The Research to Accelerate Cures and Equity (RACE) for Children Act requires an assessment of molecular targets relevant to pediatric cancer. Due to the biological complexity, candidate molecular ...targets have been primarily evaluated based on single features such as the presence of mutations or deregulated expression. As the understanding of tumor biology evolves, the relevance of certain molecular targets may need to be assessed at isoform and/or mutation variant level to optimize tailored therapeutic interventions.
The Research Acceleration for Cure and Equity (RACE) for Children Act requires sponsors to submit a Pediatric Study Plan (PSP) with a proposed pediatric investigation of new molecularly targeted ...drugs and biologics that are intended for treatment of adult cancers, and whose target is relevant to pediatric cancer or provide a justification for a plan to request a deferral or waiver of the required investigation. A landscape analysis was performed to identify trends in information gaps associated with a sponsor's first initial PSP (iPSP) submission for oncologic new molecular entities received in 2021. Comments sent to sponsors by the US Food and Drug Administration (FDA) during the review process of each evaluated iPSP were categorized using nine flags relating to different portions of the PSP. For iPSPs that included a plan for a full waiver request, the most common information gap was inadequate justification based on molecular target relevance. All other sponsor proposed plans (deferral and/or partial waiver or investigation) were found to have information gaps related to clinical study features, clinical pharmacology, and/or missing clinical or nonclinical data. This landscape analysis of iPSPs shows the trends in comments that often occur during initial review and may help to provide sponsors with more direction for preparing an adequate iPSP to fulfill statutory requirements aimed at ensuring pediatric patients are considered in the development of new molecularly targeted drugs.
In 1994, the US Food and Drug Administration (FDA) proposed an approach, based on extrapolation of efficacy findings from adults to the pediatric population, to maximize the use of adult data and ...other data when designing pediatric drug-development programs. We examined the experience of the FDA in using extrapolation to evaluate how and when it was used and any changes in scientific assumptions over time.
We reviewed 370 pediatric studies submitted to the FDA between 1998 and 2008 in response to 159 written requests (166 products) issued under the Pediatric Exclusivity Provision. We identified cases in which efficacy was extrapolated from adult data or other data, we categorized the type of pediatric data required to support extrapolation, and we determined whether the data resulted in new pediatric labeling.
Extrapolation of efficacy from adult data occurred for 82.5% of the drug products (137 of 166). Extrapolation was defined as complete for 14.5% of the products (24 of 166) and partial for 68% of them (113 of 166). Approaches to extrapolation changed over time for 19% of the therapeutic indications studied (13 of 67). When extrapolation was used, 61% of the drug products (84 of 137) obtained a new pediatric indication or extension into a new age group; this number decreased to 34% (10 of 29) when there was no extrapolation.
Extrapolating efficacy from adult data or other data to the pediatric population can streamline pediatric drug development and help to increase the number of approvals for pediatric use.
Dosing is a critical aspect of drug development in pediatrics that has led to trial failures and the inability to label the drug for pediatric use by the US Food and Drug Administration. Developing a ...structured approach for pediatric dose selection requires knowledge of the current approaches and their success or failure. This study describes the current experience with pediatric dosing methods from 2012 to 2020 and had 2 primary objectives: (1) to identify how the initial pediatric dose was selected and (2) to identify the pivotal dosing strategy used to identify the initially selected dose for safety and efficacy for pediatric clinical trials. Through September 2020, a total of 275 pediatric drug development programs were characterized for initial and pivotal dosing strategies. The success rate for labeling for pediatric use was 76.4%. The most common initial dosing strategy was previous experience with the product, followed by allometric scaling and exposure matching with adults. The most common pivotal dosing strategy was titration to target response in 33% of programs, with the second and third most common being pharmacokinetic/pharmacodynamic studies (30%) and exposure matching (20%), respectively. Additionally, about one-half of pediatric programs incorporated model-informed drug development. The emergence of titration to target response may signal a shift toward precision medicine in pediatric patients. Future work in pediatric drug dose selection should move toward the development of a structured pediatric dose selection approach.
There has been significant progress in pediatric drug development during the past 15 years. Results from 1,200 pediatric studies have been submitted to the US Food and Drug Administration (FDA). Over ...700 drug labels have been revised with information to guide pediatric use. Two international pediatric trial networks have been established.1,2 The failure rate for pediatric efficacy trials has fallen from over 40%3 to about 20%. Taken together, the outlook for pediatric drug development is positive.
The objective of this study was to evaluate the predictive performance of population models to predict renal clearance in newborns and infants. Pharmacokinetic (PK) data from eight drugs in 788 ...newborns and infants were used to evaluate the predictive performance of the population models based on postmenstrual age (PMA), postnatal age, gestational age, and body weight. For the PMA model, the average fold error for clearance (CL)predicted/CLobserved was within a twofold range for each drug in all subgroups. For drugs with > 90% renal elimination, the prediction bias ranged from 0.7−1.3. For drugs with 60–80% renal elimination, the prediction bias ranged 0.6–2.0. Our results suggest that PMA‐based sigmoidal maximum effect (Emax) model, in combination with bodyweight‐based scaling and kidney function assessment, can be used in population PK (PopPK) modeling for drugs that are primarily eliminated via renal pathway to inform initial dose selection for newborns and infants with normal renal function in clinical trials.
Nilotinib is a second-generation BCR-ABL tyrosine kinase inhibitor for the treatment of Philadelphia chromosome-positive chronic myeloid leukemia in both adult and pediatric patients. The ...pharmacokinetics (PK) of nilotinib in specific populations such as pregnant and lactating people remain poorly understood. Therefore, the objectives of the current study were to develop a physiologically based pharmacokinetic (PBPK) model to predict nilotinib PK in virtual drug-drug interaction (DDI) studies, as well as in pediatric, pregnant, and lactating populations. The nilotinib PBPK model was built in PK-Sim, which is part of the free and open-source software Open Systems Pharmacology. The observed clinical data for the validation of the nilotinib models were obtained from the literature. The model reasonably predicted nilotinib concentrations in the adult population; the DDIs between nilotinib and rifampin or ketoconazole in the adult population; and the PK in the pediatric, pregnant, and lactating populations, although in the latter 2 populations plasma concentrations were slightly underestimated. The ratio of predicted versus observed PK parameters for the adult model ranged from 0.71 to 1.11 for area under the concentration-time curve and 0.55 to 0.95 for maximum concentration. For the DDI, the predicted area under the concentration-time curve ratio and maximum concentration ratio fell within the Guest criterion. The current study demonstrated the utility of using PBPK modeling to understand the mechanistic basis of PK differences between adults and specific populations, such as pediatrics, and pregnant and lactating individuals, indicating that this technology can potentially inform or optimize dosing conditions in specific populations.
Pediatric drug dosing is challenged by the heterogeneity of developing physiology and ethical considerations surrounding a vulnerable population. Often, pediatric drug dosing leverages findings from ...the adult population; however, recent regulatory efforts have motivated drug sponsors to pursue pediatric‐specific programs to meet an unmet medical need and improve pediatric drug labeling. This paradigm is further complicated by the pathophysiological implications of obesity on drug distribution and metabolism and the roles that body composition and body size play in drug dosing. Therefore, we sought to understand the landscape of pediatric drug dosing by characterizing the dosing strategies from drug products recently approved for pediatric indications identified using FDA Drug Databases and analyze the impact of body size descriptors (age, body surface area, weight) on drug pharmacokinetics for several selected antipsychotics approved in pediatric patients. Our review of these pediatric databases revealed a dependence on body size‐guided dosing, with 68% of dosing in pediatric drug labelings being dependent on knowing either the age, body surface area, or weight of the patient to guide dosing for pediatric patients. This dependence on body size‐guided dosing drives the need for special consideration when dosing a drug in overweight and obese patients. Exploratory pharmacokinetic analyses in antipsychotics illustrate possible effects of drug exposure when applying different dosing strategies for this class of drugs. Future efforts should aim to further understand the pediatric drug dosing and obesity paradigm across pediatric age ranges and drug classes to optimize drug development and clinical care for this patient population.
Pregnancy is associated with physiological changes that may impact drug pharmacokinetics (PK). The goals of this study were to build maternal-fetal physiologically based pharmacokinetic (PBPK) models ...for acyclovir and emtricitabine, 2 anti(retro)viral drugs with active renal net secretion, and to (1) evaluate the predicted maternal PK at different stages of pregnancy; (2) predict the changes in PK target parameters following the current dosing regimen of these drugs throughout pregnancy; (3) evaluate the predicted concentrations of these drugs in the umbilical vein at delivery; (4) compare the model performance for predicting maternal PK of emtricitabine in the third trimester with that of previously published PBPK models; and (5) compare different previously published approaches for estimating the placental permeability of these 2 drugs. Results showed that the pregnancy PBPK model for acyclovir predicted all maternal concentrations within a 2-fold error range, whereas the model for emtricitabine predicted 79% of the maternal concentrations values within that range. Extrapolation of these models to earlier stages of pregnancy indicated that the change in the median PK target parameters remained well above the target threshold. Concentrations of acyclovir and emtricitabine in the umbilical vein were overall adequately predicted. The comparison of different emtricitabine PBPK models suggested an overall similar predictive performance in the third trimester, but the comparison of different approaches for estimating placental drug permeability revealed large differences. These models can enhance the understanding of the PK behavior of renally excreted drugs, which may ultimately inform pharmacotherapeutic decision making in pregnant women and their fetuses.
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