A GIPR antagonist conjugated to GLP-1 analogues promotes weight loss with improved metabolic parameters in preclinical and phase 1 settings.

Obesity is a major public health crisis. Multi-specific peptides have emerged as promising therapeutic strategies for clinical weight loss. Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are endogenous incretins that regulate weight through their receptors (R). AMG 133 (maridebart cafraglutide) is a bispecific molecule engineered by conjugating a fully human monoclonal anti-human GIPR antagonist antibody to two GLP-1 analogue agonist peptides using amino acid linkers. Here, we confirm the GIPR antagonist and GLP-1R agonist activities in cell-based systems and report the ability of AMG 133 to reduce body weight and improve metabolic markers in male obese mice and cynomolgus monkeys. In a phase 1, randomized, double-blind, placebo-controlled clinical study in participants with obesity ( NCT04478708 ), AMG 133 had an acceptable safety and tolerability profile along with pronounced dose-dependent weight loss. In the multiple ascending dose cohorts, weight loss was maintained for up to 150 days after the last dose. These findings support continued clinical evaluation of AMG 133.

Correlation of In Vitro Kinetic Stability to Preclinical In Vivo Pharmacokinetics for a Panel of Anti-PD-1 Monoclonal Antibody Interleukin 21 Mutein Immunocytokines.

The development of therapeutic fusion protein drugs is often impeded by the unintended consequences that occur from fusing together domains from independent naturally occurring proteins, consequences such as altered biodistribution, tissue uptake, or rapid clearance and potential immunogenicity. For therapeutic fusion proteins containing globular domains, we hypothesized that aberrant in vivo behavior could be related to low kinetic stability of these domains leading to local unfolding and susceptibility to partial proteolysis and/or salvage and uptake. Herein we describe an assay to measure kinetic stability of therapeutic fusion proteins by way of their sensitivity to the protease thermolysin. The results indicate that in vivo pharmacokinetics of a panel of anti-programmed cell death protein 1 monocolonal antibody:interleukin 21 immunocytokines in both mice and nonhuman primates are highly correlated with their in vitro susceptibility to thermolysin-mediated proteolysis. This assay can be used as a tool to quickly identify in vivo liabilities of globular domains of therapeutic proteins, thus aiding in the optimization and development of new multispecific drug candidates. SIGNIFICANCE STATEMENT: This work describes a novel assay utilizing protein kinetic stability to identify preclinical in vivo pharmacokinetic liabilities of multispecific therapeutic fusion proteins. This provides an efficient, inexpensive method to ascertain inherent protein stability in vitro before conducting in vivo studies, which can rapidly increase the speed of preclinical drug development.

Utility of physiologically based pharmacokinetic modeling to predict inter-antibody variability in monoclonal antibody pharmacokinetics in mice.

In this investigation, we tested the hypothesis that a physiologically based pharmacokinetic (PBPK) model incorporating measured in vitro metrics of off-target binding can largely explain the inter-antibody variability in monoclonal antibody (mAb) pharmacokinetics (PK). A diverse panel of 83 mAbs was evaluated for PK in wild-type mice and subjected to 10 in vitro assays to measure major physiochemical attributes. After excluding for target-mediated elimination and immunogenicity, 56 of the remaining mAbs with an eight-fold variability in the area under the curve (AUC0-672h: 1.74 × 106 -1.38 × 107 ng∙h/mL) and 10-fold difference in clearance (2.55-26.4 mL/day/kg) formed the training set for this investigation. Using a PBPK framework, mAb-dependent coefficients F1 and F2 modulating pinocytosis rate and convective transport, respectively, were estimated for each mAb with mostly good precision (coefficient of variation (CV%) <30%). F1 was estimated to be the mean and standard deviation of 0.961 ± 0.593, and F2 was estimated to be 2.13 ± 2.62. Using principal component analysis to correlate the regressed values of F1/F2 versus the multidimensional dataset composed of our panel of in vitro assays, we found that heparin chromatography retention time emerged as the predictive covariate to the mAb-specific F1, whereas F2 variability cannot be well explained by these assays. A sigmoidal relationship between F1 and the identified covariate was incorporated within the PBPK framework. A sensitivity analysis suggested plasma concentrations to be most sensitive to F1 when F1 > 1. The predictive utility of the developed PBPK model was evaluated against a separate panel of 14 mAbs biased toward high clearance, among which area under the curve of PK data of 12 mAbs was predicted within 2.5-fold error, and the positive and negative predictive values for clearance prediction were 85% and 100%, respectively. MAb heparin chromatography assay output allowed a priori identification of mAb candidates with unfavorable PK.

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies.

Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.

Hallmarks of neurodegenerative disease: A systems pharmacology perspective.

Age-related central neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, are a rising public health concern and have been plagued by repeated drug development failures. The complex nature and poor mechanistic understanding of the etiology of neurodegenerative diseases has hindered the discovery and development of effective disease-modifying therapeutics. Quantitative systems pharmacology models of neurodegeneration diseases may be useful tools to enhance the understanding of pharmacological intervention strategies and to reduce drug attrition rates. Due to the similarities in pathophysiological mechanisms across neurodegenerative diseases, especially at the cellular and molecular levels, we envision the possibility of structural components that are conserved across models of neurodegenerative diseases. Conserved structural submodels can be viewed as building blocks that are pieced together alongside unique disease components to construct quantitative systems pharmacology (QSP) models of neurodegenerative diseases. Model parameterization would likely be different between the different types of neurodegenerative diseases as well as individual patients. Formulating our mechanistic understanding of neurodegenerative pathophysiology as a mathematical model could aid in the identification and prioritization of drug targets and combinatorial treatment strategies, evaluate the role of patient characteristics on disease progression and therapeutic response, and serve as a central repository of knowledge. Here, we provide a background on neurodegenerative diseases, highlight hallmarks of neurodegeneration, and summarize previous QSP models of neurodegenerative diseases.

GIPR antagonist antibodies conjugated to GLP-1 peptide are bispecific molecules that decrease weight in obese mice and monkeys.

Glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) regulate glucose and energy homeostasis. Targeting both pathways with GIP receptor (GIPR) antagonist antibody (GIPR-Ab) and GLP-1 receptor (GLP-1R) agonist, by generating GIPR-Ab/GLP-1 bispecific molecules, is an approach for treating obesity and its comorbidities. In mice and monkeys, these molecules reduce body weight (BW) and improve many metabolic parameters. BW loss is greater with GIPR-Ab/GLP-1 than with GIPR-Ab or a control antibody conjugate, suggesting synergistic effects. GIPR-Ab/GLP-1 also reduces the respiratory exchange ratio in DIO mice. Simultaneous receptor binding and rapid receptor internalization by GIPR-Ab/GLP-1 amplify endosomal cAMP production in recombinant cells expressing both receptors. This may explain the efficacy of the bispecific molecules. Overall, our GIPR-Ab/GLP-1 molecules promote BW loss, and they may be used for treating obesity.

The biodistribution of therapeutic proteins: Mechanism, implications for pharmacokinetics, and methods of evaluation.

Therapeutic proteins (TPs) are a diverse drug class that include monoclonal antibodies (mAbs), recombinantly expressed enzymes, hormones and growth factors, cytokines (e.g. chemokines, interleukins, interferons), as well as a wide range of engineered fusion scaffolds containing IgG1 Fc domain for half-life extension. As the pharmaceutical industry advances more potent and selective protein-based medicines through discovery and into the clinical stages of development, it has become widely appreciated that a comprehensive understanding of the mechanisms of TP biodistribution can aid this endeavor. This review aims to highlight the literature that has advanced our understanding of the determinants of TP biodistribution. A particular emphasis is placed on the multi-faceted role of the neonatal Fc receptor (FcRn) in mAb and Fc-fusion protein disposition. In addition, characterization of the TP-target interaction at the cell-level is discussed as an essential strategy to establish pharmacokinetic-pharmacodynamic (PK/PD) relationships that may lead to more informed human dose projections during clinical development. Methods for incorporation of tissue and cell-level parameters defining these characteristics into higher-order mechanistic and semi-mechanistic PK models will also be presented.

Preclinical characterization of the ADME properties of a surrogate anti-IL-36R monoclonal antibody antagonist in mouse serum and tissues.

The decision to pursue a monoclonal antibody (mAb) as a therapeutic for disease intervention requires the assessment of many factors, such as target-biology, including the total target burden and its accessibility at the intended site of action, as well as mAb-specific properties like binding affinity and the pharmacokinetics in serum and tissue. Interleukin-36 receptor (IL-36 R) is a member of the IL-1 family cytokine receptors and an attractive target to treat numerous epithelial-mediated inflammatory conditions, including psoriatic and rheumatoid arthritis, asthma, and chronic obstructive pulmonary disease. However, information concerning the expression profile of IL-36 R at the protein level is minimal, so the feasibility of developing a therapeutic mAb against this target is uncertain. Here, we present a characterization of the properties associated with absorption, distribution, metabolism, and excretion of a high-affinity IL-36 R-targeted surrogate rat (IgG2a) mAb antagonist in preclinical mouse models. The presence of IL-36 R in the periphery was confirmed unequivocally as the driver of non-linear pharmacokinetics in blood/serum, although a predominant site of tissue accumulation was not observed based upon the kinetics of radiotracer. Additionally, the contribution of IL-36 R-mediated catabolism of mAb in kidney was tested in a 5/6 nephrectomized mouse model where minimal effects on serum pharmacokinetics were observed, although analysis of functional mAb in urine suggests that target can influence the amount of mAb excreted. Our data highlight an interesting case of target-mediated drug disposition (TMDD) where low, yet broadly expressed levels of membrane-bound target result in a cumulative effect to drive TMDD behavior typical of a large, saturable target sink. The potential differences between our mouse model and IL-36 R target profile in humans are also presented.

Understanding Inter-Individual Variability in Monoclonal Antibody Disposition.

Monoclonal antibodies (mAbs) are currently the largest and most dominant class of therapeutic proteins. Inter-individual variability has been observed for several mAbs; however, an understanding of the underlying mechanisms and factors contributing to inter-subject differences in mAb disposition is still lacking. In this review, we analyze the mechanisms of antibody disposition and the putative mechanistic determinants of inter-individual variability. Results from in vitro, preclinical, and clinical studies were reviewed evaluate the role of the neonatal Fc receptor and Fc gamma receptors (expression and polymorphism), target properties (expression, shedding, turnover, internalization, heterogeneity, polymorphism), and the influence of anti-drug antibodies. Particular attention is given to the influence of co-administered drugs and disease, and to the physiological relevance of covariates identified by population pharmacokinetic modeling, as determinants of variability in mAb pharmacokinetics.

Measurement and Quantitative Characterization of Whole-Body Pharmacokinetics of Exogenously Administered T Cells in Mice.

Here we have investigated whole-body pharmacokinetics (PK) of exogenously administered T cells in a mouse model of melanoma and have developed a physiologically based pharmacokinetic (PBPK) model to quantitatively characterize the data. T cells were isolated from the spleen of tumor-bearing mice, activated, and labeled with chromium-51 to facilitate the quantification. Labeled T cells were injected in the tumor-bearing mice, and PK was measured in 19 different tissues. It was found that T cells disappear from the blood rapidly after administration and accumulate in the tissues to various extents. Spleen, liver, lung, kidney, bone, and lymph nodes accounted for more than 90% of T cells in the body. The distribution of T cells in solid tumors was found to be very low, hovering below 1%ID/g (percent of injected dose per gram of tissue) during the entire study. However, this observation may differ for targeted TCR-T and CAR-T cells. Observed PK profiles also suggest that T-cell-based therapies may be more successful in treating cancers of the lymphatic system and bone marrow metastases compared to solid tumors. A PBPK model was developed to characterize the whole-body PK of T cells, which incorporated key processes such as extravasation, elimination, and recirculation of T cells via lymph flow. Retention factors were incorporated into the spleen, liver, and kidney compartment to adequately capture the PK profiles. The model was able to characterize observed PK profiles reasonably well, and parameters were estimated with good confidence. The PK data and PBPK model presented here provide unprecedented insight into the biodistribution of exogenously administered T cells.

Sorafenib Decreases Tumor Exposure to an Anti-carcinoembryonic Antigen Monoclonal Antibody in a Mouse Model of Colorectal Cancer.

In this investigation, we test the hypothesis that treatment with sorafenib, an anti-angiogenic agent, decreases tumor vascularization and, consequently, hinders the delivery of monoclonal antibodies (mAb) to xenograft tumors. Severe combined immunodeficiency mice bearing carcinoembryonic antigen (CEA) expressing tumor xenografts were divided into control and sorafenib-treated groups. Sorafenib was administered to the latter group at 50 mg/kg IP every 48 h, starting 4 days post-tumor implantation. When tumors attained a size of 200-300 mm(3), mice were evaluated for (a) tumor microvessel density (using immunohistochemical analysis), (b) tumor macromolecular extravasation (using Evans Blue Dye (EBD)), (c) pharmacokinetics of an anti-CEA mAb, T84.66, following an intravenous dose of 10 mg/kg, and (d) intra-tumoral spatial distribution of T84.66 (using autoradiography). Sorafenib treatment resulted in a substantial reduction in tumor growth rate, a visible reduction in tumor microvessel density, and in a 46.4% decrease in EBD extravasation in tumor tissue (p < 0.0455). For control and treated mice, no significant difference was found for the area under the mAb plasma concentration-time curve (AUC(0-7d): 1.67 × 10(3) ± 1.28 × 10(2) vs. 1.76 × 10(3) ± 1.75 × 10(2) nM × day, p = 0.51). However, tumor AUC(0-7d) was reduced by 40.8% in sorafenib-treated mice relative to that observed in control mice (5.61 × 10(2) ± 4.27 × 10(1) vs. 9.48 × 10(2) ± 5.61 × 10(1) nM × day, p < 0.001). Sorafenib therapy was also found to markedly alter mAb tumor spatial distribution. The results collectively suggest that sorafenib treatment causes a significant reduction in mAb delivery to, and distribution within, solid tumors.