Seshasai Pallikonda Chakravarthy

Comparative study of alternative models capturing Target Mediated Drug Disposition (TMDD) for CD40 agonists

PC Seshasai, Mrittika Roy, Anuraag Saini and Rukmini Kumar

Vantage Research

Introduction:

CD40 is a cell surface molecule that is expressed on antigen presenting cells (B Cells, Macrophages and Dendritic cells) and binds to its cognate ligand CD40L primarily expressed on activated T cells. The binding leads to activation of APCs, stimulation of T cells that result in robust anti-tumour response [1]. CD40 agonists generally exhibit non-linear pharmacokinetic behaviour whose PK can be best described using TMDD (Target mediated drug disposition) [2] models where the drug undergoes elimination through target-mediated endocytosis. However, in the context of sparse clinical PK data, identifying multiple parameters in a complex model can be challenging. In this work, three CD40 agonist were chosen from the public literature and simulations were carried out to fit the plasma pharmacokinetic (PK) data for multiple doses using standard TMDD and simplified models [4] and predictions were evaluated across these alternative models. Akaike Information Criteria is used as a selection criterion across different models.

One of the motivations to develop and evaluate these models is that efficacy of CD40 agonists may be limited by the quantity of agonist reaching the tumour. Hence being able to predict distribution into tumour and other peripheral compartments using such models can be critical in evaluating alternatives.

Objectives:

  1. PK models that describe TMDD can be detailed, capturing receptor-mediator interactions or further simplified (using Michaelis-Menten or Quasi Steady-State assumptions) [3]. Evaluate the trade-off between detailed modelling vs. simplified modelling and fewer parameters in the context of sparsely available clinical data.
  2. Calibrate the most suitable model using available PK data of three CD40 agonist to get predictions on tumour concentrations.

Methods: 

Full TMDD modelling approach captures mechanistic interactions between antibody and receptor and is standard for characterising the non-linear pharmacokinetic behaviour of a drug molecule. However, TMDD models may be over-parameterized and difficult to converge when there is a limited availability of data. In such cases, approximations of TMDD models such as QSS (Quasi Steady State) [KW1] and MM (Michaelis-Menten) models are used to estimate the model parameters [4]. In this work, we have used a two compartment TMDD model with plasma as the central compartment and tumour as the peripheral compartment. The drug undergoes linear clearance from the plasma compartment and receptor-mediated endocytosis from both plasma and tumour compartment. We used plasma PK data of three CD40 agonists namely CDX1140 [6], CP870, 893 [7] and ChiLob7/6 [8] from various clinical studies and evaluated the fit and performance based on the value of objective function and AIC of these alternative models [5]. The model with the least AIC value was chosen as the best model. Further, we predicted the amount of drug reaching the tumour compartment. AUC (area under the concentration-time curve) analysis were done for the three CD40 agonists and they were ranked based on their exposure in the tumour compartment.

Results: 

  1. Non-compartmental analysis (NCA) shows a dose dependent relationship for volume of distribution and clearance rate of the drug. This justifies that CD40 agonist undergoes target mediated drug disposition. Further our understanding of physiology of CD40 also points towards TMDD.
  2. MM model yields least standard errors for the parameter estimates and is the best among the other 3 models for predictions given sparse dataset. The best model should have minimal number of parameters estimated from the model to describe the data with acceptable precision.
  3. Estimates from full TMDD, MM, and QSS model suggests that there is a dose dependent relationship in the exposure of drug in the tumour compartment. Based on our analysis the exposure of various CD40 agonists in the tumour compartment was estimated and compared.

Conclusions:

Alternative models for capturing target mediated drug disposition suggested that MM model provided a good alternative when PK data is scarce as they trade-off model complexity with identifiability. QSS & QEE models, while having fewer parameters are often inconsistent with full TMDD model predictions. CD40 agonists were ranked based on their exposure in the tumour tissue. The AUC for both plasma and tumour compartments are plotted against the doses for different models.

References:
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[2] MagerDE, JuskoWJ (2001) General pharmacokinetic model for drugs exhibiting target-mediated drug disposition. J Pharmacokinet Pharmacodyn 28:507–532. doi:10.1023/A:1014414520282
[3] Mager DE, Krzyzanski W (2005) Quasi-equilibrium pharmacokinetic model for drugs exhibiting target-mediated drug disposition. Pharm Res 22(10):1589–1596. doi:10.1007/s11095-005-6650-0 3.
[4] Gibiansky L, Gibiansky E, Kakkar T and Ma P (2008) Approximations of the target-mediated drug disposition model and identifiability of model parameters. J Pharmacokinet Pharmacodyn. DOI 10.1007/s10928-008-9102-8
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[7] Robert H. Vonderheide, Keith T. Flaherty, Magi Khalil, Molly S. Stumacher, David L. Bajor, Natalie A. Hutnick, Patricia Sullivan, J. Joseph Mahany, Maryann Gallagher, Amy Kramer, Stephanie J. Green, Peter J. O’Dwyer, Kelli L. Running, Richard D. Huhn, and Scott J. Antonia (2007), Clinical Activity and Immune Modulation in Cancer Patients Treated With CP-870,893, a Novel CD40 Agonist Monoclonal Antibody, Journal of Clinical Pharmacology, 0732-183X/07/2507-876, doi: 10.1200/JCO.2006.08.3311.
[8] Peter J,2, Ruth C, Ferdousi C,Yifang G, Melanie H, Tom G, Paul K, Claude C, Anna S, Neil S, Ceri E, Margaret A. K., Elisabeth H, Alison T, Christian O,2, Martin G, and Anthony W (2015), Clinical and Biological Effects of an Agonist Anti-CD40 Antibody: A Cancer Research UK Phase I Study, Clinical Cancer Research, doi: 10.1158/1078-0432.CCR-14-2355.

Reference: PAGE () Abstr 9466 [www.page-meeting.org/?abstract=9466]

Poster: Methodology - Model Evaluation