Literature DB >> 30184267

Estimating Renal Function in Drug Development: Time to Take the Fork in the Road.

Ryan L Crass1, Manjunath P Pai1.   

Abstract

Renal function is the most commonly applied patient-specific quantitative variable used to determine drug doses. Measurement of renal function is not practical in most clinical settings; therefore, clinicians often rely on estimates when making dosing decisions. Similarly, renal function estimates are used to assign subjects in phase 1 pharmacokinetic studies, which inform dosing in late-phase clinical trials and ultimately the product label. The Cockcroft-Gault estimate of creatinine clearance has been the standard renal function metric; however, this paradigm is shifting toward the Modification of Diet in Renal Diseases (MDRD) estimate of the glomerular filtration rate (GFR). The proportion of approved new drug labels with dosing recommendations based on the MDRD equation was 16.7% in 2015, 70.0% in 2016, and 46.7% in 2017. Disharmonious recommendations from the United States Food and Drug Administration and the European Medicines Agency will continue to increase this heterogeneity in the assessment of renal function in drug development and negatively impact industry, health systems, and clinicians. In this review, we discuss the current regulatory guidance for the conduct of renal impairment pharmacokinetic studies and review the implications of this guidance across the medication use system with 3 recently approved antibiotics: ceftazidime/avibactam, delafloxacin, and meropenem/vaborbactam. Finally, we suggest measuring GFR in phase 1 studies and employing the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation to integrate data across clinical trials. This will help to harmonize CKD staging, population pharmacokinetic analyses, and dosing by estimated renal function.
© 2018, The American College of Clinical Pharmacology.

Entities:  

Keywords:  CKD-EPI; Cockcroft-Gault; MDRD; creatinine clearance; drug development; glomerular filtration rate; regulatory science

Mesh:

Substances:

Year:  2018        PMID: 30184267     DOI: 10.1002/jcph.1314

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  6 in total

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  6 in total

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