PK/PD Mediated Dose Optimization of Emactuzumab, a CSF1R Inhibitor, in Patients With Advanced Solid Tumors and Diffuse‐Type Tenosynovial Giant Cell Tumor. Issue 3 (24th July 2020)

• Record Type: Journal Article
• Authors: Smart, Kevin; Bröske, Ann‐Marie; Rüttinger, Dominik; Mueller, Claudia; Phipps, Alex; Walz, Antje‐Christine; Ries, Carola; Baehner, Monika; Cannarile, Michael; Meneses‐Lorente, Georgina
• Is Part Of: Clinical pharmacology & therapeutics. Volume 108:Issue 3(2020)
• Page Start: 616
• Page End: 624
• Publication Date: 2020-07-24
• Subjects: Pharmacology -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1002/cpt.1964
• Languages: English
• ISSNs: 0009-9236

Abstract

Abstract : Targeted biological therapies may achieve maximal therapeutic efficacy at doses below the maximum tolerated dose (MTD); therefore, the search for the MTD in clinical studies may not be ideal for these agents. Emactuzumab is an investigational monoclonal antibody that binds to and inhibits the activation of the cell surface colony‐stimulating factor‐1 receptor. Here, we show how modeling target‐mediated drug disposition coupled with pharmacodynamic end points was used to optimize the dose of emactuzumab without defining an MTD. The model could be used to recommend doses across different disease indications. The approach recommended an optimal biological dose of emactuzumab for dosing every 2 weeks (q2w) ≥ 900 mg, approximately three‐fold lower than the highest dose tested clinically. The model predicted that emactuzumab doses ≥ 900 mg q2w would achieve target saturation in excess of 90% over the entire dosing cycle. Subsequently, a dose of 1, 000 mg q2w was used in the extension phase of a phase I study of emactuzumab in patients with advanced solid tumors or diffuse‐type tenosynovial giant cell tumor. Clinical data from this study were consistent with model predictions. The model was also used to predict the optimum dose of emactuzumab for use with dosing every 3 weeks, enabling dosing flexibility with respect to comedications. In summary, this work demonstrates the value of quantitative clinical pharmacology approaches to dose selection in oncology as opposed to traditional MTD methods.