Pharmacokinetic and pharmacodynamic considerations for the next generation protein therapeutics

Abstract

Increasingly sophisticated protein engineering efforts have been undertaken lately to generate protein therapeutics with desired properties. This has resulted in the discovery of the next generation of protein therapeutics, which include: engineered antibodies, immunoconjugates, bi/multi-specific proteins, antibody mimetic novel scaffolds, and engineered ligands/receptors. These novel protein therapeutics possess unique physicochemical properties and act via a unique mechanism-of-action, which collectively makes their pharmacokinetics (PK) and pharmacodynamics (PD) different than other established biological molecules. Consequently, in order to support the discovery and development of these next generation molecules, it becomes important to understand the determinants controlling their PK/PD. This review discusses the determinants that a PK/PD scientist should consider during the design and development of next generation protein therapeutics. In addition, the role of systems PK/PD models in enabling rational development of the next generation protein therapeutics is emphasized.

Keywords: ADME; Biologics; Immunogenicity; Novel scaffold; Pharmacodynamic; Pharmacokinetic; Protein therapeutics; Toxicity.

Figure 1. Determinants for SC bioavailability of protein therapeutics

(A) Relationship between half-life of protein therapeutics at the SC site-of-injection and molecular weight (Reprinted with the permission from [26]). (B) Effect of isoelectric point on the SC bioavailability of protein therapeutics in minipig (Reprinted with the permission from [28]). The gray dot represents an outlier. (C) Relationship between the percentages of SC injected dose of protein therapeutics found in the lymph and molecular weight (Reprinted with the permission from [29]).

Figure 2

Relationship between the maximum uptake of protein therapeutics in solid tumor (represented as percentage of injected dose per gram of tumor) and molecular weight (Adapted from [39]).

Figure 3. Systems PK models developed for ADCs

(A) A tumor disposition model developed to characterize and predict the concentrations of ADC and its components in the plasma and solid tumor [44]. (B) A PBPK model developed to characterize and predict the concentrations of ADC and its components throughout the body [45].

Figure 4. Determinants for the elimination of protein therapeutics

(A) Relationship between glomerular sieving coefficient of proteins and their molecule weight (Reprinted with the permission from [47]). (B) Relationship between clearance (terminal slope of the PK profile) of protein therapeutics and their radius (Adapted from [39]). The open symbol represents IgG molecule that employs FcRn mediated salvage pathway. (C) Effect of isoelectric point on the clearance of protein therapeutics in human (Reprinted with the permission from [28]). The gray dot represents an outlier. (D) Relationship between the FcRn affinity (KD) of chosen protein therapeutics and their half-life in the clinic (Adapted from [52]).

Figure 5

Schematic of a platform PBPK model that is envisioned to encompass several animal species and human, and protein therapeutics with a wide range of molecular weight [81].