A Bispecific Modeling Framework Enables the Prediction of Efficacy, Toxicity, and Optimal Molecular Design of Bispecific Antibodies Targeting MerTK.

Inhibiting MerTK on macrophages is a promising therapeutic strategy for augmenting anti-tumor immunity. However, blocking MerTK on retinal pigment epithelial cells (RPEs) results in retinal toxicity. Bispecific antibodies (bsAbs) containing an anti-MerTK therapeutic and anti-PD-L1 targeting arm were developed to reduce drug binding to MerTK on RPEs, since PD-L1 is overexpressed on macrophages but not RPEs. In this study, we present a modeling framework using in vitro receptor occupancy (RO) and pharmacokinetics (PK) data to predict efficacy, toxicity, and therapeutic index (TI) of anti-MerTK bsAbs. We first used simulations and in vitro RO data of anti-MerTK monospecific antibody (msAb) to estimate the required MerTK RO for in vivo efficacy and toxicity. Using these estimated RO thresholds, we employed our model to predict the efficacious and toxic doses for anti-MerTK bsAbs with varying affinities for MerTK. Our model predicted the highest TI for the anti-MerTK/PD-L1 bsAb with an attenuated MerTK binding arm, which was consistent with in vivo efficacy and toxicity observations. Subsequently, we used the model, in combination with sensitivity analysis and parameter scans, to suggest an optimal molecular design of anti-MerTK bsAb with the highest predicted TI in humans. Our prediction revealed that this optimized anti-MerTK bsAb should contain a MerTK therapeutic arm with relatively low affinity, along with a high affinity targeting arm that can bind to a low abundance target with slow turnover rate. Overall, these results demonstrated that our modeling framework can guide the rational design of bsAbs.

Nonclinical Pharmacokinetics, Pharmacodynamics, and Translational Model of RO7297089, A Novel Anti-BCMA/CD16A Bispecific Tetravalent Antibody for the Treatment of Multiple Myeloma.

RO7297089, an anti-B-cell maturation antigen (BCMA)/CD16A bispecific tetravalent antibody, is being developed as a multiple myeloma (MM) therapeutic. This study characterized nonclinical pharmacokinetics (PK), pharmacodynamics (PD), soluble BCMA (sBCMA), and soluble CD16 (sCD16) changes following administration of RO7297089 to support clinical trials. Unbound and total RO7297089 concentrations were measured in cynomolgus monkeys. RO7297089 exhibited a bi-phasic systemic concentration-time profile, similar to a typical human immunoglobulin 1 antibody. Target engagement by RO7297089 led to a robust increase (~100-fold) in total systemic sBCMA levels and relatively mild increase (~2-fold) in total sCD16 levels. To describe the relationship of nonclinical PK/PD data, we developed a target-mediated drug disposition (TMDD) model that includes the systemic target engagement of membrane BCMA (mBCMA), sBCMA, membrane CD16 (mCD16), and sCD16. We then used this model to simulate the PK/PD relationship of RO7297089 in MM patients by translating relevant PK parameters and target levels, based on the literature and newly generated data such as baseline sCD16A levels. Our model suggested that the impact of TMDD on RO7297089 exposure may be more significant in MM patients due to significantly higher expression levels of both mBCMA and sBCMA compared to healthy cynomolgus monkeys. Based on model simulations, we propose more frequent dosing of RO7297089 compared to regular monthly frequency in the clinic at the beginning of treatment to ensure sustained target engagement. This study demonstrates a translational research strategy for collecting relevant nonclinical data, establishing a TMDD model, and using simulations from this model to inform clinical dose regimens.

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.

Novel Anti-LY6G6D/CD3 T-Cell-Dependent Bispecific Antibody for the Treatment of Colorectal Cancer.

New therapeutics and combination regimens have led to marked clinical improvements for the treatment of a subset of colorectal cancer. Immune checkpoint inhibitors have shown clinical efficacy in patients with mismatch-repair-deficient or microsatellite instability-high (MSI-H) metastatic colorectal cancer (mCRC). However, patients with microsatellite-stable (MSS) or low levels of microsatellite instable (MSI-L) colorectal cancer have not benefited from these immune modulators, and the survival outcome remains poor for the majority of patients diagnosed with mCRC. In this article, we describe the discovery of a novel T-cell-dependent bispecific antibody (TDB) targeting tumor-associated antigen LY6G6D, LY6G6D-TDB, for the treatment of colorectal cancer. RNAseq analysis showed that LY6G6D was differentially expressed in colorectal cancer with high prevalence in MSS and MSI-L subsets, whereas LY6G6D expression in normal tissues was limited. IHC confirmed the elevated expression of LY6G6D in primary and metastatic colorectal tumors, whereas minimal or no expression was observed in most normal tissue samples. The optimized LY6G6D-TDB, which targets a membrane-proximal epitope of LY6G6D and binds to CD3 with high affinity, exhibits potent antitumor activity both in vitro and in vivo. In vitro functional assays show that LY6G6D-TDB-mediated T-cell activation and cytotoxicity are conditional and target dependent. In mouse xenograft tumor models, LY6G6D-TDB demonstrates antitumor efficacy as a single agent against established colorectal tumors, and enhanced efficacy can be achieved when LY6G6D-TDB is combined with PD-1 blockade. Our studies provide evidence for the therapeutic potential of LY6G6D-TDB as an effective treatment option for patients with colorectal cancer.

A Novel Approach for Quantifying the Pharmacological Activity of T-Cell Engagers Utilizing In Vitro Time Course Experiments and Streamlined Data Analysis.

CD3-bispecific antibodies are a new class of immunotherapeutic drugs against cancer. The pharmacological activity of CD3-bispecifics is typically assessed through in vitro assays of cancer cell lines co-cultured with human peripheral blood mononuclear cells (PBMCs). Assay results depend on experimental conditions such as incubation time and the effector-to-target cell ratio, which can hinder robust quantification of pharmacological activity. In order to overcome these limitations, we developed a new, holistic approach for quantification of the in vitro dose-response relationship. Our experimental design integrates a time-independent analysis of the dose-response across different time points as an alternative to the static, "snap-shot" analysis based on a single time point commonly used in dose-response assays. We show that the potency values derived from static in vitro experiments depend on the incubation time, which leads to inconsistent results across multiple assays and compounds. We compared the potency values from the time-independent analysis with a model-based approach. We find comparably accurate potency estimates from the model-based and time-independent analyses and that the time-independent analysis provides a robust quantification of pharmacological activity. This approach may allow for an improved head-to-head comparison of different compounds and test systems and may prove useful for supporting first-in-human dose selection.

Anti-LYPD1/CD3 T-Cell-Dependent Bispecific Antibody for the Treatment of Ovarian Cancer.

Ovarian cancer is a diverse class of tumors with very few effective treatment options and suboptimal response rates in early clinical studies using immunotherapies. Here we describe LY6/PLAUR domain containing 1 (LYPD1) as a novel target for therapeutic antibodies for the treatment of ovarian cancer. LYPD1 is broadly expressed in both primary and metastatic ovarian cancer with ∼70% prevalence in the serous cancer subset. Bispecific antibodies targeting CD3 on T cells and a tumor antigen on cancer cells have demonstrated significant clinical activity in hematologic cancers. We have developed an anti-LYPD1/CD3 T-cell-dependent bispecific antibody (TDB) to redirect T-cell responses to LYPD1 expressing ovarian cancer. Here we characterize the nonclinical pharmacology of anti-LYPD1/CD3 TDB and show induction of a robust polyclonal T-cell activation and target dependent killing of LYPD1 expressing ovarian cancer cells resulting in efficient in vivo antitumor responses in PBMC reconstituted immune-deficient mice and human CD3 transgenic mouse models. Anti-LYPD1/CD3 TDB is generally well tolerated at high-dose levels in mice, a pharmacologically relevant species, and showed no evidence of toxicity or damage to LYPD1 expressing tissues.

Target arm affinities determine preclinical efficacy and safety of anti-HER2/CD3 bispecific antibody.

Systemic cytokine release and on-target/off-tumor toxicity to normal tissues are the main adverse effects limiting the clinical utility of T cell-redirecting therapies. This study was designed to determine how binding affinity for CD3 and tumor target HER2 impact the efficacy and nonclinical safety of anti-HER2/CD3 T cell-dependent antibodies (TDBs). Affinity was found to be a major determinant for the overall tolerability. Higher affinity for CD3 associated with rapidly elevated peripheral cytokine concentrations, weight loss in mice, and poor tolerability in cynomolgus monkeys. A TDB with lower CD3 affinity was better tolerated in cynomolgus monkeys compared with a higher CD3-affinity TDB. In contrast to tolerability, T cell binding affinity had only limited impact on in vitro and in vivo antitumor activity. High affinity for HER2 was critical for the tumor-killing activity of anti-HER2/CD3 TDBs, but higher HER2 affinity also associated with a more severe toxicity profile, including cytokine release and damage to HER2-expressing tissues. The tolerability of the anti-HER2/CD3 was improved by implementing a dose-fractionation strategy. Fine-tuning the affinities for both the tumor target and CD3 is likely a valuable strategy for achieving maximal therapeutic index of CD3 bispecific antibodies.

Tutorial on Monoclonal Antibody Pharmacokinetics and Its Considerations in Early Development.

The tutorial introduces the readers to the fundamentals of antibody pharmacokinetics (PK) in the context of drug development. Topics covered include an overview of antibody development, PK characteristics, and the application of antibody PK/pharmacodynamics (PD) in research and development decision-making. We also discuss the general considerations for planning a nonclinical PK program and describe the types of PK studies that should be performed during early development of monoclonal antibodies.

Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity.

Pharmacokinetic (PK) and pharmacodynamic (PD) models seek to describe the temporal pattern of drug exposures and their associated pharmacological effects produced at micro- and macro-scales of organization. Antibody-based drugs have been developed for a large variety of diseases, with effects exhibited through a comprehensive range of mechanisms of action. Mechanism-based PK/PD and systems pharmacology models can play a major role in elucidating and integrating complex antibody pharmacological properties, such as nonlinear disposition and dynamical intracellular signaling pathways triggered by ligation to their cognate targets. Such complexities can be addressed through the use of robust computational modeling techniques that have proven powerful tools for pragmatic characterization of experimental data and for theoretical exploration of antibody efficacy and adverse effects. The primary objectives of such multi-scale mathematical models are to generate and test competing hypotheses and to predict clinical outcomes. In this review, relevant systems pharmacology and enhanced PD (ePD) models that are used as predictive tools for antibody-based drug action are reported. Their common conceptual features are highlighted, along with approaches used for modeling preclinical and clinically available data. Key examples illustrate how systems pharmacology and ePD models codify the interplay among complex biology, drug concentrations, and pharmacological effects. New hybrid modeling concepts that bridge cutting-edge systems pharmacology models with established PK/ePD models will be needed to anticipate antibody effects on disease in subpopulations and individual patients.

Efficient production of bispecific IgG of different isotypes and species of origin in single mammalian cells.

Bispecific IgG production in single host cells has been a much sought-after goal to support the clinical development of these complex molecules. Current routes to single cell production of bispecific IgG include engineering heavy chains for heterodimerization and redesign of Fab arms for selective pairing of cognate heavy and light chains. Here, we describe novel designs to facilitate selective Fab arm assembly in conjunction with previously described knobs-into-holes mutations for preferential heavy chain heterodimerization. The top Fab designs for selective pairing, namely variants v10 and v11, support near quantitative assembly of bispecific IgG in single cells for multiple different antibody pairs as judged by high-resolution mass spectrometry. Single-cell and in vitro-assembled bispecific IgG have comparable physical, in vitro biological and in vivo pharmacokinetics properties. Efficient single-cell production of bispecific IgG was demonstrated for human IgG1, IgG2 and IgG4 thereby allowing the heavy chain isotype to be tailored for specific therapeutic applications. Additionally, a reverse chimeric bispecific IgG2a with humanized variable domains and mouse constant domains was generated for preclinical proof-of-concept studies in mice. Efficient production of a bispecific IgG in stably transfected mammalian (CHO) cells was shown. Individual clones with stable titer and bispecific IgG composition for >120 days were readily identified. Such long-term cell line stability is needed for commercial manufacture of bispecific IgG. The single-cell bispecific IgG designs developed here may be broadly applicable to biotechnology research, including screening bispecific IgG panels, and to support clinical development.

Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells.

Systems models of biological networks show promise for informing drug target selection/qualification, identifying lead compounds and factors regulating disease progression, rationalizing combinatorial regimens, and explaining sources of intersubject variability and adverse drug reactions. However, most models of biological systems are qualitative and are not easily coupled with dynamical models of drug exposure-response relationships. In this proof-of-concept study, logic-based modeling of signal transduction pathways in U266 multiple myeloma (MM) cells is used to guide the development of a simple dynamical model linking bortezomib exposure to cellular outcomes. Bortezomib is a commonly used first-line agent in MM treatment; however, knowledge of the signal transduction pathways regulating bortezomib-mediated cell cytotoxicity is incomplete. A Boolean network model of 66 nodes was constructed that includes major survival and apoptotic pathways and was updated using responses to several chemical probes. Simulated responses to bortezomib were in good agreement with experimental data, and a reduction algorithm was used to identify key signaling proteins. Bortezomib-mediated apoptosis was not associated with suppression of nuclear factor κB (NFκB) protein inhibition in this cell line, which contradicts a major hypothesis of bortezomib pharmacodynamics. A pharmacodynamic model was developed that included three critical proteins (phospho-NFκB, BclxL, and cleaved poly (ADP ribose) polymerase). Model-fitted protein dynamics and cell proliferation profiles agreed with experimental data, and the model-predicted IC50 (3.5 nM) is comparable to the experimental value (1.5 nM). The cell-based pharmacodynamic model successfully links bortezomib exposure to MM cellular proliferation via protein dynamics, and this model may show utility in exploring bortezomib-based combination regimens.

Use of genomic data in risk assessment case study: II. Evaluation of the dibutyl phthalate toxicogenomic data set.

An evaluation of the toxicogenomic data set for dibutyl phthalate (DBP) and male reproductive developmental effects was performed as part of a larger case study to test an approach for incorporating genomic data in risk assessment. The DBP toxicogenomic data set is composed of nine in vivo studies from the published literature that exposed rats to DBP during gestation and evaluated gene expression changes in testes or Wolffian ducts of male fetuses. The exercise focused on qualitative evaluation, based on a lack of available dose-response data, of the DBP toxicogenomic data set to postulate modes and mechanisms of action for the male reproductive developmental outcomes, which occur in the lower dose range. A weight-of-evidence evaluation was performed on the eight DBP toxicogenomic studies of the rat testis at the gene and pathway levels. The results showed relatively strong evidence of DBP-induced downregulation of genes in the steroidogenesis pathway and lipid/sterol/cholesterol transport pathway as well as effects on immediate early gene/growth/differentiation, transcription, peroxisome proliferator-activated receptor signaling and apoptosis pathways in the testis. Since two established modes of action (MOAs), reduced fetal testicular testosterone production and Insl3 gene expression, explain some but not all of the testis effects observed in rats after in utero DBP exposure, other MOAs are likely to be operative. A reanalysis of one DBP microarray study identified additional pathways within cell signaling, metabolism, hormone, disease, and cell adhesion biological processes. These putative new pathways may be associated with DBP effects on the testes that are currently unexplained. This case study on DBP identified data gaps and research needs for the use of toxicogenomic data in risk assessment. Furthermore, this study demonstrated an approach for evaluating toxicogenomic data in human health risk assessment that could be applied to future chemicals.

Pathway modeling of microarray data: a case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP).

Pathway activity level analysis, the approach pursued in this study, focuses on all genes that are known to be members of metabolic and signaling pathways as defined by the KEGG database. The pathway activity level analysis entails singular value decomposition (SVD) of the expression data of the genes constituting a given pathway. We explore an extension of the pathway activity methodology for application to time-course microarray data. We show that pathway analysis enhances our ability to detect biologically relevant changes in pathway activity using synthetic data. As a case study, we apply the pathway activity level formulation coupled with significance analysis to microarray data from two different rat testes exposed in utero to Dibutyl Phthalate (DBP). In utero DBP exposure in the rat results in developmental toxicity of a number of male reproductive organs, including the testes. One well-characterized mode of action for DBP and the male reproductive developmental effects is the repression of expression of genes involved in cholesterol transport, steroid biosynthesis and testosterone synthesis that lead to a decreased fetal testicular testosterone. Previous analyses of DBP testes microarray data focused on either individual gene expression changes or changes in the expression of specific genes that are hypothesized, or known, to be important in testicular development and testosterone synthesis. However, a pathway analysis may inform whether there are additional affected pathways that could inform additional modes of action linked to DBP developmental toxicity. We show that Pathway activity analysis may be considered for a more comprehensive analysis of microarray data.

Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison.

Pathway-based information has become an important source of information for both establishing evolutionary relationships and understanding the mode of action of a chemical or pharmaceutical among species. Cross-species comparison of pathways can address two broad questions: comparison in order to inform evolutionary relationships and to extrapolate species differences used in a number of different applications including drug and toxicity testing. Cross-species comparison of metabolic pathways is complex as there are multiple features of a pathway that can be modeled and compared. Among the various methods that have been proposed, reaction alignment has emerged as the most successful at predicting phylogenetic relationships based on NCBI taxonomy. We propose an improvement of the reaction alignment method by accounting for sequence similarity in addition to reaction alignment method. Using nine species, including human and some model organisms and test species, we evaluate the standard and improved comparison methods by analyzing glycolysis and citrate cycle pathways conservation. In addition, we demonstrate how organism comparison can be conducted by accounting for the cumulative information retrieved from nine pathways in central metabolism as well as a more complete study involving 36 pathways common in all nine species. Our results indicate that reaction alignment with enzyme sequence similarity results in a more accurate representation of pathway specific cross-species similarities and differences based on NCBI taxonomy.

Circadian signatures in rat liver: from gene expression to pathways.

BACKGROUND: Circadian rhythms are 24 hour oscillations in many behavioural, physiological, cellular and molecular processes that are controlled by an endogenous clock which is entrained to environmental factors including light, food and stress. Transcriptional analyses of circadian patterns demonstrate that genes showing circadian rhythms are part of a wide variety of biological pathways.Pathway activity method can identify the significant pattern of the gene expression levels within a pathway. In this method, the overall gene expression levels are translated to a reduced form, pathway activity levels, via singular value decomposition (SVD). A given pathway represented by pathway activity levels can then be as analyzed using the same approaches used for analyzing gene expression levels. We propose to use pathway activity method across time to identify underlying circadian pattern of pathways. RESULTS: We used synthetic data to demonstrate that pathway activity analysis can evaluate the underlying circadian pattern within a pathway even when circadian patterns cannot be captured by the individual gene expression levels. In addition, we illustrated that pathway activity formulation should be coupled with a significance analysis to distinguish biologically significant information from random deviations. Next, we performed pathway activity level analysis on a rich time series of transcriptional profiling in rat liver. The over-represented five specific patterns of pathway activity levels, which cannot be explained by random event, exhibited circadian rhythms. The identification of the circadian signatures at the pathway level identified 78 pathways related to energy metabolism, amino acid metabolism, lipid metabolism and DNA replication and protein synthesis, which are biologically relevant in rat liver. Further, we observed tight coordination between cholesterol biosynthesis and bile acid biosynthesis as well as between folate biosynthesis, one carbon pool by folate and purine-pyrimidine metabolism. These coupled pathways are parts of a sequential reaction series where the product of one pathway is the substrate of another pathway. CONCLUSIONS: Rather than assessing the importance of a single gene beforehand and map these genes onto pathways, we instead examined the orchestrated change within a pathway. Pathway activity level analysis could reveal the underlying circadian dynamics in the microarray data with an unsupervised approach and biologically relevant results were obtained.

Transcriptional and metabolic flux profiling of triadimefon effects on cultured hepatocytes.

Conazoles are a class of azole fungicides used to prevent fungal growth in agriculture, for treatment of fungal infections, and are found to be tumorigenic in rats and/or mice. In this study, cultured primary rat hepatocytes were treated to two different concentrations (0.3 and 0.15 mM) of triadimefon, which is a tumorigenic conazole in rat and mouse liver, on a temporal basis with daily media change. Following treatment, cells were harvested for microarray data ranging from 6 to 72 h. Supernatant was collected daily for three days, and the concentrations of various metabolites in the media and supernatant were quantified. Gene expression changes were most significant following exposure to 0.3 mM triadimefon and were characterized mainly by metabolic pathways related to carbohydrate, lipid and amino acid metabolism. Correspondingly, metabolic network flexibility analysis demonstrated a switch from fatty acid synthesis to fatty acid oxidation in cells exposed to triadimefon. It is likely that fatty acid oxidation is active in order to supply energy required for triadimefon detoxification. In 0.15 mM triadimefon treatment, the hepatocytes are able to detoxify the relatively low concentration of triadimefon with less pronounced changes in hepatic metabolism.