A minimal physiologically based pharmacokinetic model to characterize colon TNF suppression and treatment effects of an anti-TNF monoclonal antibody in a mouse inflammatory bowel disease model

Abstract

Biotherapeutic drugs against tumor necrosis factor (TNF) are effective treatments for moderate to severe inflammatory bowel disease (IBD). Here, we evaluated CNTO 5048, an antimurine TNF surrogate monoclonal antibody (mAb), in a CD45RB high adoptive T cell transfer mouse colitis model, which allows examination of the early immunological events associated with gut inflammation and the therapeutic effects. The study was designed to quantitatively understand the effects of IBD on CNTO 5048 disposition, the ability of CNTO 5048 to neutralize pathogenic TNF at the colon under disease conditions, and the impact of dosing regimen on CNTO 5048 treatment effect. CNTO 5048 and TNF concentrations in both mice serum and colon homogenate were also measured. Free TNF concentrations in colon, but not in serum, were shown to correlate well with the colon pharmacodynamic readout, such as the summed histopathology score and neutrophil score. A minimal physiologically based pharmacokinetic (mPBPK) model was developed to characterize CNTO 5048 PK and disposition, as well as colon soluble TNF target engagement (TE). The mPBPK/TE model reasonably captured the observed data and provided a quantitative understanding of an anti-TNF mAb on its colon TNF suppression and therapeutic effect in a physiologically relevant IBD animal model. These results also provided insights into the potential benefits of using induction doses for the treatment of IBD patients.

Minimal Physiologically-Based Pharmacokinetic (mPBPK) Metamodeling of Target Engagement in Skin Informs Anti-IL17A Drug Development in Psoriasis

“… b Parameter assumed to be the same as for secukinumab. c References: [1] ( Bruin et al, 2017 ); [2] ( Cao et al, 2013 ); [3] ( Shah and Betts, 2012 ); [4] ( Zheng et al, 2020 ); [5] ( Chen et al, 2016 ); [6] ( Dragatin et al, 2016 ); [7] ( Adams et al, 2020 ); [8] ( Chen et al, 2018 ); [9] ( FDA, 2015 ); [10] ( FDA, 2016 ). …”

“…Circulation of secukinumab and ixekizumab was assumed to depend predominantly on lymphatic flow and paravascular convection ( Cao et al, 2013 ). Although interaction between the antibody and IL-17A would occur ubiquitously, this process was simplified to occur in skin and serum compartments only ( Zheng et al, 2020a ). Similarly, distributary circulation of IL-17A and the drug-target complex were not modeled explicitly; instead, their dynamics in serum and in skin were considered locally ( Chen et al, 2018 ).…”

“…It inherits the key advantages of a whole-body PBPK model by using physiologically relevant parameters while focusing only on the tissue of interest hence being easier to implement ( Ayyar and Jusko, 2020 ). With specific tissue PK and target dynamics data to inform the model, target-mediated drug disposition (TMDD) kinetics can be incorporated into the central circulation and/or the specific tissue compartments, as exemplified previously in preclinical studies ( Chen et al, 2016 ; Chen et al, 2018 ; Zheng et al, 2020a ). To our knowledge, an approach integrating mPBPK modeling of human PK and IL-17A TE data with observed clinical response (e.g., disease score) has not been reported thus far.…”

Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions

“…The key determinants of antibody PK remained in the mPBPK models, such as convection as the major distribution pathway and the distribution space is limited in the interstitial fluid (ISF). The mPBPK models have been applied to characterize antibody PK profiles in various disease scenarios [ 25 , 26 , 27 , 28 , 29 , 30 , 31 ].…”

“…PBPK models are usually applied for more mechanistic exploration and species translation, while the mPBPK models could provide a simpler alternative at the systemic level but potential elaborations of tissue-of-interest. The mPBPK model has been adopted to assess the target binding dynamics in the target tissues and the effect of endosome trafficking on FcRn-mediated antibody recycling [ 23 , 25 , 26 , 27 , 28 , 30 , 115 ]. For example, Zheng et al investigated the distribution of an anti-TNF antibody candidate CNTO5048 and its TNF-suppression effect by developing an mPBPK model with an extended compartment representing mice colon [ 26 ].…”