Hepatic Impairment Physiologically Based Pharmacokinetic Model Development: Current Challenges
Author:
Publisher
Springer Science and Business Media LLC
Subject
Drug Discovery,Pharmacology,Genetics,Biochemistry
Link
https://link.springer.com/content/pdf/10.1007/s40495-021-00266-5.pdf
Reference81 articles.
1. Horak J, et al. The effect of different etiologies of hepatic impairment on the pharmacokinetics of gefitinib. Cancer Chemother Pharmacol. 2011;68(6):1485–95.
2. Verbeeck RK. Pharmacokinetics and dosage adjustment in patients with hepatic dysfunction. Eur J Clin Pharmacol. 2008;64(12):1147–61.
3. •• Kok B, Abraldes JG. Child-Pugh classification: time to abandon? Semin Liver Dis. 2019;39(1):96–103. (This article contains a comprehensive review of the failings of the Child-Pugh scoring system when used to classify disease severity in PBPK models.)
4. •• Heimbach T, et al. Physiologically-based pharmacokinetic modeling in renal and hepatic impairment populations: a pharmaceutical industry perspective. Clin Pharmacol Ther. 2020;110:297–310. (This paper evaluated the predictive accuracy of current HI PBPK models across a range of compounds.It suggests that for moderate to severe cases of HI, existing models tend to overpredict exposure because they do not account for changes in absorption induced by HI.)
5. • Morcos PN, et al. Effect of hepatic impairment on the pharmacokinetics of alectinib. J Clin Pharmacol, 2018. 58(12): p. 1618–1628. This article provides a full mechanistic PBPK model of alectinib PK in hepatically impaired patients. The model was successfully used to inform a clinical trial design. (The model was found to have overpredicted the effect of hepatic impairment in patients with moderate to severe liver disease.)
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