Improved Physical Stability of an Antibody-Drug Conjugate Using Host-Guest Chemistry.

Antibody-drug conjugates (ADCs) are an emerging class of biopharmaceutical products for oncology, with the cytotoxic pyrrolobenzodiazepine (PBD) family of "warheads" well-established in the clinic. While PBDs offer high potency, they are also characterized by their hydrophobicity, which can make formulation of the ADC challenging. Several approaches have been investigated to improve the physicochemical properties of PBD-containing ADCs, and herein a supramolecular approach was explored using cucurbit[8]uril (CB[8]). The ability of CB[8] to simultaneously encapsulate two guests was exploited to incorporate a 12-mer polyethylene glycol harboring a methyl viologen moiety at one terminus (MV-PEG12), together with a PBD harboring an indole moiety at the C2' position (SG3811). This formulation approach successfully introduced a hydrophilic PEG to mask the hydrophobicity of SG3811, improving the physical stability of the ADC while avoiding any loss of potency related to chemical modification.

Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis.

Autoassociative neural networks (ANNs) have been proposed as a nonlinear extension of principal component analysis (PCA), which is commonly used to identify linear variation patterns in high-dimensional data. While principal component scores represent uncorrelated features, standard backpropagation methods for training ANNs provide no guarantee of producing distinct features, which is important for interpretability and for discovering the nature of the variation patterns in the data. Here, we present an alternating nonlinear PCA method, which encourages learning of distinct features in ANNs. A new measure motivated by the condition of orthogonal loadings in PCA is proposed for measuring the extent to which the nonlinear principal components represent distinct variation patterns. We demonstrate the effectiveness of our method using a simulated point cloud data set as well as a subset of the MNIST handwritten digits data. The results show that standard ANNs consistently mix the true variation sources in the low-dimensional representation learned by the model, whereas our alternating method produces solutions where the patterns are better separated in the low-dimensional space.

Fractionated Dosing Improves Preclinical Therapeutic Index of Pyrrolobenzodiazepine-Containing Antibody Drug Conjugates.

Purpose: To use preclinical models to identify a dosing schedule that improves tolerability of highly potent pyrrolobenzodiazepine dimers (PBDs) antibody drug conjugates (ADCs) without compromising antitumor activity.Experimental Design: A series of dose-fractionation studies were conducted to investigate the pharmacokinetic drivers of safety and efficacy of PBD ADCs in animal models. The exposure-activity relationship was investigated in mouse xenograft models of human prostate cancer, breast cancer, and gastric cancer by comparing antitumor activity after single and fractionated dosing with tumor-targeting ADCs conjugated to SG3249, a potent PBD dimer. The exposure-tolerability relationship was similarly investigated in rat and monkey toxicology studies by comparing tolerability, as assessed by survival, body weight, and organ-specific toxicities, after single and fractionated dosing with ADCs conjugated to SG3249 (rats) or SG3400, a structurally related PBD (monkeys).Results: Observations of similar antitumor activity in mice treated with single or fractionated dosing suggests that antitumor activity of PBD ADCs is more closely related to total exposure (AUC) than peak drug concentrations (Cmax). In contrast, improved survival and reduced toxicity in rats and monkeys treated with a fractionated dosing schedule suggests that tolerability of PBD ADCs is more closely associated with Cmax than AUC.Conclusions: We provide the first evidence that fractionated dosing can improve preclinical tolerability of at least some PBD ADCs without compromising efficacy. These findings suggest that preclinical exploration of dosing schedule could be an important clinical strategy to improve the therapeutic window of highly potent ADCs and should be investigated further. Clin Cancer Res; 23(19); 5858-68. ©2017 AACR.