The meropenem’s population pharmacokinetic (PK) model
Added on 2022-08-24
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(1)
The meropenem’s population pharmacokinetic (PK) model was developed on the basis
of 116 plasma concentrations taken from 50 pediatric patients who lived in Japan
having different other infectious diseases. The population PK parameters defined in this
study are important for measuring the percentage time above least inhibitory
concentration (% T > MIC) and for optimum meropenem dose in patients at neonatal
stage. After 0.5-h infusion (approved standard dose for Japanese pediatric patients) at
20 mg / kg t.i.d., the target value of 50 % T > MIC was reached, suggesting that 0.5-h
infusion of 20 mg / kg t.i.d. is how susceptibility to the bacteria. In comparison, for
bacteria with higher MICs such as Pseudomonas aeruginosa (MIC average 2 μg / mL),
the goal achievement likelihood of 50 %T > MIC was 60.7 % by 0.5-h infusion at 40 mg /
kg t.i.d. dose (highest approved dose for Japanese pediatric patients). The simulations
discussed in this journal suggested that 40 mg / kg t.i.d. with prolonged period of
infusion (e.g., 4 h) was more beneficial against bacteria with an MIC greater than 2 μg /
mL. The expected goal attainment likelihood for 50 % T > MIC (97.0 %) was well
associated not only with the rate of efficacy of microbiologicy (97.0% ) along with the
efficacy rate (95.9 %) clinically in this Phase 3 analysis.
(2)
We researched meropenem in 23 premature (gestational age, 29-36 weeks) and 15 full-
term neonates (gestational age, 37-42 weeks). Meropenem intakes of 10, 20, and 40
mg / kg were administered randomly as one single doses (30-min intravenous infusion).
Blood was collected nine times for determining the concentration of meropenem. For
proven / suspected bacterial infections each child needed additional antimicrobials.
High-performance liquid chromatography technology was used to analyze samples. The
value of pharmacokinetic parameter of populations were acquired using the BigNPAG
software. Component construction was carried out using the probability ratio method.
The final model included in the clearance equation an average creatinine clearance
(CLcr) (Schwartz formula) and weight (Wt) (meropenem clearance= 0.00112x CLcr +
The meropenem’s population pharmacokinetic (PK) model was developed on the basis
of 116 plasma concentrations taken from 50 pediatric patients who lived in Japan
having different other infectious diseases. The population PK parameters defined in this
study are important for measuring the percentage time above least inhibitory
concentration (% T > MIC) and for optimum meropenem dose in patients at neonatal
stage. After 0.5-h infusion (approved standard dose for Japanese pediatric patients) at
20 mg / kg t.i.d., the target value of 50 % T > MIC was reached, suggesting that 0.5-h
infusion of 20 mg / kg t.i.d. is how susceptibility to the bacteria. In comparison, for
bacteria with higher MICs such as Pseudomonas aeruginosa (MIC average 2 μg / mL),
the goal achievement likelihood of 50 %T > MIC was 60.7 % by 0.5-h infusion at 40 mg /
kg t.i.d. dose (highest approved dose for Japanese pediatric patients). The simulations
discussed in this journal suggested that 40 mg / kg t.i.d. with prolonged period of
infusion (e.g., 4 h) was more beneficial against bacteria with an MIC greater than 2 μg /
mL. The expected goal attainment likelihood for 50 % T > MIC (97.0 %) was well
associated not only with the rate of efficacy of microbiologicy (97.0% ) along with the
efficacy rate (95.9 %) clinically in this Phase 3 analysis.
(2)
We researched meropenem in 23 premature (gestational age, 29-36 weeks) and 15 full-
term neonates (gestational age, 37-42 weeks). Meropenem intakes of 10, 20, and 40
mg / kg were administered randomly as one single doses (30-min intravenous infusion).
Blood was collected nine times for determining the concentration of meropenem. For
proven / suspected bacterial infections each child needed additional antimicrobials.
High-performance liquid chromatography technology was used to analyze samples. The
value of pharmacokinetic parameter of populations were acquired using the BigNPAG
software. Component construction was carried out using the probability ratio method.
The final model included in the clearance equation an average creatinine clearance
(CLcr) (Schwartz formula) and weight (Wt) (meropenem clearance= 0.00112x CLcr +
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