Population pharmacokinetic (PK) models describe drug disposition in various populations and can help identify demographic or clinical factors that affect key PK parameters, such as clearance and volume of distribution. We utilize scavenged opportunistic sampling and timed sampling to obtain concentrations from large numbers of patients who receive beta-lactam antibiotics so that we can capture factors that contribute to variability. These models allow us to use Monte Carlo Simulation to propose initial dosing regimens based on the identified factors. Ultimately, after externally validating these models, we can use them as the Bayesian prior for our model-informed precision dosing beta-lactam consult service.
This work is supported by an NIGMS R35 Maximizing Investigator Research Award.
We have shown that kidney function is an important factor in beta-lactam antibiotic clearance in various pediatric populations. Kidney function is often estimated using creatinine, which can be an unreliable marker due to its production and secretion being affected by other factors, including muscle mass, concurrent medications, and fluid overload. We are interested in studying if kidney biomarkers like Cystatin C or urinary neutrophil gelatinase-associated lipocalin (NGAL) could be a better predictor of beta-lactam clearance than creatinine or provide additional information.
This work is supported by an NIGMS R35 Maximizing Investigator Research Award.
There is a paucity of data on beta-lactam pharmacokinetics and pharmacodynamics (PK/PD) in children requiring various dialysis modes. We have obtained real-world data from scavenged opportunistic sampling to describe beta-lactam PK/PD in patients on various dialysis modes, including conventional CRRT, infant CRRT with CARPEDIEM, and Molecular Adsorbent Recirculating System (MARS) therapy, and reported our findings in case reports or case series. We are also actively studying beta-lactam PK/PD in patients on CRRT, hemodialysis, and peritoneal dialysis. Through the novel development of a CRRT module in a precision dosing software that can be added to existing population PK models, we have been able to perform Monte Carlo Simulations to determine dosing regimens required to reach antibiotic concentration targets.
This work is supported by an NIGMS R35 Maximizing Investigator Research Award.
Children with medical complexity (CMCs) are often excluded from medication trials and yet frequently experience polypharmacy. There are little data to guide the appropriate dosing in this population. Pharmacogenetic testing, which is the testing of DNA to determine how quickly a person may metabolize certain drugs, may provide data to help providers determine dosing of medications. We seek to determine the acceptability of pharmacogenetic testing in CMCs and understand the beliefs of caregivers about testing. We ultimately will study changes in health outcomes in CMCs who receive pharmacogenetic testing.
This work is supported by a philanthropic gift from the Adam R. Scripps Foundation.