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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?
Author(s) -
Liao Michael Z.,
Lu Dan,
Kågedal Matts,
Miles Dale,
Samineni Divya,
Liu Stephanie N.,
Li Chunze
Publication year - 2021
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1002/cpt.2278
Subject(s) - dosing , medicine , drug , pharmacology , drug development , food and drug administration , pharmacokinetics , intensive care medicine , oncology
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.