New pediatric analysis establishes novel dosing framework for the future

Abstract

Pharmacists have all heard the phrase “children are not little adults.” It’s popular for a reason: it represents the dangers of simply scaling adult drug dosages to children. Adult physiology, however, has historically been used to scale pediatric dose recommendations. Currently, the most accurate way to determine the initial dosage of a drug is to use a physiologically based pharmacokinetic model (PBPK) to mathematically extrapolate drug dosing from an adult to a child population. Unfortunately, the development of a PBPK remains a challenge, as it requires a deep level of raw, quantitative, physiological data related to developmental stage, disease processes, and any other variable that can affect the pharmacokinetics of a drug. This task may have become significantly less herculean, however, thanks to an open-source, comprehensive, quantitative database, published in March 2021 in the Journal of the American Association of Pharmaceutical Scientists, on the mathematical age relationships among weight, height, organ weight, and organ blood flow—all critical parameters needed when designing a pediatric PBPK. Until recently, this kind of data have been difficult to consolidate or have been locked tightly behind proprietary software. The authors hope that by making it open-source, their database will encourage the creation of widespread pediatric PBPK models that can help predict optimal dosing for pediatric patients with both old and new drugs. One of the first steps in the clinical development for most drugs seeking a pediatric indication is to demonstrate similar exposure levels at various dosages. The first dose is informed by adult pharmacokinetic data leveraged in mathematical models that rely on assumptions regarding the drug’s pharmacokinetics. These data are then scaled down to different child age groups using allometric functions of basal metabolic rates and body weight. Although this is usually sufficient, it may be inaccurate for non-small drug molecules that do not exhibit linear kinetics with time-dependent clearance or target-mediated drug disposition. Biologics pose a particular problem. Using a PBPK model to achieve more accurate results presents a solution. The general process involves creating a simulation of a population of adults whose pharmacokinetics of a particular drug is expressed as rate-based equations. The adults are then swapped with virtual children with all other pharmacokinetic parameters being held constant and their drug exposure metrics compared. If the virtual pediatric exposures are similar to that of the virtual adult population, the presumed first-in-pediatric dose can progress to a more practical application. Chang and colleagues created a comprehensive database of physiological parameters in children from newborns to 20 years. They found a singular function that described the relationships between body weight and age, height and age, organ weight and age, and organ blood flow and age. The formula can be used to estimate any of these parameters—as they relate to age—by referencing the appropriate tables and variable values in the author’s library. The analysis also includes functions predicting pediatric organ weight and blood flow for a library of organs—including heart, lung, muscle, skin, fat, bone, bone marrow, brain, kidney, liver, intestine, pancreas, thymus, and spleen—as well as blood volume and extracellular water. In fact, Chang and colleagues published a follow-up study in June 2021 in the British Journal of Clinical Pharmacology, in which they put the database to the test using it to develop their own PBPK model to characterize monoclonal antibody (mAb) pharmacokinetics in pediatric patients. The results of the investigation were in concordance with the rest of the literature: that mAb pharmacokinetics often require higher doses or more frequent dosing in order to achieve therapeutic levels. The confirmatory results appear to demonstrate a practical application of their database for use in PKPB modeling and will hopefully serve as an accessible framework for pediatric pharmacologists—particularly for biologics—in the years to come.