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McSweeney MD, Wessler T, Price LSL, Ciociola EC, Herity LB, Piscitelli JA, Zamboni WC, Forest MG, Cao Y, Lai SK. A minimal physiologically based pharmacokinetic model that predicts anti-PEG IgG-mediated clearance of PEGylated drugs in human and mouse. J Control Release 2018; 284:171-178. [PMID: 29879519 DOI: 10.1016/j.jconrel.2018.06.002] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 05/18/2018] [Accepted: 06/02/2018] [Indexed: 10/14/2022]
Abstract
Circulating antibodies that specifically bind polyethylene glycol (PEG), a polymer routinely used in protein and nanoparticle therapeutics, have been associated with reduced efficacy and increased adverse reactions to some PEGylated therapeutics. In addition to acute induction of anti-PEG antibodies (APA) by PEGylated drugs, typically low but detectable levels of APA are also found in up to 70% of the general population. Despite the broad implications of APA, the dynamics of APA-mediated clearance of PEGylated drugs, and why many patients continue to respond to PEGylated drugs despite the presence of pre-existing APA, remains not well understood. Here, we developed a minimal physiologically based pharmacokinetic (mPBPK) model that incorporates various properties of APA and PEGylated drugs. Our mPBPK model reproduced clinical PK data of APA-mediated accelerated blood clearance of pegloticase, as well as APA-dependent elimination of PEGyated liposomes in mice. Our model predicts that the prolonged circulation of PEGylated drugs will be compromised only at APA concentrations greater than ~500 ng/mL, providing a quantitative explanation to why the effects of APA on PEGylated treatments appear to be limited in most patients. This mPBPK model is readily adaptable to other PEGylated drugs and particles to predict the precise levels of APA that could render them ineffective, providing a powerful tool to support the development and interpretation of preclinical and clinical studies of various PEGylated therapeutics.
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Affiliation(s)
- M D McSweeney
- Division of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
| | - T Wessler
- Department of Mathematics, University of North Carolina, Chapel Hill, NC, USA.
| | - L S L Price
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
| | - E C Ciociola
- Division of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
| | - L B Herity
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
| | - J A Piscitelli
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
| | - W C Zamboni
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
| | - M G Forest
- Department of Mathematics, University of North Carolina, Chapel Hill, NC, USA.
| | - Y Cao
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
| | - S K Lai
- Division of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA; UNC/NCSU Joint Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, USA; Department of Microbiology and Immunology, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.
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