A Physiologically-Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics From In Vitro Data.

Monoclonal antibody (mAb) pharmacokinetics (PK) have largely been predicted via allometric scaling with little consideration for cross-species differences in neonatal Fc receptor (FcRn) affinity or clearance/distribution mechanisms. To address this, we developed a mAb physiologically-based PK model that describes the intracellular trafficking and FcRn recycling of mAbs in a human FcRn transgenic homozygous mouse and human. This model uses mAb-specific in vitro data together with species-specific FcRn tissue expression, tissue volume, and blood-flow physiology to predict mAb in vivo linear PK a priori. The model accurately predicts the terminal half-life of 90% of the mAbs investigated within a twofold error. The mechanistic nature of this model allows us to not only predict linear PK from in vitro data but also explore the PK and target binding of mAbs engineered to have pH-dependent binding to its target or FcRn and could aid in the selection of mAbs with optimal PK and pharmacodynamic properties.

Preclinical to Clinical Translation of Antibody-Drug Conjugates Using PK/PD Modeling: a Retrospective Analysis of Inotuzumab Ozogamicin.

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model was used for preclinical to clinical translation of inotuzumab ozogamicin, a CD22-targeting antibody-drug conjugate (ADC) for B cell malignancies including non-Hodgkin's lymphoma (NHL) and acute lymphocytic leukemia (ALL). Preclinical data was integrated in a PK/PD model which included (1) a plasma PK model characterizing disposition and clearance of inotuzumab ozogamicin and its released payload N-Ac-γ-calicheamicin DMH, (2) a tumor disposition model describing ADC diffusion into the tumor extracellular environment, (3) a cellular model describing inotuzumab ozogamicin binding to CD22, internalization, intracellular N-Ac-γ-calicheamicin DMH release, binding to DNA, or efflux from the tumor cell, and (4) tumor growth and inhibition in mouse xenograft models. The preclinical model was translated to the clinic by incorporating human PK for inotuzumab ozogamicin and clinically relevant tumor volumes, tumor growth rates, and values for CD22 expression in the relevant patient populations. The resulting stochastic models predicted progression-free survival (PFS) rates for inotuzumab ozogamicin in patients comparable to the observed clinical results. The model suggested that a fractionated dosing regimen is superior to a conventional dosing regimen for ALL but not for NHL. Simulations indicated that tumor growth is a highly sensitive parameter and predictive of successful outcome. Inotuzumab ozogamicin PK and N-Ac-γ-calicheamicin DMH efflux are also sensitive parameters and would be considered more useful predictors of outcome than CD22 receptor expression. In summary, a multiscale, mechanism-based model has been developed for inotuzumab ozogamicin, which can integrate preclinical biomeasures and PK/PD data to predict clinical response.

Evolution of Antibody-Drug Conjugate Tumor Disposition Model to Predict Preclinical Tumor Pharmacokinetics of Trastuzumab-Emtansine (T-DM1).

A mathematical model capable of accurately characterizing intracellular disposition of ADCs is essential for a priori predicting unconjugated drug concentrations inside the tumor. Towards this goal, the objectives of this manuscript were to: (1) evolve previously published cellular disposition model of ADC with more intracellular details to characterize the disposition of T-DM1 in different HER2 expressing cell lines, (2) integrate the improved cellular model with the ADC tumor disposition model to a priori predict DM1 concentrations in a preclinical tumor model, and (3) identify prominent pathways and sensitive parameters associated with intracellular activation of ADCs. The cellular disposition model was augmented by incorporating intracellular ADC degradation and passive diffusion of unconjugated drug across tumor cells. Different biomeasures and chemomeasures for T-DM1, quantified in the companion manuscript, were incorporated into the modified model of ADC to characterize in vitro pharmacokinetics of T-DM1 in three HER2+ cell lines. When the cellular model was integrated with the tumor disposition model, the model was able to a priori predict tumor DM1 concentrations in xenograft mice. Pathway analysis suggested different contribution of antigen-mediated and passive diffusion pathways for intracellular unconjugated drug exposure between in vitro and in vivo systems. Global and local sensitivity analyses revealed that non-specific deconjugation and passive diffusion of the drug across tumor cell membrane are key parameters for drug exposure inside a cell. Finally, a systems pharmacokinetic model for intracellular processing of ADCs has been proposed to highlight our current understanding about the determinants of ADC activation inside a cell.

Determination of Cellular Processing Rates for a Trastuzumab-Maytansinoid Antibody-Drug Conjugate (ADC) Highlights Key Parameters for ADC Design.

Antibody-drug conjugates (ADCs) are a promising class of cancer therapeutics that combine the specificity of antibodies with the cytotoxic effects of payload drugs. A quantitative understanding of how ADCs are processed intracellularly can illustrate which processing steps most influence payload delivery, thus aiding the design of more effective ADCs. In this work, we develop a kinetic model for ADC cellular processing as well as generalizable methods based on flow cytometry and fluorescence imaging to parameterize this model. A number of key processing steps are included in the model: ADC binding to its target antigen, internalization via receptor-mediated endocytosis, proteolytic degradation of the ADC, efflux of the payload out of the cell, and payload binding to its intracellular target. The model was developed with a trastuzumab-maytansinoid ADC (TM-ADC) similar to trastuzumab-emtansine (T-DM1), which is used in the clinical treatment of HER2+ breast cancer. In three high-HER2-expressing cell lines (BT-474, NCI-N87, and SK-BR-3), we report for TM-ADC half-lives for internalization of 6-14 h, degradation of 18-25 h, and efflux rate of 44-73 h. Sensitivity analysis indicates that the internalization rate and efflux rate are key parameters for determining how much payload is delivered to a cell with TM-ADC. In addition, this model describing the cellular processing of ADCs can be incorporated into larger pharmacokinetics/pharmacodynamics models, as demonstrated in the associated companion paper.

A Flow Cytometric Clonogenic Assay Reveals the Single-Cell Potency of Doxorubicin.

Standard cell proliferation assays use bulk media drug concentration to ascertain the potency of chemotherapeutic drugs; however, the relevant quantity is clearly the amount of drug actually taken up by the cell. To address this discrepancy, we have developed a flow cytometric clonogenic assay to correlate the amount of drug in a single cell with the cell's ability to proliferate using a cell tracing dye and doxorubicin, a naturally fluorescent chemotherapeutic drug. By varying doxorubicin concentration in the media, length of treatment time, and treatment with verapamil, an efflux pump inhibitor, we introduced 10(5) -10(10) doxorubicin molecules per cell; then used a dye-dilution assay to simultaneously assess the number of cell divisions. We find that a cell's ability to proliferate is a surprisingly conserved function of the number of intracellular doxorubicin molecules, resulting in single-cell IC50 values of 4-12 million intracellular doxorubicin molecules. The developed assay is a straightforward method for understanding a drug's single-cell potency and can be used for any fluorescent or fluorescently labeled drug, including nanoparticles or antibody-drug conjugates.

On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach.

Objectives of the present investigation were: (1) to compare three literature reported tumor growth inhibition (TGI) pharmacodynamic (PD) models and propose an optimal new model that best describes the xenograft TGI data for antibody drug conjugates (ADC), (2) to translate efficacy of the ADC Trastuzumab-emtansine (T-DM1) from mice to patients using the optimized PD model, and (3) to apply the translational strategy to predict clinically efficacious concentrations of a novel in-house anti-5T4 ADC, A1mcMMAF. First, the performance of all four of the PD models (i.e. 3 literature reported + 1 proposed) was evaluated using TGI data of T-DM1 obtained from four different xenografts. Based on the estimates of the pharmacodynamic/pharmacokinetic (PK/PD) modeling, a secondary parameter representing the efficacy index of the drug was calculated, which is termed as the tumor static concentration (TSC). TSC values derived from all four of the models were compared with each other, and with literature reported values, to assess the performance of these models. Subsequently, using the optimized PK/PD model, PD parameters obtained from different cell lines, human PK, and the proposed translational strategy, clinically efficacious doses of T-DM1 were projected. The accuracy of projected efficacious dose range for T-DM1 was verified by comparison with the clinical doses. Aforementioned strategy was then applied to A1mcMMAF for projecting its efficacious concentrations in clinic. TSC values for A1mcMMAF, obtained by fitting TGI data from 4 different xenografts with the proposed PK/PD model, were estimated to range from 0.6 to 11.5 µg mL⁻¹. Accordingly, the clinically efficacious doses for A1mcMMAF were projected retrospectively. All in all, the improved PD model and proposed translational strategy presented here suggest that appropriate correction for the clinical exposure and employing the TSC criterion can help translate mouse TGI data to predict first in human doses of ADCs.

Antibody biodistribution coefficients: inferring tissue concentrations of monoclonal antibodies based on the plasma concentrations in several preclinical species and human.

Tissue vs. plasma concentration profiles have been generated from a physiologically-based pharmacokinetic model of monoclonal antibody (mAb). Based on the profiles, we hypothesized that a linear relationship between the plasma and tissue concentrations of non-binding mAbs could exist; and that the relationship may be generally constant irrespective of the absolute mAb concentration, time, and animal species being analyzed. The hypothesis was verified for various tissues in mice, rat, monkey, and human using mAb or antibody-drug conjugate tissue distribution data collected from diverse literature. The relationship between the plasma and various tissue concentrations was mathematically characterized using the antibody biodistribution coefficient (ABC). Estimated ABC values suggest that typically the concentration of mAb in lung is 14.9%, heart 10.2%, kidney 13.7%, muscle 3.97%, skin 15.7%, small intestine 5.22%, large intestine 5.03%, spleen 12.8%, liver 12.1%, bone 7.27%, stomach 4.98%, lymph node 8.46%, adipose 4.78%, brain 0.351%, pancreas 6.4%, testes 5.88%, thyroid 67.5% and thymus is 6.62% of the plasma concentration. The validity of using the ABC to predict mAb concentrations in different tissues of mouse, rat, monkey, and human species was evaluated by generating validation data sets, which demonstrated that predicted concentrations were within 2-fold of the observed concentrations. The use of ABC to infer tissue concentrations of mAbs and related molecules provides a valuable tool for investigating preclinical or clinical disposition of these molecules. It can also help eliminate or optimize biodistribution studies, and interpret efficacy or toxicity of the drug in a particular tissue.

Towards a platform PBPK model to characterize the plasma and tissue disposition of monoclonal antibodies in preclinical species and human.

The objectives of the following investigation were (1) development of a physiologically based pharmacokinetic (PBPK) model capable of characterizing the plasma and tissue pharmacokinetics (PK) of nonspecific or antigen specific monoclonal antibodies (mAbs) in wild type, FcRn knockout, tumor bearing and non tumor bearing mice and (2) evaluation of the scale up potential of the model by characterizing the mouse, rat, monkey and human plasma PK of mAbs, simultaneously. A PBPK model containing 15 tissues, a carcass and a tumor compartment was developed by modifying/augmenting previously published PBPK models. Each tissue compartment was subdivided into plasma, blood cell, endothelial, interstitial and cellular sub-compartments. Each tissue was connected through blood and lymph flow to the systemic circulation. Lymph flow was set to a value 500 times lower than plasma flow and vascular reflection coefficients for each tissue were adjusted according to their vascular pore size. In each tissue endothelial space, mAb entered via pinocytosis and the interaction of FcRn with mAb was described by on and off rates. FcRn bound mAb was recycled and unbound mAb was eliminated by a first order process (K(deg)). The PBPK model was simultaneously fit to the following datasets to estimate four system parameters: (1) plasma and tissue PK of nonspecific mAb in wild type mouse with or without simultaneous intravenous immunoglobulin (IVIG) administration, (2) plasma and tissue PK of nonspecific mAb in FcRn knockout mouse, (3) plasma and tissue PK of nonspecific mAb in tumor bearing mouse, (4) plasma and tissue PK of tumor antigen specific mAb in tumor bearing mouse, and (5) plasma PK of mAb in rat, monkey and human. The model was able to characterize all the datasets reasonably well with a common set of parameters. The estimated value of the four system parameters i.e. FcRn concentration (FcRn), rate of pinocytosis per unit endosomal space (CL(up)), K(deg) and the proportionality constant (C_LNLF) between the rate at which antibody transfers from the lymph node compartment to the blood compartment and the plasma flow of the given species, were found to be 4.98E-05 M (CV% = 11.1), 3.66E-02 l/h/l (%CV = 3.48), 42.9 1/h (%CV = 15.7) and 9.1 (CV% > 50). Thus, a platform PBPK model has been developed that can not only simultaneously characterize mAb disposition data obtained from various previously published mouse PBPK models but is also capable of characterizing mAb disposition in various preclinical species and human.

The application of target information and preclinical pharmacokinetic/pharmacodynamic modeling in predicting clinical doses of a Dickkopf-1 antibody for osteoporosis.

PF-04840082 is a humanized prototype anti-Dickkopf-1 (Dkk-1) immunoglobulin isotype G(2) (IgG(2)) antibody for the treatment of osteoporosis. In vitro, PF-04840082 binds to human, monkey, rat, and mouse Dkk-1 with high affinity. After administration of PF-04840082 to rat and monkey, free Dkk-1 concentrations decreased rapidly and returned to baseline in a dose-dependent manner. In rat and monkey, PF-04840082 exhibited nonlinear pharmacokinetics (PK) and a target-mediated drug disposition (TMDD) model was used to characterize PF-04840082 versus Dkk-1 concentration response relationship. PK/pharmacodynamic (PK/PD) modeling enabled estimation of antibody non-target-mediated elimination, Dkk-1 turnover, complex formation, and complex elimination. The TMDD model was translated to human to predict efficacious dose and minimum anticipated biological effect level (MABEL) by incorporating information on typical IgG(2) human PK, antibody-target association/dissociation rates, Dkk-1 expression, and turnover rates. The PK/PD approach to MABEL was compared with the standard "no adverse effect level" (NOAEL) approach to calculating clinical starting doses and a pharmacological equilibrium method. The NOAEL method gave estimates of dose that were too high to ensure safety of clinical trials. The pharmacological equilibrium approach calculated receptor occupancy (RO) based on equilibrium dissociation constant alone and did not take into account rate of turnover of the target or antibody-target complex kinetics and, as a result, it likely produced a substantial overprediction of RO at a given dose. It was concluded that the calculation of MABEL according to the TMDD model was the most appropriate means for ensuring safety and efficacy in clinical studies.

In vitro and in vivo SAR of pyrido[3,4-d]pyramid-4-ylamine based mGluR1 antagonists.

The SAR of a series of novel pyrido[3,4-d]pyramid-4-ylamine mGluR1 antagonists is described. The multiple of the unbound K(i) in cerebrospinal fluid necessary to give morphine like analgesic effects in an electromyograph pinch model in rodents is determined and the effect of structure on CNS penetration examined.