Improving Intracellular Delivery of an Antibody-Drug Conjugate Targeting Carcinoembryonic Antigen Increases Efficacy at Clinically Relevant Doses In Vivo.

Solid tumor antibody-drug conjugates (ADC) have experienced more clinical success in the last 5 years than the previous 18-year span since the first ADC approval in 2000. While recent advances in protein engineering, linker design, and payload variations have played a role in this success, high expression and readily internalized targets have also been crucial to solid tumor therapy. However, these factors are also paradoxically connected to poor tissue penetration and lower efficacy. Previous work shows that potent ADCs can benefit from slower internalization under subsaturating doses to improve tissue penetration and increase tumor response. In contrast, faster internalization is predicted to increase efficacy under higher, tumor saturating doses. In this work, the intracellular delivery of SN-38 conjugated to an anti-carcinoembryonic antigen (anti-CEA) antibody (Ab) is increased by coadministering a noncompeting (cross-linking) anti-CEA Ab to improve efficacy in a colorectal carcinoma animal model. The SN-38 payload enables broad tumor saturation with clinically-tolerable doses, and under these saturating conditions, using a second CEA receptor cross-linking Ab yields faster internalization, which increases tumor killing efficacy. Our spheroid results show indirect bystander killing can also occur, but the more efficient direct cell killing from targeted intracellular payload release drives a greater tumor response. These results provide a strategy to increase therapeutic effectiveness with improved intracellular delivery under tumor saturating doses with the potential to expand the ADC target repertoire.

Predictive Simulations in Preclinical Oncology to Guide the Translation of Biologics.

Preclinical in vivo studies form the cornerstone of drug development and translation, bridging in vitro experiments with first-in-human trials. However, despite the utility of animal models, translation from the bench to bedside remains difficult, particularly for biologics and agents with unique mechanisms of action. The limitations of these animal models may advance agents that are ineffective in the clinic, or worse, screen out compounds that would be successful drugs. One reason for such failure is that animal models often allow clinically intolerable doses, which can undermine translation from otherwise promising efficacy studies. Other times, tolerability makes it challenging to identify the necessary dose range for clinical testing. With the ability to predict pharmacokinetic and pharmacodynamic responses, mechanistic simulations can help advance candidates from in vitro to in vivo and clinical studies. Here, we use basic insights into drug disposition to analyze the dosing of antibody drug conjugates (ADC) and checkpoint inhibitor dosing (PD-1 and PD-L1) in the clinic. The results demonstrate how simulations can identify the most promising clinical compounds rather than the most effective in vitro and preclinical in vivo agents. Likewise, the importance of quantifying absolute target expression and antibody internalization is critical to accurately scale dosing. These predictive models are capable of simulating clinical scenarios and providing results that can be validated and updated along the entire development pipeline starting in drug discovery. Combined with experimental approaches, simulations can guide the selection of compounds at early stages that are predicted to have the highest efficacy in the clinic.

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 Cmax 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.

Quantifying ADC bystander payload penetration with cellular resolution using pharmacodynamic mapping.

With the recent approval of 3 new antibody drug conjugates (ADCs) for solid tumors, this class of drugs is gaining momentum for the targeted treatment of cancer. Despite significant investment, there are still fundamental issues that are incompletely understood. Three of the recently approved ADCs contain payloads exhibiting bystander effects, where the payload can diffuse out of a targeted cell into adjacent cells. These effects are often studied using a mosaic of antigen positive and negative cells. However, the distance these payloads can diffuse in tumor tissue while maintaining a lethal concentration is unclear. Computational studies suggest bystander effects partially compensate for ADC heterogeneity in tumors in addition to targeting antigen negative cells. However, this type of study is challenging to conduct experimentally due to the low concentrations of extremely potent payloads. In this work, we use a series of 3-dimensional cell culture and primary human tumor xenograft studies to directly track fluorescently labeled ADCs and indirectly follow the payload via an established pharmacodynamic marker (γH2A. X). Using TAK-164, an anti-GCC ADC undergoing clinical evaluation, we show that the lipophilic DNA-alkylating payload, DGN549, penetrates beyond the cell targeted layer in GCC-positive tumor spheroids and primary human tumor xenograft models. The penetration distance is similar to model predictions, where the lipophilicity results in moderate tissue penetration, thereby balancing improved tissue penetration with sufficient cellular uptake to avoid significant washout. These results aid in mechanistic understanding of the interplay between antigen heterogeneity, bystander effects, and heterogeneous delivery of ADCs in the tumor microenvironment to design clinically effective therapeutics.

Practical Guide for Quantification of In Vivo Degradation Rates for Therapeutic Proteins with Single-Cell Resolution Using Fluorescence Ratio Imaging.

Many tools for studying the pharmacokinetics of biologics lack single-cell resolution to quantify the heterogeneous tissue distribution and subsequent therapeutic degradation in vivo. This protocol describes a dual-labeling technique using two near-infrared dyes with widely differing residualization rates to efficiently quantify in vivo therapeutic protein distribution and degradation rates at the single cell level (number of proteins/cell) via ex vivo flow cytometry and histology. Examples are shown for four biologics with varying rates of receptor internalization and degradation and a secondary dye pair for use in systems with lower receptor expression. Organ biodistribution, tissue-level confocal microscopy, and cellular-level flow cytometry were used to image the multi-scale distribution of these agents in tumor xenograft mouse models. The single-cell measurements reveal highly heterogeneous delivery, and degradation results show the delay between peak tumor uptake and maximum protein degradation. This approach has broad applicability in tracking the tissue and cellular distribution of protein therapeutics for drug development and dose determination.

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.

Blocking of Glucagonlike Peptide-1 Receptors in the Exocrine Pancreas Improves Specificity for ß-Cells in a Mouse Model of Type 1 Diabetes.

The diabetes community has long desired an imaging agent to quantify the number of insulin-secreting ß-cells, beyond just functional equivalents (insulin secretion), to help diagnose and monitor early stages of both type 1 and type 2 diabetes mellitus. Loss in the number of ß-cells can be masked by a compensatory increase in function of the remaining cells. Since ß-cells form only about 1% of the pancreas and decrease as the disease progresses, only a few imaging agents, such as exendin, have demonstrated clinical potential to detect a drop in the already scarce signal. However, clinical translation of imaging with exendin has been hampered by pancreatic uptake that is higher than expected in subjects with long-term diabetes who lack ß-cells. Exendin binds glucagonlike peptide-1 receptor (GLP-1R), previously thought to be expressed only on ß-cells, but recent studies report low levels of GLP-1R on exocrine cells, complicating ß-cell mass quantification. Methods: Here, we used a GLP-1R knockout mouse model to demonstrate that exocrine binding of exendin is exclusively via GLP-1R (∼1,000/cell) and not any other receptor. We then used lipophilic Cy-7 exendin to selectively preblock exocrine GLP-1R in healthy and streptozotocin-induced diabetic mice. Results: Sufficient receptors remain on ß-cells for subsequent labeling with a fluorescent- or 111In-exendin. Conclusion: Selective GLP-1R blocking, which improves contrast between healthy and diabetic pancreata and provides a potential avenue for achieving the long-standing goal of imaging ß-cell mass in the clinic.

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.

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.

Toward polarizable AMOEBA thermodynamics at fixed charge efficiency using a dual force field approach: application to organic crystals.

First principles prediction of the structure, thermodynamics and solubility of organic molecular crystals, which play a central role in chemical, material, pharmaceutical and engineering sciences, challenges both potential energy functions and sampling methodologies. Here we calculate absolute crystal deposition thermodynamics using a novel dual force field approach whose goal is to maintain the accuracy of advanced multipole force fields (e.g. the polarizable AMOEBA model) while performing more than 95% of the sampling in an inexpensive fixed charge (FC) force field (e.g. OPLS-AA). Absolute crystal sublimation/deposition phase transition free energies were determined using an alchemical path that grows the crystalline state from a vapor reference state based on sampling with the OPLS-AA force field, followed by dual force field thermodynamic corrections to change between FC and AMOEBA resolutions at both end states (we denote the three step path as AMOEBA/FC). Importantly, whereas the phase transition requires on the order of 200 ns of sampling per compound, only 5 ns of sampling was needed for the dual force field thermodynamic corrections to reach a mean statistical uncertainty of 0.05 kcal mol-1. For five organic compounds, the mean unsigned error between direct use of AMOEBA and the AMOEBA/FC dual force field path was only 0.2 kcal mol-1 and not statistically significant. Compared to experimental deposition thermodynamics, the mean unsigned error for AMOEBA/FC (1.4 kcal mol-1) was more than a factor of two smaller than uncorrected OPLS-AA (3.2 kcal mol-1). Overall, the dual force field thermodynamic corrections reduced condensed phase sampling in the expensive force field by a factor of 40, and may prove useful for protein stability or binding thermodynamics in the future.