Challenges and Opportunities for Quantitative Clinical Pharmacology in Cancer Immunotherapy: Something Old, Something New, Something Borrowed, and Something Blue

Abstract

Cancer immunotherapy (CIT) initiates or enhances the host immune response against cancer. Following decades of development, patients with previously few therapeutic options may now benefit from CIT. Although the quantitative clinical pharmacology (qCP) of previous classes of anticancer drugs has matured during this time, application to CIT may not be straightforward since CIT acts via the immune system. Here we discuss where qCP approaches might best borrow or start anew for CIT.

Tutorial on Monoclonal Antibody Pharmacokinetics and Its Considerations in Early Development

“…demonstrated the same key concept of a PK‐based strategy to select nonclinical doses/regimen in mice for approved drugs. By identifying “clinically relevant dose” instead of “maximally tolerated dose,” this approach can maximize the translatability of efficacy results, which is particularly relevant in selecting candidates for combination with approved therapeutics . Alternatively, a translatable mechanistic PK/PD model can be set up as a more advanced method if the mode of action is known.…”

“…Frequently, the recommended phase II dose (RP2D) is determined in the absence of a maximum tolerated dose (MTD) for mAbs. In these cases, clinical PK data and projected efficacious dose based on preclinical studies were the main criteria for choosing an RP2D . The ability of PK/PD modeling to predict the correct dose and dosing regimen takes on additional urgency for novel checkpoint inhibitors in cancer immunotherapy since the majority of these therapeutics exhibit heterogeneous tumor responses and lack predictive biomarkers .…”

Immunotherapy and Novel Combinations in Oncology: Current Landscape, Challenges, and Opportunities

“…However, animal models for cancer immunotherapy present very unique challenges. Not only is there a time delay in tumor response, but the interaction between the tumor and mouse immune system is uniquely complex due to the involvement of multiple cell types across different tissue compartments . For combination therapy, a synergistic effect of the combination further increases the complexity of the correlation between drug exposure and antitumor response.…”

“…In early development, exposure–response analyses typically involve the assessment of tumor growth inhibition, with specific guidelines for assessment outlined in the Response Evaluation Criteria in Solid Tumors (RECIST) and the Immune‐Related Response Criteria (irRC) . The predictive value of tumor assessments with respect to overall survival has been established for traditional cytotoxic drugs, and data from the development of nivolumab and ipilimumab suggest that there is also a relationship between tumor size assessments in early development and overall survival for immunotherapies . It may also be of value to assess other biomarkers of response that leverage the effects of immunotherapies on the immune system, such as cytokine elevation and markers of T‐cell activation.…”

Quantitative Systems Pharmacology: An Exemplar Model‐Building Workflow With Applications in Cardiovascular, Metabolic, and Oncology Drug Development

“…The rise of immunotherapies supported by regulatory approvals of cytotoxic T‐lymphocyte‐associated protein 4 (CTLA‐4), programmed cell death protein 1 (PD‐1), programmed death‐ligand 1 (PD‐L1) immune checkpoint inhibitors has brought forward additional mechanistic challenges, with the need to consider multiple immune biology events at molecular and cellular levels dynamically interacting, directly or indirectly, with tumor biology and growth, in multiple bodily compartments, including tumor tissue, and with a plethora of “druggable” immune biology targets that may result in antitumor effects . These challenges, reflective of a highly dynamic, multicompartment, multiscale, multiplayer environment make immuno‐oncology an attractive “target” for QSP modeling and its applications . A systems approach is needed to address the ever‐present questions on dose, scheduling, and sequencing (for combinations), now linked to the challenges of predicting antitumor responses through both indirect (immune mediated) and direct (targeted and Standard of care (SoC)) tumor cell kill, while searching for drug combinations that may overcome intrinsic or acquired resistance to existing treatments …”