title: Optimal Dosing for Targeted Therapies in Oncology: Drug Development Cases Leading by Example.
abstract: One of the key objectives of oncology first-in-human trials has often been to establish the maximum tolerated dose (MTD). However, targeted therapies might not exhibit dose-limiting toxicities (DLT) at doses significantly higher than sufficiently active doses, and there is frequently a limited ability to objectively quantify adverse events. Thus, while MTD-based determination of recommended phase II dose may have yielded appropriate dosing for some cytotoxics, targeted therapeutics (including monoclonal antibodies and/or immunotherapies) sometimes need alternative or complementary strategies to help identify dose ranges for a randomized dose-ranging study. One complementary strategy is to define a biologically efficacious dose (BED) using an "effect marker." An effect marker could be a target engagement, pharmacodynamic, or disease progression marker (change in tumor size for solid tumors or bone marrow blast count for some hematologic tumors). Although the concept of BED has been discussed extensively, we review specific examples in which the approach influenced oncology clinical development. Data extracted from the literature and the examples support improving dose selection strategies to benefit patients, providers, and the biopharmaceutical industry. Although the examples illustrate key contributions of effect markers in dose selection, no one-size-fits-all approach to dosing can be justified. Higher-than-optimal dosing can increase toxicity in later trials (and in clinical use), which can have a negative impact on efficacy (via lower adherence or direct sequelae of toxicities). Proper dose selection in oncology should follow a multifactorial decision process leading to a randomized, dose-ranging study instead of a single phase II dose.
authors.affiliation: Department of PPDM-Quantitative Pharmacology and Pharmacometrics, Merck & Co., Inc., Kenilworth, New Jersey.
authors.forename: Jeffrey R
authors.initials: JR
authors.lastname: Sachs
authors.affiliation: Department of PPDM-Quantitative Pharmacology and Pharmacometrics, Merck & Co., Inc., Rahway, New Jersey. kapil.mayawala@merck.com.
authors.forename: Kapil
authors.initials: K
authors.lastname: Mayawala
authors.affiliation: Department of Clinical & Scientific Informatics and EDDS IT, Merck & Co., Inc., Rahway, New Jersey.
authors.forename: Satvik
authors.initials: S
authors.lastname: Gadamsetty
authors.affiliation: Department of Clinical Oncology, Merck & Co., Inc., Rahway, New Jersey.
authors.forename: Soonmo Peter
authors.initials: SP
authors.lastname: Kang
authors.affiliation: Department of PPDM-Quantitative Pharmacology and Pharmacometrics, Merck & Co., Inc., Rahway, New Jersey.
authors.forename: Dinesh P
authors.initials: DP
authors.lastname: de Alwis
mesh_terms: D000818:Animals; D000970:Antineoplastic Agents / Q000008:administration & dosage*; D015415:Biomarkers; D004305:Dose-Response Relationship, Drug; D006801:Humans; D020714:Maximum Tolerated Dose; D058990:Molecular Targeted Therapy; D009369:Neoplasms / Q000188:drug therapy* / Q000378:metabolism; D011379:Prognosis; D016896:Treatment Outcome
chemical_list: D000970:Antineoplastic Agents; D015415:Biomarkers