title: Application of pharmacokinetic-pharmacodynamic modeling to predict the kinetic and dynamic effects of anti-methotrexate antibodies in mice.
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.
authors.affiliation: Department of Pharmaceutical Sciences, University at Buffalo, The State University at New York, 521 Hochstetter Hall, Buffalo, New York 14260, USA.
authors.forename: Evelyn D
authors.initials: ED
authors.lastname: Lobo
authors.forename: David M
authors.initials: DM
authors.lastname: Soda
authors.forename: Joseph P
authors.initials: JP
authors.lastname: Balthasar
mesh_terms: D000818:Animals; D000911:Antibodies, Monoclonal / Q000096:biosynthesis / Q000302:isolation & purification / Q000493:pharmacokinetics* / Q000494:pharmacology*; D003198:Computer Simulation; D006825:Hybridomas; D008297:Male; D008727:Methotrexate / Q000008:administration & dosage / Q000819:agonists / Q000276:immunology*; D051379:Mice; D008954:Models, Biological; D008956:Models, Chemical; D011237:Predictive Value of Tests; D015431:Weight Loss / Q000276:immunology
chemical_list: D000911:Antibodies, Monoclonal; D008727:Methotrexate