Impact of altered endogenous IgG on unspecific mAb clearance

  • Saskia Fuhrmann
  • Charlotte Kloft
  • Wilhelm HuisingaEmail author
Original Paper


Immunodeficient mice are crucial models to evaluate the efficacy of monoclonal antibodies (mAbs). When studying mAb pharmacokinetics (PK), protection from elimination by binding to the neonatal Fc receptor (FcRn) is known to be a major process influencing the unspecific clearance of endogenous and therapeutic IgG. The concentration of endogenous IgG in immunodeficient mice, however is reduced, and this effect on the FcRn protection mechanism and subsequently on unspecific mAb clearance is unknown, yet of great importance for the interpretation of mAb PK data. We used a PBPK modelling approach to elucidate the influence of altered endogenous IgG concentrations on unspecific mAb clearance. To this end, we used PK data in immunodeficient mice, i.e. nude and severe combined immunodeficiency mice. To avoid impact of target-mediated clearance processes, we focussed on mAbs without affinity to a target antigen in these mice. In addition, intravenous immunoglobulin (IVIG) data of immunocompetent mice was used to study the impact of increased total IgG concentrations on unspecific therapeutic antibody clearance. The unspecific clearance is linear, whenever therapeutic IgG concentrations, i.e. mAb and IVIG concentrations are lower than FcRn; it can be non-linear if therapeutic IgG concentrations are larger than FcRn and endogenous IgG concentrations (e.g., under IVIG therapy). Unspecific mAb clearance of immunodeficient mice is effectively linear (under mAb doses as typically used in human). Studying the impact of reduced endogenous IgG concentrations on unspecific mAb clearance is of great relevance for the extrapolation to clinical species, e.g., when predicting mAb PK in immunosuppressed cancer patients.


mAb disposition PBPK FcRn salvage mechanism Immunodeficient mice models Unspecific antibody clearance 



S.F. acknowledges fruitful discussions with Hans Peter Grimm (F. Hoffmann-La Roche Ltd, Basel, Switzerland).


  1. 1.
    Dirks NL, Meibohm B (2010) Population pharmacokinetics of therapeutic monoclonal antibodies. Clin Pharmacokinet 49(10):633–659CrossRefPubMedGoogle Scholar
  2. 2.
    Mager DE, Jusko WJ (2001) General pharmacokinetic model for drugs exhibiting target-mediated drug disposition. J Pharmacokinet Pharmacodyn 28(6):507–532CrossRefPubMedGoogle Scholar
  3. 3.
    Mager DE, Krzyzanski W (2005) Quasi-equilibrium pharmacokinetic model for drugs exhibiting target-mediated drug disposition. Pharm Res 22(10):1589–96CrossRefPubMedGoogle Scholar
  4. 4.
    Gibiansky L, Gibiansky E, Kakkar T, Ma P (2008) Approximations of the target-mediated drug disposition model and identifiability of model parameters. J Pharmacokinet Pharmacodyn 35(5):573–591CrossRefPubMedGoogle Scholar
  5. 5.
    Grimm HP (2009) Gaining insights into the consequences of target-mediated drug disposition of monoclonal antibodies using quasi-steady-state approximations. J Pharmacokinet Pharmacodyn 36(5):407–420CrossRefPubMedGoogle Scholar
  6. 6.
    Krippendorff BF, Kuester K, Kloft C, Huisinga W (2009) Nonlinear pharmacokinetics of therapeutic proteins resulting from receptor mediated endocytosis. J Pharmacokinet Pharmacodyn 36(3):239–260CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Krippendorff BF, Oyarzún DA, Huisinga W (2012) Predicting the F(ab)-mediated effect of monoclonal antibodies in vivo by combining cell-level kinetic and pharmacokinetic modelling. J Pharmacokinet Pharmacodyn 39(2):125–139CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Keizer RJ, Huitema ADR, Schellens JHM, Beijnen JH (2010) Clinical pharmacokinetics of therapeutic monoclonal antibodies. Clin Pharmacokinet 49(8):493–507CrossRefPubMedGoogle Scholar
  9. 9.
    Ferl GZ, Wu AM, DiStefano JJ (2005) A predictive model of therapeutic monoclonal antibody dynamics and regulation by the neonatal Fc receptor (FcRn). Ann Biomed Eng 33(11):1640–1652CrossRefPubMedGoogle Scholar
  10. 10.
    Garg A, Balthasar JP (2007) Physiologically-based pharmacokinetic (PBPK) model to predict IgG tissue kinetics in wild-type and FcRn-knockout mice. J Pharmacokinet Pharmacodyn 34(5):687–709CrossRefPubMedGoogle Scholar
  11. 11.
    Chen Y, Balthasar JP (2012) Evaluation of a catenary PBPK model for predicting the in vivo disposition of mAbs engineered for high-affinity binding to FcRn. AAPS J 14(4):850–859CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Jones HM, Mayawala K, Poulin P (2012) Dose selection based on physiologically based pharmacokinetic (PBPK) approaches. AAPS J 15(2):377–387CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Cao Y, Balthasar JP, Jusko WJ (2013) Second-generation minimal physiologically-based pharmacokinetic model for monoclonal antibodies. J Pharmacokinet Pharmacodyn 40(5):597–607CrossRefPubMedGoogle Scholar
  14. 14.
    Fronton L, Pilari S, Huisinga W (2014) Monoclonal antibody disposition: a simplified PBPK model and its implications for the derivation and interpretation of classical compartment models. J Pharmacokinet Pharmacodyn 41(2):87–107CrossRefPubMedGoogle Scholar
  15. 15.
    Huisinga W, Fuhrmann S, Fronton L, Krippendorff BF (2015) Target-driven pharmacokinetics of biotherapeutics. In: Zhou H, Theil FP (eds) Application of ADME and translational PK/PD in the development of therapeutic drugs. Wiley, New York, pp 197–209Google Scholar
  16. 16.
    Shah DK, Betts AM (2013) Antibody biodistribution coefficients Inferring tissue concentrations of monoclonal antibodies based on the plasma concentrations in several preclinical species and human. mAbs 5(2):297–305CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Jones HM (2013) Basic concepts in physiologically based pharmacokinetic modeling in drug discovery and development. CPT Pharmacomet Syst Pharmacol 2(e63):1–2Google Scholar
  18. 18.
    Kim R, Emi M, Tanabe K (2006) Cancer immunosuppression and autoimmune disease: beyond immunosuppressive networks for tumour immunity. Immunology 119(2):254–264CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    von Bernstorff W, Voss M, Freichel S, Schmid A, Vogel I, Jöhnk C, Henne-Bruns D, Kremer B, Kalthoff H (2001) Systemic and local immunosuppression in pancreatic cancer patients. Clin Cancer Res 7(3):925s–932sGoogle Scholar
  20. 20.
    Penn I, Starzl TE (1973) Immunosuppression and cancer. Transplant Proc 5(1):943–947PubMedPubMedCentralGoogle Scholar
  21. 21.
    Wochner RD, Drews G, Strober W, Waldmann TA (1966) Accelerated breakdown of immunoglobulin G (IgG) in myotonic dystrophy: a hereditary error of immunoglobulin catabolism. J Clin Invest 45(3):321–329CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Schuppan D, Afdhal NH (2008) Liver cirrhosis. Lancet 371:838–851CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Kawai R, Lemaire M, Steimer JL, Bruelisauer A, Niederberger W, Rowland M (1994) Physiologically based pharmacokinetic study on a cyclosporin derivative, SDZ IMM 125. J Pharmacokinet Biopharm 22(5):327–365CrossRefPubMedGoogle Scholar
  24. 24.
    Boswell CA, Mundo EE, Ulufatu S, Bumbaca D, Cahaya HS, Majidy N, Hoy MV, Schweiger MG, Fielder PJ, Prabhu S, Khawli LA (2014) Comparative physiology of mice and rats: radiometric measurement of vascular parameters in rodent tissues. Mol Pharm 11:1591–1598CrossRefPubMedGoogle Scholar
  25. 25.
    Xiao JJ (2012) Pharmacokinetic models for FcRn-mediated IgG disposition. J Biomed Biotechnol. doi: 10.1155/2012/282989
  26. 26.
    Garg A (2007) Investigation of the role of FcRn in the absorption, distribution, and elimination of monoclonal antibodies. Dissertation, State University of New York at BuffaloGoogle Scholar
  27. 27.
    Abuqayyas L, Balthasar JP (2012) Application of PBPK modeling to predict monoclonal antibody disposition in plasma and tissues in mouse models of human colorectal cancer. J Pharmacokinet Pharmacodyn 39(6):683–710CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
  29. 29.
    Baxter LT, Zhu H, Mackensen DG, Jain RK (1994) Physiologically based pharmacokinetic model for specific and nonspecific monoclonal antibodies and fragments in normal tissues and human tumor xenografts in nude mice. Cancer Res 54(6):1517–1528PubMedGoogle Scholar
  30. 30.
    Brown RP, Delp MD, Lindstedt SL, Rhomberg LR, Beliles RP (1997) Physiological parameter values for physiologically based pharmacokinetic models. Toxicol Ind Health 13(4):407–484CrossRefPubMedGoogle Scholar
  31. 31.
    Diehl KH, Hull R, Morton D, Pfister R, Rabemampianina Y, Smith D, Vidal JM, Van De Vorstenbosch C (2001) A good practice guide to the administration of substances and removal of blood, including routes and volumes. J Appl Toxicol 21:15–23CrossRefPubMedGoogle Scholar
  32. 32.
    Windberger U, Bartholovitsch A, Plasenzotti R, Korak KJ, Heinze G (2003) Whole blood viscosity, plasma viscosity and erythrocyte aggregation in nine mammalian species: reference values and comparison of data. Exp Physiol 88:431–440CrossRefPubMedGoogle Scholar
  33. 33.
    Baxter LT, Zhu H, Mackensen DG, Butler WF, Jain RK (1995) Biodistribution of monoclonal antibodies : scale-up from mouse to human using a physiologically based pharmacokinetic model. Cancer Res 55:4611–4622PubMedGoogle Scholar
  34. 34.
    Junghans RP, Anderson CL (1996) The protection receptor for IgG catabolism is the beta2-microglobulin-containing neonatal intestinal transport receptor. Proc Natl Acad Sci USA 93:5512–5516CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Bloemmen J, Eyssen H (1973) Immunoglobulin levels of sera of genetically thymusless (nude) mice. Eur J Immunol 3:117–118CrossRefPubMedGoogle Scholar
  36. 36.
    Deng R, Meng YG, Hoyte K, Lutman J, Lu Y, Iyer S, Deforge LE, Theil F, Fielder PJ, Prabhu S (2012) mAbs. Subcutaneous bioavailability of therapeutic antibodies as a function of FcRn binding affinity in mice 4(1):101–109Google Scholar
  37. 37.
    Covell DG, Barbet J, Holton OD, Black CDV, Parker RJ, Weinstein JN (1986) Pharmacokinetics of monoclonal immunoglobulin G1, F(ab’)2, and Fab in mice. Cancer Res 46:3969–3978PubMedGoogle Scholar
  38. 38.
    El-Masri HA, Portier CJ (1998) Physiologically based pharmacokinetics model of primidone and its metabolites phenobarbital and phenylethylmalonamide in humans, rats and mice. Drug Metab Dispos 26:585–594PubMedGoogle Scholar
  39. 39.
    Lagarias JC, Reeds JA, Wright MH, Wright PE (1998) Convergence properties of the Nelder–Mead simplex method in low dimensions. SIAM J Optim 9(1):112–147CrossRefGoogle Scholar
  40. 40.
    Kreutz C, Raue A, Kaschek D, Timmer J (2013) Profile likelihood in systems biology. FEBS J 280(11):2564–2571CrossRefPubMedGoogle Scholar
  41. 41.
    Kloft C, Graefe EU, Tanswell P, Scott AM, Hofheinz R, Amelsberg A, Karlsson MO (2004) Population pharmacokinetics of sibrotuzumab, a novel therapeutic monoclonal antibody, in cancer patients. Invest New Drugs 22(1):39–52CrossRefPubMedGoogle Scholar
  42. 42.
    Gill KL, Machavaram KK, Rose RH, Chetty M (2016) Potential sources of inter-subject variability in monoclonal antibody pharmacokinetics. Clin Pharmacokinet 55(7):789–805CrossRefPubMedGoogle Scholar
  43. 43.
    Fan YY, Neubert H (2016) Quantitative analysis of human neonatal Fc receptor (FcRn) tissue expression in transgenic mice by online peptide immuno-affinity LC-HRMS. Anal Chem 88(8):4239–4247CrossRefPubMedGoogle Scholar
  44. 44.
    Waldmann TA, Terry WD (1990) Familial hypercatabolic hypoproteinemia. A disorder of endogenous catabolism of albumin and immunoglobulin. J Clin Invest 86(6):2093–2098CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Zhou J, Johnson JE, Ghetie V, Ober RJ, Ward ES (2003) Generation of mutated variants of the human form of the MHC class I-related receptor, FcRn, with increased affinity for mouse immunoglobulin G. J Mol Biol 332(03):901–913CrossRefPubMedGoogle Scholar
  46. 46.
    Popov S, Hubbard JG, Kim JK, Ober B, Ghetie V, Ward ES (1996) The stoichiometry and affinity of the interaction of murine Fc fragments with the MHC class I-related receptor, FcRn. Mol Immunol 33(6):521–530CrossRefPubMedGoogle Scholar
  47. 47.
    Ober RJ, Radu CG, Ghetie V, Ward ES (2001) Differences in promiscuity for antibody-FcRn interactions across species: implications for therapeutic antibodies. Int Immunol 13(12):1551–1559CrossRefPubMedGoogle Scholar
  48. 48.
    Gurbaxani B, Dostalek M, Gardner I (2013) Are endosomal trafficking parameters better targets for improving mAb pharmacokinetics than FcRn binding affinity? Mol Biol 56(4):660–674Google Scholar
  49. 49.
    Stoop J, Zegers B (1969) Serum immunoglobulin levels in healthy children and adults. Clin Exp Immunol 4:101–112PubMedPubMedCentralGoogle Scholar
  50. 50.
    Abdiche YN, Yeung YA, Chaparro-Riggers J, Barman I, Strop P, Chin SM, Pham A, Bolton G, McDonough D, Lindquist K, Pons J, Rajpal A (2015) The neonatal Fc receptor (FcRn) binds independently to both sites of the IgG homodimer with identical affinity. mAbs 7(2):331–343CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Suzuki T, Ishii-Watabe A, Tada M, Kobayashi T, Kanayasu-Toyoda T, Kawanishi T, Yamaguchi T (2010) Importance of neonatal FcR in regulating the serum half-life of therapeutic proteins containing the Fc domain of human IgG1: a comparative study of the affinity of monoclonal antibodies and Fc-fusion proteins to human neonatal FcR. J Immunol 184(4):1968–1976CrossRefPubMedGoogle Scholar
  52. 52.
    Dostalek M, Gardner I, Gurbaxani BM, Rose RH, Chetty M (2013) Pharmacokinetics, pharmacodynamics and physiologically-based pharmacokinetic modelling of monoclonal antibodies. Clin Pharmacokinet 52:83–124CrossRefPubMedGoogle Scholar
  53. 53.
    Yip V, Palma E, Tesar DB, Mundo EE, Bumbaca D, Torres EK, Reyes NA, Shen BQ, Fielder PJ, Prabhu S, Khawli LA, Boswell CA (2014) Quantitative cumulative biodistribution of antibodies in mice: effect of modulating binding affinity to the neonatal Fc receptor. mAbs 6(3):689–696CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Akilesh S, Christianson GJ, Roopenian DC, Shaw AS (2007) Neonatal FcR expression in bone marrow-derived cells functions to protect serum IgG from catabolism. J Immunol 179(7):4580–4588CrossRefPubMedGoogle Scholar
  55. 55.
    Swiercz R, Mo M, Khare P, Schneider Z, Ober RJ, Ward ES (2016) Loss of expression of the recycling receptor, FcRn, promotes tumor cell growth by increasing albumin consumption. Oncotarget 8(2):3528–3541PubMedCentralGoogle Scholar
  56. 56.
    Gullino PM, Grantham FH, Smith SH (1965) The interstitial water space of tumors the interstitial water space of tumors. Cancer Res 25:727–731PubMedGoogle Scholar
  57. 57.
    Urva SR, Yang VC, Balthasar JP (2010) Physiologically based pharmacokinetic model for T84. 66: a monoclonal anti-CEA antibody. J Pharm Sci 99(3):1582–1600CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Saskia Fuhrmann
    • 1
    • 2
  • Charlotte Kloft
    • 3
  • Wilhelm Huisinga
    • 4
    Email author
  1. 1.Institute of Biochemistry and BiologyUniversität PotsdamPotsdamGermany
  2. 2.Graduate Research Training Program PharMetrX: Pharmacometrics & Computational Disease ModelingFreie Universität Berlin and Universität PotsdamBerlin/PotsdamGermany
  3. 3.Department of Clinical Pharmacy and Biochemistry, Institute of PharmacyFreie Universität BerlinBerlinGermany
  4. 4.Institute of MathematicsUniversität PotsdamPotsdamGermany

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