Model‐Informed Therapeutic Dose Optimization Strategies for Antibody–Drug Conjugates in Oncology: What Can We Learn From US Food and Drug Administration–Approved Antibody–Drug Conjugates?. Issue 5 (8th July 2021)

• Record Type: Journal Article
• Authors: Liao, Michael Z.; Lu, Dan; Kågedal, Matts; Miles, Dale; Samineni, Divya; Liu, Stephanie N.; Li, Chunze
• Is Part Of: Clinical pharmacology & therapeutics. Volume 110:Issue 5(2021)
• Page Start: 1216
• Page End: 1230
• Publication Date: 2021-07-08
• Subjects: Pharmacology -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1002/cpt.2278
• Languages: English
• ISSNs: 0009-9236

Abstract

Abstract : Antibody–drug conjugates (ADCs) combine the specificity of an antibody with the cytotoxicity of a chemical agent. They represent a rapidly evolving area of oncology drug development and hold significant promise. There are currently nine ADCs on the market, more than half of which gained US Food and Drug Administration approval more recently, since 2019. Despite their enormous promise, the therapeutic window for these ADCs remains relatively narrow, especially when compared with other oncology drugs, such as targeted therapies or checkpoint inhibitors. In this review, we provide a detailed overview of the five dosing regimen optimization strategies that have been leveraged to broaden the therapeutic window by mitigating the safety risks while maintaining efficacy. These include body weight cap dosing; treatment duration capping; dose schedule (e.g., dosing frequency and dose fractionation); response‐guided dosing recommendations; and randomized dose‐finding. We then discuss how the lessons learned from these studies can inform ADC development going forward. Informed application of these dosing strategies should allow researchers to maximize the safety and efficacy for next‐generation ADCs.