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Updated: May 9, 2026

Cellular Affinity of Particle-Stabilized Emulsion to Boost Antigen Internalization
Published on: September 2, 2022
A physiologically-based pharmacokinetic (PBPK) model of squalene-containing adjuvant in human vaccines
Million A Tegenge1, Robert J Mitkus
1Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration, 1401 Rockville Pike, Rockville, MD, 20852, USA, million.tegenge@fda.hhs.gov.
Abstract:
Squalene is used in the oil phase of certain emulsion vaccine adjuvants, but its fate as a vaccine component following intramuscular (IM) injection in humans is unknown. In this study, we constructed a physiologically-based pharmacokinetic (PBPK) model for intramuscularly injected squalene-in-water (SQ/W) emulsion, in order to make a quantitative estimation of the tissue distribution of squalene following a single IM injection in humans. The PBPK model incorporates relevant physicochemical properties of squalene; estimates of the time course of cracking of a SQ/W emulsion; anatomical and physiological parameters at the injection site and beyond; and local, preferential lymphatic transport. The model predicts that a single dose of SQ/W emulsion will be removed from human deltoid muscle within six days following IM injection. The major proportion of the injected squalene will be distributed to draining lymph nodes and adipose tissues. The model indicates slow decay from the latter compartment most likely due to partitioning into neutral lipids and a low rate of squalene biotransformation there. Parallel pharmacokinetic modeling for mouse muscle suggests that the kinetics of SQ/W emulsion correspond to the immunodynamic time course of a commercial squalene-containing adjuvant reported in that species. In conclusion, this study makes important pharmacokinetic predictions of the fate of a squalene-containing emulsion in humans. The results of this study may be relevant for understanding the immunodynamics of this new class of vaccine adjuvants and may be useful in future quantitative risk analyses that incorporate mode-of-action data.
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