Multichannel imaging to quantify four classes of pharmacokinetic distribution in tumors

Clinical translation of antibody drug conjugate dosing in solid tumors from preclinical mouse data

Antibody drug conjugates (ADCs) have made impressive strides in the clinic in recent years with 11 Food and Drug Administration approvals, including 6 for the treatment of patients with solid tumors. Despite this success, the development of new agents remains challenging with a high failure rate in the clinic. Here, we show that current approved ADCs for the treatment of patients with solid tumors can all show substantial efficacy in some mouse models when administered at a similar weight-based [milligrams per kilogram (mg/kg)] dosing in mice that is tolerated in the clinic. Mechanistically, equivalent mg/kg dosing results in a similar drug concentration in the tumor and a similar tissue penetration into the tumor due to the unique delivery features of ADCs. Combined with computational approaches, which can account for the complex distribution within the tumor microenvironment, these scaling concepts may aid in the evaluation of new agents and help design therapeutics with maximum clinical efficacy.

Mechanistically Weighted Metric to Predict In Vivo Antibody-Receptor Occupancy: An Analytical Approach

In situ clinical measurement of receptor occupancy (RO) is challenging, particularly for solid tumors, necessitating the use of mathematical models that predict tumor receptor occupancy to guide dose decisions. A potency metric, average free tissue target to initial target ratio (AFTIR), was previously described based on a mechanistic compartmental model and is informative for near-saturating dose regimens. However, the metric fails at clinically relevant subsaturating antibody doses, as compartmental models cannot capture the spatial heterogeneity of distribution faced by some antibodies in solid tumors. Here we employ a partial differential equation (PDE) Krogh cylinder model to simulate spatiotemporal receptor occupancy and derive an analytical solution, a mechanistically weighted global AFTIR, that can better predict receptor occupancy regardless of dosing regimen. In addition to the four key parameters previously identified, a fifth key parameter, the absolute receptor density (targets/cell), is incorporated into the mechanistic AFTIR metric. Receptor density can influence equilibrium intratumoral drug concentration relative to whether the dose is saturating or not, thereby influencing the tumor penetration depth of the antibody. We derive mechanistic RO predictions based on distinct patterns of antibody tumor penetration, presented as a global AFTIR metric guided by a Thiele Modulus and a local saturation potential (drug equivalent of binding potential for positron emissions tomography imaging) and validate the results using rigorous global and local sensitivity analysis. This generalized AFTIR serves as a more accurate analytical metric to aid clinical dose decisions and rational design of antibody-based therapeutics without the need for extensive PDE simulations. SIGNIFICANCE STATEMENT: Determining antibody-receptor occupancy (RO) is critical for dosing decisions in pharmaceutical development, but direct clinical measurement of RO is often challenging and invasive, particularly for solid tumors. Significant efforts have been made to develop mathematical models and simplified analytical metrics of RO, but these often require complex computer simulations. Here we present a mathematically rigorous but simplified analytical model to accurately predict RO across a range of affinities, doses, drug, and tumor properties.

Imaging the Alternatively Spliced D Domain of Tenascin C in a Preclinical Model of Inflammatory Bowel Disease

PURPOSE

To image colon-expressed alternatively spliced D domain of tenascin C in preclinical colitis models using near infrared (NIR)-labeled targeted molecular imaging agents.

PROCEDURES

A human IgG1 with nanomolar binding affinity specific to the alternatively spliced D domain of tenascin C was generated. Immunohistochemistry identified disease-specific expression of this extracellular matrix protein in the colon of mice given dextran sulfate sodium in the drinking water. The antibody reagent was labeled with the NIR fluorophore IRDye 800CW via amine chemistry and intravenously dosed to evaluate in vivo targeting specificity. Increasing doses of imaging agent were given to estimate the saturating dose.

RESULTS

The NIR-labeled proteins successfully targeted colonic lesions in a murine model of colitis. Co-administration of a molar excess competing unlabeled dose reduced normalized uptake in diseased colon by > 70%. Near infrared ex vivo images of colon resected from diseased animals showed saturation at doses exceeding 1 nmol and was confirmed with additional quantitative ex vivo biodistribution. Cellular-level specificity and protein stability were assessed via microscopy.

CONCLUSIONS

Our imaging data suggest the alternatively spliced D domain of tenascin C is a promising target for delivery-based applications in inflammatory bowel diseases.

Design of high avidity and low affinity antibodies for in situ control of antibody drug conjugate targeting

Antibody-Drug Conjugates (ADCs) have rapidly expanded in the clinic, with 7 new approvals in 3 years. For solid tumors, high doses of ADCs improve tissue penetration and efficacy. These doses are enabled by lower drug-to-antibody ratios and/or co-administration of unconjugated antibody carrier doses to avoid payload toxicity. While effective for highly expressed targets, these strategies may not maintain efficacy with lower target expression. To address this issue, a carrier dose that adjusts binding in situ according to cellular expression was designed using computational modeling. Previous studies demonstrated that coadministration of unconjugated antibody with the corresponding ADC at an 8:1 ratio improves ADCs efficacy in high HER2 expressing tumors. By designing a High Avidity, Low Affinity (HALA) carrier antibody, ADC binding is partially blocked in high expression cells, improving tissue penetration. In contrast, the HALA antibody cannot compete with the ADC in low expressing cells, allowing ADC binding to the majority of receptors. Thus, the amount of competition from the carrier dose automatically adjusts to expression levels, allowing tailored competition between different patients/metastases. The computational model highlights two dimensionless numbers, the Thiele modulus and a newly defined competition number, to design an optimal HALA antibody carrier dose for any target.

Cellular-Resolution Imaging of Bystander Payload Tissue Penetration from Antibody-Drug Conjugates

After several notable clinical failures in early generations, antibody-drug conjugates (ADCs) have made significant gains with seven new FDA-approvals within the last 3 years. These successes have been driven by a shift towards mechanistically informed ADC design, where the payload, linker, drug-to-antibody ratio, and conjugation are increasingly tailored to a specific target and clinical indication. However, fundamental aspects needed for design, such as payload distribution, remain incompletely understood. Payloads are often classified as 'bystander' or 'non-bystander' depending on their ability to diffuse out of targeted cells into adjacent cells that may be antigen negative or more distant from tumor vessels, helping to overcome heterogeneous distribution. Seven of the eleven FDA-approved ADCs employ these bystander payloads, but the depth of penetration and cytotoxic effects as a function of physicochemical properties and mechanism of action have not been fully characterized. Here, we utilized tumor spheroids and pharmacodynamic marker staining to quantify tissue penetration of the three major classes of agents: microtubule inhibitors, DNA-damaging agents, and topoisomerase inhibitors. PAMPA data and co-culture assays were performed to compare to the 3D tissue culture data. The results demonstrate a spectrum in bystander potential and tissue penetration depending on the physicochemical properties and potency of the payload. Generally, directly targeted cells show a greater response even with bystander payloads, consistent with the benefit of deeper ADC penetration. These results are compared to computational simulations to help scale the data from in vitro and preclinical animal models to the clinic.

Antibody Co-Administration Can Improve Systemic and Local Distribution of Antibody-Drug Conjugates to Increase In Vivo Efficacy

Several antibody-drug conjugates (ADC) showing strong clinical responses in solid tumors target high expression antigens (HER2, TROP2, Nectin-4, and folate receptor alpha/FRα). Highly expressed tumor antigens often have significant low-level expression in normal tissues, resulting in the potential for target-mediated drug disposition (TMDD) and increased clearance. However, ADCs often do not cross-react with normal tissue in animal models used to test efficacy (typically mice), and the impact of ADC binding to normal tissue antigens on tumor response remains unclear. An antibody that cross-reacts with human and murine FRα was generated and tested in an animal model where the antibody/ADC bind both human tumor FRα and mouse FRα in normal tissue. Previous work has demonstrated that a "carrier" dose of unconjugated antibody can improve the tumor penetration of ADCs with high expression target-antigens. A carrier dose was employed to study the impact on cross-reactive ADC clearance, distribution, and efficacy. Co-administration of unconjugated anti-FRα antibody with the ADC-improved efficacy, even in low expression models where co-administration normally lowers efficacy. By reducing target-antigen-mediated clearance in normal tissue, the co-administered antibody increased systemic exposure, improved tumor tissue penetration, reduced target-antigen-mediated uptake in normal tissue, and increased ADC efficacy. However, payload potency and tumor antigen saturation are also critical to efficacy, as shown with reduced efficacy using too high of a carrier dose. The judicious use of higher antibody doses, either through lower DAR or carrier doses, can improve the therapeutic window by increasing efficacy while lowering target-mediated toxicity in normal tissue.

Anchor, Spacer, and Ligand-Modified Engineered Exosomes for Trackable Targeted Therapy

Exosomes have been widely demonstrated as an effective anticancer therapeutic moiety. However, their clinical translation has been limited by the requirement of prohibitively high therapeutic doses due to their lack of specificity in delivery and, consequently, short systemic half-life. To overcome these challenges, we engineered a platform for modifying exosomes with an active targeting modality composed of membrane Anchor (BODIPY)-Spacer (PEG)-targeting Ligands (cyclic RGD peptide) (ASL). Herein, we show that the intramembrane incorporation of a trackable, targeting system renders ASL exosomes (AExs) a modular platform. AExs significantly overcome challenges associated with exosome modification, including potential damage for functionalization, or destabilizing interactions between dyes and drugs. ASL-modification not only enhanced stability in imparting active targeting but also introduced a built-in bioimaging modality. Our studies show that AExs target B16F10 melanoma tumor sites by the specific interaction of cyclic RGD and integrin. Doxorubicin encapsulated AExs (dAExs) significantly inhibited the growth of melanoma in vitro and in vivo. Thus, we conclude that ASL-modification allows exosomes to be transformed into a novel therapeutic vehicle uniquely integrating in vivo tracking and robust targeting with drug delivery. We anticipate that the therapeutic, targeting, and diagnostic modularity provided by ASL will potentiate translational applications of exosome-based vehicles beyond anticancer therapy.

Electrostatic driven transport enhances penetration of positively charged peptide surfaces through tumor extracellular matrix

Drug carriers achieve poor and heterogeneous distribution within solid tumors due to limited transport through the tumor extracellular matrix (ECM). The tumor ECM forms a net negatively charged network that interacts with and hinders the transport of molecules in part due to electrostatic interactions. Traditionally, the surfaces of drug delivery systems are passivated to minimize these interactions, but the mechanism of how charge interactions impact transport and penetration within the tumor microenvironment (TME) is not well understood. Here, we used T7 bacteriophage as a model biological nanoparticle to display peptides of different charges on its surface and elucidate how charge-based binding drives transport, uptake, and retention within tumor tissue. In contrast to current studies with neutrally charged surfaces, we discovered that a positively charged peptide displayed on T7 enhanced its penetration through a tumor-like ECM when compared to neutrally and negatively charged peptides. The positively charged peptide displayed on T7 facilitated weak and reversible binding with the TME to achieve Donnan partitioning and deep penetration into ex vivo tumor tissue. Additionally, the positively charged peptide-presenting T7 has a high number of intra-tissue binding sites in the TME (~4 µM) that enables almost 100% retention in the tumor tissue for up to 24 h. These results, coupled with transport studies of systematically mutated T7, show that electrostatic interactions can be responsible for uptake and retention of the positively charged peptide-presenting T7 within the net negatively charged TME. STATEMENT OF SIGNIFICANCE: The TME selectively hinders the transport of drugs and drug delivery systems due to their size, shape, and intermolecular interactions. Typically, the focus in drug delivery has been to develop delivery systems smaller than the pore size of the tumor ECM and/or develop inert surface coatings that have negligible interactions with the tumor ECM for diffusive transport. While there is an association of the surface charge of carriers with their transport through the tumor ECM, the mechanism of charge-driven transport is poorly understood. In this work, we elucidate the mechanism and find that interestingly, particles with a weakly positive surface charge interact with the net negatively charged tumor ECM to significantly improve their uptake, penetration, and retention in tumor tissue.

Increased Tumor Penetration of Single-Domain Antibody-Drug Conjugates Improves In Vivo Efficacy in Prostate Cancer Models

Targeted delivery of chemotherapeutics aims to increase efficacy and lower toxicity by concentrating drugs at the site-of-action, a method embodied by the seven current FDA-approved antibody-drug conjugates (ADC). However, a variety of pharmacokinetic challenges result in relatively narrow therapeutic windows for these agents, hampering the development of new drugs. Here, we use a series of prostate-specific membrane antigen-binding single-domain (Humabody) ADC constructs to demonstrate that tissue penetration of protein-drug conjugates plays a major role in therapeutic efficacy. Counterintuitively, a construct with lower in vitro potency resulted in higher in vivo efficacy than other protein-drug conjugates. Biodistribution data, tumor histology images, spheroid experiments, in vivo single-cell measurements, and computational results demonstrate that a smaller size and slower internalization rate enabled higher tissue penetration and more cell killing. The results also illustrate the benefits of linking an albumin-binding domain to the single-domain ADCs. A construct lacking an albumin-binding domain was rapidly cleared, leading to lower tumor uptake (%ID/g) and decreased in vivo efficacy. In conclusion, these results provide evidence that reaching the maximum number of cells with a lethal payload dose correlates more strongly with in vivo efficacy than total tumor uptake or in vitro potency alone for these protein-drug conjugates. Computational modeling and protein engineering can be used to custom design an optimal framework for controlling internalization, clearance, and tissue penetration to maximize cell killing. SIGNIFICANCE: A mechanistic study of protein-drug conjugates demonstrates that a lower potency compound is more effective in vivo than other agents with equal tumor uptake due to improved tissue penetration and cellular distribution.

An Agent-Based Systems Pharmacology Model of the Antibody-Drug Conjugate Kadcyla to Predict Efficacy of Different Dosing Regimens

The pharmaceutical industry has invested significantly in antibody-drug conjugates (ADCs) with five FDA-approved therapies and several more showing promise in late-stage clinical trials. The FDA-approved therapeutic Kadcyla (ado-trastuzumab emtansine or T-DM1) can extend the survival of patients with tumors overexpressing HER2. However, tumor histology shows that most T-DM1 localizes perivascularly, but coadministration with its unconjugated form (trastuzumab) improves penetration of the ADC into the tumor and subsequent treatment efficacy. ADC dosing schedule, e.g., dose fractionation, has also been shown to improve tolerability. However, it is still not clear how coadministration with carrier doses impacts efficacy in terms of receptor expression, dosing regimens, and payload potency. Here, we develop a hybrid agent-based model (ABM) to capture ADC and/or antibody delivery and to predict tumor killing and growth kinetics. The results indicate that a carrier dose improves efficacy when the increased number of cells targeted by the ADC outweighs the reduced fractional killing of the targeted cells. The threshold number of payloads per cell required for killing plays a pivotal role in defining this cutoff. Likewise, fractionated dosing lowers ADC efficacy due to lower tissue penetration from a reduced maximum plasma concentration. It is only beneficial when an increase in tolerability from fractionation allows a higher ADC/payload dose that more than compensates for the loss in efficacy from fractionation. Overall, the multiscale model enables detailed depictions of heterogeneous ADC delivery, cancer cell death, and tumor growth to show how carrier dosing impacts efficacy to design the most efficacious regimen.

Hitting Undruggable Targets: Viewing Stabilized Peptide Development through the Lens of Quantitative Systems Pharmacology

Stabilized peptide therapeutics have the potential to hit currently undruggable targets, dramatically expanding the druggable genome. However, major obstacles to their development include poor intracellular delivery, rapid degradation, low target affinity, and membrane toxicity. With the emergence of multiple stabilization techniques and screening technologies, the high efficacy of various bioactive peptides has been demonstrated in vitro, albeit with limited success in vivo. We discuss here the chemical and pharmacokinetic barriers to achieving in vivo efficacy, analyze the characteristics of FDA-approved peptide drugs, and propose a developmental tool that considers the molecular properties of stabilized peptides in a comprehensive and quantitative manner to achieve the necessary rates for in vivo delivery to the target, efficacy, and ultimately clinical translation.

Improved Tumor Penetration and Single-Cell Targeting of Antibody-Drug Conjugates Increases Anticancer Efficacy and Host Survival

Current antibody-drug conjugates (ADC) have made advances in engineering the antibody, linker, conjugation site, small-molecule payload, and drug-to-antibody ratio (DAR). However, the relationship between heterogeneous intratumoral distribution and efficacy of ADCs is poorly understood. Here, we compared trastuzumab and ado-trastuzumab emtansine (T-DM1) to study the impact of ADC tumor distribution on efficacy. In a mouse xenograft model insensitive to trastuzumab, coadministration of trastuzumab with a fixed dose of T-DM1 at 3:1 and 8:1 ratios dramatically improved ADC tumor penetration and resulted in twice the improvement in median survival compared with T-DM1 alone. In this setting, the effective DAR was lowered, decreasing the amount of payload delivered to each targeted cell but increasing the number of cells that received payload. This result is counterintuitive because trastuzumab acts as an antagonist in vitro and has no single-agent efficacy in vivo, yet improves the effectiveness of T-DM1 in vivo Novel dual-channel fluorescence ratios quantified single-cell ADC uptake and metabolism and confirmed that the in vivo cellular dose of T-DM1 alone exceeded the minimum required for efficacy in this model. In addition, this technique characterized cellular pharmacokinetics with heterogeneous delivery after 1 day, degradation and payload release by 2 days, and in vitro cell killing and in vivo tumor shrinkage 2 to 3 days later. This work demonstrates that the intratumoral distribution of ADC, independent of payload dose or plasma clearance, plays a major role in ADC efficacy.Significance: This study shows how lowering the drug-to-antibody ratio during treatment can improve the intratumoral distribution of a antibody-drug conjugate, with implications for improving the efficacy of this class of cancer drugs. Cancer Res; 78(3); 758-68. ©2017 AACR.

Imaging of anticancer drug action in single cells

Imaging is widely used in anticancer drug development, typically for whole-body tracking of labelled drugs to different organs or to assess drug efficacy through volumetric measurements. However, increasing attention has been drawn to pharmacology at the single-cell level. Diverse cell types, including cancer-associated immune cells, physicochemical features of the tumour microenvironment and heterogeneous cell behaviour all affect drug delivery, response and resistance. This Review summarizes developments in the imaging of in vivo anticancer drug action, with a focus on microscopy approaches at the single-cell level and translational lessons for the clinic.

Tracking Antibody Distribution with Near-Infrared Fluorescent Dyes: Impact of Dye Structure and Degree of Labeling on Plasma Clearance

Monoclonal antibodies labeled with near-infrared (NIR) fluorophores have potential use in disease detection, intraoperative imaging, and pharmacokinetic characterization of therapeutic antibodies in both the preclinical and clinical setting. Recent work has shown conjugation of NIR fluorophores to antibodies can potentially alter antibody disposition at a sufficiently high degree of labeling (DoL); however, other reports show minimal impact after labeling with NIR fluorophores. In this work, we label two clinically approved antibodies, Herceptin (trastuzumab) and Avastin (bevacizumab), with NIR dyes IRDye 800CW (800CW) or Alexa Fluor 680 (AF680), at 1.2 and 0.3 dyes/antibody and examine the impact of fluorophore conjugation on antibody plasma clearance and tissue distribution. At 0.3 DoL, AF680 conjugates exhibited similar clearance to unlabeled antibody over 17 days while 800CW conjugates diverged after 4 days, suggesting AF680 is a more suitable choice for long-term pharmacokinetic studies. At the 1.2 DoL, 800CW conjugates cleared faster than unlabeled antibodies after several hours, in agreement with other published reports. The tissue biodistribution for bevacizumab–800CW and −AF680 conjugates agreed well with literature reported biodistributions using radiolabels. However, the greater tissue autofluorescence at 680 nm resulted in limited detection above background at low (∼2 mg/kg) doses and 0.3 DoL for AF680, indicating that 800CW is more appropriate for short-term biodistribution measurements and intraoperative imaging. Overall, our work shows a DoL of 0.3 or less for non-site-specifically labeled antibodies (with a Poisson distribution) is ideal for limiting the impact of NIR fluorophores on antibody pharmacokinetics.

Quantitative Impact of Plasma Clearance and Down-regulation on GLP-1 Receptor Molecular Imaging

PURPOSE

Quantitative molecular imaging of beta cell mass (BCM) would enable early detection and treatment monitoring of type 1 diabetes. The glucagon-like peptide-1 (GLP-1) receptor is an attractive target due to its beta cell specificity and cell surface location. We quantitatively investigated the impact of plasma clearance and receptor internalization on targeting efficiency in healthy B6 mice.

PROCEDURES

Four exenatide-based probes were synthesized that varied in molecular weight, binding affinity, and plasma clearance. The GLP-1 receptor internalization rate and in vivo receptor expression were quantified.

RESULTS

Receptor internalization (54,000 receptors/cell in vivo) decreased significantly within minutes, reducing the benefit of a slower-clearing agent. The multimers and albumin binding probes had higher kidney and liver uptake, respectively.

CONCLUSIONS

Slow plasma clearance is beneficial for GLP-1 receptor peptide therapeutics. However, for exendin-based imaging of islets, down-regulation of the GLP-1 receptor and non-specific background uptake result in a higher target-to-background ratio for fast-clearing agents.

Residualization Rates of Near-Infrared Dyes for the Rational Design of Molecular Imaging Agents

PURPOSE

Near-infrared (NIR) fluorescence imaging is widely used for tracking antibodies and biomolecules in vivo. Clinical and preclinical applications include intraoperative imaging, tracking therapeutics, and fluorescent labeling as a surrogate for subsequent radiolabeling. Despite their extensive use, one of the fundamental properties of NIR dyes, the residualization rate within cells following internalization, has not been systematically studied. This rate is required for the rational design of probes and proper interpretation of in vivo results.

PROCEDURES

In this brief report, we measure the cellular residualization rate of eight commonly used dyes encompassing three core structures (cyanine, boron-dipyrromethene (BODIPY), and oxazine/thiazine/carbopyronin).

RESULTS

We identify residualizing (half-life >24 h) and non-residualizing (half-life <24 h) dyes in both the far-red (~650-680 nm) and near-infrared (~740-800 nm) regions.

CONCLUSIONS

This data will allow researchers to independently and rationally select the wavelength and residualizing nature of dyes for molecular imaging agent design.

Multiscale Modeling of Antibody-Drug Conjugates: Connecting Tissue and Cellular Distribution to Whole Animal Pharmacokinetics and Potential Implications for Efficacy

Antibody-drug conjugates exhibit complex pharmacokinetics due to their combination of macromolecular and small molecule properties. These issues range from systemic concerns, such as deconjugation of the small molecule drug during the long antibody circulation time or rapid clearance from nonspecific interactions, to local tumor tissue heterogeneity, cell bystander effects, and endosomal escape. Mathematical models can be used to study the impact of these processes on overall distribution in an efficient manner, and several types of models have been used to analyze varying aspects of antibody distribution including physiologically based pharmacokinetic (PBPK) models and tissue-level simulations. However, these processes are quantitative in nature and cannot be handled qualitatively in isolation. For example, free antibody from deconjugation of the small molecule will impact the distribution of conjugated antibodies within the tumor. To incorporate these effects into a unified framework, we have coupled the systemic and organ-level distribution of a PBPK model with the tissue-level detail of a distributed parameter tumor model. We used this mathematical model to analyze new experimental results on the distribution of the clinical antibody-drug conjugate Kadcyla in HER2-positive mouse xenografts. This model is able to capture the impact of the drug-antibody ratio (DAR) on tumor penetration, the net result of drug deconjugation, and the effect of using unconjugated antibody to drive ADC penetration deeper into the tumor tissue. This modeling approach will provide quantitative and mechanistic support to experimental studies trying to parse the impact of multiple mechanisms of action for these complex drugs.

Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design

Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared – non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.