Article
Dean Bottino, Rachael Liu, Hojjat Bazzazi, Karthik Venkatakrishnan
Characterizing Exposure–Response Relationship for Therapeutic Monoclonal Antibodies in Immuno-Oncology and Beyond: Challenges, Perspectives, and Prospects
Summary
- Recent data from immuno-oncology clinical studies show that the exposure–response (E–R) relationship for therapeutic monoclonal antibodies (mAbs) is often confounded by various factors.
- The complex interplay involves patient characteristics, disease, drug exposure, clearance, and treatment response, presenting challenges in E–R analysis.
- An integrative framework is proposed to understand the E–R relationship, involving an interconnected triangle of baseline factors, drug exposure, and treatment response.
- This framework identifies three components of the E–R relationship: exposure-driven E–R, baseline-driven E–R, and response-driven E–R.
- Strategies to decouple these components and mitigate confounding effects are reviewed, highlighting their merits and limitations.
- A roadmap for selecting strategies is proposed, including the use of single-dose pharmacokinetic models and multivariable or case control analysis in randomized studies.
- Discussion includes the importance of data from multiple dose levels, the role of prognostic and predictive factors, and the potential utility of baseline clearance and its changes over time.
Analysis of the exposure response (E–R) relationship has long been an important tool for dose selection and optimization and regulatory decisions during all stages of drug development. In general, it is assumed that the E–R relationship is driven by the exposure and, therefore, a positive E–R correlation suggests that a higher exposure at a higher dose would lead to a better response. However, several recent reports from clinical studies with therapeutic monoclonal antibodies (mAbs) in oncology or immuno-oncology field have shown that this is not always true...
Complex E–R relationship, immuno-oncology, single-dose PK model, therapeutic monoclonal antibodies
Related Topics
You May Also Like
Dean Bottino, Rachael Liu, Hojjat Bazzazi, Karthik Venkatakrishnan
Article
Kirill Peskov, Ivan Azarov, Lulu Chu, Veronika Voronova, Yuri Kosinsky, Gabriel Helmlinger
Quantitative Mechanistic Modeling in Support of Pharmacological Therapeutics Development in Immuno-Oncology
Article
Jayson L. Parker, Sebnem S. Kuzulugil, Kirill Pereverzev, Stephen Mac, Gilberto Lopes, Zain Shah, Ashini Weerasinghe, Daniel Rubinger, Adam Falconi, Ayse Bener, Bora Caglayan, Rohan Tangri, Nicholas Mitsakakis
Does biomarker use in oncology improve clinical trial failure risk? A large-scale analysis
Article
Avi Cherla, MSc; Huseyin Naci, MHS, PhD; Aaron S. Kesselheim, MD, JD, MPH; Bishal Gyawali, MD, PhD; Elias Mossialos, MD, PhD
Assessment of Coverage in England of Cancer Drugs Qualifying for US Food and Drug Administration Accelerated Approval
Article
Vanessa Arciero, BS, Seanthel Delos Santos, Liza Koshy
Assessment of Food and Drug Administration- and European Medicines Agency-Approved Systemic Oncology Therapies and Clinically Meaningful Improvements in Quality of Life: A Systematic Review
Article
iNIZIO