Literature DB >> 12884253

Application of pharmacokinetic-pharmacodynamic modeling to predict the kinetic and dynamic effects of anti-methotrexate antibodies in mice.

Evelyn D Lobo1, David M Soda, Joseph P Balthasar.   

Abstract

We have shown that intravenous (i.v.) administration of anti-methotrexate (MTX) antibodies (AMAb) reduces the systemic exposure of intraperitoneal (i.p.) MTX therapy, and we have proposed that AMAb effects on MTX systemic exposure would allow a reduction in MTX-induced systemic toxicity (i.e., producing a desirable antagonistic effect). However, many literature reports have shown that anti-toxin antibodies occasionally demonstrate unexpected agonist-like activity, increasing the extent of toxicity induced by their ligand. In this report, we have utilized a pharmacokinetic-pharmacodynamic (PKPD) model to predict the potential of AMAb to increase or decrease the magnitude of MTX-induced body weight loss in mice. Simulations predicted that both anti-MTX immunoglobulin G (AMI) and anti-MTX Fab fragments (AMF) would lead to increases or decreases in MTX toxicity, with effects dependent on the dosing protocol used. Based on the computer simulations, two protocols were selected for in vivo evaluation of predicted agonistic or antagonistic effects. Murine monoclonal AMI and AMF were produced, purified, and characterized. Agonistic effects were tested after 24-h infusion of i.p. MTX (10 mg/kg) and i.v. administration of an equimolar dose of AMI. Antagonistic effects were tested after 72-h infusion of i.p. MTX (5 mg/kg) and i.v. infusion of an equimolar dose of AMF. Consistent with model predictions of agonist-like activity, the 24-h AMI protocol led to significantly increased animal mortality (all animals died, p < 0.005) and mean nadir weight loss (p < 0.005). Also consistent with the predictions of the PKPD model, the 72-h AMF protocol significantly decreased animal mortality and mean nadir body weight loss (p < 0.01). Thus, these studies demonstrate that agonistic and antagonistic effects of anti-toxin antibodies may be predicted through the use of an integrated PKPD model. Copyright 2003 Wiley-Liss, Inc.

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Year:  2003        PMID: 12884253     DOI: 10.1002/jps.10432

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  8 in total

Review 1.  Clinical pharmacokinetics of therapeutic monoclonal antibodies.

Authors:  Ron J Keizer; Alwin D R Huitema; Jan H M Schellens; Jos H Beijnen
Journal:  Clin Pharmacokinet       Date:  2010-08       Impact factor: 6.447

2.  PK/TD modeling for prediction of the effects of 8C2, an anti-topotecan mAb, on topotecan-induced toxicity in mice.

Authors:  Dhaval K Shah; Joseph P Balthasar
Journal:  Int J Pharm       Date:  2014-02-06       Impact factor: 5.875

3.  Pharmacokinetic and pharmacodynamic effects of high-dose monoclonal antibody therapy in a rat model of immune thrombocytopenia.

Authors:  Feng Jin; Zia R Tayab; Joseph P Balthasar
Journal:  AAPS J       Date:  2006-01-13       Impact factor: 4.009

4.  Comparison of the effects of antibody-coated liposomes, IVIG, and anti-RBC immunotherapy in a murine model of passive chronic immune thrombocytopenia.

Authors:  Rong Deng; Joseph P Balthasar
Journal:  Blood       Date:  2006-11-28       Impact factor: 22.113

5.  Predicting the effects of 8C2, a monoclonal anti-topotecan antibody, on plasma and tissue disposition of topotecan.

Authors:  Dhaval K Shah; Joseph P Balthasar
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-12-25       Impact factor: 2.745

6.  Mathematical modeling of topotecan pharmacokinetics and toxicodynamics in mice.

Authors:  Jin Chen; Qiang Lu; Joseph P Balthasar
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-09-21       Impact factor: 2.410

7.  A Tutorial on Target-Mediated Drug Disposition (TMDD) Models.

Authors:  P Dua; E Hawkins; P H van der Graaf
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-06-15

8.  Unraveling the pharmacokinetic interaction of ticagrelor and MEDI2452 (Ticagrelor antidote) by mathematical modeling.

Authors:  J Almquist; M Penney; S Pehrsson; A-S Sandinge; A Janefeldt; S Maqbool; S Madalli; J Goodman; S Nylander; P Gennemark
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-06-16
  8 in total

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