Biologics are the fastest growing area in the pharmaceutical industry, particularly in cancer therapy because they bind tumor specific antigens with limited off-target effects. Antibody Drug Conjugates (ADC's) are one of the newest classes of biologics to be approved by the FDA for solid tumors. Development of these agents is exceedingly complex given the inter-related pharmacokinetics and pharmacodynamics of the biologic and small molecule. Optimizing the dose and the drug antibody ratio (DAR) to achieve a therapeutic microdistribution within the tumor while maintaining safe systemic concentrations are important determinants of ADC efficacy. Here we have developed experimental and computational tools for understanding ADC distribution across several length scales.
In this study, we developed a dual near infrared fluorescent dye labeling technique to follow biologics at high temporal resolution from whole animal to organ, tissue, cellular, and subcellular spatial resolution to understand metabolism and distribution of ADC's. For proof-of-principle, we quantified the metabolism of two antibodies, cetuximab and anti-A33, and one protein, EGF, in vitro and in vivo using a non-residualizing fluorophore to track intact protein and a residualizing fluorophore to measure cumulative uptake (Figure 1A and 1B). Fluorescent microscopy images qualitatively show tumor distribution, heterogeneity, and variability at the cellular, tissue, and organ scales (Figure 1C), while biodistribution studies quantitatively show cumulative uptake into different organs. Quantitative localization in tumors showed high %ID/g (percent injected dose per gram) for both antibodies as expected from their slow clearance. High renal uptake and metabolism was seen for EGF due to rapid filtration in the kidneys. Histological examination of the tumors showed heterogeneous distribution at low doses with increasing penetration distance and homogeneous distribution as dose increased.
Supplementing the experimental work, a computational model incorporating tumor distribution (reaction-diffusion partial differential equations) into a whole animal physiologically based pharmacokinetic (PBPK ordinary differential equation) model allowed for the simultaneous simulation of tissue and systemic distribution. The ability to track biomolecules across these spatial resolutions in vitro, in vivo, and in silico will both aid in understanding the multi-scale distribution of novel therapeutics and facilitate the development of predictive computer models for understanding therapeutic antibody distribution. In particular, these techniques are being applied to improve the distribution of the clinically relevant antibody-drug conjugate (ADC) Kadcyla, where the local heterogeneity can be quantified at the cellular level to determine the impact of tumoral distribution on efficacy.
In conclusion, a technique for simultaneously imaging residualizing and non-residualizing near-infrared fluorescently labeled biologics was developed to track the distribution and metabolism of biologics from the whole animal to tissue and cellular resolution. These data were paired with a predictive reaction-diffusion equation model to understand the impact of dose, local metabolism, and expression on tumoral distribution. This approach can be used to follow antibodies and other protein therapeutics in vivo to understand the interplay between the pharmacokinetics and pharmacodynamics of this class of agents.
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