel RCTs reported ACR Pedi 30, 50, and/or 70 responses 3 months after treatment initiation. All treatment arms showed improved ACR Pedi responses over controls. RRs ranged from 1.05 to 3.73 in ACR Pedi 30, from 1.20 to 7.90 in ACR Pedi 50, and from 1.19 to 8.73 in ACR Pedi 70. An enhanced effect for ACR Pedi 70 was observed with infliximab combined with methotrexate in PJIA vs. methotrexate monotherapy. A slightly higher risk of gastrointestinal AEs and infections was observed with treatment arms compared to placebo or methotrexate monotherapy.ConclusionInvestigated bDMARDs and JAKi showed superior treatment responses compared to controls after 3 months of treatment, which were more pronounced in ACR Pedi 50 and 70 than in ACR Pedi 30. Higher susceptibility to infections associated with bDMARDs or JAKi vs. control arms must be weighed against efficacious treatment of the underlying disease and prevention of disease-related damage. Additional RCTs are warranted to further inform development and utilization of biologics in JIA.

ObjectivesThe objective of this pharmacometric (PMX) study was to (i) characterize population pharmacokinetics (PPK) and exposure-pain response associations following intranasal (0.1 mg/kg) or intravenous (IV, 0.05 mg/kg) administration of nalbuphine, with the goal to (ii) evaluate strategies for optimized dosing and timing of painful interventions in infants 1–3 months old.MethodsPPK analysis of nalbuphine serum concentrations, prospectively collected 15, 30, and between 120 and 180 min post-dose, utilizing the software package Monolix. The final PPK model was applied to derive individual time-matched concentration predictions for each pain assessment (Neonatal Infant Pain Score, NIPS) after establishment of venous access and urinary catheterization or lumbar puncture. Drug exposure-pain response simulations were performed to evaluate potential benefits of higher doses with respect to a previously proposed target concentration of 12 mcg/L (efficacy threshold).ResultsThirty-eight of 52 study subjects receiving nalbuphine had at least one concentration measurement and were included in the pharmacometric analysis. A two-compartment model with allometric scaling was applied to describe population PK data, with intranasal bioavailability estimated to be 41% (95%CI: 26–56%). Model-based simulations showed that the proposed efficacy threshold (12 mcg/L) is expected to be exceeded with an IV dose of 0.05 mg/kg for 6 min, with 0.1 mg/kg for 30 min and with 0.2 mg/kg for 80 min. This efficacy threshold is not achieved with intranasal doses of 0.1 and 0.2 mg/kg, whereas an intranasal dose of 0.4 mg/kg is expected to exceed such threshold for 30 to 100 min.ConclusionThis PMX study confirmed that bioavailability of intranasal nalbuphine is close to 50%. Exposure-pain response simulations indicated that an intranasal dose of 0.4 mg/kg is required to provide a comparable pain control as achieved with an IV dose of 0.1–0.2 mg/kg. The optimal time window for painful procedures appears to be within the first 30 min after IV administration of 0.1 mg/kg nalbuphine, whereas such procedures should be scheduled 30 min after an intranasal dose of 0.4 mg/kg nalbuphine. Additional clinical studies are warranted to confirm these PMX based recommendations and to further optimize pain management in this vulnerable infant population.

In this work, we study the problem of clustering survival data $-$ a challenging and so far under-explored task. We introduce a novel semi-supervised probabilistic approach to cluster survival data by leveraging recent advances in stochastic gradient variational inference. In contrast to previous work, our proposed method employs a deep generative model to uncover the underlying distribution of both the explanatory variables and censored survival times. We compare our model to the related work on clustering and mixture models for survival data in comprehensive experiments on a wide range of synthetic, semi-synthetic, and real-world datasets, including medical imaging data. Our method performs better at identifying clusters and is competitive at predicting survival times. Relying on novel generative assumptions, the proposed model offers a holistic perspective on clustering survival data and holds a promise of discovering subpopulations whose survival is regulated by different generative mechanisms., Comment: ICLR 2022

Additional file 1.

OptiDose is a drug dosing algorithm that computes the optimal doses for a given patient and dosing schedule based on control theory. Here, a sensitivity analysis for OptiDose using derivative based and regression methods is performed. Two sensitivity measures with respect to the model parameters are presented, the sensitivity of the optimal doses and the sensitivity of the minimized cost functional. Further, the sensitivity analysis is applied to typical pharmacokinetic-pharmacodynamic examples. published

Additional file 1: Supplementary data S1. Search terms. Supplementary data S2. Review protocol. Supplemetary data S3. Outcome/Endpoint inclusion criteria for literature search.

L-Thyroxine (L-T4) is the treatment of choice of congenital hypothyroidism (CH). Longitudinal measurements of free T4 (FT4) serum concentrations were collected over the first two years of life with oral L-T4 treatment in infants with CH. Purpose of this study was to develop an integrated mathematical model to characterize the kinetics of exogenous L-Thyroxine (L-T4) after multiple dosing in infants with CH, and the dynamics of residual endogenous FT4 synthesis under treatment in the context of severe, moderate and mild disease. A total of 200 FT4 concentrations from 30 patients were available for analysis. At start of treatment, mean (standard deviation [SD]) postnatal age and weight of the population were 11 (8) days and 3.9 (1.3) kg. Mean (SD) pretreatment FT4 concentration was 11.3 (7.4) pmol/L. Measured FT4 concentrations were modelled as sum of residual endogenous FT4 and exogenously administered FT4 (L-T4). The integrated mathematical model consists of an absorption compartment for the exogenous FT4 administration, and a central compartment for measured FT4 with linear elimination. Hence, for residual endogenous and exogenous FT4 the same elimination rate constant was assumed. For the residual endogenous synthesis, different approaches were tested: a constant production and typical time-dependent production functions. FT4 data were analyzed using nonlinear mixed-effects modeling. The integrated mathematical model with a time-dependent non-linear Emax function describing a decreasing residual endogenous FT4 synthesis for increasing time provided the best data fit in terms of Akaike value and various goodness-of-fit plots. This is in line with the expected progressive suppression of the thyroid stimulating hormone by the exogenous FT4, and the subsequent decrease of residual FT4 endogenous synthesis. The developed mathematical model allows simulation of FT4 pharmacokinetic profiles for different disease severities and different dosing regimens.

Biologic disease modifying antirheumatic drugs (bDMARDs) and Janus Kinase (JAK) inhibitors are prescribed in adult and paediatric rheumatology. Due to age-dependent changes, disease course, and pharmacokinetic processes paediatric patients with inflammatory rheumatic diseases (PiRD) differ from adult rheumatology patients.A systematic literature search for randomized clinical trials (RCTs) in PiRD treated with bDMARDs/JAK inhibitors was conducted on Medline, clinicaltrials.gov , clinicaltrialsregister.eu and conference abstracts as of July 2020. RCTs were included if (i) patients were aged ≤20 years, (ii) patients had a predefined rheumatic diagnosis and (iii) RCT reported predefined outcomes. Selected studies were excluded in case of (i) observational or single arm study or (ii) sample size ≤5 patients. Study characteristics were extracted.Out of 608 screened references, 65 references were selected, reporting 35 unique RCTs. All 35 RCTs reported efficacy while 34/3 provided safety outcomes and 16/35 provided pharmacokinetic data. The most common investigated treatments were TNF inhibitors (60%), IL-1 inhibitors (17%) and IL-6 inhibitors (9%). No RCTs with published results were identified for baricitinib, brodalumab, certolizumab pegol, guselkumab, risankizumab, rituximab, sarilumab, secukinumab, tildrakizumab, or upadacitinib. In patients with juvenile idiopathic arthritis (JIA) 25/35 RCTs were conducted. The remaining 10 RCTs were performed in non-JIA patients including plaque psoriasis, Kawasaki Disease, systemic lupus erythematosus and non-infectious uveitis. In JIA-RCTs, the control arm was mainly placebo and the concomitant treatments were either methotrexate, non-steroidal anti-inflammatory drugs (NSAID) or corticosteroids. Non-JIA patients mostly received NSAID. There are ongoing trials investigating abatacept, adalimumab, baricitinib, brodalumab, certolizumab pegol, etanercept, guselkumab, infliximab, risankizumab, secukinumab, tofacitinib and tildrakizumab.Despite the FDA Modernization Act and support of major paediatric rheumatology networks, such as the Pediatric Rheumatology Collaborative Study Group (PRCSG) and the Paediatric Rheumatology International Trials Organization (PRINTO), which resulted in drug approval for PiRD indications, there are limited RCTs in PiRD patients. As therapy response is influenced by age-dependent changes, pharmacokinetic processes and disease course it is important to consider developmental changes in bDMARDs/JAK inhibitor use in PiRD patients. As such it is critical to collaborate and conduct international RCTs to appropriately investigate and characterize efficacy, safety and pharmacokinetics of bDMARDs/JAK inhibitors in paediatric rheumatology.

Timing of complete data and samples, by timepoint and location. Table S2. Complete and correct data and samples when timing as a correctness factor is neglected (i.e. all data collected within one calendar day are correct). Table S3. Caregiver feasibility questionnaire. Table S4. Main difficulties experienced by caregivers during conduct of study. (PDF 205Â kb)

Proportion of complete and correct data and samples by patient and location. (PDF 8Â kb)

Proportion of complete and correct data and samples by location and day. (PDF 6Â kb)

CO2 Capture and Storage (CCS) is a promising solution to separate CO2 from flue gas, to reduce the CO2 emissions in the atmosphere, and hence to reduce global warming. In CCS, one important constraint is the high additional energy requirement of the different capture processes. That statement is partly explained by the low CO2 fraction in the inlet flue gas and the high output targets in terms of CO2 capture and purity (>90%).Gas permeation across dense membrane can be used in post combustion CO2 capture. Gas permeation in a dense membrane is ruled by a mass transfer mechanism and separation performance in a dense membrane are characterized by component’s effective permeability and selectivity. One of the newest and encouraging type of membrane in terms of separation performance is the facilitated transport membrane. Each particular type of membrane is defined by a specific mass transfer law. The most important difference to the mass transfer behavior in a dense membrane is related to the facilitated transport mechanism and the solution diffusion mechanism and its restrictions and limitations.Permeation flux modelling across a dense membrane is required to perform a post combustion CO2 capture process simulation. A CO2 gas permeation separation process is composed of a two-steps membrane process, one drying step and a compression unit. Simulation on the energy requirement and surface area of the different membrane modules in the global system are useful to determine the benefits of using dense membranes in a post combustion CO2 capture technology, La technologie de Captage et Stockage du CO2 (CSC) est considérée comme une des principales solutions pour limiter les rejets de gaz à effet de serre (CO2) et lutter contre le réchauffement climatique. L’étape de captage fait appel à un procédé de séparation des fumées de post combustion qui a pour fonction l’extraction sélective du CO2 des autres composés. Les principales performances visées sont un taux de capture et une pureté du CO2 supérieurs à 90%, ainsi qu’une consommation énergétique minimale afin de ne pas générer un niveau trop élevé d’émissions secondaires de CO2. La perméation gazeuse par membrane dense est une technologie de séparation potentiellement applicable au captage du CO2 en post combustion. Sur la base de différents types de matériaux et mécanisme de transport associés (processus physique ou chimique) une large plage de valeurs de perméabilité et de sélectivité peut être atteinte. Une des dernières familles de membrane ayant démontrée des performances de séparation pouvant être intéressantes pour le captage du CO2 sont les membranes à transport facilité dites ‘’réactives ‘’. Une analyse systématique des performances de séparation de modules membranaires basés sur des membranes physiques (polymères denses) et sur des membranes réactives (transport facilité) pour le traitement de fumées de post combustion a été réalisée. La simulation d’un procédé de captage complet, incluant un ou deux étages de séparation membranaire, une étape de séchage et une étape de compression a ensuite été effectuée. L’ensemble des résultats, en particulier la pénalité énergétique globale du système et l’estimation des surfaces membranaires nécessaires, permet de positionner la technologie de perméation gazeuse comparativement aux autres procédés de captage

Proportion of complete and correct data and samples by patient and location. (PDF 8Â kb)

Development of mobile application. (PDF 74Â kb)

Proportion of complete and correct data and samples by location and day. (PDF 6Â kb)

Timing of complete data and samples, by timepoint and location. Table S2. Complete and correct data and samples when timing as a correctness factor is neglected (i.e. all data collected within one calendar day are correct). Table S3. Caregiver feasibility questionnaire. Table S4. Main difficulties experienced by caregivers during conduct of study. (PDF 205Â kb)

This study assessed the effect of differences in renal function on the pharmacokinetics and pharmacodynamics of dapagliflozin, a renal sodium glucose co-transporter-2 (SGLT2) inhibitor for the treatment of type 2 diabetes mellitus (T2DM).A single 50 mg dose of dapagliflozin was used to assess pharmacokinetics and pharmacodynamics in five groups: healthy non-diabetic subjects; patients with T2DM and normal kidney function and patients with T2DM and mild, moderate or severe renal impairment based on estimated creatinine clearance. Subsequently, 20 mg once daily multiple doses of dapagliflozin were evaluated in the patients with T2DM. Formation rates of dapagliflozin 3-O-glucuronide (D3OG), an inactive metabolite, were evaluated using human isolated kidney and liver microsomes.Plasma concentrations of dapagliflozin and D3OG were incrementally increased with declining kidney function. Steady-state Cmax for dapagliflozin were 4%, 6% and 9% higher and for D3OG were 20%, 37% and 52% higher in patients with mild, moderate and severe renal impairment, respectively, compared with normal function. AUC(0,τ) was likewise higher. D3OG formation in kidney microsomes was three-fold higher than in liver microsomes and 109-fold higher than in intestine microsomes. Compared with patients with normal renal function, pharmacodynamic effects were attenuated with renal impairment. Steady-state renal glucose clearance was reduced by 42%, 83% and 84% in patients with mild, moderate or severe renal impairment, respectively.These results indicate that both kidney and liver significantly contribute to dapagliflozin metabolism, resulting in higher systemic exposure with declining kidney function. Dapagliflozin pharmacodynamics in diabetic subjects with moderate to severe renal impairment are consistent with the observation of reduced efficacy in this patient population.

The studies presented in this thesis have increased our understanding of the impact of growth and development on how to optimally use commonly prescribed drugs in the neonatal population and also have provided insights in the maturation of the kidney, illustrated by different kidney function and injury biomarkers over the entire pediatric age range (extreme preterm to adolescents). Throughout this thesis we have developed multiple population pharmacokinetic models allowing to assess the impact of maturation on the drug disposition of commonly used drugs in the neonatal population such as amoxicillin (Chapter 4), methadone (Chapter 5) and ibuprofen (Chapter 6). We have shown that characterizing developmental pharmacokinetics is a crucial first step to gain insights in drug exposure in neonates and infants, although further research on developmental pharmacodynamics is warranted to unravel the exposure-response relationship in these vulnerable pediatric populations. Moreover, we have provided age-dependent reference ranges for kidney function and injury biomarkers in extreme preterm neonates (Chapter 7) and healthy infants, children and adolescents (Chapters 9 and 10), which will support earlier detection of kidney injury in neonatal and pediatric patients who are exposed to nephrotoxic drugs. The results of the developed population pharmacokinetic models and the implementation of their outcome, together with the established age-dependent reference ranges for kidney biomarkers will hopefully contribute to current clinical practice and ultimately will help guide neonatal and pediatric pharmacotherapy.