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Developing next-generation antibody-drug conjugates for breast cancer drug delivery: hurdles and advances in the clinic.

Aug 2026 · Expert Opinion on Drug Delivery · 0 citations · 77 references
Medicine

TL;DR

This review synthesizes literature spanning 1990-2026 on advances in ADC design and their clinical and translational implementation in breast cancer to support reframing antigen selection as a system-level challenge, supported by delivery-focused engineering, precision-medicine-driven trial design, and adaptive methodology.

Abstract

INTRODUCTION Breast cancer remains a leading cause of mortality among women worldwide, with diagnoses projected to reach 3.5 million annually by 2050. Therapeutic progress is hindered by marked molecular heterogeneity and distinct biological and clinical subtypes. Antibody - drug conjugates (ADCs) have emerged as a promising strategy for treatment‑resistant disease, combining targeted delivery with potent cytotoxic payloads. AREAS COVERED This review synthesizes literature spanning 1990-2026 on advances in ADC design and their clinical and translational implementation in breast cancer. Primary research articles were then inputted into Research Rabbit to identify additional original research articles and maximize data retrieval. EXPERT OPINION The success of ADCs is limited less by payload potency than by delivery biology. Efficacy depends on patient context, tumor site - specific factors, and bystander effects in antigen‑heterogeneous environments. However, current development often overlooks systemic antigen sinks, metastatic microenvironments, and evolving resistance. Future progress requires reframing antigen selection as a system‑level challenge, supported by delivery‑focused engineering and adaptive trial design. Traditional ADCs rely on a narrow range of tumor antigens and payloads, restricting therapeutic index and applicability. Future progress requires reframing antigen selection as a system-level challenge, supported by delivery-focused engineering, precision-medicine-driven trial design, and adaptive methodology.

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