Multicellular tumor spheroids have been increasingly used by researchers to produce more physiologically relevant experimental environments. However, tracking of spheroid growth and treatment-induced ...volume reduction has not been readily adopted. Here, squamous carcinoma cells were seeded at different starting cell numbers with growth and reduction kinetics monitored using live cell imaging. Following the initial growth phase, spheroids were treated with auristatin as small molecule (MMAE) or as antibody-drug conjugate containing non-cleavable auristatin drug payload (033-F). Compared to cells in monolayers, 033-F had notably weaker potency against spheroids despite potency levels of MMAE being similar against monolayers and spheroids. Accumulation of released payload from 033-F was reduced in higher volume spheroids, likely contributing to the potency differences. Despite lowered potency towards spheroids with 033-F, spheroid volume was still readily reduced by 033-F in a dose-dependent fashion, with >85% volume reductions at the highest concentrations for all spheroid sizes. Additionally, the core of the larger spheroids showed more resiliency towards microtubule inhibition. Overall, this work highlights how various in-vivo 'features' such as tumor penetration, cell interactions, and increased resistance to therapeutics can be integrated into a spheroid model and tracked over time by automated imaging technology.
The stability of antibody–drug conjugates (ADCs) in circulation is critical for maximum efficacy and minimal toxicity. An ADC reaching the intended target intact can deliver the highest possible drug ...load to the tumor and reduce off-target toxicity from free drug in the blood. As such, assessment of ADC stability is a vital piece of data during development. However, traditional ADC stability assays can be manually intensive, low-throughput, and require large quantities of ADC material. Here, we introduce an automated, high-throughput plasma stability assay for screening drug release and aggregation over 144 h for up to 40 ADCs across five matrices simultaneously. The amount of ADC material during early drug development is often limited, so this assay was implemented in 384-well format to minimize material requirements to <100 μg of each ADC and 100 μL of plasma per species type. Drug release and aggregation output were modeled using nonlinear regression equations to calculate formation rates for each data type. A set of 15 ADCs with different antibodies and identical valine–citrulline–p-aminobenzylcarbamate–monomethylauristatin E linker-drug payloads was tested and formation rates were compared across ADCs and between species, revealing several noteworthy trends. In particular, a wide range in aggregation was found when altering only the antibody, suggesting a key role for plasma stability screening early in the development process to find and remove antibody candidates with the potential to create unstable ADCs. The assay presented here can be leveraged to provide stability data on new chemistry and antibody screening initiatives, select the best candidate for in vivo studies, and provide results that highlight stability issues inherent to particular ADC designs throughout all stages of ADC development.
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