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

Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice

Quantitative predictive modeling of cancer growth, progression, and individual response to therapy is a rapidly growing field. Researchers from mathematical modeling, systems biology, pharmaceutical industry, and regulatory bodies, are collaboratively working on predictive models that could be applied for drug development and, ultimately, the clinical management of cancer patients. A plethora of modeling paradigms and approaches have emerged, making it challenging to compile a comprehensive review across all subdisciplines. It is therefore critical to gauge fundamental design aspects against requirements, and weigh opportunities and limitations of the different model types. In this review, we discuss three fundamental types of cancer models: space-structured models, ecological models, and immune system focused models. For each type, it is our goal to illustrate which mechanisms contribute to variability and heterogeneity in cancer growth and response, so that the appropriate architecture and complexity of a new model becomes clearer. We present the main features addressed by each of the three exemplary modeling types through a subjective collection of literature and illustrative exercises to facilitate inspiration and exchange, with a focus on providing a didactic rather than exhaustive overview. We close by imagining a future multi-scale model design to impact critical decisions in oncology drug development.

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.

Design and Evaluation of ZD06519, a Novel Camptothecin Payload for Antibody Drug Conjugates

In recent years, the field of antibody drug conjugates (ADC) has seen a resurgence, largely driven by the clinical benefit observed in patients treated with ADCs incorporating camptothecin-based topoisomerase I inhibitor payloads. Herein, we present the development of a novel camptothecin ZD06519 (FD1), which has been specifically designed for its application as an ADC payload. A panel of camptothecin analogs with different substituents at the C-7 and C-10 positions of the camptothecin core was prepared and tested in vitro. Selected compounds spanning a range of potency and hydrophilicity were elaborated into drug-linkers, conjugated to trastuzumab, and evaluated in vitro and in vivo. ZD06519 was selected on the basis of its favorable properties as a free molecule and as an antibody conjugate, which include moderate free payload potency (∼1 nmol/L), low hydrophobicity, strong bystander activity, robust plasma stability, and high-monomeric ADC content. When conjugated to different antibodies using a clinically validated MC-GGFG-based linker, ZD06519 demonstrated impressive efficacy in multiple cell line-derived xenograft models and noteworthy tolerability in healthy mice, rats, and non-human primates.

[64Cu]Cu-PEG-FUD peptide for noninvasive and sensitive detection of murine pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease resulting in irreversible scarring within the lungs. However, the lack of biomarkers that enable real-time assessment of disease activity remains a challenge in providing efficient clinical decision-making and optimal patient care in IPF. Fibronectin (FN) is highly expressed in fibroblastic foci of the IPF lung where active extracellular matrix (ECM) deposition occurs. Functional upstream domain (FUD) tightly binds the N-terminal 70-kilodalton domain of FN that is crucial for FN assembly. In this study, we first demonstrate the capacity of PEGylated FUD (PEG-FUD) to target FN deposition in human IPF tissue ex vivo. We subsequently radiolabeled PEG-FUD with 64Cu and monitored its spatiotemporal biodistribution via μPET/CT imaging in mice using the bleomycin-induced model of pulmonary injury and fibrosis. We demonstrated [64Cu]Cu-PEG-FUD uptake 3 and 11 days following bleomycin treatment, suggesting that radiolabeled PEG-FUD holds promise as an imaging probe in aiding the assessment of fibrotic lung disease activity.

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.

Validity conditions of approximations for a target-mediated drug disposition model: A novel first-order approximation and its comparison to other approximations

Target-mediated drug disposition (TMDD) is a phenomenon characterized by a drug's high-affinity binding to a target molecule, which significantly influences its pharmacokinetic profile within an organism. The comprehensive TMDD model delineates this interaction, yet it may become overly complex and computationally demanding in the absence of specific concentration data for the target or its complexes. Consequently, simplified TMDD models employing quasi-steady state approximations (QSSAs) have been introduced; however, the precise conditions under which these models yield accurate results require further elucidation. Here, we establish the validity of three simplified TMDD models: the Michaelis-Menten model reduced with the standard QSSA (mTMDD), the QSS model reduced with the total QSSA (qTMDD), and a first-order approximation of the total QSSA (pTMDD). Specifically, we find that mTMDD is applicable only when initial drug concentrations substantially exceed total target concentrations, while qTMDD can be used for all drug concentrations. Notably, pTMDD offers a simpler and faster alternative to qTMDD, with broader applicability than mTMDD. These findings are confirmed with antibody-drug conjugate real-world data. Our findings provide a framework for selecting appropriate simplified TMDD models while ensuring accuracy, potentially enhancing drug development and facilitating safer, more personalized treatments.

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.

Spatiotemporal Quantification of HER2-targeting Antibody-Drug Conjugate Bystander Activity and Enhancement of Solid Tumor Penetration

PURPOSE

Antibody-drug conjugate (ADC) has had a transformative effect on the treatment of many solid tumors, yet it remains unclear how ADCs exert bystander activity in the tumor microenvironment.

EXPERIMENTAL DESIGN

Here, we directly visualized and spatiotemporally quantified the intratumor biodistribution and pharmacokinetics of different ADC components by developing dual-labeled fluorescent probes.

RESULTS

Mechanistically, we found that tumor penetration of ADCs is distinctly affected by their ability to breach the binding site barrier (BSB) in perivascular regions of tumor vasculature, and bystander activity of ADC can only partially breach BSB. Furthermore, bystander activity of ADCs can work in synergy with coadministration of their parental antibodies, leading to fully bypassing BSBs and enhancing tumor penetration via a two-step process.

CONCLUSIONS

These promising preclinical data allowed us to initiate a phase I/II clinical study of coadministration of RC48 and trastuzumab in patients with malignant stomach cancer to further evaluate this treatment strategy in humans.

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.

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.

Targeting Trop-2 in cancer: Recent research progress and clinical application

The development of new antitumor drugs depends mainly upon targeting tumor cells precisely. Trophoblast surface antigen 2 (Trop-2) is a type I transmembrane glycoprotein involved in Ca2+ signaling in tumor cells. It is highly expressed in various tumor tissues than in normal tissues and represents a novel and promising molecular target for caner targeted therapy. Up to now, the mechanisms and functions associated with Trop-2 have been extensively studied in a variety of solid tumors. According to these findings, Trop-2 plays an important role in cell proliferation, apoptosis, cell adhesion, epithelial-mesenchymal transition, as well as tumorigenesis and tumor progression. In addition, Trop-2 related drugs are also being developed widely. There are a number of Trop-2 related ADC drugs that have demonstrated potent antitumor activity and are currently been studied, such as Sacituzumab Govitecan (SG) and Datopotamab Deruxtecan (Dato-Dxd). In this study, we reviewed the progress of Trop-2 research in solid tumors. We also sorted out the composition and rationale of Trop-2 related drugs and summarized the related clinical trials. Finally, we discussed the current status of Trop-2 research and expanded our perspectives on its future research directions. Importantly, we found that Trop-2 targeted ADCs have great potential for combination with other antitumor therapies. Trop-2 targeted ADCs can reprogramme tumor microenvironment through multiple signaling pathways, ultimately activating antitumor immunity.

BT8009; A Nectin-4 Targeting Bicycle Toxin Conjugate for Treatment of Solid Tumors

Multiple tumor types overexpress Nectin-4 and the antibody-drug conjugate (ADC), enfortumab vedotin (EV) shows striking efficacy in clinical trials for metastatic urothelial cancer, which expresses high levels of Nectin-4, validating Nectin-4 as a clinical target for toxin delivery in this indication. Despite excellent data in urothelial cancer, little efficacy data are reported for EV in other Nectin-4 expressing tumors and EV therapy can produce significant toxicities in many patients, frequently leading to discontinuation of treatment. Thus, additional approaches to this target with the potential to extend utility and reduce toxicity are warranted. We describe the preclinical development of BT8009, a "Bicycle Toxin Conjugate" (BTC) consisting of a Nectin-4-binding bicyclic peptide, a cleavable linker system and the cell penetrant toxin mono-methylauristatin E (MMAE). BT8009 shows significant antitumor activity in preclinical tumor models, across a variety of cancer indications and is well tolerated in preclinical safety studies. In several models, it shows superior or equivalent antitumor activity to an EV analog. As a small hydrophilic peptide-based drug BT8009 rapidly diffuses from the systemic circulation, through tissues to penetrate the tumor and target tumor cells. It is renally eliminated from the circulation, with a half-life of 1-2 hours in rat and non-human primate. These physical and PK characteristics differentiate BT8009 from ADCs and may provide benefit in terms of tumor penetration and reduced systemic exposure. BT8009 is currently in a Phase 1/2 multicenter clinical trial across the US, Canada, and Europe, enrolling patients with advanced solid tumors associated with Nectin-4 expression.

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.

Pathophysiological and pharmacological considerations to improve the design and application of antibody-drug conjugates

Antibody-drug conjugates (ADC) have emerged as one of the pillars of clinical disease management in oncology. The biggest hurdle to widespread development and application of ADCs has been a narrow therapeutic index. Advances in antibody technologies and formats as well as novel linker and payload chemistries have begun to facilitate structural improvements to ADCs. However, the interplay of structural characteristics with physiologic and pharmacologic factors determining therapeutic success has garnered less attention. This review elaborates on the pharmacology of ADCs, the pathophysiology of cancerous tissues, and the reciprocal consequences on ADC properties and functions. While most currently approved ADCs utilize either microtubule inhibition or DNA damage as primary mechanisms of action, we present arguments to expand this repertoire and highlight the need for payload mechanisms that exploit disease-specific vulnerabilities. We promote the idea that the choice of antibody format, targeting antigen, linker properties, and payload of an ADC should be deliberately fit for purpose by taking the pathophysiology of disease and the specific pharmacology of the drug entity into account, thus allowing a higher probability of clinical success.

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.

Antibody-Drug Conjugate Targets, Drugs and Linkers

Antibody-drug conjugates offer the possibility of directing powerful cytotoxic agents to a malignant tumor while sparing normal tissue. The challenge is to select an antibody target expressed exclusively or at highly elevated levels on the surface of tumor cells and either not all or at low levels on normal cells. The current review explores 78 targets that have been explored as antibody-drug conjugate targets. Some of these targets have been abandoned, 9 or more are the targets of FDA-approved drugs, and most remain active clinical interest. Antibody-drug conjugates require potent cytotoxic drug payloads, several of these small molecules are discussed, as are the linkers between the protein component and small molecule components of the conjugates. Finally, conclusions regarding the elements for the successful antibody-drug conjugate are discussed.

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.

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.

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 C_max 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.

Transient Competitive Inhibition Bypasses the Binding Site Barrier to Improve Tumor Penetration of Trastuzumab and Enhance T-DM1 Efficacy

Poor penetration of mAbs in solid tumors is explained, in part, by the binding site barrier hypothesis. Following extravasation, mAbs rapidly bind cellular antigens, leading to the observation that, at subsaturating doses, therapeutic antibody in solid tumors localizes around tumor vasculature. Here we report a unique strategy to overcome the binding site barrier through transient competitive inhibition of antibody-antigen binding. The anti-trastuzumab single domain antibody 1HE was identified through in vitro binding assays as a model inhibitor. Coadministration of 1HE did not alter the plasma pharmacokinetics of trastuzumab or ado-trastuzumab emtansine (T-DM1) in vivo. Administration of 1HE alone was rapidly eliminated with a terminal plasma half-life of 1.2 hours, while coadministrations of 1HE with trastuzumab had a terminal half-life of 56 hours. In mice harboring SKOV3 xenografts, coadministration of 1HE with trastuzumab led to significant increases in both penetration of trastuzumab from vasculature and the percentage of tumor area that stained positive for trastuzumab. 1HE coadministered with a single dose of T-DM1 to NCI-N87 xenograft-bearing mice significantly enhanced T-DM1 efficacy, increasing median survival. These results support the hypothesis that transient competitive inhibition can improve therapeutic antibody distribution in solid tumors and enhance antibody efficacy. SIGNIFICANCE: This study describes the development of a transient competitive inhibition strategy that enhances the tumor penetration and efficacy of anticancer antibodies.See related commentary by van Dongen, p. 3956.

Targeting cancer with antibody-drug conjugates: Promises and challenges

Antibody-drug conjugates (ADCs) are a rapidly expanding class of biotherapeutics that utilize antibodies to selectively deliver cytotoxic drugs to the tumor site. As of May 2021, the U.S. Food and Drug Administration (FDA) has approved ten ADCs, namely Adcetris®, Kadcyla®, Besponsa®, Mylotarg®, Polivy®, Padcev®, Enhertu®, Trodelvy®, Blenrep®, and Zynlonta™ as monotherapy or combinational therapy for breast cancer, urothelial cancer, myeloma, acute leukemia, and lymphoma. In addition, over 80 investigational ADCs are currently being evaluated in approximately 150 active clinical trials. Despite the growing interest in ADCs, challenges remain to expand their therapeutic index (with greater efficacy and less toxicity). Recent advances in the manufacturing technology for the antibody, payload, and linker combined with new bioconjugation platforms and state-of-the-art analytical techniques are helping to shape the future development of ADCs. This review highlights the current status of marketed ADCs and those under clinical investigation with a focus on translational strategies to improve product quality, safety, and efficacy.