Physiologically based pharmacokinetic (PBPK) modeling for prediction of celecoxib pharmacokinetics according to CYP2C9 genetic polymorphism

Kim, Young-Hoon; Kang, Pureum; Cho, Chang‐Keun; Jung, Eui Hyun; Park, Hye-Jeong; Lee, Yun Jeong; Bae, Jung‐Woo; Jang, Choon‐Gon; Lee, Seok‐Yong

doi:10.1007/s12272-021-01346-2

Cited by 26 publications

(10 citation statements)

References 57 publications

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“…However, conflicting data were obtained by Brenner et al [47], showing no correlation between the celecoxib pharmacokinetics and the CYP2C9 genotype in 12 healthy participants. Of note, more recent studies have shown a significant impact of CYP2C9 polymorphisms on the celecoxib pharmacokinetics, as demonstrated in 39 healthy volunteers [48]. Nonetheless, the association of these findings with the pharmacodynamic outcome (i.e., pain relief efficacy) is rather uncertain to date and needs further investigation.…”

Section: Celecoxibmentioning

confidence: 95%

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Pharmacogenetics and Pain Treatment with a Focus on Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Antidepressants: A Systematic Review

et al. 2022

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Background: This systematic review summarizes the impact of pharmacogenetics on the effect and safety of non-steroidal anti-inflammatory drugs (NSAIDs) and antidepressants when used for pain treatment. Methods: A systematic literature search was performed according to the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines regarding the human in vivo efficacy and safety of NSAIDs and antidepressants in pain treatment that take pharmacogenetic parameters into consideration. Studies were collected from PubMed, Scopus, and Web of Science up to the cutoff date 18 October 2021. Results: Twenty-five articles out of the 6547 initially detected publications were identified. Relevant medication–gene interactions were noted for drug safety. Interactions important for pain management were detected for (1) ibuprofen/CYP2C9; (2) celecoxib/CYP2C9; (3) piroxicam/CYP2C8, CYP2C9; (4) diclofenac/CYP2C9, UGT2B7, CYP2C8, ABCC2; (5) meloxicam/CYP2C9; (6) aspirin/CYP2C9, SLCO1B1, and CHST2; (7) amitriptyline/CYP2D6 and CYP2C19; (8) imipramine/CYP2C19; (9) nortriptyline/CYP2C19, CYP2D6, ABCB1; and (10) escitalopram/HTR2C, CYP2C19, and CYP1A2. Conclusions: Overall, a lack of well powered human in vivo studies assessing the pharmacogenetics in pain patients treated with NSAIDs or antidepressants is noted. Studies indicate a higher risk for partly severe side effects for the CYP2C9 poor metabolizers and NSAIDs. Further in vivo studies are needed to consolidate the relevant polymorphisms in NSAID safety as well as in the efficacy of NSAIDs and antidepressants in pain management.

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Section: Celecoxibmentioning

confidence: 95%

“…Aithal et al revealed only slightly lower 4-hydroxylation rates of CYP2C9*3 carriers among 24 patients [65]. However, conflicting data are available, which proposed no association between the CYP2C9 genotype and diclofenac pharmacokinetics in 12 healthy participants [48].…”

Section: Diclofenacmentioning

confidence: 99%

Pharmacogenetics and Pain Treatment with a Focus on Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Antidepressants: A Systematic Review

et al. 2022

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“…Additionally, the accuracy of simulated PK parameters (e.g., AUC 0– t , C max and T max ) was assessed using the twofold error (within a 0.5–2 fold range), which was widely used for acceptable prediction in PBPK model evaluation (eq ). 0.5 ≤ normalr normala normalt normali normalo .25em normals normalc normalo normalr normale = normalp normalr normale normald normalo normalb normals ≤ 2 …”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…Additionally, the accuracy of simulated PK parameters (e.g., AUC 0−t , C max and T max ) was assessed using the twofold error (within a 0.5−2 fold range), which was widely used for acceptable prediction in PBPK model evaluation (eq 4). 45 0.5 ratio score pred obs 2 = (4) Note: Pred, the predicted value; obs, the observed value. Finally, the simulated geometric mean ratios of exposure parameters (AUC 0−t and C max ) of the test to reference formulations (T/R) were compared with the observed ones and used to reassess whether the bioequivalence result was simulated.…”

Section: Evaluation Metricsmentioning

confidence: 99%

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Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Zhang

Wu³

et al. 2022

Mol. Pharmaceutics

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To evaluate the influence of solubility and permeability on the pharmacokinetic prediction performance of orally administered drugs using avirtual bioequivalence (VBE) model, a total of 23 orally administered drugs covering Biopharmaceutics Classification System (BCS) classes 1−4 were selected. A VBE model (i.e., a physiologically based pharmacokinetic model integrated with dissolution data) based on a B 2 O simulator was applied for pharmacokinetic (PK) prediction in a virtual population. Parameter sensitivity analysis was used for input parameter selection. The predictive performances of PK parameters (i.e., AUC 0−t , C max , and T max ), PK profiles, and bioequivalence (BE) results were evaluated using the twofold error, average fold error (AFE), absolute average fold error (AAFE), and BE reassessment metrics. All models successfully simulated the mean PK profiles, with AAFE < 2 and AFE ranging from 0.58 to 1.66. As for the PK parameters, except for the time of peak concentration, T max , of isosorbide mononitrate, other simulated PK parameters were all within a twofold error. The simulated PK behaviors were comparable to the observed ones, both for test (T) and reference (R) products, and the simulated T/R arithmetic mean ratios were all within 0.88−1.16 of the observed values. These four evaluation metrics were distributed equally among BCS class 1−4 drugs. The VBE model showed powerful performance to predict the PK behavior of orally administered drugs with various combinations of solubility and permeability, irrespective of the BCS category.

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Models for Drug Individualization: Patient to Population Level

Klein

Mason

Lockard

et al. 2022

Recent Advances in Therapeutic Drug Monitoring and Clinical Toxicology

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Physiologically based pharmacokinetic (PBPK) modeling for prediction of celecoxib pharmacokinetics according to CYP2C9 genetic polymorphism

Cited by 26 publications

References 57 publications

Pharmacogenetics and Pain Treatment with a Focus on Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Antidepressants: A Systematic Review

Pharmacogenetics and Pain Treatment with a Focus on Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Antidepressants: A Systematic Review

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Models for Drug Individualization: Patient to Population Level

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