Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Jul;74(1):66-74.
doi: 10.1111/j.1365-2125.2012.04172.x.

Pharmacokinetic predictions for patients with renal impairment: focus on peptides and protein drugs

Affiliations

Pharmacokinetic predictions for patients with renal impairment: focus on peptides and protein drugs

David Czock et al. Br J Clin Pharmacol. 2012 Jul.

Abstract

What is already known about this subject: • Renal impairment may affect the pharmacokinetics of peptide and protein drugs. • Molecular size is a predictor. Small molecules are eliminated by the kidneys, whereas large molecules (>67 kDa) are not. • Urinary recovery of peptide and protein drugs in healthy volunteers is not predictive for pharmacokinetic changes in patients with renal impairment.

What this study adds: • An apparently continuous non-linear relationship between molecular weight and pharmacokinetic alterations as observed in patients with severe renal impairment or end-stage renal disease is described. • Potentially relevant pharmacokinetic changes were found for drugs with a molecular weight below 50 kDa. • Analysis of observed pharmacokinetics in patients with severe renal impairment may be a useful approach, especially when urinary recovery in healthy volunteers is not predictive.

Aim: Drug dosage adjustments in renal impairment are usually based on estimated individual pharmacokinetics. The extent of pharmacokinetic changes in patients with renal impairment must be known for this estimation. If measured data are not available, an estimate based on drug elimination in urine of healthy subjects or patients with normal renal function is commonly made. This is not reliable, however, if renal drug metabolism is involved, as is presumably the case for many peptide and protein drugs. In the present study a new method to predict pharmacokinetic changes for such drugs based on molecular weight was derived.

Methods: Articles reporting measured pharmacokinetics of peptide and protein drugs in patients with severe renal impairment or end-stage renal disease were identified from the scientific literature, the pharmacokinetic parameter values were extracted and a statistical data synthesis was performed. A sigmoid E(max) model was applied and fitted to the data and the prediction error was analyzed.

Results: Overall, 98 peptide and protein drugs were identified. Relevant pharmacokinetic data in patients with renal impairment were found for 21 of these drugs. The average drug clearance was 30% and the average prolongation in half-life was 3.1-fold for low molecular weight peptides or proteins. The median root squared percentage of the prediction error was 18% (drug clearance) and 12% (half-life).

Conclusion: An apparently continuous non-linear relationship between molecular weight and pharmacokinetic alterations in patients with severe renal impairment was found. The derived equations could be used as a rough guide for decisions on drug dosage adjustments in such patients.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Pharmacokinetic changes in severe renal impairment or end-stage renal disease. For example, a fractional clearance (fCL) of 0.4 indicates that the observed total body clearance of a drug was 40% of the observed clearance in healthy subjects or patients with normal renal function. Similarly, a half-life factor (formula image) of 3 indicates a three-fold prolongation of half-life in renal failure. The continuous lines represent the fitted sigmoid Emax model (equation 4). The broken lines represent the hypothetical condition of no change

Similar articles

Cited by

References

    1. Dettli L. Drug dosage in renal disease. Clin Pharmacokinet. 1976;1:126–34. - PubMed
    1. Welling PG, Craig WA, Kunin CM. Prediction of drug dosage in patients with renal failure using data derived from normal subjects. Clin Pharmacol Ther. 1975;18:45–52. - PubMed
    1. Pichette V, Leblond FA. Drug metabolism in chronic renal failure. Curr Drug Metab. 2003;4:91–103. - PubMed
    1. Silvers A, Swenson RS, Farquhar JW, Reaven GM. Derivation of a three compartment model describing disappearance of plasma insulin-131-I in man. J Clin Invest. 1969;48:1461–9. - PMC - PubMed
    1. Rubenstein AH, Mako ME, Horwitz DL. Insulin and the kidney. Nephron. 1975;15:306–26. - PubMed