Physiologically-based pharmacokinetic modeling to predict the exposure and provide dosage regimens of Ustekinumab in pediatric patients with inflammatory bowel disease

Physiologically-based pharmacokinetic modeling to predict the exposure and provide dosage regimens of adalimumab in patients with juvenile idiopathic arthritis

BACKGROUND

Adalimumab has been approved for treating juvenile idiopathic arthritis (JIA). This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model for adalimumab in JIA patients to optimize personalized treatment.

METHODS

A comprehensive literature search identified 13 clinical studies as the dataset for constructing and validating a PBPK model of adalimumab. Initially, a PBPK model for adalimumab in adults was constructed using PK-Sim and Mobi software. Subsequently, virtual pediatric populations were created by incorporating age-dependent parameters from the PK-Sim database, extending the model to JIA patients. Finally, based on the developed PBPK model for adalimumab in JIA patients, dosing regimens were evaluated for different age groups.

RESULTS

This study successfully developed and validated a PBPK model for adalimumab in both adult and pediatric populations. The model for adults accurately predicted 92.90% of the concentrations within 0.5-2 times the observed values, while the pediatric model predicted 90.62% of the concentrations within 0.5-2-fold range. For pediatric patients with JIA, age- and weight-based dosing is recommended to achieve trough concentrations comparable to those in adults.

CONCLUSION

A PBPK model for adalimumab in pediatric patients with JIA was developed, providing a basis for personalized dosing regimens in this population.

Physiologically-based pharmacokinetic modeling to predict the exposure and to assess pharmacodynamics of daptomycin in infants within 1 year old

Daptomycin is widely used in pediatric patients for serious infections caused by Gram-positive bacteria, however, studies regarding its safety and efficacy in infants within 1 year old are very limited. A physiologically-based pharmacokinetic (PBPK) model of daptomycin was built for children aged 1-17 years old and extrapolated to infants within 1 year old to evaluate pharmacodynamics (PD) based on efficacy and safety considerations. Monte Carlo Simulations (MCSs) were conducted to determine the probabilities of target attainment (PTA) and cumulative fractions of response (CFR) of daptomycin. The pharmacokinetic (PK) of daptomycin did not differ much in the population of infants within 1 year of age, with peak plasma concentration (Cmax) and area under the curve (AUC) maintained at an approximate level at all months of age, while the average trough concentration of daptomycin was 3.49 μg/mL when 10 mg/kg daptomycin was given, and 4.98 ug /mL at 15 mg/kg. According to the results of the MCSs, 10mg/kg daptomycin provides good antimicrobial effect for S.pneumoniae and MSSA. With the increase of dosage, the CFR value of daptomycin against MRSA, E.faecalis and E.faecium also gradually reached >90 %, except for E.faecalis with an average CFR of only 82.94 % at 12mg/kg. This is a daptomycin PBPK model in infants within 1 year of age, dose regimen higher than 10 mg/kg should be recommended for this population in the treatment of MRSA, E. faecalis, and E. faecalis.

Progress in understanding of relationship between blood concentrations of ustekinumab and clinical outcomes of inflammatory bowel disease

Ustekinumab is widely used in the treatment of immune diseases due to its well-established efficacy and safety profile. In recent years, studies have found that adjusting dosing strategies and optimizing drug concentrations during long-term therapy can significantly improve the prognosis of some patients. Therapeutic drug concentration monitoring (TDM) can measure the concentration of ustekinumab in vivo, thereby guiding personalized treatment strategy decisions. This review elaborates on the relationship between different drug concentrations of ustekinumab and clinical efficacy and outcomes, and explores the value of individualized treatment strategies based on TDM for clinical treatment based on the existing literature.

Integration of Ontogeny-Based Changes for Predicting the Exposure of Diphenhydramine in the Pediatric Population: A PBPK Modeling Approach

BACKGROUND

Diphenhydramine is an anti-tussive used periodically to treat seasonal colds, contact dermatitis, and anaphylactic reactions. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model of diphenhydramine in predicting its systemic exposure among healthy pediatrics (children and adolescents) by leveraging data files from adults (young and elderly).

METHODS

The data profiles comprising serum/plasma concentration over time and parameters related to diphenhydramine were scrutinized via exhaustive literature analysis and consolidated in the PK-Sim software version 11.1. This modeling methodology commences with developing an adult model and then translating it to the pediatrics which compares the predicted concentration-time datasets with the reported values.

RESULTS

The accuracy of model anticipations was then assessed for each pharmacokinetics (PK) variable, i.e., the area under the curve from 0 to infinity (AUC0-∞), maximal serum/plasma concentration (Cmax), and clearance of the diphenhydramine in plasma (CL) by employing the predicted/observed ratios (Rpre/obs), and average fold error (AFE), which fell within the pre-defined benchmark of 2-fold. The predicted and observed Cmax values for pediatrics were 3-fold greater in comparison to the young adults following a 25 mg dose depicting a need to monitor dosage schedules among children closely.

CONCLUSIONS

These model-based anticipations confirmed the authenticity of the developed pediatric model and enhanced the comprehension of developmental variations on PK of diphenhydramine. This may assist healthcare professionals in ensuring the significance of lifespan applicability in personalized dose regimens, promoting therapeutic efficacy and minimizing side effects in chronic conditions among children.