Significant progress has been made in understanding pharmacokinetics (PK), pharmacodynamics (PD), as well as toxicity profiles of therapeutic proteins in animals and humans, which have been in commercial development for more than three decades. However, in the PK arena, many fundamental questions remain to be resolved. Investigative and bioanalytical tools need to be established to improve the translation of PK data from animals to humans, and from in vitro assays to in vivo readouts, which would ultimately lead to a higher success rate in drug development. In toxicology, it is known, in general, what studies are needed to safely develop therapeutic proteins, and what studies do not provide relevant information. One of the major complicating factors in nonclinical and clinical programs for therapeutic proteins is the impact of immunogenicity. In this review, we will highlight the emerging science and technology, as well as the challenges around the pharmacokinetic- and safety-related issues in drug development of mAbs and other therapeutic proteins.

Recent data from immuno-oncology clinical studies have shown the exposure-response (E-R) relationship for therapeutic monoclonal antibodies (mAbs) was often confounded by various factors due to the complex interplay of patient characteristics, disease, drug exposure, clearance, and treatment response and presented challenges in characterization and interpretation of E-R analysis. To tackle the challenges, exposure relationships for therapeutic mAbs in immuno-oncology and oncology are reviewed, and a general framework for an integrative understanding of E-R relationship is proposed. In this framework, baseline factors, drug exposure, and treatment response are envisioned to form an interconnected triangle, driving the E-R relationship and underlying three components that compose the apparent relationship: exposure-driven E-R, baseline-driven E-R, and response-driven E-R. Various strategies in data analysis and study design to decouple those components and mitigate the confounding effect are reviewed for their merits and limitations, and a potential roadmap for selection of these strategies is proposed. Specifically, exposure metrics based on a single-dose pharmacokinetic model can be used to mitigate responsedriven E-R, while multivariable analysis and/or case control analysis of data obtained from multiple dose levels in a randomized study may be used to account for the baseline-driven E-R. In this context, the importance of collecting data from multiple dose levels, the role of prognostic factors and predictive factors, the potential utility of clearance at baseline and its change over time, and future directions are discussed.

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We obtained mice deficient for major histocompatibility complex (