Quantitative evaluation of trastuzumab deruxtecan pharmacokinetics and pharmacodynamics in mouse models of varying degrees of HER2 expression.

Trastuzumab deruxtecan (T-DXd; DS-8201; ENHERTU®) is a human epithelial growth factor receptor 2 (HER2)-directed antibody drug conjugate (ADC) with demonstrated antitumor activity against a range of tumor types. Aiming to understand the relationship between antigen expression and downstream efficacy outcomes, T-DXd was administered in tumor-bearing mice carrying NCI-N87, Capan-1, JIMT-1, and MDA-MB-468 xenografts, characterized by varying HER2 levels. Plasma pharmacokinetics (PK) of total antibody, T-DXd, and released DXd and tumor concentrations of released DXd were evaluated, in addition to monitoring γΗ2AX and pRAD50 pharmacodynamic (PD) response. A positive relationship was observed between released DXd concentrations in tumor and HER2 expression, with NCI-N87 xenografts characterized by the highest exposures compared to the remaining cell lines. γΗ2AX and pRAD50 demonstrated a sustained increase over several days occurring with a time delay relative to tumoral-released DXd concentrations. In vitro investigations of cell-based DXd disposition facilitated the characterization of DXd kinetics across tumor cells. These outputs were incorporated into a mechanistic mathematical model, utilized to describe PK/PD trends. The model captured plasma PK across dosing arms as well as tumor PK in NCI-N87, Capan-1, and MDA-MB-468 models; tumor concentrations in JIMT-1 xenografts required additional parameter adjustments reflective of complex receptor dynamics. γΗ2AX longitudinal trends were well characterized via a unified PD model implemented across xenografts demonstrating the robustness of measured PD trends. This work supports the application of a mechanistic model as a quantitative tool, reliably projecting tumor payload concentrations upon T-DXd administration, as the first step towards preclinical-to-clinical translation.

A PKPD Case Study: Achieving Clinically Relevant Exposures of AZD5991 in Oncology Mouse Models.

Capturing human equivalent drug exposures preclinically is a key challenge in the translational process. Motivated by the need to recapitulate the pharmacokinetic (PK) profile of the clinical stage Mcl-1 inhibitor AZD5991 in mice, we describe the methodology used to develop a refined mathematical model relating clinically relevant concentration profiles to efficacy. Administration routes were explored to achieve target exposures matching the clinical exposure of AZD5991. Intravenous infusion using vascular access button (VAB) technology was found to best reproduce clinical target exposures of AZD5991 in mice. Exposure-efficacy relationships were evaluated, demonstrating that dissimilar PK profiles result in differences in target engagement and efficacy outcomes. Thus, these data underscore the importance of accurately ascribing key PK metrics in the translational process to enable clinically meaningful predictions of efficacy.

Discovery and Optimization of the First ATP Competitive Type-III c-MET Inhibitor.

Recent clinical reports have highlighted the need for wild-type (WT) and mutant dual inhibitors of c-MET kinase for the treatment of cancer. We report herein a novel chemical series of ATP competitive type-III inhibitors of WT and D1228V mutant c-MET. Using a combination of structure-based drug design and computational analyses, ligand 2 was optimized to a highly selective chemical series with nanomolar activities in biochemical and cellular settings. Representatives of the series demonstrate excellent pharmacokinetic profiles in rat in vivo studies with promising free-brain exposures, paving the way for the design of brain permeable drugs for the treatment of c-MET driven cancers.

ADME and DMPK considerations for the discovery and development of antibody drug conjugates (ADCs).

 The therapeutic concept of antibody drug conjugates (ADCs) is to selectively target tumour cells with small molecule cytotoxic drugs to maximise cell kill benefit and minimise healthy tissue toxicity.An ADC generally consists of an antibody that targets a protein on the surface of tumour cells chemically linked to a warhead small molecule cytotoxic drug.To deliver the warhead to the tumour cell, the antibody must bind to the target protein and in general be internalised into the cell. Following internalisation, the cytotoxic agent can be released in the endosomal or lysosomal compartment (via different mechanisms). Diffusion or transport out of the endosome or lysosome allows the cytotoxic drug to express its cell-killing pharmacology. Alternatively, some ADCs (e.g. EDB-ADCs) rely on extracellular cleavage releasing membrane permeable warheads.One potentially important aspect of the ADC mechanism is the 'bystander effect' whereby the cytotoxic drug released in the targeted cell can diffuse out of that cell and into other (non-target expressing) tumour cells to exert its cytotoxic effect. This is important as solid tumours tend to be heterogeneous and not all cells in a tumour will express the targeted protein.The combination of large and small molecule aspects in an ADC poses significant challenges to the disposition scientist in describing the ADME properties of the entire molecule.This article will review the ADC landscape and the ADME properties of successful ADCs, with the aim of outlining best practice and providing a perspective of how the field can further facilitate the discovery and development of these important therapeutic modalities.

Quantitative Evaluation of Dendritic Nanoparticles in Mice: Biodistribution Dynamics and Downstream Tumor Efficacy Outcomes.

A physiologically based pharmacokinetic model was developed to describe the tissue distribution kinetics of a dendritic nanoparticle and its conjugated active pharmaceutical ingredient (API) in plasma, liver, spleen, and tumors. Tumor growth data from MV-4-11 tumor-bearing mice were incorporated to investigate the exposure/efficacy relationship. The nanoparticle demonstrated improved antitumor activity compared to the conventional API formulation, owing to the extended released API concentrations at the site of action. Model simulations further enabled the identification of critical parameters that influence API exposure in tumors and downstream efficacy outcomes upon nanoparticle administration. The model was utilized to explore a range of dosing schedules and their effect on tumor growth kinetics, demonstrating the improved antitumor activity of nanoparticles with less frequent dosing compared to the same dose of naked APIs in conventional formulations.

A mechanistic tumor penetration model to guide antibody drug conjugate design.

Antibody drug conjugates (ADCs) represent novel anti-cancer modalities engineered to specifically target and kill tumor cells expressing corresponding antigens. Due to their large size and their complex kinetics, these therapeutic agents often face heterogeneous distributions in tumors, leading to large untargeted regions that escape therapy. We present a modeling framework which includes the systemic distribution, vascular permeability, interstitial transport, as well as binding and payload release kinetics of ADC-therapeutic agents in mouse xenografts. We focused, in particular, on receptor dynamics such as endocytic trafficking mechanisms within cancer cells, to simulate their impact on tumor mass shrinkage upon ADC administration. Our model identified undesirable tumor properties that can impair ADC tissue homogeneity, further compromising ADC success, and explored ADC design optimization scenarios to counteract upon such unfavorable intrinsic tumor tissue attributes. We further demonstrated the profound impact of cytotoxic payload release mechanisms and the role of bystander killing effects on tumor shrinkage. This model platform affords a customizable simulation environment which can aid with experimental data interpretation and the design of ADC therapeutic treatments.

Multicellular model for intercellular synchronization in circadian neural networks.

We developed a multicellular model characterized by a high degree of heterogeneity to investigate possible mechanisms that underlie circadian network synchronization and rhythmicity in the suprachiasmatic nucleus (SCN). We populated a two-dimensional grid with 400 model neurons coupled via γ-aminobutyric acid (GABA) and vasoactive intestinal polypeptide (VIP) neurotransmitters through a putative Ca(2+) mediated signaling cascade to investigate their roles in gene expression and electrical firing activity of cell populations. As observed experimentally, our model predicted that GABA would affect the amplitude of circadian oscillations but not synchrony among individual oscillators. Our model recapitulated experimental findings of decreased synchrony and average periods, loss of rhythmicity, and reduced circadian amplitudes as VIP signaling was eliminated. In addition, simulated increases of VIP reduced periodicity and synchrony. We therefore postulated a physiological range of VIP within which the system is able to produce sustained and synchronized oscillations. Our model recapitulated experimental findings of diminished amplitudes and periodicity with decreasing intracellular Ca(2+) concentrations, suggesting that such behavior could be due to simultaneous decrease of individual oscillation amplitudes and population synchrony. Simulated increases in Cl(-) levels resulted in increased Cl(-) influx into the cytosol, a decrease of inhibitory postsynaptic currents, and ultimately a shift of GABA-elicited responses from inhibitory to excitatory. The simultaneous reduction of IPSCs and increase in membrane resting potential produced GABA dose-dependent increases in firing rates across the population, as has been observed experimentally. By integrating circadian gene regulation and electrophysiology with intracellular and intercellular signaling, we were able to develop the first (to our knowledge) multicellular model that allows the effects of clock genes, electrical firing, Ca(2+), GABA, and VIP on circadian system behavior to be predicted.

Small-world network models of intercellular coupling predict enhanced synchronization in the suprachiasmatic nucleus.

The suprachiasmatic nucleus (SCN) of the hypothalamus is a multioscillator system that drives daily rhythms in mammalian behavior and physiology. Based on recent data implicating vasoactive intestinal polypeptide (VIP) as the key intercellular synchronizing agent, we developed a multicellular SCN model to investigate the effects of cellular heterogeneity and intercellular connectivity on circadian behavior. A 2-dimensional grid was populated with 400 model cells that were heterogeneous with respect to their uncoupled rhythmic behavior (intrinsic and damped pacemakers with a range of oscillation periods) and VIP release characteristics (VIP producers and nonproducers). We constructed small-world network architectures in which local connections between VIP producing cells and their 4 nearest neighbors were augmented with random connections, resulting in long-range coupling across the grid. With only 10% of the total possible connections, the small-world network model was able to produce similar phase synchronization indices as a mean-field model with VIP producing cells connected to all other cells. Partial removal of random connections decreased the synchrony among neurons, the amplitude of VIP and cAMP response element binding protein oscillations, the mean period of intrinsic periods across the population, and the percentage of oscillating cells. These results indicate that small-world connectivity provides the optimal compromise between the number of connections and control of circadian amplitude and synchrony. This model predicts that small decreases in long-range VIP connections in the SCN could have dramatic effects on period and amplitude of daily rhythms, features commonly described with aging.