Proposals for model-based paediatric medicinal development within the current European Union regulatory framework

Rare disease clinical trials in the European Union: navigating regulatory and clinical challenges

BACKGROUND

Clinical development for orphan drugs presents significant difficulties and challenges. There is no unique or standard design, conduct, and outcome assessment methodology and it is sometimes impractical to fit design models of rare disease trials in any practiced and well-known framework. In the European Union (EU) these challenges encompass a broad array of subjects, including trial design, study outcomes, patient recruitment, trial conduct ethics, trial cost, and chances of success. This literature-based review study aims to provide a thorough overview of the critical aspects of rare disease trials in the EU by analyzing the current landscape of rare disease trials, highlighting key challenges, delving into regulatory and research initiatives and innovation in trial designs, and proposing multi-faceted solutions to implement effective rare disease clinical trials in the region.

DISCUSSION

Traditional clinical trial designs, validation, and evaluation methodologies used for nonorphan drugs often prove unsuitable for orphan drugs, given the small patient populations, sometimes fewer than 1000 cases. There is an increasing need for accessible therapies and both regulators as well as industry are trying to develop affordable and effective drugs to address this need. Despite several steps that have been taken, the timely development of drugs remains a challenge. One of the reasons behind the long development timeline is the recruitment, retention, and conduct of rare disease trials. To optimize the development timelines of orphan drugs in the EU, it is important to ensure that the safety and efficacy of the product is not compromised. Industry and regulatory agencies must implement innovative trial designs, devise flexible policies, and incorporate real-world data for assessing clinical outcomes.

CONCLUSION

Collaboration among academic institutions, pharmaceutical companies (both small and major), patient groups, and health authorities is crucial in overcoming obstacles related to clinical trials and providing assistance and creative ideas. The ultimate objective of granting rare disease patients timely and affordable access to medications with a positive balance between benefits and risks is to be met.

Machine learning in medication prescription: A systematic review

BACKGROUND

Medication prescription is a complex process that could benefit from current research and development in machine learning through decision support systems. Particularly pediatricians are forced to prescribe medications "off-label" as children are still underrepresented in clinical studies, which leads to a high risk of an incorrect dose and adverse drug effects.

METHODS

PubMed, IEEE Xplore and PROSPERO were searched for relevant studies that developed and evaluated well-performing machine learning algorithms following the PRISMA statement. Quality assessment was conducted in accordance with the IJMEDI checklist. Identified studies were reviewed in detail, including the required variables for predicting the correct dose, especially of pediatric medication prescription.

RESULTS

The search identified 656 studies, of which 64 were reviewed in detail and 36 met the inclusion criteria. According to the IJMEDI checklist, five studies were considered to be of high quality. 19 of the 36 studies dealt with the active substance warfarin. Overall, machine learning algorithms based on decision trees or regression methods performed superior regarding their predictive power than algorithms based on neural networks, support vector machines or other methods. The use of ensemble methods like bagging or boosting generally enhanced the accuracy of the dose predictions. The required input and output variables of the algorithms were considerably heterogeneous and differ strongly among the respective substance.

CONCLUSIONS

By using machine learning algorithms, the prescription process could be simplified and dosing correctness could be enhanced. Despite the heterogenous results among the different substances and cases and the lack of pediatric use cases, the identified approaches and required variables can serve as an excellent starting point for further development of algorithms predicting drug doses, particularly for children. Especially the combination of physiologically-based pharmacokinetic models with machine learning algorithms represents a great opportunity to enhance the predictive power and accuracy of the developed algorithms.

Use of Newer and Repurposed Antibiotics against Gram-Negative Bacteria in Neonates

Antimicrobial resistance has become a significant public health problem globally with multidrug resistant Gram negative (MDR-GN) bacteria being the main representatives. The emergence of these pathogens in neonatal settings threatens the well-being of the vulnerable neonatal population given the dearth of safe and effective therapeutic options. Evidence from studies mainly in adults is now available for several novel antimicrobial compounds, such as new β-lactam/β-lactamase inhibitors (e.g., ceftazidime-avibactam, meropenem-vaborbactam, imipenem/cilastatin-relebactam), although old antibiotics such as colistin, tigecycline, and fosfomycin are also encompassed in the fight against MDR-GN infections that remain challenging. Data in the neonatal population are scarce, with few clinical trials enrolling neonates for the evaluation of the efficacy, safety, and dosing of new antibiotics, while the majority of old antibiotics are used off-label. In this article we review data about some novel and old antibiotics that are active against MDR-GN bacteria causing sepsis and are of interest to be used in the neonatal population.

Modeling adult COX-2 cerebrospinal fluid pharmacokinetics to inform pediatric investigation

AIM

Hysteresis is reported between plasma concentration and analgesic effect from nonsteroidal anti-inflammatory drugs. It is possible that the temporal delay between plasma and CSF nonsteroidal anti-inflammatory drugs mirrors this hysteresis. The temporal relationship between plasma and CSF concentrations of COX-inhibitors (celecoxib, rofecoxib, valdecoxib) has been described. The purpose of this secondary data analysis was to develop a compartmental model for plasma and CSF disposition of these COX-2 inhibitors.

METHODS

Plasma and CSF concentration-time profiles and protein binding data in 10 adult volunteers given oral celecoxib 200 mg, valdecoxib 40 mg and rofecoxib 50 mg were available for study. Nonlinear mixed effects models with a single plasma compartment were used to link a single CSF compartment with a transfer factor and an equilibration rate constant (Keq). To enable predictive modeling in pediatrics, celecoxib pharmacokinetics were standardized using allometry.

RESULTS

Movement of all three unbound plasma COX-2 drugs into CSF was characterized by a common equilibration half-time (T_1/2 keq) of 0.84 h. Influx was faster than efflux and a transfer scaling factor of 2.01 was required to describe conditions at steady-state. Estimated celecoxib clearance was 49 (95% CI 34-80) L/h/70 kg and the volume of distribution was 346 (95% CI 237-468) L/70 kg. The celecoxib absorption half-time was 0.35 h with a lag time of 0.62 h. Simulations predicted a 70-kg adult given oral celecoxib 200 mg with maintenance 100 mg twice daily would have a mean steady-state total (bound and unbound) plasma concentration of 174 μg L^-1 and CSF concentration of 1.1 μg L^-1 . A child (e.g., 25 kg, typically 7 years) given oral celecoxib 6 mg kg^-1 with maintenance of 3 mg kg^-1 twice daily would have 282 and 1.7 μg L^-1 mean plasma and CSF concentrations, respectively.

CONCLUSIONS

Transfer of unbound COX-2 inhibitors from plasma to CSF compartment can be described with a delayed effect model using an equilibration rate constant to collapse observed hysteresis. An additional transfer factor was required to account for passage across the blood-brain barrier. Use of a target concentration strategy for dose and consequent plasma (total and unbound) and CSF concentration prediction could be used to inform pediatric clinical studies.

In Silico Studies to Support Vaccine Development

The progress that has been made in computer science positioned in silico studies as an important and well-recognized methodology in the drug discovery and development process. It has numerous advantages in terms of costs and also plays a huge impact on the way the research is conducted since it can limit the use of animal models leading to more sustainable research. Currently, human trials are already being partly replaced by in silico trials. EMA and FDA are both endorsing these studies and have been providing webinars and guidance to support them. For instance, PBPK modeling studies are being used to gather data on drug interactions with other drugs and are also being used to support clinical and regulatory requirements for the pediatric population, pregnant women, and personalized medicine. This trend evokes the need to understand the role of in silico studies in vaccines, considering the importance that these products achieved during the pandemic and their promising hope in oncology. Vaccines are safer than other current oncology treatments. There is a huge variety of strategies for developing a cancer vaccine, and some of the points that should be considered when designing the vaccine technology are the following: delivery platforms (peptides, lipid-based carriers, polymers, dendritic cells, viral vectors, etc.), adjuvants (to boost and promote inflammation at the delivery site, facilitating immune cell recruitment and activation), choice of the targeted antigen, the timing of vaccination, the manipulation of the tumor environment, and the combination with other treatments that might cause additive or even synergistic anti-tumor effects. These and many other points should be put together to outline the best vaccine design. The aim of this article is to perform a review and comprehensive analysis of the role of in silico studies to support the development of and design of vaccines in the field of oncology and infectious diseases. The authors intend to perform a literature review of all the studies that have been conducted so far in preparing in silico models and methods to support the development of vaccines. From this point, it was possible to conclude that there are few in silico studies on vaccines. Despite this, an overview of how the existing work could support the design of vaccines is described.

Current knowledge, challenges and innovations in developmental pharmacology: A combined conect4children Expert Group and European Society for Developmental, Perinatal and Paediatric Pharmacology White Paper

Developmental pharmacology describes the impact of maturation on drug disposition (pharmacokinetics, PK) and drug effects (pharmacodynamics, PD) throughout the paediatric age range. This paper, written by a multidisciplinary group of experts, summarizes current knowledge, and provides suggestions to pharmaceutical companies, regulatory agencies and academicians on how to incorporate the latest knowledge regarding developmental pharmacology and innovative techniques into neonatal and paediatric drug development. Biological aspects of drug absorption, distribution, metabolism and excretion throughout development are summarized. Although this area made enormous progress during the last two decades, remaining knowledge gaps were identified. Minimal risk and burden designs allow for optimally informative but minimally invasive PK sampling, while concomitant profiling of drug metabolites may provide additional insight in the unique PK behaviour in children. Furthermore, developmental PD needs to be considered during drug development, which is illustrated by disease- and/or target organ-specific examples. Identifying and testing PD targets and effects in special populations, and application of age- and/or population-specific assessment tools are discussed. Drug development plans also need to incorporate innovative techniques such as preclinical models to study therapeutic strategies, and shift from sequential enrolment of subgroups, to more rational designs. To stimulate appropriate research plans, illustrations of specific PK/PD-related as well as drug safety-related challenges during drug development are provided. The suggestions made in this joint paper of the Innovative Medicines Initiative conect4children Expert group on Developmental Pharmacology and the European Society for Developmental, Perinatal and Paediatric Pharmacology, should facilitate all those involved in drug development.

Pharmacokinetic modeling and simulation to understand diamorphine dose-response in neonates, children, and adolescents

Pharmacokinetic-pharmacodynamic modeling and simulation can facilitate understanding and prediction of exposure-response relationships in children with acute or chronic pain. The pharmacokinetics of diamorphine (diacetylmorphine, heroin), a strong opioid, remain poorly quantified in children and dose is often guided by clinical acumen. This tutorial demonstrates how a model to describe intranasal and intravenous diamorphine pharmacokinetics can be fashioned from a model for diamorphine disposition in adults and a model describing morphine disposition in children. Allometric scaling and maturation models were applied to clearances and volumes to account for differences in size and age between children and adults. The utility of modeling and simulation to gain insight into the analgesic exposure-response relationship is demonstrated. The model explains reported observations, can be used for interrogation, interpolated to determine equianalgesia and inform future clinical studies. Simulation was used to illustrate how diamorphine is rapidly metabolized to morphine via its active metabolite 6-monoacetylmorphine, which mediates an early dopaminergic response accountable for early euphoria. Morphine formation is then responsible for the slower, prolonged analgesic response. Time-concentration profiles of diamorphine and its metabolites reflected disposition changes with age and were used to describe intravenous and intranasal dosing regimens. These indicated that morphine exposure in children after intranasal diamorphine 0.1 mg.kg-1 was similar to that after intranasal diamorphine 5 mg in adults. A target concentration of morphine 30 μg.L-1 can be achieved by a diamorphine intravenous infusion in neonates 14 μg.kg-1 .h-1 , in a 5-year-old child 42 μg.kg-1 .h-1 and in an 15 year-old-adolescent 33 μg.kg-1 .h-1 .

Reviewing Data Integrated for PBPK Model Development to Predict Metabolic Drug-Drug Interactions: Shifting Perspectives and Emerging Trends

Physiologically-based pharmacokinetics (PBPK) modeling is a robust tool that supports drug development and the pharmaceutical industry and regulatory authorities. Implementation of predictive systems in the clinics is more than ever a reality, resulting in a surge of interest for PBPK models by clinicians. We aimed to establish a repository of available PBPK models developed to date to predict drug-drug interactions (DDIs) in the different therapeutic areas by integrating intrinsic and extrinsic factors such as genetic polymorphisms of the cytochromes or environmental clues. This work includes peer-reviewed publications and models developed in the literature from October 2017 to January 2021. Information about the software, type of model, size, and population model was extracted for each article. In general, modeling was mainly done for DDI prediction via Simcyp^® software and Full PBPK. Overall, the necessary physiological and physio-pathological parameters, such as weight, BMI, liver or kidney function, relative to the drug absorption, distribution, metabolism, and elimination and to the population studied for model construction was publicly available. Of the 46 articles, 32 sensibly predicted DDI potentials, but only 23% integrated the genetic aspect to the developed models. Marked differences in concentration time profiles and maximum plasma concentration could be explained by the significant precision of the input parameters such as Tissue: plasma partition coefficients, protein abundance, or Ki values. In conclusion, the models show a good correlation between the predicted and observed plasma concentration values. These correlations are all the more pronounced as the model is rich in data representative of the population and the molecule in question. PBPK for DDI prediction is a promising approach in clinical, and harmonization of clearance prediction may be helped by a consensus on selecting the best data to use for PBPK model development.

Pharmacokinetics of Antibiotics in Pediatric Intensive Care: Fostering Variability to Attain Precision Medicine

Children show important developmental and maturational changes, which may contribute greatly to pharmacokinetic (PK) variability observed in pediatric patients. These PK alterations are further enhanced by disease-related, non-maturational factors. Specific to the intensive care setting, such factors include critical illness, inflammatory status, augmented renal clearance (ARC), as well as therapeutic interventions (e.g., extracorporeal organ support systems or whole-body hypothermia [WBH]). This narrative review illustrates the relevance of both maturational and non-maturational changes in absorption, distribution, metabolism, and excretion (ADME) applied to antibiotics. It hereby provides a focused assessment of the available literature on the impact of critical illness—in general, and in specific subpopulations (ARC, extracorporeal organ support systems, WBH)—on PK and potential underexposure in children and neonates. Overall, literature discussing antibiotic PK alterations in pediatric intensive care is scarce. Most studies describe antibiotics commonly monitored in clinical practice such as vancomycin and aminoglycosides. Because of the large PK variability, therapeutic drug monitoring, further extended to other antibiotics, and integration of model-informed precision dosing in clinical practice are suggested to optimise antibiotic dose and exposure in each newborn, infant, or child during intensive care.

Simplified Dosing Regimens for Gentamicin in Neonatal Sepsis

Background: The effectiveness of antibiotics for the treatment of severe bacterial infections in newborns in resource-limited settings has been determined by empirical evidence. However, such an approach does not warrant optimal exposure to antibiotic agents, which are known to show different disposition characteristics in this population. Here we evaluate the rationale for a simplified regimen of gentamicin taking into account the effect of body size and organ maturation on pharmacokinetics. The analysis is supported by efficacy data from a series of clinical trials in this population.

Methods: A previously published pharmacokinetic model was used to simulate gentamicin concentration vs. time profiles in a virtual cohort of neonates. Model predictive performance was assessed by supplementary external validation procedures using therapeutic drug monitoring data collected in neonates and young infants with or without sepsis. Subsequently, clinical trial simulations were performed to characterize the exposure to intra-muscular gentamicin after a q.d. regimen. The selection of a simplified regimen was based on peak and trough drug levels during the course of treatment.

Results: In contrast to current World Health Organization guidelines, which recommend gentamicin doses between 5 and 7.5 mg/kg, our analysis shows that gentamicin can be used as a fixed dose regimen according to three weight-bands: 10 mg for patients with body weight <2.5 kg, 16 mg for patients with body weight between 2.5 and 4 kg, and 30 mg for those with body weight >4 kg.

Conclusion: The choice of the dose of an antibiotic must be supported by a strong scientific rationale, taking into account the differences in drug disposition in the target patient population. Our analysis reveals that a simplified regimen is feasible and could be used in resource-limited settings for the treatment of sepsis in neonates and young infants with sepsis aged 0–59 days.

Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies.

Use of prior knowledge and extrapolation in paediatric drug development: A case study with deferasirox

The characterisation of pharmacokinetics, pharmacodynamics and dose-exposure-response relationships requires data arising from well-designed study protocols and a relatively large sample from the target patient population. Such a prerequisite is unrealistic for paediatric rare diseases, where the patient population is often vulnerable and very small. In such cases, different sources of data and knowledge need to be considered to ensure trial designs are truly informative and oncoming data can be analysed efficiently. Here, we use clinical trial simulations to assess the contribution of historical data for (1) the analysis of sparse samples from a limited number of children and (2) the optimisation of study design when an increase in the number of subjects is not feasible. The evaluation of the pharmacokinetics of deferasirox in paediatric patients affected by haemoglobinopathies was used as case study. Our investigation shows that the incorporation of prior knowledge increases parameter precision and probability of successful convergence from only 12% with no priors to 56% and 75% for weakly and highly informative priors, respectively. In addition, results suggest that even when only one sample is collected per subject, as implemented in the original trial and in many other examples in clinical research, there is a 60% probability of biased parameter estimates (>25%). In conjunction with adult prior information and optimisation techniques, the probability of bias could be limited to <20% by increasing the number of samples/subject from 1 to 3. The methodology described here can be easily applied to other studies in small populations.

Regulatory strategies for rare diseases under current global regulatory statutes: a discussion with stakeholders

Rare or orphan diseases often are inherited and overwhelmingly affect children. Many of these diseases have no treatments, are incurable, and have a devastating impact on patients and their families. Regulatory standards for drug approval for rare diseases must ensure that patients receive safe and efficacious treatments. However, regulatory bodies have shown flexibility in applying these standards to drug development in rare diseases, given the unique challenges that hinder efficient and effective traditional clinical trials, including low patient numbers, limited understanding of disease pathology and progression, variability in disease presentation, and a lack of established endpoints.

To take steps toward improving rare disease clinical development strategies under current global regulatory statutes, Amicus Therapeutics, Inc. and BioNJ convened a 1-day meeting that included representatives from the Food and Drug Administration (FDA), biopharmaceutical industry, and not-for-profit agencies. The meeting focused on orphan diseases in pediatric and adult patients and was intended to identify potential strategies to overcome regulatory hurdles through open collaboration.

During this meeting, several strategies were identified to minimize the limitations associated with low patient numbers in rare diseases, including the use of natural history to generate historical control data in comparisons, simulations, and identifying inclusion/exclusion criteria and appropriate endpoints. Novel approaches to clinical trial design were discussed to minimize patient exposure to placebo and to reduce the numbers of patients and clinical trials needed for providing substantial evidence. Novel statistical analysis approaches were also discussed to address the inherent challenges of small patient numbers. Areas of urgent unmet need were identified, including the need to develop registries that protect patient identities, to establish close collaboration and communication between the sponsor and regulatory bodies to address methodological and statistical challenges, to collaborate in pre-competitive opportunities within multiple sponsors and in conjunction with academia and disease-specific patient advocacy groups for optimal data sharing, and to develop harmonized guidelines for data extrapolation from source to target pediatric populations. Ultimately, these innovations will help in solving many regulatory challenges in rare disease drug development and encourage the availability of new treatments for patients with rare diseases.

Clinical Pharmacology and Pharmacometrics to Better Understand Physiological Changes During Pregnancy and Neonatal Life

Pregnant women, fetuses, and newborns are particularly vulnerable patient populations. During pregnancy, the body is subject to physiological changes that influence the pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in pregnant women can result in sub-therapeutic or toxic effects, putting not only the pregnant woman but also her fetus at risk. During neonatal life, maturation processes also affect pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in newborns leads not only to short-term complications but can also have a negative impact on the long-term development of infants and children. For these reasons, it is crucial to characterize physiological changes in pregnant women, describe placental transfer kinetics of drugs, and describe physiological changes related to the transition from intrauterine to extrauterine life and maturation processes in preterm and term neonates. Quantitative pharmacological approaches such as pharmacometric and physiologically-based modeling and model-based simulations can be useful to better understand and predict such physiological changes and their effects on drug exposure and response. This review article (1) gives an overview of physiological changes in pregnant women, their fetuses, and (pre)term neonates, (2) presents case studies to illustrate applications of new modeling and simulation approaches, and (3) discusses challenges and opportunities in optimizing and personalizing treatments during pregnancy and neonatal life.

Dose adjustment in orphan disease populations: the quest to fulfill the requirements of physiologically based pharmacokinetics

INTRODUCTION

While the media is engaged and fascinated by the idea of 'Precision Medicine', the nuances related to 'Precision Dosing' seem to be largely ignored. Assuming the 'right drug' is selected, clinicians still need to decide on the 'right dose' for individuals. Ideally, optimal dosing should be studied in clinical trials; however, many drugs on the market lack evidence-based dosing recommendations, and small groups of patients (orphan disease populations) are dependent on local guidance and clinician experience to determine drug dosage adjustments. Areas Covered: This report explores the current understanding of dosing adjustment in special populations and examines the requirements for developing 'in silico' models for pediatric, elderly and pregnant patients. The report also highlights current use of modeling to provide evidence-based recommendations for drug labeling in the absence of complete clinical trials in orphan disease populations. Expert Opinion: Physiologically based pharmacokinetics (PBPK) is an attractive prospect for determining the best drug dosage adjustments in special populations. However, it is not sufficient for individualized, or even stratified dosing, unless the systems (drug-independent) data required to build robust PBPK models are obtained. Such models are not a substitute for clinical trials, but they are an alternative to undocumented and inconsistent guesswork.

Paracetamol in Older People: Towards Evidence-Based Dosing?

Paracetamol is the most commonly used analgesic in older people, and is mainly dosed according to empirical dosing guidelines. However, the pharmacokinetics and thereby the effects of paracetamol can be influenced by physiological changes occurring with ageing. To investigate the steps needed to reach more evidence-based paracetamol dosing regimens in older people, we applied the concepts used in the paediatric study decision tree. A search was performed to retrieve studies on paracetamol pharmacokinetics and safety in older people (> 60 years) or studies that performed a (sub) analysis of pharmacokinetics and/or safety in older people. Of 6088 articles identified, 259 articles were retained after title and abstract screening. Further abstract and full-text screening identified 27 studies, of which 20 described pharmacokinetics and seven safety. These studies revealed no changes in absorption with ageing. A decreased (3.9-22.9%) volume of distribution (Vd) in robust older subjects and a further decreased Vd (20.3%) in frail older compared with younger subjects was apparent. Like Vd, age and frailty decreased paracetamol clearance (29-45.7 and 37.5%) compared with younger subjects. Due to limited and heterogeneous evidence, it was difficult to draw firm and meaningful conclusions on changed risk for paracetamol safety in older people. This review is a first step towards bridging knowledge gaps to move to evidence-based paracetamol dosing in older subjects. Remaining knowledge gaps are safety when using therapeutic dosages, pharmacokinetics changes in frail older people, and to what extent changes in paracetamol pharmacokinetics should lead to a change in dosage in frail and robust older people.

Better medicines for neonates: Improving medicine development, testing, and prescribing

Pharmacotherapy is a powerful tool to improve the outcome of neonates. Unfortunately, the potential health impact of pharmacotherapy in neonates remains underexplored. This necessitates a structured approach to go beyond the current practice of trial and error, reflected in off-label prescription. The existing regulatory framework hereby provides a structure to reflect about aspects like pharmacokinetic models for dose selection and outcome assessment, including long-term safety. Future medicine development should also be driven by neonatal needs, diseases and pathophysiology, since surfactant is the latest product developed for preterm neonates. The potential impact is illustrated by ongoing repurposing (propranolol, allopurinol, erythropoietin, Insulin-like Growth Factor-1) projects. Clinical researchers will be crucial to close the knowledge gap by developing dose selection tools and outcome assessment tools and by exploring pathophysiological mechanisms. The final step of such a structured approach cycle is the subsequent translation of accumulated knowledge into improved prescribing.

Considerations for pediatric trial designs and analyses

There are challenges in designing pediatric trials arising from special ethical issues and the relatively small accessible patient population. The application of conventional phase 3 trial designs to pediatrics is not realistic in some therapeutic areas. To address this issue, we propose various approaches for designing pediatric trials that incorporate data available from adult studies using James-Stein shrinkage estimation, empirical shrinkage estimation, and Bayesian methods. We also apply the concept of consistency used in multi-regional trials to pediatric trials. The performance of these methods is assessed through representative scenarios and an example using actual Type 2 diabetes mellitus (T2DM) trials.

European regulatory perspective on pediatric physiologically based pharmacokinetic models

Physiologically based pharmacokinetic (PBPK) models offer a mechanistic understanding of the disposition of the drug in the body. When well informed and conducted, this may lead to more efficient clinical studies in the vulnerable pediatric population. A review of pediatric submissions to European regulatory authorities has shown a limited number of recent examples. The use of PBPK models to inform pediatric drug development is encouraged. It is, however, important to consider the confidence in the predictions. A qualification of the PBPK platform for the intended purpose should be performed, and a learn-and-confirm approach is recommended. Further research in this area is encouraged to inform important parameters, and to increase availability of pediatric data for model qualification.

Impact of disease, drug and patient adherence on the effectiveness of antiviral therapy in pediatric HIV

INTRODUCTION

Maintaining effective antiretroviral treatment for life is a major problem in both resource-limited and resource-rich countries. Despite the progress observed in paediatric antiretroviral therapy, approximately 12% of children still experience treatment failure due to drug resistance, inadequate dosing and poor adherence. We explore the current status of antiretroviral therapy in children with focus on the interaction between disease, drug pharmacokinetics and patient behavior, all of which are strongly interconnected and determine treatment outcome. Areas covered: An overview is provided of the viral characteristics and available drug combinations aimed at the prevention of resistance. In this context, the role of patient adherence is scrutinized. A detailed assessment of factors affecting adherence is presented together with the main strategies to enhance treatment response in children. Expert opinion: Using modeling and simulation, a framework for characterizing the forgiveness of non-adherence for specific antiretroviral drugs in children is proposed in which information on pharmacokinetics, pharmacokinetic-pharmacodynamic relationships and viral dynamics is integrated. This approach represents an opportunity for the simplification of dosing regimens taking into account the interaction between these factors. Based on clinical trial simulation scenarios, we envisage the possibility of assessing the impact of variable adherence to antiretroviral drug combinations in HIV-infected children.

Enhancing value of clinical pharmacodynamics in oncology drug development: An alliance between quantitative pharmacology and translational science

Clinical pharmacodynamic evaluation is a key component of the "pharmacologic audit trail" in oncology drug development. We posit that its value can and should be greatly enhanced via application of a robust quantitative pharmacology framework informed by biologically mechanistic considerations. Herein, we illustrate examples of intersectional blindspots across the disciplines of quantitative pharmacology and translational science and offer a roadmap aimed at enhancing the caliber of clinical pharmacodynamic research in the development of oncology therapeutics.

Population pharmacokinetics and dosing recommendations for the use of deferiprone in children younger than 6 years

AIMS

Despite long clinical experience with deferiprone, there is limited information on its pharmacokinetics in children aged <6 years. Here we assess the impact of developmental growth on the pharmacokinetics of deferiprone in this population using a population approach. Based on pharmacokinetic bridging concepts, we also evaluate whether the recommended doses yield appropriate systemic exposure in this group of patients.

METHODS

Data from a study in which 18 paediatric patients were enrolled were available for the purposes of this analysis. Patients were randomised to three deferiprone dose levels (8.3, 16.7 and 33.3 mg kg^-1 ). Blood samples were collected according to an optimised sampling scheme in which each patient contributed to a maximum of five samples. A population pharmacokinetic model was developed using NONMEM v.7.2. Model selection criteria were based on graphical and statistical summaries.

RESULTS

A one-compartment model with first-order absorption and first-order elimination best described the pharmacokinetics of deferiprone. Drug disposition parameters were affected by body weight, with both clearance and volume increasing allometrically with size. Simulation scenarios show that comparable systemic exposure (AUC) is achieved in children and adults after similar dose levels in mg kg^-1 , with median (5-95^th quantiles) AUC values, respectively, of 340.6 (223.2-520.0) μmol l^-1  h and 318.5 (200.4-499.0) μmol l^-1  h at 75 mg kg^-1 day^-1 , and 453.7 (297.3-693.0) μmol l^-1  h and 424.2 (266.9-664.0) μmol l^-1  h at 100 mg kg^-1  day^-1 given as three times daily (t.i.d.) doses.

CONCLUSIONS

Based on the current findings, a dosing regimen of 25 mg kg^-1  t.i.d. is recommended in children aged <6 years, with the possibility of titration up to 33.3 mg kg^-1  t.i.d.

Bottom-up Meets Top-down: Complementary Physiologically Based Pharmacokinetic and Population Pharmacokinetic Modeling for Regulatory Approval of a Dosing Algorithm of Valganciclovir in Very Young Children

Population pharmacokinetic (PopPK) and physiologically based pharmacokinetic (PBPK) models are frequently used to support pediatric drug development. Both methods have strengths and limitations and we used them complementarily to support the regulatory approval of a dosing algorithm for valganciclovir (VGCV) in children <4 months old. An existing pediatric PBPK model was extended to neonates and showed that potential physiological differences compared with older children are minor. The PopPK model was used to simulate ganciclovir (GCV) exposures in children with population typical combinations of body size and renal function and to assess the effectiveness of an alternative dosing algorithm suggested by the US Food and Drug Administration. PBPK and PopPK confirmed that the proposed VGCV dosing algorithm achieves similar GCV exposures in children of all ages and that the alternative dosing algorithm leads to underexposure in a substantial fraction of patients. Our approach raised the confidence in the VGCV dosing algorithm for children <4 months old and supported the regulatory approval.

PBPK modeling and simulation in drug research and development

Physiologically based pharmacokinetic (PBPK) modeling and simulation can be used to predict the pharmacokinetic behavior of drugs in humans using preclinical data. It can also explore the effects of various physiologic parameters such as age, ethnicity, or disease status on human pharmacokinetics, as well as guide dose and dose regiment selection and aid drug-drug interaction risk assessment. PBPK modeling has developed rapidly in the last decade within both the field of academia and the pharmaceutical industry, and has become an integral tool in drug discovery and development. In this mini-review, the concept and methodology of PBPK modeling are briefly introduced. Several case studies were discussed on how PBPK modeling and simulation can be utilized through various stages of drug discovery and development. These case studies are from our own work and the literature for better understanding of the absorption, distribution, metabolism and excretion (ADME) of a drug candidate, and the applications to increase efficiency, reduce the need for animal studies, and perhaps to replace clinical trials. The regulatory acceptance and industrial practices around PBPK modeling and simulation is also discussed.

Children in clinical trials: towards evidence-based pediatric pharmacotherapy using pharmacokinetic-pharmacodynamic modeling

INTRODUCTION

In pediatric pharmacotherapy, many drugs are still used off-label, and their efficacy and safety is not well characterized. Different efficacy and safety profiles in children of varying ages may be anticipated, due to developmental changes occurring across pediatric life.

AREAS COVERED

Beside pharmacokinetic (PK) studies, pharmacodynamic (PD) studies are urgently needed. Validated PKPD models can be used to derive optimal dosing regimens for children of different ages, which can be evaluated in a prospective study before implementation in clinical practice. Strategies should be developed to ensure that formularies update their drug dosing guidelines regularly according to the most recent advances in research, allowing for clinicians to integrate these guidelines in daily practice. Expert commentary: We anticipate a trend towards a systems-level approach in pediatric modeling to optimally use the information gained in pediatric trials. For this approach, properly designed clinical PKPD studies will remain the backbone of pediatric research.

Clinical research in neonates and infants: Challenges and perspectives

To date, up to 65% of drugs used in neonates and infants are off-label or unlicensed, as they were implemented in clinical care without the usual regulatory phases of pharmacological drug development. Pharmacotherapy in this age group is still mainly based on the individual clinical expertise of specialized pediatricians. Pharmacological trials involving neonates are indeed more difficult to perform: appropriate dosing is hampered by the rapid physiological changes occurring at this stage of development, and the selection of proper end-points and biomarkers is complicated by the limited knowledge of the pathophysiology of the specific diseases of infancy. Moreover, there are many ethical challenges in planning and conducting drug studies in pediatric patients (especially in newborns and infants). In the current review, we address some challenges and discuss possible perspectives to stimulate scientific and clinical pharmacological research in neonates and infants. We hereby aim to illustrate the add on value of the regulatory framework for model-based neonatal medicinal development currently used in Europe and the United States. We provide several examples of successful recent pharmacological trials performed in neonates and infants. In these examples, success was ensured by the implementation of specific pharmacokinetic assessments, thanks to accurate drug dosing achieved with a combination of dose validation, population pharmacokinetics and mathematical models of drug clearance and distribution; moreover, age-specific pharmacodynamics was considered via appropriate evaluations of drug efficacy with end-points adapted to the peculiar pathophysiology of diseases in this age group. These "pharmacological" challenges add to the ethical challenges that are always present in planning and conducting clinical studies in neonates and infants and support the opinion that clinical research in pediatrics should be evaluated by ad hoc ethical committees with specific expertise.

Sampling Optimization in Pharmacokinetic Bridging Studies: Example of the Use of Deferiprone in Children With β-Thalassemia

Despite wide clinical experience with deferiprone, the optimum dosage in children younger than 6 years remains to be established. This analysis aimed to optimize the design of a prospective clinical study for the evaluation of deferiprone pharmacokinetics in children. A 1-compartment model with first-order oral absorption was used for the purposes of the analysis. Different sampling schemes were evaluated under the assumption of a constrained population size. A sampling scheme with 5 samples per subject was found to be sufficient to ensure accurate characterization of the pharmacokinetics of deferiprone. Whereas the accuracy of parameters estimates was high, precision was slightly reduced because of the small sample size (CV% >30% for Vd/F and KA). Mean AUC ± SD was found to be 33.4 ± 19.2 and 35.6 ± 20.2 mg · h/mL, and mean Cmax ± SD was found to be 10.2 ± 6.1 and 10.9 ± 6.7 mg/L based on sparse and frequent sampling, respectively. The results showed that typical frequent sampling schemes and sample sizes do not warrant accurate model and parameter identifiability. Expectation of the determinant (ED) optimality and simulation-based optimization concepts can be used to support pharmacokinetic bridging studies. Of importance is the accurate estimation of the magnitude of the covariate effects, as they partly determine the dose recommendation for the population of interest.

Physiologically based pharmacokinetic and pharmacodynamic modeling in cancer drug development: status, potential and gaps

INTRODUCTION

Modeling and simulation have become important means of answering questions relevant to the development of a drug, making it possible to assess risks early and to reduce costs. Physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models contribute to a comprehensive understanding of the drug, covering specific questions from early discovery through lifecycle management stages. As for other disease areas, in oncology, PBPK and PD models are important topics that remain to be addressed.

AREAS COVERED

This review describes current PBPK and PD approaches, their applicability in drug development in general and specifically in the area of oncology. It discusses the current status and then focuses on key challenges and the potential for future use. It provides cases in which modeling currently cannot answer the questions and assesses the requirements to close gaps for PBPK/PD in oncology.

EXPERT OPINION

PBPK/PD models have led to improvements in identifying risks and reducing costs during the drug development process. Nevertheless, there is a lot of potential, where more rigorous integration of biological knowledge and specific experimental design would result in a more comprehensive biological picture. Ideally, such approaches would reveal the extent to which preclinical work can be extrapolated to clinical settings, thus enabling reliable prediction and, ultimately, reducing failed trials in clinical oncology.

Extrapolation of Valacyclovir Posology to Children Based on Pharmacokinetic Modeling

BACKGROUND

Valacyclovir is a prodrug of acyclovir. Although acyclovir is approved for children in Europe, valacyclovir is not approved, despite being used off-label. The aim of the study was to extrapolate the approved dosages of acyclovir, to valacyclovir dosages, in children using Monte Carlo simulations based on the population pharmacokinetic (PopPK) models of valacyclovir and acyclovir.

METHODS

Assuming that the recommended dosages of acyclovir are efficacious, a PopPK model of acyclovir was used to perform simulations to determine a critical concentration (Ccrit) for which a target criterion is fulfilled, ie, 90% of the simulated patients have acyclovir levels above Ccrit for at least half the time. The same was done for a secondary target, drug exposure, determining a critical area under the curve in 24 hours at steady state. Then a PopPK model of valacyclovir was used to determine by simulations, dosage regimens that fulfill the criteria for both targets. This was repeated for various indications and age groups.

RESULTS

Indicatively, for the treatment of varicella zoster virus, in ages 2-12 years, Ccrit and critical area under the curve in 24 hours at steady state were found to be 0.39 mg/L and 9.6 mg/L × h, respectively, using the acyclovir approved doses 20 mg/kg 4 times daily. For these breakpoints, a 20 mg/kg, 3 times daily, valacyclovir dose achieves the targets in 97% and 100% of the patients, respectively. We found that some patients receive higher than the ideal doses of acyclovir.

CONCLUSIONS

Simulations were used to determine the appropriate doses of valacyclovir in children to support a pediatric investigation plan targeting a paediatric-use marketing authorization application in the European Medicines Agency.

Treating disorders of the neonatal central nervous system: pharmacokinetic and pharmacodynamic considerations with a focus on antiepileptics

A major consideration in the treatment of neonatal disorders is that the selected drug, dose and dosage frequency is safe, effective and appropriate for the intended patient population. Thus, a thorough knowledge of the pharmacokinetics and pharmacodynamics of the chosen drug within the patient population is essential. In paediatric and neonatal populations two additional challenges can often complicate drug treatment - the inherently greater physiological variability, and a lack of robust clinical evidence of therapeutic range. There has traditionally been an overreliance in paediatric medicine on extrapolating doses from adult values by adjusting for bodyweight or body surface area, but many other sources of variability exist which complicate the choice of dose in neonates. The lack of reliable drug dosage data in neonates has been highlighted by regulatory authorities, as only ~50% of the most commonly used paediatric medicines have been examined in a paediatric population. Moreover, there is a paucity of information on the pharmacokinetic parameters which affect drug concentrations in different body tissues, and pharmacodynamic responses to drugs in the neonate. Thus, in the present review, we draw attention to the main pharmacokinetic factors that influence the unbound brain concentration of neuroactive drugs. Moreover, the pharmacodynamic differences between neonates and adults that affect the activity of centrally-acting therapeutic agents are briefly examined, with a particular emphasis on antiepileptic drugs.

Influence of covariate distribution on the predictive performance of pharmacokinetic models in paediatric research

AIMS

The accuracy of model-based predictions often reported in paediatric research has not been thoroughly characterized. The aim of this exercise is therefore to evaluate the role of covariate distributions when a pharmacokinetic model is used for simulation purposes.

METHODS

Plasma concentrations of a hypothetical drug were simulated in a paediatric population using a pharmacokinetic model in which body weight was correlated with clearance and volume of distribution. Two subgroups of children were then selected from the overall population according to a typical study design, in which pre-specified body weight ranges (10-15 kg and 30-40 kg) were used as inclusion criteria. The simulated data sets were then analyzed using non-linear mixed effects modelling. Model performance was assessed by comparing the accuracy of AUC predictions obtained for each subgroup, based on the model derived from the overall population and by extrapolation of the model parameters across subgroups.

RESULTS

Our findings show that systemic exposure as well as pharmacokinetic parameters cannot be accurately predicted from the pharmacokinetic model obtained from a population with a different covariate range from the one explored during model building. Predictions were accurate only when a model was used for prediction in a subgroup of the initial population.

CONCLUSIONS

In contrast to current practice, the use of pharmacokinetic modelling in children should be limited to interpolations within the range of values observed during model building. Furthermore, the covariate point estimate must be kept in the model even when predictions refer to a subset different from the original population.

Characterizing variability in warfarin dose requirements in children using modelling and simulation

Aims

Although genetic, clinical and demographic factors have been shown to explain approximately half of the inter-individual variability in warfarin dose requirement in adults, less is known about causes of dose variability in children. This study aimed to identify and quantify major genetic, clinical and demographic sources of warfarin dose variability in children using modelling and simulation.

Methods

Clinical, demographic and genetic data from 163 children with a median age of 6.3 years (range 0.06–18.9 years), covering over 183 years of warfarin therapy and 6445 INR observations were used to update and optimize a published adult pharmacometric warfarin model for use in children.

Results

Genotype effects in children were found to be comparable with what has been reported for adults, with CYP2C9 explaining up to a four-fold difference in dose (CYP2C9 *1/*1 vs. *3/*3) and VKORC1 explaining up to a two-fold difference in dose (VKORC1 G/G vs. A/A), respectively. The relationship between bodyweight and warfarin dose was non-linear, with a three-fold difference in dose for a four-fold difference in bodyweight. In addition, age, baseline and target INR, and time since initiation of therapy, but not CYP4F2 genotype, had a significant impact on typical warfarin dose requirements in children.

Conclusions

The updated model provides quantitative estimates of major clinical, demographic and genetic factors impacting on warfarin dose variability in children. With this new knowledge more individualized dosing regimens can be developed and prospectively evaluated in the pursuit of improving both efficacy and safety of warfarin therapy in children.

Population pharmacokinetics of deferiprone in healthy subjects

AIMS

To characterize the pharmacokinetics of deferiprone in healthy subjects using a model-based approach and to assess the effect of demographic and physiological factors on drug exposure.

METHODS

Data from 55 adult healthy subjects receiving deferiprone (solution 100 mg ml(-1)) were used for model building purposes. A population pharmacokinetic analysis was performed using nonmem v.7.2. The contribution of gender, age, weight and creatinine clearance (CLcr) on drug disposition was evaluated according to standard forward inclusion, backward deletion procedures. Model selection criteria were based on graphical and statistical summaries.

RESULTS

A one compartment model with first order oral absorption was found to describe best the pharmacokinetics of deferiprone. Simulated exposure values were comparable with previously published data. Mean AUC estimates were 45.8 and 137.4 mg l(-1)  h, whereas Cmax increased from 17.6 to 26.5 mg l(-1) after administration of 25 and 75 mg kg(-1) doses, respectively. Gender differences in the apparent volume of distribution (20%) have been identified, which are unlikely to be of clinical relevance. Furthermore, simulation scenarios reveal that dose adjustment is required for patients with reduced CLcr . Doses of 60, 40 and 25 mg kg(-1) for patients showing mild, moderate and severe renal impairment are proposed based on CLcr values of 60-89, 30-59 and 15-29 ml min(-1), respectively.

CONCLUSIONS

Our analysis has enabled the assessment of the impact of gender and CLcr on the pharmacokinetics of deferiprone. Moreover, it provides the basis for dosing recommendations in renal impairment. The implication of these covariates on systemic exposure is currently not available in the prescribing information of deferiprone.

Bridging the gap: a review of dose investigations in paediatric investigation plans

Aims

In the EU, development of new medicines for children should follow a prospectively agreed paediatric investigation plan (PIP). Finding the right dose for children is crucial but challenging due to the variability of pharmacokinetics across age groups and the limited sample sizes available. We examined strategies adopted in PIPs to support paediatric dosing recommendations to identify common assumptions underlying dose investigations and the attempts planned to verify them in children.

Methods

We extracted data from 73 PIP opinions recently adopted by the Paediatric Committee of the European Medicines Agency. These opinions represented 79 medicinal development programmes and comprised a total of 97 dose investigation studies. We identified the design of these dose investigation studies, recorded the analyses planned and determined the criteria used to define target doses.

Results

Most dose investigation studies are clinical trials (83 of 97) that evaluate a single dosing rule. Sample sizes used to investigate dose are highly variable across programmes, with smaller numbers used in younger children (< 2 years). Many studies (40 of 97) do not pre-specify a target dose criterion. Of those that do, most (33 of 57 studies) guide decisions using pharmacokinetic data alone.

Conclusions

Common assumptions underlying dose investigation strategies include dose proportionality and similar exposure−response relationships in adults and children. Few development programmes pre-specify steps to verify assumptions in children. There is scope for the use of Bayesian methods as a framework for synthesizing existing information to quantify prior uncertainty about assumptions. This process can inform the design of optimal drug development strategies.

Optimizing pharmacokinetic bridging studies in paediatric oncology using physiologically-based pharmacokinetic modelling: application to docetaxel

AIM

Applying physiologically-based pharmacokinetic (PBPK) modelling in paediatric cancer drug development is still challenging. We aimed to demonstrate how PBPK modelling can be applied to optimize dose and sampling times for a paediatric pharmacokinetic (PK) bridging study in oncology and to compare with the allometric scaling population PK (AS-popPK) approach, using docetaxel as an example.

METHODS

A PBPK model for docetaxel was first developed for adult cancer patients using Simcyp® and subsequently used to predict its PK profiles in children by accounting for age-dependent physiological differences. Dose (mg m(-2) ) requirements for children aged 0-18 years were calculated to achieve targeted exposure in adults. Simulated data were then analyzed using population PK modelling with MONOLIX® in order to perform design optimization with the population Fisher information matrix (PFIM). In parallel, the AS-popPK approach was performed for the comparison.

RESULTS

The PBPK model developed for docetaxel adequately predicted its PK profiles in both adult and paediatric cancer patients (predicted clearance and volume of distribution within 1.5 fold of observed data). The revised dose of docetaxel for a child over 1.5 years old was higher than the adult dose. Considering clinical constraints, the optimal design contained two groups of 15 patients, having three or four sampling times and had good predicted relative standard errors (RSE<30%) for almost all parameters. The AS-popPK approach performed reasonably well but could not predict for very young children.

CONCLUSION

This research shows the clinical utility of PBPK modelling in combination with population PK modelling and optimal design to support paediatric oncology development.

Extrapolation of enalapril efficacy from adults to children using pharmacokinetic/pharmacodynamic modelling

OBJECTIVES

To extrapolate enalapril efficacy to children 0-6 years old, a pharmacokinetic/pharmacodynamic (PKPD) model was built using literature data, with blood pressure as the PD endpoint.

METHODS

A PK model of enalapril was developed from literature paediatric data up to 16 years old. A PD model of enalapril was fitted to adult literature response vs time data with various doses. The final PKPD model was validated with literature paediatric efficacy observations (diastolic blood pressure (DBP) drop after 2 weeks of treatment) in children of age 6 years and higher. The model was used to predict enalapril efficacy for ages 0-6 years.

KEY FINDINGS

A two-compartment PK model was chosen with weight, reflecting indirectly age as a covariate on clearance and central volume. An indirect link PD model was chosen to describe drug effect. External validation of the model's capability to predict efficacy in children was successful. Enalapril efficacy was extrapolated to ages 1-11 months and 1-6 years finding the mean DBP drop 11.2 and 11.79 mmHg, respectively.

CONCLUSIONS

Mathematical modelling was used to extrapolate enalapril efficacy to young children to support a paediatric investigation plan targeting a paediatric-use marketing authorization application.

Integration of PKPD relationships into benefit-risk analysis

AIM

Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit-risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit-risk assessment. In addition, we propose the use of pharmacokinetic-pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents.

METHODS

A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit-risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile.

RESULTS

A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit-risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit-risk balance before extensive evidence is generated in clinical practice.

CONCLUSIONS

Benefit-risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials.

Modeling and simulation in pediatric drug therapy: Application of pharmacometrics to define the right dose for children

During the past decades significant progress has been made in our understanding of the importance of age-appropriate development of new drug therapies in children. Importantly, several regulatory initiatives in Europe and the US have provided a framework for a rationale. In the US, most notably the enactment of the Best Pharmaceuticals for Children Act (BPCA) and Product Research and Equity Act (PREA) has facilitated the studying of on-patent and off-patent drugs in children. The biggest challenge in pediatric studies is defining a safe and effective dose or dose range in a patient population that can span from premature neonates to adolescents. From a mechanism-based perspective, advances in the science of quantitative pharmacology and pharmacometrics have resulted in the development of model-based approaches to better describe and understand important age-related factors influencing drug disposition and response in pediatric patients. The application of modeling and simulation has been shown to result in better estimates of pediatric doses as evidenced by several studies, although the optimal approach is still being debated. The extrapolation of efficacy findings from adults to the pediatric population has streamlined the development process especially for studies in older children. However, a focus on developmental changes in neonates and infants as well as further developing a paradigm for conducting pharmacodynamic studies in neonates, infants, and children remain important unmet needs. In this overview we will review current approaches for age-appropriate dose selection and highlight ongoing efforts to define exposure-response and clinical outcome relationships across the pediatric age spectrum.

Psychiatric diseases moving towards adolescents and children: How much room is there for extrapolation?

Since medicines for psychiatric diseases are often studied in adults first, it would be useful if data from efficacy trials in adults could be extrapolated to children and adolescents. However, it is not sufficient to adapt the adult dosages to achieve systemic exposure levels similar to those effective in adults. This can be done with increasing predictive accuracy but before accepting that the same plasma levels should result in the same efficacy as in adults both the mechanism of action of the drug and the pathophysiology of the disease must be considered. For psychiatric disorders there is often insufficient evidence to support the assumptions for extrapolating efficacy as it is not even always sure that the same diagnostic categories correspond to the same disease in adults and children. Even when the basic biological alteration behind the disorder could be considered the same, the psychodynamic consequences and the role of non-pharmacological approaches to treatment may substantially differ across age groups. These facts, together with the absence of detailed historical data on the actual correlations between paediatric and adult responses for many types of psycho-therapeutic medicines, make it difficult to accept extrapolation as the main proof of efficacy in children and adolescents. A corollary is that since efficacy studies will normally be required, they should not be unduly postponed. For products addressing a medical need with good scientific plausibility, they should be initiated as soon as the anticipated safety concerns can be reasonably managed within the context of a paediatric clinical trial.

Development of a paediatric population pharmacokinetic model for valacyclovir from literature non-compartmental values originating from sparse studies and Bayesian priors: a simulation study

A preliminary population pharmacokinetic (PopPK) model of valacyclovir in children was developed from non-compartmental analysis (NCA) parameter values from literature, including several age groups, combined with Bayesian priors from a PopPK model of acyclovir, the active metabolite of valacyclovir, from literature too. Also a simulation study was carried out to evaluate the performance of various modelling choices related to the estimation of model parameters from NCA parameters originating from sparse PK studies. Assuming a one-compartment model with first order absorption, a mixed effects, meta-analysis approach was utilized which allows accounting the random intergroup variability, the detection of covariates and the application of informative Bayesian priors on the parameters. The conclusions from the simulation study calculating bias and precision for various cases, were that a model which takes explicitly into account the sampling schedule, performs better than a model using the theoretical expressions of calculating the NCA parameters. Also by using the geometric rather than the arithmetic means of NCA parameters, less biased results are obtained. These findings guided the choices for the valacyclovir model, for which informative priors from a PopPK model of acyclovir were applied for some of the parameters, in order to include a richer covariate model for clearance, not supported by the NCA dataset and a value for bioavailability. This preliminary valacyclovir model can be used in simulations to provide dosage recommendations for children of various ages and to help design more efficiently prospective clinical trials.

Pharmacogenetics-based warfarin dosing in children

Clinical factors, demographic variables and variations in two genes, CYP2C9 and VKORC1, have been shown to contribute to the variability in warfarin dose requirements among adult patients. Less is known about their relative importance for dose variability in children. A few small studies have been reported, but the results have been conflicting, especially regarding the impact of genotypes. In this article, we critically review published pharmacogenetic-based prediction models for warfarin dosing in children, and present results from a head-to-head comparison of predictive performance in a distinct cohort of warfarin-treated children. Finally we discuss what properties a prediction model should have, and what knowledge gaps need to be filled, to improve warfarin therapy in children of all ages.

Model-based assessment of dosing strategies in children for monoclonal antibodies exhibiting target-mediated drug disposition

Body weight/body surface area–based and/or tiered fixed dosing strategies are widely utilized for monoclonal antibodies with linear clearance to scale adult clinical doses to children. However, there is limited knowledge on whether or not body weight–based dosing strategies also yield comparable dose-concentration-response relationships in adults and children for monoclonal antibodies that exhibit target-mediated drug disposition. Our findings indicate that it is important to interpret pharmacokinetics information in a pharmacokinetics/pharmacodynamics context as similar systemic drug exposure in adults and children may not be reflective of the corresponding target occupancy. They further indicate that BW-based dosing is superior to fixed dosing for the same target concentration, whereas the opposite holds true for the same target amount in adults and children. Michaelis-Menten approximations yielded similar profiles compared to the full target-mediated drug disposition model for all simulation scenarios and may be used to guide the selection of appropriate dosing regimens in children.

[Pediatric drug development: ICH harmonized tripartite guideline E11 within the United States of America, the European Union, and Japan]

To address the lack of appropriate pediatric drugs available on the global market, in 2000 the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) issued the ICH E11 guideline regarding the Clinical Investigation of Medicinal Products in the Pediatric Population. This guideline considerably changes the environment of drug development for children. It has been written specifically to harmonize, promote, and facilitate high-quality and ethical clinical research for children within the ICH regions, i.e., the United States of America (USA), the European Union (EU), and Japan. This article details the various regulations applicable in each ICH region following the publication of the guideline. The framework of rewards, incentives, and obligations for pharmaceutical companies established for the development of pediatric drugs are compared. It appears that the USA and the EU have both developed specific regulations for pediatric drug development while Japan has not. However, in Japan, pharmaceutical companies (PCs) are encouraged to develop pediatric drugs voluntarily, and they may be granted additional months of market exclusivity or the postponement of the drug re-examination deadline. In both the USA and the EU, regulations aimed to increase the number of clinical studies conducted in children, in order to ensure that the necessary data are generated, determining the conditions in which a drug may be authorized to treat the pediatric population. PCs are encouraged to develop pediatric assessment, including pediatric clinical trials, which is described in a pediatric plan submitted to the relevant authorities. A system of rewards for PCs submitting an application for marketing authorization containing pediatric use information has been put in place to cover the additional investment for testing drugs in children. Subject to conditions, these rewards consist in a 6-month extension of the patent or supplementary protection. Regarding the approval for new medicinal products in these two regions, regulations require PCs to include, when it is relevant, a pediatric assessment in their drug research and development plan, which must be approved. Although these regions have implemented the ICH guideline, the regulation differs with respect to the timing of studies in children relative to adults and approval of a pediatric drug development plan. Except for special cases, the pediatric investigation plan in the EU is required to be prepared and submitted to the competent authorities upon availability of adult pharmacokinetic studies (after phase I), which means at an early phase of a new drug development plan. In the USA, the pediatric plan is requested later during the phase II or III trials. In practice, it has become difficult for pharmaceutical industries to develop a practicable clinical program for pediatrics including timelines for studies in children that satisfy both EU and USA authorities. Nevertheless, at an early stage of the development strategy, direct support and advice from competent authorities can be obtained. For the ICH regions, pediatric committees are well-established albeit less structured in Japan. Their roles are to review and assess pediatric plans, to issue recommendations, to advise pharmaceutical companies on the content and format of pediatric data to be methodically collected and analyzed, and to avoid exposing children to unnecessary or redundant clinical trials. This regulatory framework encourages the study and the development of pediatric drugs, but it is still quite difficult to actually measure the impact of the ICH E11 on increasing the number of drugs for pediatric use.

Dosage individualization in children: integration of pharmacometrics in clinical practice

BACKGROUND

Children are in a continuous and dynamically changing state of growth and development. A thorough understanding of developmental pharmacokinetics (PK) and pharmacodynamics (PD) is required to optimize drug therapy in children.

DATA SOURCES

Based on recent publications and the experience of our group, we present an outline on integrating pharmacometrics in pediatric clinical practice to develop evidence-based personalized pharmacotherapy.

RESULTS

Antibiotics in septic neonates and immunosuppressants in pediatric transplant recipients are provided as proof-of-concept to demonstrate the utility of pharmacometrics in clinical practice. Dosage individualization based on developmental PK-PD model has potential benefits of improving the efficacy and safety of drug therapy in children.

CONCLUSION

The pharmacometric technique should be better developed and used in clinical practice to personalize drug therapy in children in order to decrease variability of drug exposure and associated risks of overdose or underdose.

Paediatric drug development: the impact of evolving regulations

Children deserve medicines that are adapted to their needs. The need to include children in drug development has been recognised increasingly over the past few decades. Legal and regulatory frameworks are well established in the EU and US. The amount of work done to study medicines for children is significantly greater than it was 10 years go. Proof-of-concept has been demonstrated for all segments of the paediatric drug development pipeline. It is now time to examine how the practice of developing medicines for children has evolved within those frameworks and to determine how that work should be generalised. This review describes the development of medicines for children and critically appraises the work that has been done within those frameworks. Significant effort is needed to realize the potential provided by the current regulatory framework. Using the work programme of the Global Research in Paediatrics (GRiP) Network of Excellence as a template we outline current work and future growing points.