Physiological Considerations for Modeling in vivo Antibody-Target Interactions

Improvement of daratumumab- or elotuzumab-mediated NK cell activity by the bi-specific 4-1BB agonist, DARPin α-FAPx4-1BB: A preclinical study in multiple myeloma

Multiple myeloma (MM) progression is closely dependent on cells in the bone marrow (BM) microenvironment, including fibroblasts (FBs) and immune cells. In their BM niche, MM cells adhere to FBs sustaining immune evasion, drug resistance and the undetectable endurance of tumor cells known as minimal residual disease (MRD). Here, we describe the novel bi-specific designed ankyrin repeat protein (DARPin) α-FAPx4-1BB (MP0310) with FAP-dependent 4-1BB agonistic activity. The α-FAPx4-1BB DARPin simultaneously binds to FAP and 4-1BB overexpressed by activated FBs and immune cells, respectively. Although flow cytometry analysis showed that T and NK cells from MM patients were not activated and did not express 4-1BB, stimulation with daratumumab or elotuzumab, monoclonal antibodies (mAbs) currently used for the treatment of MM, significantly upregulated 4-1BB both in vitro and in MM patients following mAb-based therapy. The mAb-induced 4-1BB overexpression allowed the engagement of α-FAPx4-1BB that acted as a bridge between FAP+FBs and 4-1BB+NK cells. Therefore, α-FAPx4-1BB enhanced both the adhesion of daratumumab-treated NK cells on FBs as well as their activation by improving release of CD107a and perforin, hence MM cell killing via antibody-mediated cell cytotoxicity (ADCC). Interestingly, α-FAPx4-1BB significantly potentiated daratumumab-mediated ADCC in the presence of FBs, suggesting that it may overcome the BM FBs' immunosuppressive effect. Overall, we speculate that treatment with α-FAPx4-1BB may represent a valuable strategy to improve mAb-induced NK cell activity fostering MRD negativity in MM patients through the eradication of latent MRD cells.

Design of Crosslinking Antibodies For T-Cell Activation: Experimental and Computational Analysis of PD-1/CD137 Bispecific Agents

Bispecific and multispecific agents have become increasingly utilized in cancer treatment and immunotherapy, yet their complex design parameters present a challenge in developing successful therapeutics. Bispecifics that crosslink receptors on two opposing cells can provide specific activation of a receptor only when these cells are in close spatial proximity, such as an immune cell and cancer cell in a tumor. These agents, including T cell activating bispecifics, can avoid off-tumor toxicity through activation only in the tumor microenvironment by utilizing a tumor target to cluster T-cell receptors for a selective costimulatory signal. Here, we investigate a panel of PD-1/CD137 targeted Humabody VH domains to determine the key factors for T cell activation, such as affinity, valency, expression level, domain orientation, and epitope location. Target expression is a dominant factor determining both specificity and potency of T cell activation. Given an intrinsic expression level, the affinity can be tuned to modulate the level of activation and IC50 and achieve specificity between low and high expression levels. Changing the epitope location and linker length showed minor improvements to activation at low expression levels, but increasing the valency for the target decreased activation at all expression levels. By combining non-overlapping epitopes for the target, we achieved higher receptor activation at low expression levels. A kinetic model was able to capture these trends, offering support for the mechanistic interpretation. This work provides a framework to quantify factors for T cell activation by cell-crosslinking bispecific agents and guiding principles for the design of new agents.

Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors

The spread of cancer from organ to organ (metastasis) is responsible for the vast majority of cancer deaths; however, most current anti-cancer drugs are designed to arrest or reverse tumor growth without directly addressing disease spread. It was recently discovered that tumor cell-secreted interleukin-6 (IL-6) and interleukin-8 (IL-8) synergize to enhance cancer metastasis in a cell-density dependent manner, and blockade of the IL-6 and IL-8 receptors (IL-6R and IL-8R) with a novel bispecific antibody, BS1, significantly reduced metastatic burden in multiple preclinical mouse models of cancer. Bispecific antibodies (BsAbs), which combine two different antigen-binding sites into one molecule, are a promising modality for drug development due to their enhanced avidity and dual targeting effects. However, while BsAbs have tremendous therapeutic potential, elucidating the mechanisms underlying their binding and inhibition will be critical for maximizing the efficacy of new BsAb treatments. Here, we describe a quantitative, computational model of the BS1 BsAb, exhibiting how modeling multivalent binding provides key insights into antibody affinity and avidity effects and can guide therapeutic design. We present detailed simulations of the monovalent and bivalent binding interactions between different antibody constructs and the IL-6 and IL-8 receptors to establish how antibody properties and system conditions impact the formation of binary (antibody-receptor) and ternary (receptor-antibody-receptor) complexes. Model results demonstrate how the balance of these complex types drives receptor inhibition, providing important and generalizable predictions for effective therapeutic design.

Immunoglobulins and serum proteins impair anti-tumor NK cell effector functions in malignant ascites

Introduction

Malignant ascites indicates ovarian cancer progression and predicts poor clinical outcome. Various ascites components induce an immunosuppressive crosstalk between tumor and immune cells, which is poorly understood. In our previous study, imbalanced electrolytes, particularly high sodium content in malignant ascites, have been identified as a main immunosuppressive mechanism that impaired NK and T-cell activity.

Methods

In the present study, we explored the role of high concentrations of ascites proteins and immunoglobulins on antitumoral NK effector functions. To this end, a coculture system consisting of healthy donor NK cells and ovarian cancer cells was used. The anti-EGFR antibody Cetuximab was added to induce antibody-dependent cellular cytotoxicity (ADCC). NK activity was assessed in the presence of different patient ascites samples and immunoglobulins that were isolated from ascites.

Results

Overall high protein concentration in ascites impaired NK cell degranulation, conjugation to tumor cells, and intracellular calcium signaling. Immunoglobulins isolated from ascites samples competitively interfered with NK ADCC and inhibited the conjugation to target cells. Furthermore, downregulation of regulatory surface markers CD16 and DNAM-1 on NK cells was prevented by ascites-derived immunoglobulins during NK cell activation.

Conclusion

Our data show that high protein concentrations in biological fluids are able to suppress antitumoral activity of NK cells independent from the mechanism mediated by imbalanced electrolytes. The competitive interference between immunoglobulins of ascites and specific therapeutic antibodies could diminish the efficacy of antibody-based therapies and should be considered in antibody-based immunotherapies.

Minimally sufficient experimental design using identifiability analysis

Mathematical models are increasingly being developed and calibrated in tandem with data collection, empowering scientists to intervene in real time based on quantitative model predictions. Well-designed experiments can help augment the predictive power of a mathematical model but the question of when to collect data to maximize its utility for a model is non-trivial. Here we define data as model-informative if it results in a unique parametrization, assessed through the lens of practical identifiability. The framework we propose identifies an optimal experimental design (how much data to collect and when to collect it) that ensures parameter identifiability (permitting confidence in model predictions), while minimizing experimental time and costs. We demonstrate the power of the method by applying it to a modified version of a classic site-of-action pharmacokinetic/pharmacodynamic model that describes distribution of a drug into the tumor microenvironment (TME), where its efficacy is dependent on the level of target occupancy in the TME. In this context, we identify a minimal set of time points when data needs to be collected that robustly ensures practical identifiability of model parameters. The proposed methodology can be applied broadly to any mathematical model, allowing for the identification of a minimally sufficient experimental design that collects the most informative data.

Application of quantitative protein mass spectrometric data in the early predictive analysis of membrane-bound target engagement by monoclonal antibodies

Model-informed drug discovery advocates the use of mathematical modeling and simulation for improved efficacy in drug discovery. In the case of monoclonal antibodies (mAbs) against cell membrane antigens, this requires quantitative insight into the target tissue concentration levels. Protein mass spectrometry data are often available but the values are expressed in relative, rather than in molar concentration units that are easier to incorporate into pharmacokinetic models. Here, we present an empirical correlation that converts the parts per million (ppm) concentrations in the PaxDb database to their molar equivalents that are more suitable for pharmacokinetic modeling. We evaluate the insight afforded to target tissue distribution by analyzing the likely tumor-targeting accuracy of mAbs recognizing either epidermal growth factor receptor or its homolog HER2. Surprisingly, the predicted tissue concentrations of both these targets exceed the Kd values of their respective therapeutic mAbs. Physiologically based pharmacokinetic (PBPK) modeling indicates that in these conditions only about 0.05% of the dosed mAb is likely to reach the solid tumor target cells. The rest of the dose is eliminated in healthy tissues via both nonspecific and target-mediated processes. The presented approach allows evaluation of the interplay between the target expression level in different tissues that determines the overall pharmacokinetic properties of the drug and the fraction that reaches the cells of interest. This methodology can help to evaluate the efficacy and safety properties of novel drugs, especially if the off-target cell degradation has cytotoxic outcomes, as in the case of antibody-drug conjugates.

Targeting endothelial vascular cell adhesion molecule-1 in atherosclerosis: drug discovery and development of vascular cell adhesion molecule-1-directed novel therapeutics

Vascular cell adhesion molecule-1 (VCAM-1) has been well established as a critical contributor to atherosclerosis and consequently as an attractive therapeutic target for anti-atherosclerotic drug candidates. Many publications have demonstrated that disrupting the VCAM-1 function blocks monocyte infiltration into the sub-endothelial space, which effectively prevents macrophage maturation and foam cell transformation necessary for atherosclerotic lesion formation. Currently, most VCAM-1-inhibiting drug candidates in pre-clinical and clinical testing do not directly target VCAM-1 itself but rather down-regulate its expression by inhibiting upstream cytokines and transcriptional regulators. However, the pleiotropic nature of these regulators within innate immunity means that optimizing dosage to a level that suppresses pathological activity while preserving normal physiological function is extremely challenging and oftentimes infeasible. In recent years, highly specific pharmacological strategies that selectively inhibit VCAM-1 function have emerged, particularly peptide- and antibody-based novel therapeutics. Studies in such VCAM-1-directed therapies so far remain scarce and are limited by the constraints of current experimental atherosclerosis models in accurately representing the complex pathophysiology of the disease. This has prompted the need for a comprehensive review that recounts the evolution of VCAM-1-directed pharmaceuticals and addresses the current challenges in novel anti-atherosclerotic drug development.

Global parameter optimisation and sensitivity analysis of antivenom pharmacokinetics and pharmacodynamics

In recent years it has become possible to design snakebite antivenoms with diverse pharmacokinetic properties. Owing to the pharmacokinetic variability of venoms, the choice of antivenom scaffold may influence a treatment's neutralisation coverage. Computation offers a useful medium through which to assess the pharmacokinetics and pharmacodynamics of envenomation-treatment systems, as antivenoms with identical neutralising capacities can be simulated. In this study, we simulate envenomation and treatment with a variety of antivenoms, to define the properties of effective antivenoms. Systemic envenomation and treatment were described using a two-compartment pharmacokinetic model. Treatment of Naja sumatrana and Cryptelytrops purpureomaculatus envenomation was simulated with a set of 200,000 theoretical antivenoms across 10 treatment time delays. These two venoms are well-characterised and have differing pharmacokinetic properties. The theoretical antivenom set varied across molecular weight, dose, kon, koff, and valency. The best and worst treatments were identified using an area under the curve metric, and a global sensitivity analysis was performed to quantify the influence of the input parameters on treatment outcome. The simulations show that scaffolds of diverse molecular formats can be effective. Molecular weight and valency have a negligible direct impact on treatment outcome, however low molecular weight scaffolds offer more flexibility across the other design parameters, particularly when treatment is delayed. The simulations show kon to primarily mediate treatment efficacy, with rates above 105 M-1s-1 required for the most effective treatments. koff has the greatest impact on the performance of less effective scaffolds. While the same scaffold preferences for improved treatment are seen for both model snakes, the parameter bounds for C. purpureomaculatus envenomation are more constrained. This paper establishes a computational framework for the optimisation of antivenom design.

The influence of variable-heavy chain families on IgG2, 3, 4, FcγRs and B-cell superantigens protein G and L binding using biolayer interferometry

As the most abundant immunoglobulin in blood and the most common human isotype used for therapeutic monoclonal antibodies, the engagement and activation of its Fc receptors by IgGs are crucial for antibody function. Assumed to be relatively constant within subtypes, recent studies reveal that antibody variable regions exert distal effects of modulating antibody-receptor interactions on antibody isotypes. These variable (V)-region distal effects are also expected for the IgG subtypes. With an in-depth understanding of the V-region effects, researchers can make a more informed antibody engineering approach and antibody purification strategy accounting for the functions of microbial immune evasion . In this study, we created a panel of IgG2/IgG3/IgG4 antibodies by changing the VH family (VH1-7) frameworks while retaining the complementary determining regions of pertumuzab and measured their interactions with FcγRIa, FcγRIIaH167, FcγRIIaR167, FcγRIIb/c, FcγRIIIaF176, FcγRIIIaV176, FcγRIIIbNA1 and FcγRIIIbNA2 receptors alongside B-cell superantigens Protein L and G using biolayer interferometry. The panel of 21 IgGs demonstrated that the VH frameworks influenced receptor binding sites on the constant region in a non-canonical manner. However, there was minimal influence on the binding of bacterial B-cell superantigens Proteins L and Protein G on the IgGs, showing their robustness against V-region effects. These results demonstrate the role of V-regions during the humanization of therapeutic antibodies that can influence FcR-dependent immune responses while retaining binding by bacterial B-cell superantigens for antibody purification. These in vitro measurements provide a clue to detailed antibody engineering and understanding of antibody superantigen functions that would be relevant with in vivo validation.

Direct bioanalysis or indirect calculation of target engagement and free drug exposure: do we apply double standards?

Analysis of "free" drug/target concentrations is important to set up appropriate pharmacokinetic-pharmacodynamic models, to evaluate active-drug exposure and target engagement. Such "free-analyte" determination could be done by direct bioanalysis using an appropriate "free-analyte" assay. Development of "free" assays is often considered challenging from a technological and regulatory perspective. The application of a "total-total" approach, where the "free-analyte" concentration is determined mathematically, is considered a more convenient option. In this perspective, we examine and discuss the challenges of this "total-total" approach, from the affinity data, the importance of applying an appropriate "total" assay, the impact of additional binding partners and the variability of the total drug/target assays and their impact on the quality and variability of the final "free-analyte" dataset.

In Vivo Applications of Bioorthogonal Reactions: Chemistry and Targeting Mechanisms

Bioorthogonal chemistry involves selective biocompatible reactions between functional groups that are not normally present in biology. It has been used to probe biomolecules in living systems, and has advanced biomedical strategies such as diagnostics and therapeutics. In this review, the challenges and opportunities encountered when translating in vitro bioorthogonal approaches to in vivo settings are presented, with a focus on methods to deliver the bioorthogonal reaction components. These methods include metabolic bioengineering, active targeting, passive targeting, and simultaneously used strategies. The suitability of bioorthogonal ligation reactions and bond cleavage reactions for in vivo applications is critically appraised, and practical considerations such as the optimum scheduling regimen in pretargeting approaches are discussed. Finally, we present our own perspectives for this area and identify what, in our view, are the key challenges that must be overcome to maximise the impact of these approaches.