Side effects of pediatric drug treatment are responsible for nearly 10% of childhood hospitalizations, nearly half of which are life-threatening. Despite the need to know more about these drugs and the adverse effects they may have on children, little evidence is currently available.
Clinical trials remain the gold standard for identifying adverse drug events (ADRs) for adults, but they present both ethical and methodological concerns for the pediatric population. Rapidly changing biological and physiological developments only increase the challenges of understanding the potential impacts of different drug treatments at different stages of childhood.
Researchers at Columbia University Irving Medical Center have developed a new algorithm that identified nearly 20,000 ADE signals (information about a new or known side effect that may be caused by a particular medication) across the seven stages of pediatric development and matched them to made freely available. This process is enhanced by a new approach that allows neighboring development stages to improve signal detection power, helping it overcome limited data within individual stages.
This use of predictive modeling on real-world data may help fill a critical gap in healthcare research around the understudied pediatric community.
DBMI associate professor Nicholas Tatonetti and Nick Giangreco, a recent PhD graduate in systems biology at Columbia University, shared these findings in the study A Pediatric Drug Effects Database to Assess the Mechanisms ontogenetics of child growth and development, recently published in Medium.
“For many reasons, children have never been included in clinical trials,” Tatonetti said. “There are many ethical issues with including children in trials, and there are several limitations when children are included, which make it difficult to assess drug efficacy and safety.”
Due to these factors, few drugs are specifically approved for use in children, although once drugs are approved for adults, doctors may prescribe them “off label” to children.
“Because drugs are not studied and approved directly in children, doctors must rely on guidelines for adults,” he added. “Essentially, treating children as if they were just little adults is often an incorrect assumption. This study is an attempt to systematically elucidate potential side effects when drugs are used off-label in children.”
The study goes beyond simply differentiating side effects in children from those in adults. It focuses on ADEs across seven developmental stages, beginning in neonatal term through late adolescence, and is informed by sharing information from neighboring developmental stages. For example, the development of infants and toddlers is close enough that there are more common characteristics than there would be for infants and those in early or late adolescence.
“Before, kids were basically grouped together,” Tatonetti said. “There were only a few studies that focused only on children, and they basically focused on people 18 and under or 21 and under in a group. The innovation here uses known developmental stages and our newly introduced DGAMs (Generalized Additive Disproportionality Models) to improve power and enable this analysis.”
Tatonetti pointed out that these signals are not validated and are primarily intended for researchers. Parents should consult their pediatrician about specific side effects of medications.
Giangreco, currently a quantitative translational scientist at Regeneron, noted one of the many side effects identified by this model.
“We have corroborated that the FDA found that the asthma drug montelukast caused psychiatric side effects,” he said. “We also saw this in our database, but we were able to identify certain developmental stages where the risk was greater, particularly the second year of life.”
The study also incorporates pediatric enzyme expression data and found that dynamically expressed pharmacogenes in childhood are associated with pediatric ADEs.
“It was a biologically inspired modeling strategy,” Giangreco said. “We used what we knew about biological processes occurring during childhood and formed the modeling strategy. These safety signals came from this prior knowledge of the biological processes that occur. Our data-driven approach really tried to capture what we thought were the biologically important and physiologically dynamic processes that occur during childhood and use them to unravel observations across developmental stages.”
The model was run on a database of 264,453 pediatric reports in the FDA Adverse Event Reporting System (FAERS). The study result is available through KidSIDES, a free and publicly accessible database of pediatric medication safety signals for the research community, as well as the Pediatric Medication Safety Portal (PDSportal), which will facilitate the evaluation of drug safety signals throughout the growth and growth of the child. development.
“The primary intent is for other researchers to use it, to track any signals they might observe,” Tatonetti said. “If they are experts in a particular drug use or a particular disease area and have observed these types of effects, they could follow them and be reassured, or could look at what other evidence there is for this effect. when we aggregate them.. Clinicians can use it as a gut check. Maybe they’ve seen an effect, or they’re wondering if others are seeing that effect, and they can check the PDSPortal to see if d others see this effect or to prompt them to write another case report to the FDA.”