Modeling the Pharmacokinetics of a Monoclonal Antibody on Preclinical Data using Non-linear Mixed Effects

According to the World Health Organization, Hepatitis B is a viral infection that attacks the liver and can cause both acute and chronic disease and thus putting people at high risk of death from cirrhosis and liver cancer. Hepatitis B is a major global health problem, since millions of people get infected every year in different parts of the world, particularly in the Western Pacific Region and African Region. It’s only in recent times that even Monoclonal Antibodies (mAbs) entered in the list of therapeutic molecules developed to fight Hepatitis B Virus (HBV) infection, thanks to their therapeutic properties and advantages such as high specificity, long half-life, high potency and limited off target toxicity. Modeling the Pharmacokinetics (PK) of a drug is fundamental in order to explore and understand ”what the body does to the drug”; in particular, in the case of monoclonal antibodies, many aspects of their PK are still poorly understood and using mathematical modeling in the development process can help to manage critical aspects as the high inter-subject variability and low tissue distribution. The aim of this work was to develop a Non-Linear Mixed Effects model to characterize the pharmacokinetics of a monoclonal antibody engineered to fight the Hepatitis B virus. Data come from the preclinical phase, in which the drug was administered to different groups of cynomolgus monkeys in four different studies. The drug was administered either through the Intravenous (IV) and Subcutaneous (SC) routes, as occurs in most preclinical studies involving monoclonal antibodies. Different models describing the mAb pharmacokinetics were developed, starting from the simplest one as the one compartment model with linear elimination, to the Target Mediated Drug Disposition models, which are typically used to describe the monoclonal antibodies pharmacokinetics. In the end, a population model able to describe the mAb pharmacokinetics and the inter-subject variability on preclinical data was developed. PK parameters estimated from the model were used to obtain an estimate of key PK parameters of drug kinetics on humans through allometric scaling techniques; finally, these parameters were used to assess the First-in-Human starting dose. Model development and statistical analysis were performed with R and Monolix. Future developments of this work include to assess in humans the PK parameters obtained from the allometric scaling and the predicted exposure of the estimated First-in-Human dose and to refine the model in order to describe the monoclonal antibody PK after the repeated dose.