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.

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As a key mediator of efficacy and toxicity, the linker connecting the payload in antibody drug conjugates determines cellular distribution and payload release. Sorkin et al. ( 2019) have created novel fluorescence-based linkers to quantify the rate of intracellular bond cleavage and track live-cell kinetics for designing more effective agents.

Antibody-drug conjugates (ADCs) 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 Trop-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. Additionally, 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 (%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 multi-scale delivery can be used to inform the design of next-generation ADCs and prodrugs for other targets.

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.