Design of Crosslinking Antibodies For T-Cell Activation: Experimental and Computational Analysis of PD-1/CD137 Bispecific Agents.

Bispecific and multispecific agents have become increasingly utilized in cancer treatment and immunotherapy, yet their complex design parameters present a challenge in developing successful therapeutics. Bispecifics that crosslink receptors on two opposing cells can provide specific activation of a receptor only when these cells are in close spatial proximity, such as an immune cell and cancer cell in a tumor. These agents, including T cell activating bispecifics, can avoid off-tumor toxicity through activation only in the tumor microenvironment by utilizing a tumor target to cluster T-cell receptors for a selective costimulatory signal. Here, we investigate a panel of PD-1/CD137 targeted Humabody VH domains to determine the key factors for T cell activation, such as affinity, valency, expression level, domain orientation, and epitope location. Target expression is a dominant factor determining both specificity and potency of T cell activation. Given an intrinsic expression level, the affinity can be tuned to modulate the level of activation and IC50 and achieve specificity between low and high expression levels. Changing the epitope location and linker length showed minor improvements to activation at low expression levels, but increasing the valency for the target decreased activation at all expression levels. By combining non-overlapping epitopes for the target, we achieved higher receptor activation at low expression levels. A kinetic model was able to capture these trends, offering support for the mechanistic interpretation. This work provides a framework to quantify factors for T cell activation by cell-crosslinking bispecific agents and guiding principles for the design of new agents.

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.

Optimizing Solid Tumor Treatment with Antibody-drug Conjugates Using Agent-Based Modeling: Considering the Role of a Carrier Dose and Payload Class.

INTRODUCTION: Antibody-drug conjugates (ADCs) show significant clinical efficacy in the treatment of solid tumors, but a major limitation to their success is poor intratumoral distribution. Adding a carrier dose improves both distribution and overall drug efficacy of ADCs, but the optimal carrier dose has not been outlined for different payload classes. OBJECTIVE: In this work, we study two carrier dose regimens: 1) matching payload potency to cellular delivery but potentially not reaching cells farther away from blood vessels, or 2) dosing to tumor saturation but risking a reduction in cell killing from a lower amount of payload delivered per cell. METHODS: We use a validated computational model to test four different payloads conjugated to trastuzumab to determine the optimal carrier dose as a function of target expression, ADC dose, and payload potency. RESULTS: We find that dosing to tumor saturation is more efficacious than matching payload potency to cellular delivery for all payloads because the increase in the number of cells targeted by the ADC outweighs the loss in cell killing on targeted cells. An important exception exists if the carrier dose reduces the payload uptake per cell to the point where all cell killing is lost. Likewise, receptor downregulation can mitigate the benefits of a carrier dose. CONCLUSIONS: Because tumor saturation and in vitro potency can be measured early in ADC design, these results provide insight into maximizing ADC efficacy and demonstrate the benefits of using simulation to guide ADC design.

In vivo Auto-tuning of Antibody-Drug Conjugate Delivery for Effective Immunotherapy using High-Avidity, Low-Affinity Antibodies.

Antibody-drug conjugates (ADCs) have experienced a surge in clinical approvals in the past five years. Despite this success, a major limitation to ADC efficacy in solid tumors is poor tumor penetration, which leaves many cancer cells untargeted. Increasing antibody doses or co-administering ADC with an unconjugated antibody can improve tumor penetration and increase efficacy when target receptor expression is high. However, it can also reduce efficacy in low-expression tumors where ADC delivery is limited by cellular uptake. This creates an intrinsic problem because many patients express different levels of target between tumors and even within the same tumor. Here, we generated High-Avidity, Low-Affinity (HALA) antibodies that can automatically tune the cellular ADC delivery to match the local expression level. Using HER2 ADCs as a model, HALA antibodies were identified with the desired HER2 expression-dependent competitive binding with ADCs in vitro. Multi-scale distribution of trastuzumab emtansine and trastuzumab deruxtecan co-administered with the HALA antibody were analyzed in vivo, revealing that the HALA antibody increased ADC tumor penetration in high-expression systems with minimal reduction in ADC uptake in low-expression tumors. This translated to greater ADC efficacy in immunodeficient mouse models across a range of HER2 expression levels. Furthermore, Fc-enhanced HALA antibodies showed improved Fc-effector function at both high and low expression levels and elicited a strong response in an immunocompetent mouse model. These results demonstrate that HALA antibodies can expand treatment ranges beyond high expression targets and leverage strong immune responses.

Impact of tissue penetration and albumin binding on design of T cell targeted bispecific agents.

Bispecific agents are a rapidly growing class of cancer therapeutics, and immune targeted bispecific agents have the potential to expand functionality well beyond monoclonal antibody agents. Humabodies⁎ are fully human single domain antibodies that can be linked in a modular fashion to form multispecific therapeutics. However, the effect of heterogeneous delivery on the efficacy of crosslinking bispecific agents is currently unclear. In this work, we utilize a PSMA-CD137 Humabody with an albumin binding half-life extension (HLE) domain to determine the impact of tissue penetration on T cell activating bispecific agents. Using heterotypic spheroids, we demonstrate that increased tissue penetration results in higher T cell activation at sub-saturating concentrations. Next, we tested the effect of two different albumin binding moieties on tissue distribution using albumin-specific HLE domains with varying affinities for albumin and a non-specific lipophilic dye. The results show that a specific binding mechanism to albumin does not influence tissue penetration, but a non-specific mechanism reduced both spheroid uptake and distribution in the presence of albumin. These results highlight the potential importance of tissue penetration on bispecific agent efficacy and describe how the design parameters including albumin-binding domains can be selected to maximize the efficacy of bispecific agents.

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.

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.

Generation of DAR1 Antibody-Drug Conjugates for Ultrapotent Payloads Using Tailored GlycoConnect Technology.

GlycoConnect technology can be readily adapted to provide different drug-to-antibody ratios (DARs) and is currently also evaluated in various clinical programs, including ADCT-601 (DAR2), MRG004a (DAR4), and XMT-1660 (DAR6). While antibody-drug conjugates (ADCs) typically feature a DAR2-8, it has become clear that ADCs with ultrapotent payloads (e.g., PBD dimers and calicheamicin) can only be administered to patients at low doses (<0.5 mg/kg), which may compromise effective biodistribution and may be insufficient to reach target receptor saturation in the tumor. Here, we show that GlycoConnect technology can be readily extended to DAR1 ADCs without the need of antibody re-engineering. We demonstrate that various ultrapotent, cytotoxic payloads are amenable to this methodology. In a follow-up experiment, HCC-1954 tumor spheroids were treated with either an AlexaFluor647-labeled DAR1 or DAR2 PBD-based ADC to study the effect on tumor penetration. Significant improvement of tumor spheroid penetration was observed for the DAR1 ADC compared to the DAR2 ADC at an equal payload dose, underlining the potential of a lower DAR for ADCs bearing ultrapotent payloads.

Antibody-Drug Conjugate Sacituzumab Govitecan Drives Efficient Tissue Penetration and Rapid Intracellular Drug Release.

Antibody-drug conjugates (ADC) are a rapidly growing class of targeted cancer treatments, but the field has experienced significant challenges from their complex design. This study examined the multiscale distribution of sacituzumab govitecan (SG; Trodelvy), a recently clinically approved ADC, to clarify the mechanism(s) of efficacy given its unique design strategy. We employed a multiscale quantitative pharmacokinetic approach, including near-infrared fluorescence imaging, single-cell flow cytometry measurements, payload distribution via γH2AX pharmacodynamic staining, and a novel dual-labeled fluorescent technique to track the ADC and payload in a high trophoblast cell-surface antigen 2 expression xenograft model of gastric cancer (NCI-N87). We found that rapid release of the SN-38 payload from the hydrolysable linker inside cells imparts more DNA damage in vitro and in vivo than an ADC with a more stable enzyme cleavable linker. With SG, little to no extracellular payload release in the tumor was observed using a dual-labeled fluorescence technique, although bystander effects were detected. The high dosing regimen allowed the clinical dose to reach the majority of cancer cells, which has been linked to improved efficacy. In addition, the impact of multiple doses (day 1 and day 8) of a 21-day cycle was found to further improve tissue penetration despite not changing tumor uptake [percent injected dose per gram (%ID/g)] of the ADC. These results show increased ADC efficacy with SG can be attributed to efficient tumor penetration and intracellular linker cleavage after ADC internalization. This quantitative approach to study multiscale delivery can be used to inform the design of next-generation ADCs and prodrugs for other targets.

Pharmacokinetics and Pharmacodynamics of TAK-164 Antibody Drug Conjugate Coadministered with Unconjugated Antibody.

The development of new antibody-drug conjugates (ADCs) has led to the approval of 7 ADCs by the FDA in 4 years. Given the impact of intratumoral distribution on efficacy of these therapeutics, coadministration of unconjugated antibody with ADC has been shown to improve distribution and efficacy of several ADCs in high and moderately expressed tumor target systems by increasing tissue penetration. However, the benefit of coadministration in low expression systems is less clear. TAK-164, an ADC composed of an anti-GCC antibody (5F9) conjugated to a DGN549 payload, has demonstrated heterogeneous distribution and bystander killing. Here, we evaluated the impact of 5F9 coadministration on distribution and efficacy of TAK-164 in a primary human tumor xenograft mouse model. Coadministration was found to improve the distribution of TAK-164 within the tumor, but it had no significant impact (increase or decrease) on efficacy. Experimental and computational evidence indicates that this was not a result of tumor saturation, increased binding to perivascular cells, or compensatory bystander effects. Rather, the cellular potency of DGN549 was matched with the single-cell uptake of TAK-164 making its IC50 close to its equilibrium binding affinity (KD), and as such, coadministration dilutes total DGN549 in cells below the maximum cytotoxic concentration, thereby offsetting an increased number of targeted cells with decreased ability to kill each cell. These results provide new insights on matching payload potency to ADC delivery to help identify when increasing tumor penetration is beneficial for improving ADC efficacy and demonstrate how mechanistic simulations can be leveraged to design clinically effective ADCs.

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.

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.

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

After several notable clinical failures in early generations, antibody-drug conjugates (ADC) 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 "nonbystander" 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 11 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 coculture assays were performed to compare with 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 tissue penetration. These results are compared with computational simulations to help scale the data from in vitro and preclinical animal models to the clinic.

Simulating the Selection of Resistant Cells with Bystander Killing and Antibody Coadministration in Heterogeneous Human Epidermal Growth Factor Receptor 2-Positive Tumors.

Intratumoral heterogeneity is a leading cause of treatment failure resulting in tumor recurrence. For the antibody-drug conjugate (ADC) ado-trastuzumab emtansine (T-DM1), two major types of resistance include changes in human epidermal growth factor receptor 2 (HER2) expression and reduced payload sensitivity, which is often exacerbated by heterogenous HER2 expression and ADC distribution during treatment. ADCs with bystander payloads, such as trastuzumab-monomethyl auristatin E (T-MMAE), can reach and kill adjacent cells with lower receptor expression that cannot be targeted directly with the ADC. Additionally, coadministration of T-DM1 with its unconjugated antibody, trastuzumab, can improve distribution and minimize heterogeneous delivery. However, the effectiveness of trastuzumab coadministration and ADC bystander killing in heterogenous tumors in reducing the selection of resistant cells is not well understood. Here, we use an agent-based model to predict outcomes with these different regimens. The simulations demonstrate that both T-DM1 and T-MMAE benefit from trastuzumab coadministration for tumors with high average receptor expression (up to 70% and 40% decrease in average tumor volume, respectively), with greater benefit for nonbystander payloads. However, the benefit decreases as receptor expression is reduced, reversing at low concentrations (up to 360% and 430% increase in average tumor volume for T-DM1 and T-MMAE, respectively) for this mechanism that impacts both ADC distribution and efficacy. For tumors with intrinsic payload resistance, coadministration uniformly exhibits better efficacy than ADC monotherapy (50%-70% and 19%-36% decrease in average tumor volume for T-DM1 and T-MMAE, respectively). Finally, we demonstrate that several regimens select for resistant cells at clinical tolerable doses, which highlights the need to pursue other mechanisms of action for durable treatment responses. SIGNIFICANCE STATEMENT: Experimental evidence demonstrates heterogeneity in the distribution of both the antibody-drug conjugate and the target receptor in the tumor microenvironment, which can promote the selection of resistant cells and lead to recurrence. This study quantifies the impact of increasing the antibody dose and utilizing bystander payloads in heterogeneous tumors. Alternative cell-killing mechanisms are needed to avoid enriching resistant cell populations.

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.

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.

Optoacoustic Imaging of Glucagon-like Peptide-1 Receptor with a Near-Infrared Exendin-4 Analog.

Limitations in current imaging tools have long challenged the imaging of small pancreatic islets in animal models. Here, we report the first development and in vivo validation testing of a broad-spectrum and high-absorbance near-infrared optoacoustic contrast agent, E4x12-Cy7. Our near-infrared tracer is based on the amino acid sequence of exendin-4 and targets the glucagon-like peptide-1 receptor (GLP-1R). Cell assays confirmed that E4x12-Cy7 has a high-binding affinity (dissociation constant, Kd, 4.6 ± 0.8 nM). Using the multispectral optoacoustic tomography, we imaged E4x12-Cy7 and optoacoustically visualized ß-cell insulinoma xenografts in vivo for the first time. In the future, similar optoacoustic tracers that are specific for ß-cells and combines optoacoustic and fluorescence imaging modalities could prove to be important tools for monitoring the pancreas for the progression of diabetes.

Co-administered antibody improves penetration of antibody-dye conjugate into human cancers with implications for antibody-drug conjugates.

Poor tissue penetration remains a major challenge for antibody-based therapeutics of solid tumors, but proper dosing can improve the tissue penetration and thus therapeutic efficacy of these biologics. Due to dose-limiting toxicity of the small molecule payload, antibody-drug conjugates (ADCs) are administered at a much lower dose than their parent antibodies, which further reduces tissue penetration. We conducted an early-phase clinical trial (NCT02415881) and previously reported the safety of an antibody-dye conjugate (panitumumab-IRDye800CW) as primary outcome. Here, we report a retrospective exploratory analysis of the trial to evaluate whether co-administration of an unconjugated antibody could improve the intratumoral distribution of the antibody-dye conjugate in patients. By measuring the multiscale distribution of the antibody-dye conjugate, this study demonstrates improved microscopic antibody distribution without increasing uptake (toxicity) in healthy tissue when co-administered with the parent antibody, supporting further clinical investigation of the co-administration dosing strategy to improve the tumor penetration of ADCs.