Integration of Pharmacogenetics and Pharmacogenomics in Drug Development: Implications for Regulatory and Medical Decision Making in Pediatric Diseases

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Predicting CYP3A-mediated midazolam metabolism in critically ill neonates, infants, children and adults with inflammation and organ failure.

Aims: Inflammation and organ failure have been reported to have an impact on cytochrome P450 (CYP) 3A-mediated clearance of midazolam in critically ill children. Our aim was to evaluate a previously developed population pharmacokinetic model both in critically ill children and other populations, in order to allow the model to be used to guide dosing in clinical practice. Methods: The model was evaluated externally in 136 individuals, including (pre)term neonates, infants, children and adults (body weight 0.77–90 kg, C-reactive protein level 0.1–341 mg l–1 and 0–4 failing organs) using graphical and numerical diagnostics. Results: The pharmacokinetic model predicted midazolam clearance and plasma concentrations without bias in postoperative or critically ill paediatric patients and term neonates [median prediction error (MPE) 180%). Conclusion: The recently published pharmacokinetic model for midazolam, quantifying the influence of maturation, inflammation and organ failure in children, yields unbiased clearance predictions and can therefore be used for dosing instructions in term neonates, children and adults with varying levels of critical illness, including healthy adults, but not for extrapolation to preterm neonates

A physiological approach to renal clearance : from premature neonates to adults

Aims We propose using glomerular filtration rate (GFR) as the physiological basis for distinguishing components of renal clearance. Methods Gentamicin, amikacin and vancomycin are thought to be predominantly excreted by the kidneys. A mixed-effects joint model of the pharmacokinetics of these drugs was developed, with a wide dispersion of weight, age and serum creatinine. A dataset created from 18 sources resulted in 27,338 drug concentrations from 9,901 patients. Body size and composition, maturation and renal function were used to describe differences in drug clearance and volume of distribution. Results This study demonstrates that GFR is a predictor of two distinct components of renal elimination clearance: (1) GFR clearance associated with normal GFR and (2) non-GFR clearance not associated with normal GFR. All three drugs had GFR clearance estimated as a drug-specific percentage of normal GFR (gentamicin 39%, amikacin 90% and vancomycin 57%). The total clearance (sum of GFR and non-GFR clearance), standardized to 70 kg total body mass, 176 cm, male, renal function 1, was 5.58 L/h (95% confidence interval [CI] 5.50-5.69) (gentamicin), 7.77 L/h (95% CI 7.26-8.19) (amikacin) and 4.70 L/h (95% CI 4.61-4.80) (vancomycin). Conclusions GFR provides a physiological basis for renal drug elimination. It has been used to distinguish two elimination components. This physiological approach has been applied to describe clearance and volume of distribution from premature neonates to elderly adults with a wide dispersion of size, body composition and renal function. Dose individualization has been implemented using target concentration intervention

A physiological approach to renal clearance:From premature neonates to adults

Aims: We propose using glomerular filtration rate (GFR) as the physiological basis for distinguishing components of renal clearance. Methods: Gentamicin, amikacin and vancomycin are thought to be predominantly excreted by the kidneys. A mixed-effects joint model of the pharmacokinetics of these drugs was developed, with a wide dispersion of weight, age and serum creatinine. A dataset created from 18 sources resulted in 27,338 drug concentrations from 9,901 patients. Body size and composition, maturation and renal function were used to describe differences in drug clearance and volume of distribution. Results: This study demonstrates that GFR is a predictor of two distinct components of renal elimination clearance: (1) GFR clearance associated with normal GFR and (2) non-GFR clearance not associated with normal GFR. All three drugs had GFR clearance estimated as a drug-specific percentage of normal GFR (gentamicin 39%, amikacin 90% and vancomycin 57%). The total clearance (sum of GFR and non-GFR clearance), standardized to 70 kg total body mass, 176 cm, male, renal function 1, was 5.58 L/h (95% confidence interval [CI] 5.50-5.69) (gentamicin), 7.77 L/h (95% CI 7.26-8.19) (amikacin) and 4.70 L/h (95% CI 4.61-4.80) (vancomycin). Conclusions: GFR provides a physiological basis for renal drug elimination. It has been used to distinguish two elimination components. This physiological approach has been applied to describe clearance and volume of distribution from premature neonates to elderly adults with a wide dispersion of size, body composition and renal function. Dose individualization has been implemented using target concentration intervention.</p

First dose in neonates: Are juvenile mice, adults, and in vitro-in silico data predictive of neonatal pharmacokinetics of fluconazole

BACKGROUND: Selection of the first-dose-in-neonates is challenging. The objective of this proof-of-concept study was to evaluate a pharmacokinetic (PK) bridging approach to predict a neonatal dosing regimen. METHODS: We selected fluconazole as a paradigm compound. We used data from PK studies in juvenile mice and adults to develop population PK models using NONMEM. We also develop a physiologically-based PK model from in vitro–in silico data using Simcyp. These three models were then used to predict neonatal pharmacokinetics and dosing regimens for fluconazole. RESULTS: From juvenile mice to neonates, a correction factor of maximum lifespan potential should be used for extrapolation, while a “renal factor” taking into account renal maturation was required for successful bridging based on adult and in vitro-in silico data. Simulations results demonstrated that the predicted drug exposure based on bridging approach was comparable to the observed value in neonates. The prediction errors were -2.2%, +10.1% and -4.6% for juvenile mice, adults and in vitro-in silico data, respectively. CONCLUSION: A model-based PK bridging approach provided consistent predictions of fluconazole PK parameters in neonates and demonstrated the feasibility of this approach to justify the first-dose-in-neonates, based on all data available from different sources (including physiological informations, preclinical studies and adult data), allowing evidence-based decisions of neonatal dose rather than empiricism