Biologics, especially monoclonal antibodies, are increasingly important in the pharmaceutical marketplace. Population pharmacokinetic (PK) analyses could be useful to guide the need for dose adjustments among special populations, yet it is unknown how commonly such analyses are performed during biologics development. We summarized the characteristics of population PK models of biologics and examined their role in informing the drug labels. To do so, we extracted relevant characteristics of 86 biologics approved by the U.S. Food and Drug Administration's Center for Drug Evaluation and Research between 2003 and 2017. Ninety-four percent of monoclonal antibodies (51 of 54 biologics), 75% of fusion proteins with Fc receptor (6 of 8 biologics), and 33% of other proteins (8 of 24 biologics) included population PK analyses. Of these analyses, approximately half (45%) used a 2-compartment model with linear clearance as the base model structure. Body size was the most frequently included covariate in the final models (included in 94% of the 64 biologics in which covariate analysis was performed), although age (11%), sex (35%), race (26%), and renal function (27%) were also included in some models. In 70% to 90% of cases in which the effect of these covariates was examined, information regarding the effect of these on PK was included in the label. These results suggest that population PK analyses provide important information about the impact of intrinsic factors on the PK in the label of biologics by the U.S. Food and Drug Administration.
Keywords: U.S. Food and Drug Administration (FDA); biologics; label; population pharmacokinetics; special populations.
© 2019, The American College of Clinical Pharmacology.