Effect of molecular size on interstitial pharmacokinetics and tissue catabolism of antibodies

Synthesis and Evaluation of a Cathepsin B-Recognizing Trifunctional Chelating Agent to Improve Tumor Retention of Radioimmunoconjugates

Cathepsin B (CTSB) is a lysosomal protease that is overexpressed in tumor cells. Radioimmunoconjugates (RICs) composed of CTSB-recognizing chelating agents are expected to increase the molecular weights of their radiometabolites by forming conjugates with CTSB in cells, resulting in their improved retention in tumor cells. We designed a novel CTSB-recognizing trifunctional chelating agent, azide-[111In]In-DOTA-CTSB-substrate ([111In]In-ADCS), to synthesize a RIC, trastuzumab-[111In]In-ADCS ([111In]In-TADCS), and evaluated its utility to improve tumor retention of the RIC. [111In]In-ADCS and [111In]In-TADCS were synthesized with satisfactory yield and purity. [111In]In-ADCS was markedly stable in murine plasma until 96 h postincubation. [111In]In-ADCS showed binding to CTSB in vitro, and the conjugation was blocked by the addition of CTSB inhibitor. In the internalization assay, [111In]In-TADCS exhibited high-level retention in SK-OV-3 cells, indicating the in vitro utility of the CTSB-recognizing unit. In the biodistribution assay, [111In]In-TADCS showed high-level tumor accumulation, but the retention was hardly improved. In the first attempt to combine a CTSB-recognizing unit and RIC, these findings show the fundamental properties of the CTSB-recognizing trifunctional chelating agent to improve tumor retention of RICs.

A minimal physiologically based pharmacokinetic model to study the combined effect of antibody size, charge, and binding affinity to FcRn/antigen on antibody pharmacokinetics

Protein therapeutics have revolutionized the treatment of a wide range of diseases. While they have distinct physicochemical characteristics that influence their absorption, distribution, metabolism, and excretion (ADME) properties, the relationship between the physicochemical properties and PK is still largely unknown. In this work we present a minimal physiologically-based pharmacokinetic (mPBPK) model that incorporates a multivariate quantitative relation between a therapeutic's physicochemical parameters and its corresponding ADME properties. The model's compound-specific input includes molecular weight, molecular size (Stoke's radius), molecular charge, binding affinity to FcRn, and specific antigen affinity. Through derived and fitted empirical relationships, the model demonstrates the effect of these compound-specific properties on antibody disposition in both plasma and peripheral tissues using observed PK data in mice and humans. The mPBPK model applies the two-pore hypothesis to predict size-based clearance and exposure of full-length antibodies (150 kDa) and antibody fragments (50-100 kDa) within a onefold error. We quantitatively relate antibody charge and PK parameters like uptake rate, non-specific binding affinity, and volume of distribution to capture the relatively faster clearance of positively charged mAb as compared to negatively charged mAb. The model predicts the terminal plasma clearance of slightly positively and negatively charged antibody in humans within a onefold error. The mPBPK model presented in this work can be used to predict the target-mediated disposition of a drug when compound-specific and target-specific properties are known. To our knowledge, a combined effect of antibody weight, size, charge, FcRn, and antigen has not been incorporated and studied in a single mPBPK model previously. By conclusively incorporating and relating a multitude of protein's physicochemical properties to observed PK, our mPBPK model aims to contribute as a platform approach in the early stages of drug development where many of these properties can be optimized to improve a molecule's PK and ultimately its efficacy.

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.

Comparison of monoclonal antibody disposition predictions using different physiologically based pharmacokinetic modelling platforms

Physiologically based pharmacokinetic (PBPK) models can be used to leverage physiological and in vitro data to predict monoclonal antibody (mAb) concentrations in serum and tissues. However, it is currently not known how consistent predictions of mAb disposition are across PBPK modelling platforms. In this work PBPK simulations of IgG, adalimumab and infliximab were compared between three platforms (Simcyp, PK-Sim, and GastroPlus). Accuracy of predicted serum and tissue concentrations was assessed using observed data collected from the literature. Physiological and mAb related input parameters were also compared and sensitivity analyses were carried out to evaluate model behavior when input values were altered. Differences in serum kinetics of IgG between platforms were minimal for a dose of 1 mg/kg, but became more noticeable at higher dosages (> 100 mg/kg) and when reference (healthy) physiological input values were altered. Predicted serum concentrations of both adalimumab and infliximab were comparable across platforms, but were noticeably higher than observed values. Tissue concentrations differed remarkably between the platforms, both for total- and interstitial fluid (ISF) concentrations. The accuracy of total tissue concentrations was within a three-fold of observed values for all tissues, except for brain tissue concentrations, which were overpredicted. Predictions of tissue ISF concentrations were less accurate and were best captured by GastroPlus. Overall, these simulations show that the different PBPK platforms generally predict similar mAb serum concentrations, but variable tissue concentrations. Caution is therefore warranted when PBPK models are used to simulate effect site tissue concentrations of mAbs without data to verify the predictions.

Human serum albumin binders: A piggyback ride for long-acting therapeutics

Human serum albumin (HSA) is the most abundant protein in the blood and has desirable properties as a drug carrier. One of the most promising ways to exploit HSA as a carrier is to append an albumin-binding moiety (ABM) to a drug for in situ HSA binding upon administration. Nature- and library-derived ABMs vary in size, affinity, and epitope, differentially improving the pharmacokinetics of an appended drug. In this review, we evaluate the current state of knowledge regarding various aspects of ABMs and the unique advantages of ABM-mediated drug delivery. Furthermore, we discuss how ABMs can be specifically modulated to maximize potential benefits in clinical development.

Unveiling CD59-Antibody Interactions to Design Paratope-Mimicking Peptides for Complement Modulation

CD59 is an abundant immuno-regulatory human protein that protects cells from damage by inhibiting the complement system. CD59 inhibits the assembly of the Membrane Attack Complex (MAC), the bactericidal pore-forming toxin of the innate immune system. In addition, several pathogenic viruses, including HIV-1, escape complement-mediated virolysis by incorporating this complement inhibitor in their own viral envelope. This makes human pathogenic viruses, such as HIV-1, not neutralised by the complement in human fluids. CD59 is also overexpressed in several cancer cells to resist the complement attack. Consistent with its importance as a therapeutical target, CD59-targeting antibodies have been proven to be successful in hindering HIV-1 growth and counteracting the effect of complement inhibition by specific cancer cells. In this work, we make use of bioinformatics and computational tools to identify CD59 interactions with blocking antibodies and to describe molecular details of the paratope-epitope interface. Based on this information, we design and produce paratope-mimicking bicyclic peptides able to target CD59. Our results set the basis for the development of antibody-mimicking small molecules targeting CD59 with potential therapeutic interest as complement activators.