Applied physiologically-based pharmacokinetic modeling to assess uridine diphosphate-glucuronosyltransferase-mediated drug-drug interactions for Vericiguat.

Vericiguat (Verquvo; US: Merck, other countries: Bayer) is a novel drug for the treatment of chronic heart failure. Preclinical studies have demonstrated that the primary route of metabolism for vericiguat is glucuronidation, mainly catalyzed by uridine diphosphate-glucuronosyltransferase (UGT)1A9 and to a lesser extent UGT1A1. Whereas a drug-drug interaction (DDI) study of the UGT1A9 inhibitor mefenamic acid showed a 20% exposure increase, the effect of UGT1A1 inhibitors has not been assessed clinically. This modeling study describes a physiologically-based pharmacokinetic (PBPK) approach to complement the clinical DDI liability assessment and support prescription labeling. A PBPK model of vericiguat was developed based on in vitro and clinical data, verified against data from the mefenamic acid DDI study, and applied to assess the UGT1A1 DDI liability by running an in silico DDI study with the UGT1A1 inhibitor atazanavir. A minor effect with an area under the plasma concentration-time curve (AUC) ratio of 1.12 and a peak plasma concentration ratio of 1.04 was predicted, which indicates that there is no clinically relevant DDI interaction anticipated. Additionally, the effect of potential genetic polymorphisms of UGT1A1 and UGT1A9 was evaluated, which showed that an average modest increase of up to 1.7-fold in AUC may be expected in the case of concomitantly reduced UGT1A1 and UGT1A9 activity for subpopulations expressing non-wild-type variants for both isoforms. This study is a first cornerstone to qualify the PK-Sim platform for use of UGT-mediated DDI predictions, including PBPK models of perpetrators, such as mefenamic acid and atazanavir, and sensitive UGT substrates, such as dapagliflozin and raltegravir.

Physiologically based pharmacokinetic (PBPK) modelling of oral drug absorption in older adults - an AGePOP review.

The older population consisting of persons aged 65 years or older is the fastest-growing population group and also the major consumer of pharmaceutical products. Due to the heterogenous ageing process, this age group shows high interindividual variability in the dose-exposure-response relationship and, thus, a prediction of drug safety and efficacy is challenging. Although physiologically based pharmacokinetic (PBPK) modelling is a well-established tool to inform and confirm drug dosing strategies during drug development for special population groups, age-related changes in absorption are poorly accounted for in current PBPK models. The purpose of this review is to summarise the current state-of-knowledge in terms of physiological changes with increasing age that can influence the oral absorption of dosage forms. The capacity of common PBPK platforms to incorporate these changes and describe the older population is also discussed, as well as the implications of extrinsic factors such as drug-drug interactions associated with polypharmacy on the model development process. The future potential of this field will rely on addressing the gaps identified in this article, which can subsequently supplement in-vitro and in-vivo data for more robust decision-making on the adequacy of the formulation for use in older adults and inform pharmacotherapy.

Classification of Breast Cancer Histopathological Images Using DenseNet and Transfer Learning.

Breast cancer is one of the most common invading cancers in women. Analyzing breast cancer is nontrivial and may lead to disagreements among experts. Although deep learning methods achieved an excellent performance in classification tasks including breast cancer histopathological images, the existing state-of-the-art methods are computationally expensive and may overfit due to extracting features from in-distribution images. In this paper, our contribution is mainly twofold. First, we perform a short survey on deep-learning-based models for classifying histopathological images to investigate the most popular and optimized training-testing ratios. Our findings reveal that the most popular training-testing ratio for histopathological image classification is 70%: 30%, whereas the best performance (e.g., accuracy) is achieved by using the training-testing ratio of 80%: 20% on an identical dataset. Second, we propose a method named DenTnet to classify breast cancer histopathological images chiefly. DenTnet utilizes the principle of transfer learning to solve the problem of extracting features from the same distribution using DenseNet as a backbone model. The proposed DenTnet method is shown to be superior in comparison to a number of leading deep learning methods in terms of detection accuracy (up to 99.28% on BreaKHis dataset deeming training-testing ratio of 80%: 20%) with good generalization ability and computational speed. The limitation of existing methods including the requirement of high computation and utilization of the same feature distribution is mitigated by dint of the DenTnet.

Nifurtimox for Treatment of Chagas Disease in Pediatric Patients: the Challenges of Applying Pharmacokinetic-Pharmacodynamic Principles to Dose Finding.

The antiparasitic drug nifurtimox was approved in the USA in 2020 for the treatment of patients with Chagas disease aged less than 18 years and weighing at least 2.5 kg, based on outcomes from the phase 3 CHICO study. Accordingly, pediatric patients with Chagas disease take nifurtimox thrice daily with food at one of two body weight-adjusted dose ranges. We investigated possible relationships between pharmacokinetic (PK) data, and pharmacodynamic efficacy and safety data collected in an analysis population of 111 participants in CHICO, using a published population PK model to estimate nifurtimox exposure at the patient level. Pediatric exposure to nifurtimox was benchmarked against levels of nifurtimox exposure known to be effective in adults with Chagas disease. Given the complex dosing regimen for nifurtimox, we also modeled nifurtimox exposure associated with simpler dosing strategies. We found no relationship between exposure to nifurtimox and efficacy measures (e.g., serological response to treatment), or between exposure and safety outcomes (including typical adverse events, e.g., headache, decreased appetite, nausea/vomiting). The analysis population appeared to represent the overall CHICO population based on the similarity of their baseline characteristics and the profiles of adverse events in the two groups. Modeled exposure based on the dosing regimen in CHICO was within the reference range derived from phase 1 data in adults. The relationship between nifurtimox exposure and cure is complex; a simplified pediatric dosing regimen is unlikely to be beneficial.

Model-informed bridging of rivaroxaban doses for thromboprophylaxis in pediatric patients aged 9 years and older with congenital heart disease.

Rivaroxaban is approved in various regions for the treatment of acute venous thromboembolism (VTE) in children aged between 0 and 18 years and was recently investigated for thromboprophylaxis in children aged between 2 and 8 years (with body weights <30 kg) with congenital heart disease who had undergone the Fontan procedure. In the absence of clinical data, rivaroxaban doses for thromboprophylaxis in post-Fontan children aged 9 years and older or ≥30 kg were derived by a bridging approach that used physiologically-based pharmacokinetic (PBPK) and population pharmacokinetic (popPK) models based on pharmacokinetic (PK) data from 588 pediatric patients and from adult patients who received 10 mg once daily for thromboprophylaxis after major orthopedic surgeries as a reference. Both models showed a tendency toward underestimating rivaroxaban exposure in post-Fontan patients aged between 2 and 5 years but accurately described rivaroxaban PK in post-Fontan patients aged between 5 and 8 years. Under the assumption that hepatic function is not impaired in post-Fontan patients, PBPK and popPK simulations indicated that half of the rivaroxaban doses for the same body weight given to pediatric patients treated for acute VTE would yield in pediatric post-Fontan patients exposures similar to the exposure observed in adult patients receiving 10 mg rivaroxaban once daily for thromboprophylaxis. Simulation-derived doses (7.5 mg rivaroxaban once daily for body weights 30-<50 kg and 10 mg once daily for body weights ≥50 kg) were therefore included in the recent US label of rivaroxaban for thromboprophylaxis in children aged 2 years and older with congenital heart disease who have undergone the Fontan procedure.

Population Pharmacokinetics of Nifurtimox in Adult and Pediatric Patients With Chagas Disease.

Nifurtimox (LAMPIT) has been used for decades for the treatment of Chagas disease, a chronic and potentially life-threatening disease caused by the parasite Trypanosoma cruzi. The pharmacokinetic (PK) information on nifurtimox in humans derived from controlled clinical studies is very limited. The objective was to investigate and compare the population PK of nifurtimox in adult and pediatric patients with Chagas disease to confirm the clinical dosing regimen in children, which was based on allometric approaches using the concept that a dose-equivalent exposure would reach equivalent antiparasitic efficacy as in adults. The resulting adult model adequately described the PK in adults. Significant predictors of the availability in PK were food intake, tablet formulation (fast- vs slow-dissolution tablet), study, and body weight. As the resulting adult model could not adequately predict the sparse sampled pediatric patient data, these data were analyzed separately to derive exposure estimates for comparison with adult exposure. In the population PK model for pediatric patients, significant covariates were body weight and age. As compared to adults, children aged >2 years were estimated to have 50.6% higher apparent clearance. No hints of dose nonlinearity were observed in a dose range of 30 to 240 mg single dose in adults and 15 to 300 mg 3 times daily (8-20 mg/kg) in children. Altogether, this study retroactively showed that the current mg/kg dosing regimen in children reached similar exposure as in adults receiving an 8 mg/kg total daily dose.

Clinical investigation of the biopharmaceutical characteristics of nifurtimox tablets - Implications for quality control and application.

Nifurtimox is approved in Chagas disease and has been used in endemic countries since the 1960s. Nifurtimox, available as a 120 mg tablet, is administered with food typically three times daily, and dose is adjusted for age and bodyweight. Accurately or reproducibly fragmenting the 120 mg tablet for dose adjustment in young children and those with low bodyweight is problematic. Based on the existing tablet formulation, new nifurtimox 30 mg and 120 mg tablets have been developed in a format that can be divided accurately into 15 mg and 60 mg fragments. In adults with chronic Chagas disease, we investigated whether nifurtimox bioavailability is affected by tablet dissolution rate, and whether different diets affect nifurtimox bioavailability. In an open-label, three-period cross-over study (n=36; ClinicalTrials.gov, NCT03350295), patients randomly received three 30 mg tablet formulations (slow, medium, or fast dissolution; a 4 × 30 mg dose of one formulation per period). In an open-label, four-period cross-over study (n=24; ClinicalTrials.gov, NCT03334838) patients randomly fasted or received one of three meal types (high-fat/high-calorie, low-fat, dairy-based) before ingesting nifurtimox (a 4 × 30 mg dose per period). Acceptance criteria for no difference between groups were 90% confidence intervals (CIs) of exposure ratios in the range 0.8-1.25. Nifurtimox bioavailability was unaffected by tablet dissolution kinetics. Ratios of area under the curve at final assessment (AUC(0-tlast) [90% CI]) were: fast/medium dissolution, 1.061 (0.990-1.137); slow/medium dissolution, 0.964 (0.900-1.033); fast/slow dissolution, 1.100 (1.027-1.179). Compared with a fasting state, nifurtimox bioavailability increased by 73% after a high-fat/high-calorie meal (AUC(0-tlast) ratio [90% CI], 1.732 [1.581-1.898]); smaller increases were seen with the other meal types (low-fat: 1.602 [1.462-1.755]; dairy-based: 1.340 [1.222-1.468]). Although type of diet can affect bioavailability, taking nifurtimox with food is most important.

Population pharmacokinetic analysis of rivaroxaban in children and comparison to prospective physiologically-based pharmacokinetic predictions.

Rivaroxaban has been investigated in the EINSTEIN-Jr program for the treatment of acute venous thromboembolism (VTE) in children aged 0 to 18 years and in the UNIVERSE program for thromboprophylaxis in children aged 2 to 8 years with congenital heart disease after Fontan-procedure. Physiologically-based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) modeling were used throughout the pediatric development of rivaroxaban according to the learn-and-confirm paradigm. The development strategy was to match pediatric drug exposures to adult exposure proven to be safe and efficacious. In this analysis, a refined pediatric PopPK model for rivaroxaban based on integrated EINSTEIN-Jr data and interim PK data from part A of the UNIVERSE phase III study was developed and the influence of potential covariates and intrinsic factors on rivaroxaban exposure was assessed. The model adequately described the observed pediatric PK data. PK parameters and exposure metrics estimated by the PopPK model were compared to the predictions from a previously published pediatric PBPK model for rivaroxaban. Ninety-one percent of the individual post hoc clearance estimates were found within the 5th to 95th percentile of the PBPK model predictions. In patients below 2 years of age, however, clearance was underpredicted by the PBPK model. The iterative and integrative use of PBPK and PopPK modeling and simulation played a major role in the establishment of the bodyweight-adjusted rivaroxaban dosing regimen that was ultimately confirmed to be a safe and efficacious dosing regimen for children aged 0 to 18 years with acute VTE in the EINSTEIN-Jr phase III study.

Predictive Performance of Physiology-Based Pharmacokinetic Dose Estimates for Pediatric Trials: Evaluation With 10 Bayer Small-Molecule Compounds in Children.

Development and guidance of dosing schemes in children have been supported by physiology-based pharmacokinetic (PBPK) modeling for many years. PBPK models are built on a generic basis, where compound- and system-specific parameters are separated and can be exchanged, allowing the translation of these models from adults to children by accounting for physiological differences. Owing to these features, PBPK modeling is a valuable approach to support clinical decision making for dosing in children. In this analysis, we evaluate pediatric PBPK models for 10 small-molecule compounds that were applied to support clinical decision processes at Bayer for their predictive power in different age groups. Ratios of PBPK-predicted to observed PK parameters for the evaluated drugs in different pediatric age groups were estimated. Predictive performance was analyzed on the basis of a 2-fold error range and the bioequivalence range (ie, 0.8 ≤ predicted/observed ≤ 1.25). For all 10 compounds, all predicted-to-observed PK ratios were within a 2-fold error range (n = 27), with two-thirds of the ratios within the bioequivalence range (n = 18). The findings demonstrate that the pharmacokinetics of these compounds was successfully and adequately predicted in different pediatric age groups. This illustrates the applicability of PBPK for guiding dosing schemes in the pediatric population.

A generic framework for the physiologically-based pharmacokinetic platform qualification of PK-Sim and its application to predicting cytochrome P450 3A4-mediated drug-drug interactions.

The success of applications of physiologically-based pharmacokinetic (PBPK) modeling in drug development and drug labeling has triggered regulatory agencies to demand rigorous demonstration of the predictive capability of the specific PBPK platform for a particular intended application purpose. The effort needed to comply with such qualification requirements exceeds the costs for any individual PBPK application. Because changes or updates of a PBPK platform would require (re-)qualification, a reliable and efficient generic qualification framework is needed. We describe the development and implementation of an agile and sustainable technical framework for automatic PBPK platform (re-)qualification of PK-Sim® embedded in the open source and open science GitHub landscape of Open Systems Pharmacology. The qualification approach enables the efficient assessment of all aspects relevant to the qualification of a particular purpose and provides transparency and traceability for all stakeholders. As a showcase example for the power and versatility of the qualification framework, we present the qualification of PK-Sim® for the intended purpose of predicting cytochrome P450 3A4 (CYP3A4)-mediated drug-drug interactions (DDIs). Several perpetrator PBPK models featuring various degrees of CYP3A4 modulation and different types of mechanisms (competitive inhibition, mechanism-based inactivation, and induction) were coupled with a set of PBPK models of sensitive CYP3A4 victim drugs. Simulations were compared to a comprehensive data set of 135 observations from published clinical DDI studies. The platform's overall predictive performance showed reasonable accuracy and precision (geometric mean fold error of 1.4 for both area under the plasma concentration-time curve ratios and peak plasma concentration ratios with/without perpetrator) and suggests that PK-Sim® can be applied to quantitatively assess CYP3A4-mediated DDI in clinically untested scenarios.

Integration of physiological changes during the postpartum period into a PBPK framework and prediction of amoxicillin disposition before and shortly after delivery.

The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for amoxicillin for non-pregnant, pregnant and postpartum populations by compiling a database incorporating reported changes in the anatomy and physiology throughout the postpartum period. A systematic literature search was conducted to collect data on anatomical and physiological changes in postpartum women. Empirical functions were generated describing the observed changes providing the basis for a generic PBPK framework. The fraction unbound ([Formula: see text]) of predominantly albumin-bound drugs was predicted in postpartum women and compared with experimentally observed values. Finally, a specific amoxicillin PBPK model was newly developed, verified for non-pregnant populations and translated into the third trimester of pregnancy (29.4-36.9 gestational weeks) and early postpartum period (drug administration 1.5-3.8 h after delivery). Pharmacokinetic predictions were evaluated using published clinical data. The literature search yielded 105 studies with 1092 anatomical and physiological data values on 3742 postpartum women which were used to generate various functions describing the observed trends. The [Formula: see text] could be adequately scaled to postpartum women. The pregnancy PBPK model predicted amoxicillin disposition adequately as did the postpartum PBPK model, although clearance was somewhat underestimated. While more research is needed to establish fully verified postpartum PBPK models, this study provides a repository of anatomical and physiological changes in postpartum women that can be applied to future modeling efforts. Ultimately, structural refinement of the developed postpartum PBPK model could be used to investigate drug transfer to the neonate via breast-feeding in silico.

Predictive Pediatric Modeling and Simulation Using Ontogeny Information.

Food and Drug Administration submissions of physiologically based pharmacokinetic (PBPK) modeling and simulation of small-molecule drugs document the relevance of pediatric drug development and, in particular, information on dosing strategies in children. The most relevant prerequisite for reliable PBPK-based translation of adult pharmacokinetics of a small molecule to children is knowledge of the drug-specific absorption, distribution, metabolism, and elimination (ADME) processes in adults together with existing information about ontogeny of ADME processes relevant for the drug. All mechanisms driving a drug's clearance are of specific importance. For other drug modalities, our knowledge of ADME processes and ontogeny is still limited. More research is required, for example, to understand why some therapeutic proteins show complex differences in pharmacokinetics between adults and children, whereas other proteins seem to follow simple allometric scaling rules. Ontogeny information originates from various sources, such as (semi)quantitative mRNA expression, in vitro activity data, and deconvolution of in vivo pharmacokinetic data. The workflow for pediatric predictions is well described in several articles documenting successful translation from adults to children. The technical hurdles for PBPK modeling are low. State-of-the-art PBPK modeling software tools provide integrated pediatric translation workflows. For example, PK-Sim and MoBi are freely available as fully transparent open-source software via Open Systems Pharmacology (OSP). With the latest 2019 software release, version 8.0, OSP even provides a fully integrated technical framework for the qualification (and requalification) of any specific intended PBPK use in line with Food and Drug Administration and European Medicines Agency PBPK guidance. Qualification packages for pediatric translation are available on the OSP platform.

Applied Concepts in PBPK Modeling: How to Extend an Open Systems Pharmacology Model to the Special Population of Pregnant Women.

This tutorial presents the workflow of adapting an adult physiologically based pharmacokinetic (PBPK) model to the pregnant populations using the Open Systems Pharmacology (OSP) software suite (www.open-systems-pharmacology.org). This workflow is illustrated using a previously published PBPK model for metronidazole that is extrapolated to pregnancy by parameterizing and extending the model structure in terms of pregnancy-induced physiological changes. Importantly, this workflow can be applied to other scenarios where PBPK models need to be re-parameterized or structurally modified.

A Physiologically Based Pharmacokinetic Model for Pregnant Women to Predict the Pharmacokinetics of Drugs Metabolized Via Several Enzymatic Pathways.

BACKGROUND: Physiologically based pharmacokinetic modeling is considered a valuable tool for predicting pharmacokinetic changes in pregnancy to subsequently guide in-vivo pharmacokinetic trials in pregnant women. The objective of this study was to extend and verify a previously developed physiologically based pharmacokinetic model for pregnant women for the prediction of pharmacokinetics of drugs metabolized via several cytochrome P450 enzymes. METHODS: Quantitative information on gestation-specific changes in enzyme activity available in the literature was incorporated in a pregnancy physiologically based pharmacokinetic model and the pharmacokinetics of eight drugs metabolized via one or multiple cytochrome P450 enzymes was predicted. The tested drugs were caffeine, midazolam, nifedipine, metoprolol, ondansetron, granisetron, diazepam, and metronidazole. Pharmacokinetic predictions were evaluated by comparison with in-vivo pharmacokinetic data obtained from the literature. RESULTS: The pregnancy physiologically based pharmacokinetic model successfully predicted the pharmacokinetics of all tested drugs. The observed pregnancy-induced pharmacokinetic changes were qualitatively and quantitatively reasonably well predicted for all drugs. Ninety-seven percent of the mean plasma concentrations predicted in pregnant women fell within a twofold error range and 63% within a 1.25-fold error range. For all drugs, the predicted area under the concentration-time curve was within a 1.25-fold error range. CONCLUSION: The presented pregnancy physiologically based pharmacokinetic model can quantitatively predict the pharmacokinetics of drugs that are metabolized via one or multiple cytochrome P450 enzymes by integrating prior knowledge of the pregnancy-related effect on these enzymes. This pregnancy physiologically based pharmacokinetic model may thus be used to identify potential exposure changes in pregnant women a priori and to eventually support informed decision making when clinical trials are designed in this special population.

Gestation-Specific Changes in the Anatomy and Physiology of Healthy Pregnant Women: An Extended Repository of Model Parameters for Physiologically Based Pharmacokinetic Modeling in Pregnancy.

BACKGROUND: In the past years, several repositories for anatomical and physiological parameters required for physiologically based pharmacokinetic modeling in pregnant women have been published. While providing a good basis, some important aspects can be further detailed. For example, they did not account for the variability associated with parameters or were lacking key parameters necessary for developing more detailed mechanistic pregnancy physiologically based pharmacokinetic models, such as the composition of pregnancy-specific tissues. OBJECTIVES: The aim of this meta-analysis was to provide an updated and extended database of anatomical and physiological parameters in healthy pregnant women that also accounts for changes in the variability of a parameter throughout gestation and for the composition of pregnancy-specific tissues. METHODS: A systematic literature search was carried out to collect study data on pregnancy-related changes of anatomical and physiological parameters. For each parameter, a set of mathematical functions was fitted to the data and to the standard deviation observed among the data. The best performing functions were selected based on numerical and visual diagnostics as well as based on physiological plausibility. RESULTS: The literature search yielded 473 studies, 302 of which met the criteria to be further analyzed and compiled in a database. In total, the database encompassed 7729 data. Although the availability of quantitative data for some parameters remained limited, mathematical functions could be generated for many important parameters. Gaps were filled based on qualitative knowledge and based on physiologically plausible assumptions. CONCLUSION: The presented results facilitate the integration of pregnancy-dependent changes in anatomy and physiology into mechanistic population physiologically based pharmacokinetic models. Such models can ultimately provide a valuable tool to investigate the pharmacokinetics during pregnancy in silico and support informed decision making regarding optimal dosing regimens in this vulnerable special population.

Physiologically Based Pharmacokinetic Modeling of Renally Cleared Drugs in Pregnant Women.

BACKGROUND: Since pregnant women are considerably underrepresented in clinical trials, information on optimal dosing in pregnancy is widely lacking. Physiologically based pharmacokinetic (PBPK) modeling may provide a method for predicting pharmacokinetic changes in pregnancy to guide subsequent in vivo pharmacokinetic trials in pregnant women, minimizing associated risks. OBJECTIVES: The goal of this study was to build and verify a population PBPK model that predicts the maternal pharmacokinetics of three predominantly renally cleared drugs (namely cefazolin, cefuroxime, and cefradine) at different stages of pregnancy. It was further evaluated whether the fraction unbound (f u) could be estimated in pregnant women using a proposed scaling approach. METHODS: Based on a recent literature review on anatomical and physiological changes during pregnancy, a pregnancy population PBPK model was built using the software PK-Sim®/MoBi®. This model comprised 27 compartments, including nine pregnancy-specific compartments. The PBPK model was verified by comparing the predicted maternal pharmacokinetics of cefazolin, cefuroxime, and cefradine with observed in vivo data taken from the literature. The proposed scaling approach for estimating the f u in pregnancy was evaluated by comparing the predicted f u with experimentally observed f u values of 32 drugs taken from the literature. RESULTS: The pregnancy population PBPK model successfully predicted the pharmacokinetics of cefazolin, cefuroxime, and cefradine at all tested stages of pregnancy. All predicted plasma concentrations fell within a 2-fold error range and 85% of the predicted concentrations within a 1.25-fold error range. The f u in pregnancy could be adequately predicted using the proposed scaling approach, although a slight underestimation was evident in case of drugs bound to α1-acidic glycoprotein. CONCLUSION: Pregnancy population PBPK models can provide a valuable tool to predict a priori the pharmacokinetics of predominantly renally cleared drugs in pregnant women. These models can ultimately support informed decision making regarding optimal dosing regimens in this vulnerable special population.

Developing a mobile application to better inform patients and enable effective consultation in implant dentistry.

The field of dentistry lacks satisfactory tools to help visualize planned procedures and their potential results to patients. Dentists struggle to provide an effective image in their patient's mind of the end results of the planned treatment only through verbal explanations. Thus, verbal explanations alone often cannot adequately help the patients make a treatment decision. Inadequate attempts are frequently made by dentists to sketch the procedure for the patient in an effort to depict the treatment. These attempts however require an artistic ability not all dentists have. Real case photographs are sometimes of help in explaining and illustrating treatments. However, particularly in implant cases, real case photographs are often ineffective and inadequate. The purpose of this study is to develop a mobile application with an effective user interface design to support the dentist-patient interaction by providing the patient with illustrative descriptions of the procedures and the end result. Sketching, paper prototyping, and wire framing were carried out with the actual user's participation. Hard and soft dental tissues were modeled using three dimensional (3D) modeling programs and real cases. The application enhances the presentation to the patients of potential implants and implant supported prosthetic treatments with rich 3D illustrative content. The application was evaluated in terms of perceived ease of use and perceived usefulness through an online survey. The application helps improve the information sharing behavior of dentists to enhance the patients' right to make informed decisions. The paper clearly demonstrates the relevance of interactive communication technologies for dentist-patient communication.

Evaluation of changes in oral drug absorption in preterm and term neonates for Biopharmaceutics Classification System (BCS) class I and II compounds.

AIMS: Evidence suggests that the rate of oral drug absorption changes during early childhood. Yet, respective clinical implications are currently unclear, particularly for preterm neonates. The objective of this study was to evaluate changes in oral drug absorption after birth for different Biopharmaceutics Classification System (BCS) class I and II compounds to better understand respective implications for paediatric pharmacotherapy. METHODS: Two paradigm compounds were selected for BCS class I (paracetamol (acetaminophen) and theophylline) and II (indomethacin and ibuprofen), respectively, based on the availability of clinical literature data following intravenous and oral dosing. A comparative population pharmacokinetic analysis was performed in a step-wise manner in NONMEM® 7.2 to characterize and predict changes in oral drug absorption after birth for paracetamol, theophylline and indomethacin. RESULTS: A one compartment model with an age-dependent maturation function for oral drug absorption was found appropriate to characterize the pharmacokinetics of paracetamol. Our findings indicate that the rate at which a drug is absorbed from the GI tract reaches adult levels within about 1 week after birth. The maturation function for paracetamol was found applicable to theophylline and indomethacin once solubility limitations were overcome via drug formulation. The influence of excipients on solubility and, hence, oral bioavailability was confirmed for ibuprofen, a second BCS class II compound. CONCLUSIONS: The findings of our study suggest that the processes underlying changes in oral drug absorption after birth are drug-independent and that the maturation function identified for paracetamol may be generally applicable to other BCS class I and II compounds for characterizing drug absorption in preterm as well as term neonates.

A novel maturation function for clearance of the cytochrome P450 3A substrate midazolam from preterm neonates to adults.

BACKGROUND AND OBJECTIVE: Major changes in cytochrome P450 (CYP) 3A activity may be expected in the first few months of life with, later, relatively limited changes. In this analysis we studied the maturation of in vivo CYP3A-mediated clearance of midazolam, as model drug, from preterm neonates of 26 weeks gestational age (GA) to adults. METHODS: Pharmacokinetic data after intravenous administration of midazolam were obtained from six previously reported studies. Subjects were premature neonates (n = 24; GA 26-33.5 weeks, postnatal age (PNA) 3-11 days, and n = 24; GA 26-37 weeks, PNA 0-1 days), 23 children after elective major craniofacial surgery (age 3-23 months), 18 pediatric intensive-care patients (age 2 days-17 years), 18 pediatric oncology patients (age 3-16 years), and 20 healthy male adults (age 20-31 years). Population pharmacokinetic modeling with systematic covariate analysis was performed by use of NONMEM v6.2. RESULTS: Across the entire lifespan from premature neonates to adults, bodyweight was a significant covariate for midazolam clearance. The effect of bodyweight was best described by use of an allometric equation with an exponent changing with bodyweight in an exponential manner from 0.84 for preterm neonates (0.77 kg) to 0.44 for adults (89 kg), showing that the most rapid maturation occurs during the youngest age range. CONCLUSIONS: An in-vivo maturation function for midazolam clearance from premature neonates to adults has been developed. This function can be used to derive evidence-based doses for children, and to simulate exposure to midazolam and possibly other CYP3A substrates across the pediatric age range in population pharmacokinetic models or physiologically based pharmacokinetic models.

Developmental changes in the expression and function of cytochrome P450 3A isoforms: evidence from in vitro and in vivo investigations.

The aim of this review is to discuss our current understanding of the developmental changes of the drug-metabolizing enzyme cytochrome P450 (CYP) 3A and its impact on drug therapy. In the last 10 years, several methods have been used to study the ontogeny of specific CYP3A isoforms in vitro and in vivo. Although most studies confirm previous findings that CYP3A4/5 activity is low at birth and reaches adult values in the first years of life, there are still important gaps in our knowledge of the exact developmental patterns of individual CYP3A isoforms, especially in this age range. Moreover, most in vivo clinical studies have also failed to cover the whole pediatric age range. To date, this information gap still hampers the design of age-specific dosing guidelines of CYP3A substrate drugs, especially in neonates and infants. Innovative study methods, including opportunistic sampling and sensitive analytical assays used in combination with physiologically based pharmacokinetics, and population pharmacokinetic model concepts may help to improve our understanding of the ontogeny of CYP3A and aid the application of this knowledge in clinical practice.