A Modeling and Experimental Investigation of the Effects of Antigen Density, Binding Affinity, and Antigen Expression Ratio on Bispecific Antibody Binding to Cell Surface Targets

Successful targeting of multidrug-resistant tumors with bispecific antibodies

Multidrug resistance (MDR) hinders efficacious cancer chemotherapy. Overexpression of the P-glycoprotein (P-gp) efflux pump (EP) on cancer cells is a primary cause of MDR since it expels numerous anticancer drugs. Small molecule intracellular P-gp antagonists have been investigated clinically to redress MDR but have failed primarily due to adverse effects on P-gp in normal tissue. We used a new approach to counteract P-gp with bispecific antibodies (BsAbs) that simultaneously bound P-gp and CD47 in cis on MDR cells but not normal tissue. Affinities of the individual arms of the BsAbs were low enough to minimize normal tissue binding, but, when the two targets were co-located on MDR cancer cells, both arms of the BsAb engaged with effective avidity. Proof-of-concept was shown in three different MDR xenograft tumor models with a non-humanized chimeric BsAb (targeting P-gp and CD47) that potently restored tumor sensitivity to paclitaxel. Fully humanized variants were successfully developed and characterized. Significant anti-tumor efficacy was observed with the BsAbs both when combined with paclitaxel and as single agents in the absence of paclitaxel. Treatment of MDR cancers with BsAbs using this novel approach has several distinct advantages over prior efforts with small molecule antagonists, including 1) invoking a direct immune attack on the tumors, 2) multimodal mechanisms of action, 3) tumor-specific targeting (with reduced toxicity to normal tissue), and 4) broad applicability as single agents and compatibility with other therapeutics.

Quantifying antibody binding: techniques and therapeutic implications

The binding kinetics of an antibody for its target antigen represent key determinants of its biological function and success as a novel biotherapeutic. Defining these interactions and kinetics is critical for understanding the pharmacological and pharmacodynamic profiles of antibodies in therapeutic applications, with line of sight to clinical translation. In this review, we discuss the latest developments in approaches to measure and modulate antibody-antigen interactions, including antibody engineering, novel antibody formats, current, and emerging technologies for measuring antibody-antigen binding interactions, and emerging perspectives within the field. We also explore how emerging computational methods are set to become powerful tools for modeling antibody-binding interactions under physiologically relevant conditions. Finally, we consider the therapeutic implications of modulating target engagement in terms of pharmacodynamics and pharmacokinetics.

Quantitative Pharmacology Methods for Bispecific T Cell Engagers

T Cell Engager (TCE)s are an exciting therapeutic modality in immuno-oncology that acts to bypass antigen presentation and forms a direct link between cancer and immune cells in the Tumor Microenvironment (TME). TCEs are efficacious only when the drug is bound to both immune and cancer cell targets. Therefore, approaches that maximize the formation of the drug-target trimer in the TME are expected to increase the drug's efficacy. In this study, we quantitatively investigate how the concentration of ternary complex and its biodistribution depend on both the targets' specific properties and the design characteristics of the TCE, and specifically on the binding kinetics of the drug to its targets. A simplified mathematical model of drug-target interactions is considered here, with insights from the "three-body" problem applied to the model. Parameter identifiability analysis performed on the model demonstrates that steady state data, which is often available at the early pre-clinical stages, is sufficient to estimate the binding affinity of the TCE molecule to both targets. We used the model to analyze several existing antibodies, both clinically approved and under development, to explore their common kinetic features. The manuscript concludes with an assessment of a full quantitative pharmacology model that accounts for drug disposition into the peripheral compartment.

Investigations of Influence of Antibody Binding Kinetics on Tumor Distribution and Anti-Tumor Efficacy

The pharmacokinetics of antibodies with varied binding kinetics were simulated to assess the role of affinity and binding microconstants (kon, koff) on tumor exposure and intra-tumoral distribution. Anti-HER2 constructs (trastuzumab, pertuzumab, VK3VH6, and conjugates with DM1 and gelonin) were produced, purified, and tested for binding and cytotoxicity in vitro, and for intra-tumoral distribution and anti-tumor efficacy in mice. Simulations demonstrated that homogeneity in intra-tumoral distribution increases with increases in koff and with decreases in kon. Interestingly, simulations also predicted that homogeneity in tumor distribution may be improved by decreasing kon and koff in parallel (without changing affinity). Relative to trastuzumab, pertuzumab exhibits similar affinity but a ~ fivefold smaller kon and koff, while VK3VH6 exhibits a similar koff but a ~ 30-fold lower kon and affinity. Conjugate concentrations associated with 50% inhibition of cell proliferation (IC50s) were found to vary with affinity, where IC50 values were similar for pertuzumab and trastuzumab, and higher for VK3VH6. Consistent with model simulations, VK3VH6 and pertuzumab demonstrated more homogeneous tumor distribution than trastuzumab. Although treatment differences were not statistically significant, pertuzumab and VK3VH6 conjugates showed trends for increased survival time relative to mice treated with trastuzumab conjugates. Our simulation and experimental results demonstrate complex relationships between antibody-antigen binding kinetics, intratumoral distribution, and efficacy. The rate constant of association, kon, is an underappreciated determinant of intra-tumoral distribution; among high-affinity antibodies, those with lower values of kon may be expected to exhibit improved intra-tumoral distribution and, potentially, efficacy.

Decoupling Individual Host Response and Immune Cell Engager Cytotoxic Potency

Immune cell engagers are molecular agents, usually antibody-based constructs, engineered to recruit immune cells against cancer cells and kill them. They are versatile and powerful tools for cancer immunotherapy. Despite the multiplication of engagers tested and accepted in the clinic, how molecular and cellular parameters influence their actions is poorly understood. In particular, disentangling the respective roles of host immune cells and engager biophysical characteristics is needed to improve their design and efficiency. Focusing here on harnessing antibody-dependent Natural Killer cell cytotoxicity, we measure the efficiency of 6 original bispecific antibodies (bsAb), associating an anti-HER2 nanobody and an anti-CD16 nanobody. In vitro cytotoxicity data using primary human NK cells on different target cell lines exposing different antigen densities were collected, exhibiting a wide range of bsAb dose response. In order to rationalize our observations, we introduce a simple multiscale model, postulating that the density of bsAb bridging the two cells is the main parameter triggering the cytotoxic response. We introduce two microscopic parameters: the surface cooperativity describing bsAb affinity at the bridging step and the threshold of bridge density determining the donor-dependent response. Both parameters permit ranking Abs and donors and predicting bsAb potency as a function of antibodies bulk affinities and receptor surface densities on cells. Our approach thus provides a general way to decouple donor response from immune engager characteristics, rationalizing the landscape of molecule design.

In situ self-reassembling nanosystem enhances PD-L1 blockade for cancer immunotherapy

Although immune checkpoint inhibitors (ICIs) have made great progress in cancer treatment, their off-tumor distribution, low affinity of traditional ICIs and insufficient T cells infiltration at tumor site limit immunotherapeutic efficacy. Herein, we engineer a highly specific and effective PD-L1 inhibitor (PEC) that modulates the level of binding sites with PD-L1. Specifically, PEC is a hybrid system composed of E. coli membrane expressing PD-L1 binding protein and cancer cell membrane. Notably, PEC can target the tumor site, produce oxygen in response to H2O2, rupture into membrane fragments, and reassemble to form vesicles retaining the PD-L1 binding protein. Through in situ fracture and reassembly, PEC transforms from a hybrid membrane to a single E. coli membrane, leading to the increased density of PD-L1 binding protein. Consequently, the reassembled vesicles can bind to more PD-L1 on tumor cells and induce its degradation in lysosomes. Furthermore, the cGAS-STING signaling activators HZD is encapsulated into PEC to promote T cells infiltration. We demonstrate that PEC@HZD achieves sequential T cells recruitment and functional enhancement, thus stimulating a powerful antitumor immune response. This work provides a new perspective on tailoring ICIs to improve cancer immunotherapy.

Underappreciated layers of antibody-mediated immune synapse architecture and dynamics

The biologic activities of antibody drugs are dictated by structure-function relationships-emerging from the kind, composition, and degree of interactions with a target antigen and with soluble and cellular antibody receptors of the innate immune system. These activities are canonically understood to be both modular: antigen recognition is driven by the heterodimeric antigen-binding fragment, and innate immune recruitment by the homodimeric constant/crystallizable fragment. The model that treats these domains with a high degree of independence has served the field well but is not without limitations. Here, we consider how new insights, particularly from structural studies, complicate the model of neat biophysical separation between these domains and shape our understanding of antibody effector functions. The emerging model endeavors to explain the phenotypic impact of both antibody intrinsic characteristics and extrinsic features-fitting them within a spatiotemporal paradigm that better accounts for observed antibody activities. In this review, we will use insights from recent models of classical complement complexes and T cell immune synapse formation to explore how structural differences in antibody-mediated immune synapses may relate to their functional diversity.

Strategies to boost antibody selectivity in oncology

Antibodies in oncology are being equipped with toxic cargoes and effector functions that can kill cells at very low concentrations. A key challenge is that most targets on cancer cells are also present on at least some healthy cells. Shared targets can result in off-tumor binding and compromise the safety and potential of therapeutic candidates. In this review, we survey strategies that can help direct biologics to cancer sites more selectively. These strategies are becoming increasingly feasible thanks to advances in molecular design and engineering. The objective is to create therapeutics that exploit changes in cancer and leverage the human body infrastructure, enabling therapeutics that discriminate not just self from non-self but diseased from healthy tissue.

General quasi-equilibrium multivalent binding model to study diverse and complex drug-receptor interactions of biologics

Pharmacokinetics and pharmacodynamics of many biologics are influenced by their complex binding to biological receptors. Biologics consist of diverse groups of molecules with different binding kinetics to its receptors including IgG with simple one-to-one drug receptor bindings, bispecific antibody (BsAb) that binds to two different receptors, and antibodies that can bind to six or more identical receptors. As the binding process is typically much faster than elimination (or internalization) and distribution processes, quasi-equilibrium (QE) binding models are commonly used to describe drug-receptor binding kinetics of biologics. However, no general QE modeling framework is available to describe complex binding kinetics for diverse classes of biologics. In this paper, we describe novel approaches of using differential algebraic equations (DAE) to solve three QE multivalent drug-receptor binding (QEMB) models. The first example describes the binding kinetics of three-body equilibria of BsAb that binds to 2 different receptors for trimer formation. The second example models an engineered IgG variant (Multabody) that can bind to 24 identical target receptors. The third example describes an IgG with modified neonatal Fc receptor (FcRn) binding affinity that competes for the same FcRn receptor as endogenous IgG. The model parameter estimates were obtained by fitting the model to all data simultaneously. The models allowed us to study potential roles of cooperative binding on bell-shaped drug exposure-response relationships of BsAb, and concentration-depended distribution of different drug-receptor complexes for Multabody. This DAE-based QEMB model platform can serve as an important tool to better understand complex binding kinetics of diverse classes of biologics.

Revolutionizing cancer treatment: the emerging potential and potential challenges of in vivo self-processed CAR cell therapy

Chimeric antigen receptor (CAR) cell immunotherapies, including CAR-T, CAR-Macrophages, CAR-Natural Killer, CAR-γδ T, etc., have demonstrated significant advancements in the treatment of both hematologic malignancies and solid tumors. Despite the notable successes of traditional CAR cell manufacturing, its application remains constrained by the complicated production process and expensive costs. Consequently, efforts are focused on streamlining CAR cell production to enhance efficacy and accessibility. Among numerous proposed strategies, direct in vivo generation of CAR cells represents the most substantial technical challenge, yet holding great promise for achieving clinical efficacy. Herein, we outlined the current state-of-the-art in vivo CAR therapy, including CAR technology development, transfection vectors, and influence factors of construction of CAR in vivo. We also reviewed the types and characteristics of different delivery systems and summarized the advantages of in vivo CAR cell therapy, such as rapid preparation and cost-effectiveness. Finally, we discussed the limitations, including technical issues, challenges in target and signal design, and cell-related constraints. Meanwhile, strategies have correspondingly been proposed to advance the development of CAR cell therapy, in order to open the new horizons on cancer treatment.

Therapeutic potential of cis-targeting bispecific antibodies

The growing clinical success of bispecific antibodies (bsAbs) has led to rapid interest in leveraging dual targeting in order to generate novel modes of therapeutic action beyond mono-targeting approaches. While bsAbs that bind targets on two different cells (trans-targeting) are showing promise in the clinic, the co-targeting of two proteins on the same cell surface through cis-targeting bsAbs (cis-bsAbs) is an emerging strategy to elicit new functionalities. This includes the ability to induce proximity, enhance binding to a target, increase target/cell selectivity, and/or co-modulate function on the cell surface with the goal of altering, reversing, or eradicating abnormal cellular activity that contributes to disease. In this review, we focus on the impact of cis-bsAbs in the clinic, their emerging applications, and untangle the intricacies of improving bsAb discovery and development.

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.

Amphiphilic α-Peptoid-deoxynojirimycin Conjugate-based Multivalent Glycosidase Inhibitor for Hypoglycemic Effect and Fluorescence Imaging

Multivalent glycosidase inhibitors based on 1-deoxynojirimycin derivatives against α-glucosidases have been rapidly developed. Nonetheless, the mechanism based on self-assembled multivalent glucosidase inhibitors in living systems needs to be further studied. It remains to be determined whether the self-assembly possesses sufficient stability to endure transit through the small intestine and subsequently bind to the glycosidases located therein. In this paper, two amphiphilic compounds, 1-deoxynojirimycin and α-peptoid conjugates (LP-4DNJ-3C and LP-4DNJ-6C), were designed. Their self-assembling behaviors, multivalent α-glucosidase inhibition effect, and fluorescence imaging on living organs were studied. LP-4DNJ-6C exhibited better multivalent α-glucosidase inhibition activities in vitro. Moreover, the self-assembly of LP-4DNJ-6C could effectively form a complex with Nile red. The complex showed fluorescence quenching effect upon binding with α-glucosidases and exhibited potent fluorescence imaging in the small intestine. This result suggests that a multivalent hypoglycemic effect achieved through self-assembly in the intestine is a viable approach, enabling the rational design of multivalent hypoglycemic drugs.

In vivo Auto-tuning of Antibody-Drug Conjugate Delivery for Effective Immunotherapy using High-Avidity, Low-Affinity Antibodies

Antibody-drug conjugates (ADCs) have experienced a surge in clinical approvals in the past five years. Despite this success, a major limitation to ADC efficacy in solid tumors is poor tumor penetration, which leaves many cancer cells untargeted. Increasing antibody doses or co-administering ADC with an unconjugated antibody can improve tumor penetration and increase efficacy when target receptor expression is high. However, it can also reduce efficacy in low-expression tumors where ADC delivery is limited by cellular uptake. This creates an intrinsic problem because many patients express different levels of target between tumors and even within the same tumor. Here, we generated High-Avidity, Low-Affinity (HALA) antibodies that can automatically tune the cellular ADC delivery to match the local expression level. Using HER2 ADCs as a model, HALA antibodies were identified with the desired HER2 expression-dependent competitive binding with ADCs in vitro. Multi-scale distribution of trastuzumab emtansine and trastuzumab deruxtecan co-administered with the HALA antibody were analyzed in vivo, revealing that the HALA antibody increased ADC tumor penetration in high-expression systems with minimal reduction in ADC uptake in low-expression tumors. This translated to greater ADC efficacy in immunodeficient mouse models across a range of HER2 expression levels. Furthermore, Fc-enhanced HALA antibodies showed improved Fc-effector function at both high and low expression levels and elicited a strong response in an immunocompetent mouse model. These results demonstrate that HALA antibodies can expand treatment ranges beyond high expression targets and leverage strong immune responses.

Design and engineering of bispecific antibodies: insights and practical considerations

Bispecific antibodies (bsAbs) have attracted significant attention due to their dual binding activity, which permits simultaneous targeting of antigens and synergistic binding effects beyond what can be obtained even with combinations of conventional monospecific antibodies. Despite the tremendous therapeutic potential, the design and construction of bsAbs are often hampered by practical issues arising from the increased structural complexity as compared to conventional monospecific antibodies. The issues are diverse in nature, spanning from decreased biophysical stability from fusion of exogenous antigen-binding domains to antibody chain mispairing leading to formation of antibody-related impurities that are very difficult to remove. The added complexity requires judicious design considerations as well as extensive molecular engineering to ensure formation of high quality bsAbs with the intended mode of action and favorable drug-like qualities. In this review, we highlight and summarize some of the key considerations in design of bsAbs as well as state-of-the-art engineering principles that can be applied in efficient construction of bsAbs with diverse molecular formats.

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.

Targeting lung cancer with clinically relevant EGFR mutations using anti-EGFR RNA aptamer

A significant fraction of non-small cell lung cancer (NSCLC) cases are due to oncogenic mutations in the tyrosine kinase domain of the epidermal growth factor receptor (EGFR). Anti-EGFR antibodies have shown limited clinical benefit for NSCLC, whereas tyrosine kinase inhibitors (TKIs) are effective, but resistance ultimately occurs. The current landscape suggests that alternative ligands that target wild-type and mutant EGFRs are desirable for targeted therapy or drug delivery development. Here we evaluate NSCLC targeting using an anti-EGFR aptamer (MinE07). We demonstrate that interaction sites of MinE07 overlap with clinically relevant antibodies targeting extracellular domain III and that MinE07 retains binding to EGFR harboring the most common oncogenic and resistance mutations. When MinE07 was linked to an anti-c-Met aptamer, the EGFR/c-Met bispecific aptamer (bsApt) showed superior labeling of NSCLC cells in vitro relative to monospecific aptamers. However, dual targeting in vivo did not improve the recognition of NSCLC xenografts compared to MinE07. Interestingly, biodistribution of Cy7-labeled bsApt differed significantly from Alexa Fluor 750-labeled bsApt. Overall, our findings demonstrate that aptamer formulations containing MinE07 can target ectopic lung cancer without additional stabilization or PEGylation and highlights the potential of MinE07 as a targeting reagent for the recognition of NSCLC harboring clinically relevant EGFRs.

Parameter estimation and identifiability analysis for a bivalent analyte model of monoclonal antibody-antigen binding

Surface plasmon resonance (SPR) is an extensively used technique to characterize antigen-antibody interactions. Affinity measurements by SPR typically involve testing the binding of antigen in solution to monoclonal antibodies (mAbs) immobilized on a chip and fitting the kinetics data using 1:1 Langmuir binding model to derive rate constants. However, when it is necessary to immobilize antigens instead of the mAbs, a bivalent analyte (1:2) binding model is required for kinetics analysis. This model is lacking in data analysis packages associated with high throughput SPR instruments and the packages containing this model do not explore multiple local minima and parameter identifiability issues that are common in non-linear optimization. Therefore, we developed a method to use a system of ordinary differential equations for analyzing 1:2 binding kinetics data. Salient features of this method include a grid search on parameter initialization and a profile likelihood approach to determine parameter identifiability. Using this method we found a non-identifiable parameter in data set collected under the standard experimental design. A simulation-guided improved experimental design led to reliable estimation of all rate constants. The method and approach developed here for analyzing 1:2 binding kinetics data will be valuable for expeditious therapeutic antibody discovery research.

Mechanism-based pharmacokinetic and pharmacodynamic modeling for bispecific antibodies: challenges and opportunities

INTRODUCTION

Unlike conventional antibodies, bispecific antibodies (bsAbs) are engineered antibody- or antibody fragment-based molecules that can simultaneously recognize two different epitopes or antigens. Over the past decade, there has been an explosion of bsAbs being developed across therapeutic areas. Development of bsAbs presents unique challenges and mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) modeling has served as a powerful tool to optimize their development and realize their clinical utility.

AREAS COVERED

In this review, the guiding principles and case examples of how fit-for-purpose, mechanism-based PK/PD models have been applied to answer questions commonly encountered in bsAb development are presented. Such models characterize the key pharmacological elements of bsAbs, and they can be utilized for model-informed drug development. We also include the discussion of challenges, knowledge gaps and future direction for such models.

EXPERT OPINION

Mechanistic PK/PD modeling is a powerful tool to support the development of bsAbs. These models can be extrapolated to predict treatment outcomes based on mechanisms of action (MoA) and clinical observations to form positive learn-and-confirm cycles during drug development, due to their abilities to differentiate system- and drug-specific parameters. Meanwhile, the models should keep being adapted according to novel drug design and MoA, providing continuous opportunities for model-informed drug development.

Modelling ligand depletion for simultaneous affinity and binding site quantification on cells and tissue

The quantification of the number of targets in biological systems is an important parameter to assess the suitability of surface markers as targets for drugs, drug delivery and medical imaging. Likewise, quantifying the interaction with the target in terms of affinity and binding kinetics is essential during drug development. Commonly used approaches to quantify membrane antigens on live cells are based on manual saturation techniques that are labour-intensive, require careful calibration of the generated signal and do not quantify the binding rates. Here, we present how measuring interactions in real-time on live cells and tissue under ligand depletion conditions can be used to simultaneously quantify the kinetic binding parameters as well as the number of available binding sites in a biological system. Suitable assay design was explored with simulated data and feasibility of the method verified with experimental data for exemplary low molecular weight peptide and antibody radiotracers as well as fluorescent antibodies. In addition to revealing the number of accessible target sites and improving the accuracy of binding kinetics and affinities, the presented method does not require knowledge about the absolute signal generated per ligand molecule. This enables a simplified workflow for use with both radioligands and fluorescent binders.

Engineering of a Bispecific Nanofitin with Immune Checkpoint Inhibitory Activity Conditioned by the Cross-Arm Binding to EGFR and PDL1

Re-education of the tumor microenvironment with immune checkpoint inhibitors (ICI) has provided the most significant advancement in cancer management, with impressive efficacy and durable response reported. However, low response rates and a high frequency of immune-related adverse events (irAEs) remain associated with ICI therapies. The latter can be linked to their high affinity and avidity for their target that fosters on-target/off-tumor binding and subsequent breaking of immune self-tolerance in normal tissues. Many multispecific protein formats have been proposed to increase the tumor cell’s selectivity of ICI therapies. In this study, we explored the engineering of a bispecific Nanofitin by the fusion of an anti-epidermal growth factor receptor (EGFR) and anti-programmed cell death ligand 1 (PDL1) Nanofitin modules. While lowering the affinity of the Nanofitin modules for their respective target, the fusion enables the simultaneous engagement of EGFR and PDL1, which translates into a selective binding to tumor cells co-expressing EGFR and PDL1 only. We demonstrated that affinity-attenuated bispecific Nanofitin could elicit PDL1 blockade exclusively in an EGFR-directed manner. Overall, the data collected highlight the potential of this approach to enhance the selectivity and safety of PDL1 checkpoint inhibition.

Design and selection of optimal ErbB-targeting bispecific antibodies in pancreatic cancer

The ErbB family of receptor tyrosine kinases is a primary target for small molecules and antibodies for pancreatic cancer treatment. Nonetheless, the current treatments for this tumor are not optimal due to lack of efficacy, resistance, or toxicity. Here, using the novel BiXAb™ tetravalent format platform, we generated bispecific antibodies against EGFR, HER2, or HER3 by considering rational epitope combinations. We then screened these bispecific antibodies and compared them with the parental single antibodies and antibody pair combinations. The screen readouts included measuring binding to the cognate receptors (mono and bispecificity), intracellular phosphorylation signaling, cell proliferation, apoptosis and receptor expression, and also immune system engagement assays (antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity). Among the 30 BiXAbs™ tested, we selected 3Patri-1Cetu-Fc, 3Patri-1Matu-Fc and 3Patri-2Trastu-Fc as lead candidates. The in vivo testing of these three highly efficient bispecific antibodies against EGFR and HER2 or HER3 in pre-clinical mouse models of pancreatic cancer showed deep antibody penetration in these dense tumors and robust tumor growth reduction. Application of such semi-rational/semi-empirical approach, which includes various immunological assays to compare pre-selected antibodies and their combinations with bispecific antibodies, represents the first attempt to identify potent bispecific antibodies against ErbB family members in pancreatic cancer.

Altered blood-brain barrier transport of nanotherapeutics in lysosomal storage diseases

Treatment of neurological lysosomal storage disorders (LSDs) are limited because of impermeability of the blood-brain barrier (BBB) to macromolecules. Nanoformulations targeting BBB transcytosis are being explored, but the status of these routes in LSDs is unknown. We studied nanocarriers (NCs) targeted to the transferrin receptor (TfR), ganglioside GM1 or ICAM1, associated to the clathrin, caveolar or cell adhesion molecule (CAM) routes, respectively. We used brain endothelial cells and mouse models of acid sphingomyelinase-deficient Niemann Pick disease (NPD), and postmortem LSD patients' brains, all compared to respective controls. NC transcytosis across brain endothelial cells and brain distribution in mice were affected, yet through different mechanisms. Reduced TfR and clathrin expression were found, along with decreased transcytosis in cells and mouse brain distribution. Caveolin-1 expression and GM1 transcytosis were also reduced, yet increased GM1 levels seemed to compensate, providing similar NC brain distribution in NPD vs. control mice. A tendency to lower NHE-1 levels was seen, but highly increased ICAM1 expression in cells and human brains correlated with increased transcytosis and brain distribution in mice. Thus, transcytosis-related alterations in NPD and likely other LSDs may impact therapeutic access to the brain, illustrating the need for these mechanistic studies.

Avidity in antibody effector functions and biotherapeutic drug design

Antibodies are the cardinal effector molecules of the immune system and are being leveraged with enormous success as biotherapeutic drugs. A key part of the adaptive immune response is the production of an epitope-diverse, polyclonal antibody mixture that is capable of neutralizing invading pathogens or disease-causing molecules through binding interference and by mediating humoral and cellular effector functions. Avidity - the accumulated binding strength derived from the affinities of multiple individual non-covalent interactions - is fundamental to virtually all aspects of antibody biology, including antibody-antigen binding, clonal selection and effector functions. The manipulation of antibody avidity has since emerged as an important design principle for enhancing or engineering novel properties in antibody biotherapeutics. In this Review, we describe the multiple levels of avidity interactions that trigger the overall efficacy and control of functional responses in both natural antibody biology and their therapeutic applications. Within this framework, we comprehensively review therapeutic antibody mechanisms of action, with particular emphasis on engineered optimizations and platforms. Overall, we describe how affinity and avidity tuning of engineered antibody formats are enabling a new wave of differentiated antibody drugs with tailored properties and novel functions, promising improved treatment options for a wide variety of diseases.

Characterizing the Pharmacokinetics and Biodistribution of Therapeutic Proteins: An Industry White Paper

Characterization of the pharmacokinetics and biodistribution of therapeutic proteins (TPs) is a hot topic within the pharmaceutical industry, particularly with an ever-increasing catalog of novel modality TPs. Here, we review the current practices, and provide a summary of extensive cross-company discussions as well as a survey completed by International Consortium for Innovation and Quality members on this theme. A wide variety of in vitro, in vivo and in silico techniques are currently used to assess pharmacokinetics and biodistribution of TPs, and we discuss the relevance of these from an industry perspective, focusing on pharmacokinetic/pharmacodynamic understanding at the preclinical stage of development, and translation to human. We consider that the 'traditional in vivo biodistribution study' is becoming insufficient as a standalone tool, and thorough characterization of the interaction of the TP with its target(s), target biology, and off-target interactions at a microscopic scale are key to understand the overall biodistribution on a full-body scale. Our summary of the current challenges and our recommendations to address these issues could provide insight into the implementation of best practices in this area of drug development, and continued cross-company collaboration will be of tremendous value. SIGNIFICANCE STATEMENT: The Innovation and Quality Consortium Translational and ADME Sciences Leadership Group working group for the absorption, distribution, metabolism, and excretion of therapeutic proteins evaluates the current practices and challenges in characterizing the pharmacokinetics and biodistribution of therapeutic proteins during drug development, and proposes recommendations to address these issues. Incorporating the in vitro, in vivo and in silico approaches discussed herein may provide a pragmatic framework to increase early understanding of pharmacokinetic/pharmacodynamic relationships, and aid translational modeling for first-in-human dose predictions.

Nonclinical Pharmacokinetics and Pharmacodynamics Characterization of Anti-CD79b/CD3 T Cell-Dependent Bispecific Antibody Using a Surrogate Molecule: A Potential Therapeutic Agent for B Cell Malignancies

The T cell-dependent bispecific (TDB) antibody, anti-CD79b/CD3, targets CD79b and CD3 cell-surface receptors expressed on B cells and T cells, respectively. Since the anti-CD79b arm of this TDB binds only to human CD79b, a surrogate TDB that binds to cynomolgus monkey CD79b (cyCD79b) was used for preclinical characterization. To evaluate the impact of CD3 binding affinity on the TDB pharmacokinetics (PK), we utilized non-tumor-targeting bispecific anti-gD/CD3 antibodies composed of a low/high CD3 affinity arm along with a monospecific anti-gD arm as controls in monkeys and mice. An integrated PKPD model was developed to characterize PK and pharmacodynamics (PD). This study revealed the impact of CD3 binding affinity on anti-cyCD79b/CD3 PK. The surrogate anti-cyCD79b/CD3 TDB was highly effective in killing CD79b-expressing B cells and exhibited nonlinear PK in monkeys, consistent with target-mediated clearance. A dose-dependent decrease in B cell counts in peripheral blood was observed, as expected. Modeling indicated that anti-cyCD79b/CD3 TDB’s rapid and target-mediated clearance may be attributed to faster internalization of CD79b, in addition to enhanced CD3 binding. The model yielded unbiased and precise curve fits. These findings highlight the complex interaction between TDBs and their targets and may be applicable to the development of other biotherapeutics.

A general model of multivalent binding with ligands of heterotypic subunits and multiple surface receptors

Multivalent cell surface receptor binding is a ubiquitous biological phenomenon with functional and therapeutic significance. Predicting the amount of ligand binding for a cell remains an important question in computational biology as it can provide great insight into cell-to-cell communication and rational drug design toward specific targets. In this study, we extend a mechanistic, two-step multivalent binding model. This model predicts the behavior of a mixture of different multivalent ligand complexes binding to cells expressing various types of receptors. It accounts for the combinatorially large number of interactions between multiple ligands and receptors, optionally allowing a mixture of complexes with different valencies and complexes that contain heterogeneous ligand units. We derive the macroscopic predictions and demonstrate how this model enables large-scale predictions on mixture binding and the binding space of a ligand. This model thus provides an elegant and computationally efficient framework for analyzing multivalent binding.

RNA BioMolecular Electronics: towards new tools for biophysics and biomedicine

The last half-century has witnessed the birth and development of a new multidisciplinary field at the edge between materials science, nanoscience, engineering, and chemistry known as Molecular Electronics. This field deals with the electronic properties of individual molecules and their integration as active components in electronic circuits and has also been applied to biomolecules, leading to BioMolecular Electronics and opening new perspectives for single-molecule biophysics and biomedicine. Herein, we provide a brief introduction and overview of the BioMolecular electronics field, focusing on nucleic acids and potential applications for these measurements. In particular, we review the recent demonstration of the first single-molecule electrical detection of a biologically-relevant nucleic acid. We also show how this could be used to study biomolecular interactions and applications in liquid biopsy for early cancer detection, among others. Finally, we discuss future perspectives and challenges in the applications of this fascinating research field.

Key metrics to expanding the pipeline of successful antibody-drug conjugates

Although the recent FDA approval of six new antibody-drug conjugates (ADCs) is promising, attrition of ADCs during clinical development remains high. The inherent complexity of ADCs is a double-edged sword that provides opportunities for perfecting therapeutic action while also increasing confounding factors in therapeutic failures. ADC design drives their pharmacokinetics and pharmacodynamics, and requires deeper analysis than the commonly used C_max and area under the curve (AUC) metrics to scale dosing to the clinic. Common features of current FDA-approved ADCs targeting solid tumors include humanized IgG1 antibody domains, highly expressed tumor receptors, and large antibody doses. The potential consequences of these shared features for clinical pharmacokinetics and mechanism of action are discussed, and key design aspects for successful solid tumor ADCs are highlighted.

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

With more than 90 approved drugs by 2020, therapeutic antibodies have played a central role in shifting the treatment landscape of many diseases, including autoimmune disorders and cancers. While showing many therapeutic advantages such as long half-life and highly selective actions, therapeutic antibodies still face many outstanding issues associated with their pharmacokinetics (PK) and pharmacodynamics (PD), including high variabilities, low tissue distributions, poorly-defined PK/PD characteristics for novel antibody formats, and high rates of treatment resistance. We have witnessed many successful cases applying PK/PD modeling to answer critical questions in therapeutic antibodies’ development and regulations. These models have yielded substantial insights into antibody PK/PD properties. This review summarized the progress, challenges, and future directions in modeling antibody PK/PD and highlighted the potential of applying mechanistic models addressing the development questions.

OptiDose: Computing the Individualized Optimal Drug Dosing Regimen Using Optimal Control

Providing the optimal dosing strategy of a drug for an individual patient is an important task in pharmaceutical sciences and daily clinical application. We developed and validated an optimal dosing algorithm (OptiDose) that computes the optimal individualized dosing regimen for pharmacokinetic-pharmacodynamic models in substantially different scenarios with various routes of administration by solving an optimal control problem. The aim is to compute a control that brings the underlying system as closely as possible to a desired reference function by minimizing a cost functional. In pharmacokinetic-pharmacodynamic modeling, the controls are the administered doses and the reference function can be the disease progression. Drug administration at certain time points provides a finite number of discrete controls, the drug doses, determining the drug concentration and its effect on the disease progression. Consequently, rewriting the cost functional gives a finite-dimensional optimal control problem depending only on the doses. Adjoint techniques allow to compute the gradient of the cost functional efficiently. This admits to solve the optimal control problem with robust algorithms such as quasi-Newton methods from finite-dimensional optimization. OptiDose is applied to three relevant but substantially different pharmacokinetic-pharmacodynamic examples.

Controlling Conjugated Antibodies at the Molecular Level for Active Targeting Nanoparticles toward HER2-Positive Cancer Cells

For active targeting nanodrug delivery systems conjugated with antibodies, both lack of control of the antibody at the molecular level and protein corona formation remarkably decreases targeting efficacy. Herein, we designed a series of silica nanoparticles toward HER2-positive breast cancer cells, with an anti-HER2 Fab-6His density ranging from 50 to 180 molecules per nanoparticle. Through the site-directed immobilization method we developed, the antigen-binding domain of anti-HER2 Fab was mostly accessible to the HER2 receptor. Both polyethylene glycol (PEG) chains and a high density of Fab were shown to suppress protein corona formation and macrophage uptake. The dependency of targeting efficacy and cytotoxicity on Fab density was shown using a series of breast cancer cell lines with different levels of the HER2 expression. The high density of Fab stimulates quick responses from HER2-positive cells. Combined with PEG chains, conjugated antibodies with a well-controlled orientation and density significantly improves delivery performance and sheds light on the design and preparation of an improved active targeting nanodrug delivery system.

Design and Efficacy of a Monovalent Bispecific PD-1/CTLA4 Antibody That Enhances CTLA4 Blockade on PD-1+ Activated T Cells

The clinical benefit of PD-1 blockade can be improved by combination with CTLA4 inhibition but is commensurate with significant immune-related adverse events suboptimally limiting the doses of anti-CTLA4 mAb that can be used. MEDI5752 is a monovalent bispecific antibody designed to suppress the PD-1 pathway and provide modulated CTLA4 inhibition favoring enhanced blockade on PD-1⁺ activated T cells. We show that MEDI5752 preferentially saturates CTLA4 on PD-1⁺ T cells versus PD-1^- T cells, reducing the dose required to elicit IL2 secretion. Unlike conventional PD-1/CTLA4 mAbs, MEDI5752 leads to the rapid internalization and degradation of PD-1. Moreover, we show that MEDI5752 preferentially localizes and accumulates in tumors providing enhanced activity when compared with a combination of mAbs targeting PD-1 and CTLA4 in vivo. Following treatment with MEDI5752, robust partial responses were observed in two patients with advanced solid tumors. MEDI5752 represents a novel immunotherapy engineered to preferentially inhibit CTLA4 on PD-1⁺ T cells. SIGNIFICANCE: The unique characteristics of MEDI5752 represent a novel immunotherapy engineered to direct CTLA4 inhibition to PD-1⁺ T cells with the potential for differentiated activity when compared with current conventional mAb combination strategies targeting PD-1 and CTLA4. This molecule therefore represents a step forward in the rational design of cancer immunotherapy.See related commentary by Burton and Tawbi, p. 1008.This article is highlighted in the In This Issue feature, p. 995.

Informing Development of Bispecific Antibodies Using Physiologically Based Pharmacokinetic-Pharmacodynamic Models: Current Capabilities and Future Opportunities

Antibody therapeutics continue to represent a significant portion of the biotherapeutic pipeline, with growing promise for bispecific antibodies (BsAbs). BsAbs can target 2 different antigens at the same time, such as simultaneously binding tumor-cell receptors and recruiting cytotoxic immune cells. This simultaneous engagement of 2 targets can be potentially advantageous, as it may overcome disadvantages posed by a monotherapy approach, like the development of resistance to treatment. Combination therapy approaches that modulate 2 targets simultaneously offer similar advantages, but BsAbs are more efficient to develop. Unlike combination approaches, BsAbs can facilitate spatial proximity of targets that may be necessary to induce the desired effect. Successful development of BsAbs requires understanding antibody formatting and optimizing activity for both targets prior to clinical trials. To realize maximal efficacy, special attention is required to fully define pharmacokinetic (PK)/pharmacodynamic (PD) relationships enabling selection of dose and regimen. The application of physiologically based pharmacokinetics (PBPK) has been evolving to inform the development of novel treatment modalities such as bispecifics owing to the increase in our understanding of pharmacology, utility of multiscale models, and emerging clinical data. In this review, we discuss components of PBPK models to describe the PK characteristics of BsAbs and expand the discussion to integration of PBPK and PD models to inform development of BsAbs. A framework that can be adopted to build PBPK-PD models to inform the development of BsAbs is also proposed. We conclude with examples that highlight the application of PBPK-PD and share perspectives on future opportunities for this emerging quantitative tool.

A computational diffusion model to study antibody transport within reconstructed tumor microenvironments

Background

Antibodies revolutionized cancer treatment over the past decades. Despite their successfully application, there are still challenges to overcome to improve efficacy, such as the heterogeneous distribution of antibodies within tumors. Tumor microenvironment features, such as the distribution of tumor and other cell types and the composition of the extracellular matrix may work together to hinder antibodies from reaching the target tumor cells. To understand these interactions, we propose a framework combining in vitro and in silico models. We took advantage of in vitro cancer models previously developed by our group, consisting of tumor cells and fibroblasts co-cultured in 3D within alginate capsules, for reconstruction of tumor microenvironment features.

Results

In this work, an experimental-computational framework of antibody transport within alginate capsules was established, assuming a purely diffusive transport, combined with an exponential saturation effect that mimics the saturation of binding sites on the cell surface. Our tumor microenvironment in vitro models were challenged with a fluorescent antibody and its transport recorded using light sheet fluorescence microscopy. Diffusion and saturation parameters of the computational model were adjusted to reproduce the experimental antibody distribution, with root mean square error under 5%. This computational framework is flexible and can simulate different random distributions of tumor microenvironment elements (fibroblasts, cancer cells and collagen fibers) within the capsule. The random distribution algorithm can be tuned to follow the general patterns observed in the experimental models.

Conclusions

We present a computational and microscopy framework to track and simulate antibody transport within the tumor microenvironment that complements the previously established in vitro models platform. This framework paves the way to the development of a valuable tool to study the influence of different components of the tumor microenvironment on antibody transport.

A kinetic proofreading model for bispecific protein degraders

Bispecific protein degraders (BPDs) engage the ubiquitin-proteasome system (UPS) to catalytically degrade intracellular proteins through the formation of ternary complexes with the target protein and E3 ubiquitin ligases. Here, we describe the development of a mechanistic modeling framework for BPDs that includes the reaction network governing ternary complex formation and degradation via the UPS. A critical element of the model framework is a multi-step process that results in a time delay between ternary complex formation and protein degradation, thereby balancing ternary complex stability against UPS degradation rates akin to the kinetic proofreading concept that has been proposed to explain the accuracy and specificity of biological processes including protein translation and T cell receptor signal transduction. Kinetic proofreading likely plays a central role in the cell's ability to regulate substrate recognition and degradation by the UPS, and the model presented here applies this concept in the context of a quantitative pharmacokinetic (PK)-pharmacodynamic (PD) framework to inform the design of potent and selective BPDs.

Fine-tuning bispecific therapeutics

Bispecific therapeutics target two distinct antigens simultaneously and provide novel functionalities that are not attainable with single monospecific molecules or combinations of them. The unique potential of bispecific therapeutics is driving extensive efforts to discover synergistic dual targets, design molecular formats to integrate bispecific elements, and accelerate successful clinical translation. In particular, the past decade has witnessed a boom in the design and development of bispecific antibody formats with more than 100 collections to date. Despite the remarkable progress that has been made to expand the number of formats, qualitative fine-tuning of bispecific formats is needed to achieve optimal dual-target engagement based on understanding of the spatiotemporal interdependence of the two physically linked binding specificities and the complex target biology associated with bispecific approaches. This review provides insights into the design parameters - including affinity, valency, and geometry - that need to be considered at an early stage of development in order to take the best advantage of bispecific therapeutics.

Tumor-derived extracellular vesicles: molecular parcels that enable regulation of the immune response in cancer

Extracellular vesicles (EVs) are a heterogeneous collection of membrane-bound vesicles released by cells that contain bioactive cargoes including proteins, lipids and nucleic acids. Multiple subpopulations of EVs have now been recognized and these include exosomes and microvesicles. EVs have been thought to facilitate intercellular and distal communication to bring about various processes that enable tumor progression and metastases. Here, we describe the current knowledge of the functional cargo contained within EVs, with a focus on tumor microvesicles, and review the emerging theory of how EVs support immune suppression in cancer.

Target-Mediated Drug Disposition Model for Bispecific Antibodies: Properties, Approximation, and Optimal Dosing Strategy

Bispecific antibodies (BsAbs) bind to two different targets, and create two binary and one ternary complex (TC). These molecules have shown promise as immuno-oncology drugs, and the TC is considered the pharmacologically active species that drives their pharmacodynamic effect. Here, we have presented a general target-mediated drug disposition (TMDD) model for these BsAbs, which bind to two different targets on different cell membranes. The model includes four different binding events for BsAbs, turnover of the targets, and internalization of the complexes. In addition, a quasi-equilibrium (QE) approximation with decreased number of binding parameters and, if necessary, reduced internalization parameters is presented. The model is further used to investigate the kinetics of BsAb and TC concentrations. Our analysis shows that larger doses of BsAbs may delay the build-up of the TC. Consequently, a method to compute the optimal dosing strategy of BsAbs, which will immediately create and maintain maximal possible TC concentration, is presented.

Multivalent Ligand Binding to Cell Membrane Antigens: Defining the Interplay of Affinity, Valency, and Expression Density

Nature uses multivalency to govern many biological processes. The development of macromolecular and cellular therapies has largely been dependent on engineering similar polyvalent interactions to enable effective targeting. Such therapeutics typically utilize high-affinity binding domains that have the propensity to recognize both antigen-overexpressing tumors and normal-expressing tissues, leading to "on-target, off-tumor" toxicities. One strategy to improve these agents' selectivity is to reduce the binding affinity, such that biologically relevant interactions between the therapeutic and target cell will only exist under conditions of high avidity. Preclinical studies have validated this principle of avidity optimization in the context of chimeric antigen receptor (CAR) T cells; however, a rigorous analysis of this approach in the context of soluble multivalent targeting scaffolds has yet to be undertaken. Using a modular protein nanoring capable of displaying ≤8 fibronectin domains with engineered specificity for a model antigen, epithelial cell adhesion molecule (EpCAM), this study demonstrates that binding affinity and ligand valency can be optimized to afford discrimination between EpCAM^High (2.8-3.8 × 10⁶ antigens/cell) and EpCAM^Low (5.2 × 10⁴ to 2.2 × 10⁵ antigens/cell) tissues both in vitro and in vivo.

A Model for the Binding of Fluorescently Labeled Anti-Human CD4 Monoclonal Antibodies to CD4 Receptors on Human Lymphocytes

The CD4 glycoprotein is a component of the T cell receptor complex which plays an important role in the human immune response. This manuscript describes the measurement and modeling of the binding of fluorescently labeled anti-human CD4 monoclonal antibodies (mAb; SK3 clone) to CD4 receptors on the surface of human peripheral blood mononuclear cells (PBMC). CD4 mAb fluorescein isothiocyanate (FITC) and CD4 mAb allophycoerythrin (APC) conjugates were obtained from commercial sources. Four binding conditions were performed, each with the same PBMC sample and different CD4 mAb conjugate. Each binding condition consisted of the PBMC sample incubated for 30 min in labeling solutions containing progressively larger concentrations of the CD4 mAb-label conjugate. After the incubation period, the cells were re-suspended in PBS-based buffer and analyzed using a flow cytometer to measure the mean fluorescence intensity (MFI) of the labeled cell populations. A model was developed to estimate the equilibrium concentration of bound CD4 mAb-label conjugates to CD4 receptors on PBMC. A set of parameters was obtained from the best fit of the model to the measured MFI data and the known number of CD4 receptors on PBMC surface. Divalent and monovalent binding had to be invoked for the APC and FITC CD4 mAb conjugates, respectively. This suggests that the mAb binding depends on the size of the label, which has significant implications for quantitative flow cytometry. The study supports the National Institute of Standards and Technology program to develop quantitative flow cytometry measurements.

Challenges and Solutions in Developing Ultrasensitive Biosensors

This Perspective focuses on the latest strategies and challenges for the development of bioanalytical sensors with sub-picomolar detection limits. Achieving sub-picomolar detection limits has three major challenges: (1) assay sensitivity, (2) response time, and (3) selectivity (including limiting background signals). Each of these challenges is discussed, along with how nanomaterials provide the solutions. One strategy to gain greater sensitivity involves confining the sensing volume to the nanoscale, as used in nanopore- or nanoparticle-based sensors, because nanoparticles are ubiquitous in amplification. Methods to improve response time typically focus on obtaining an intimate mixture between the sensor and the sample either by extending the length scale of nanoscale sensors using nanostructuring or by dispersing magnetic nanoparticles through the sample to capture the analyte. Loading nanoparticles with many biorecognition species is one solution to help address the challenge of selectivity. Many examples in this Perspective explore the detection of prostate-specific antigen which enables a comparison between strategies. Finally, exciting future opportunities in developing single-molecule sensors and the requirements to go even lower in concentration are explored.

Guiding principles for mechanistic modeling of bispecific antibodies

System based pharmacokinetic (PK) models can be used to study and predict the distribution of antibody based drugs into target tissues and assess the pharmacobinding (PB) of the drug to the target and the subsequent pharmacodynamic (PD) changes. In the absence of relevant PD readouts, compounded in cases of novel mechanisms, one can rely on binding between the drug and the target, computed as target occupancy (TO), as a relevant biomarker. This approach assumes that at maximum TO across the dosing interval, the drug-target interaction must demonstrate the intended pharmacology. Such analysis can help set laboratory objectives for protein engineers and chemists and guide them to the appropriate design and binding affinity of the molecule. Analysis of mechanistic models to guide affinity optimization against soluble and membrane-bound targets has been done for monoclonal antibodies (mAbs) (Tiwari et al., The AAPS Journal, 2017). However, comparable understanding of bispecific antibodies (BsAb; drugs with two targets, which are either soluble, membrane-bound, or a combination of the two) is still lacking. We propose to extend the work done by Tiwari et al. (2017) to BsAb. We focus on describing a generic BsAb with two membrane-bound targets, and explore the impact of various parameters on the TO of the BsAb to each target. Performed analysis can guide the optimization of dissociation constant (K_D) of the BsAb, and can also help in identifying druggable targets. Proposed model can be modified and tailored to specific biologics as needed.

A phase I study of LY3164530, a bispecific antibody targeting MET and EGFR, in patients with advanced or metastatic cancer

PURPOSE

The phase I study characterized the safety, pharmacokinetics, anti-tumor activity, and recommended phase II dose/schedule of LY3164530 in patients with advanced or metastatic cancer.

METHODS

Patients received LY3164530 on days 1 and 15 (Schedule 1: 300, 600, 1000, and 1250 mg) or Days 1, 8, 15, and 22 (Schedule 2: 500 and 600 mg) of each 28 days cycle. Dose escalation used a modified toxicity probability interval model.

RESULTS

Dose escalation defined a maximum tolerated dose (MTD) of 1000 mg on Schedule 1 and 500 mg on Schedule 2. Treatment-emergent adverse events related to study treatment were consistent with epidermal growth factor receptor (EGFR) inhibition and included maculopapular rash/dermatitis acneiform (83%, Grade 3/4 17%), hypomagnesemia (55%, Grade 3/4 7%), paronychia (35%), fatigue (28%, Grade 3/4 3%), skin fissures (24%), and hypokalemia (21%, Grade 3/4 7%). Partial response was achieved in three patients on Schedule 2 with colorectal cancer (n = 2) or squamous cell cancer. Overall response rate (ORR) was 10.3%, disease control rate (ORR + stable disease [SD]) was 51.7 and 17.2% of patients had SD ≥ 4 months. The in vivo stability of the bispecific antibody was confirmed. Schedule 2 provided greater and more consistent inhibition of mesenchymal-epithelial transition (MET)/EGFR throughout the dosing interval than Schedule 1.

CONCLUSIONS

Although this study defined the LY3164530 MTD and pharmacokinetics on both schedules, significant toxicities associated with EGFR inhibition and lack of a potential predictive biomarker limit future development. Nonetheless, the results provide insight into the development of bispecific antibody therapy.

Improving Lateral Flow Assay Performance Using Computational Modeling

The performance, field utility, and low cost of lateral flow assays (LFAs) have driven a tremendous shift in global health care practices by enabling diagnostic testing in previously unserved settings. This success has motivated the continued improvement of LFAs through increasingly sophisticated materials and reagents. However, our mechanistic understanding of the underlying processes that drive the informed design of these systems has not received commensurate attention. Here, we review the principles underpinning LFAs and the historical evolution of theory to predict their performance. As this theory is integrated into computational models and becomes testable, the criteria for quantifying performance and validating predictive power are critical. The integration of computational design with LFA development offers a promising and coherent framework to choose from an increasing number of novel materials, techniques, and reagents to deliver the low-cost, high-fidelity assays of the future.

Synthetic Cancer-Targeting Innate Immune Stimulators Give Insights into Avidity Effects

Multispecific and multivalent antibodies are seen as promising cancer therapeutics, and numerous antibody fragments and derivatives have been developed to exploit avidity effects that result in increased selectivity. Most of these multispecific and multivalent antibody strategies make use of recombinant expression of antigen-binding modules. In contrast, chemical synthesis and chemoselective ligations can be used to generate a variety of molecules with different numbers and combinations of binding moieties in a modular and homogeneous fashion. In this study we synthesized a series of targeted immune system engagers (ISErs) by using solid-phase peptide synthesis and chemoselective ligations. To explore avidity effects, we constructed molecules bearing different numbers and combinations of two "binder" peptides that target ephrin A2 and integrin α₃ receptors and an "effector" peptide that binds to formyl peptide receptors and stimulates an immune response. We investigated various strategies for generating multivalent and multispecific targeted innate immune stimulators and studied their activities in terms of binding to cancer cells and stimulation of immune cells. This study gives insights into the influence that multivalency and receptor density have on avidity effects and is useful for the design of potential anticancer therapeutics.