The linear pharmacokinetics (PK) of therapeutic monoclonal antibodies (mAbs) can be considered a class property with values that are similar to endogenous IgG. Knowledge of these parameters across species could be used to avoid unnecessary in vivo PK studies and to enable early PK predictions and pharmacokinetic/pharmacodynamic (PK/PD) simulations. In this work, population-pharmacokinetic (popPK) modeling was used to determine a single set of ‘typical’ popPK parameters describing the linear PK of mAbs in human, cynomolgus monkey and transgenic mice expressing the human neonatal Fc receptor (hFcRn Tg32), using a rich dataset of 27 mAbs. Non-linear PK was excluded from the datasets and a 2-compartment model was applied to describe mAb disposition. Typical human popPK estimates compared well with data from comparator mAbs with linear PK in the clinic. Outliers with higher than typical clearance were found to have non-specific interactions in an affinity-capture self-interaction nanoparticle spectroscopy assay, offering a potential tool to screen out these mAbs at an early stage. Translational strategies were investigated for prediction of human linear PK of mAbs, including use of typical human popPK parameters and allometric exponents from cynomolgus monkey and Tg32 mouse. Each method gave good prediction of human PK with parameters predicted within 2-fold. These strategies offer alternative options to the use of cynomolgus monkeys for human PK predictions of linear mAbs, based on in silico methods (typical human popPK parameters) or using a rodent species (Tg32 mouse), and call into question the value of completing extensive in vivo preclinical PK to inform linear mAb PK.

Regorafenib is an oral multikinase inhibitor with clinical efficacy in a range of advanced solid tumours. A population pharmacokinetic (PK) model was developed to evaluate the variability of the PK of regorafenib and its pharmacologically active metabolites M-2 and M-5 in solid tumours. Methods: The model was initially developed using densely sampled phase 1 data and information on food intake to incorporate enterohepatic circulation (EHC) that was identified to considerably contribute to the PK of regorafenib. This was then applied to sparsely sampled data from four phase 3 studies in patients with advanced solid tumours. The need for exact food intake data to estimate individual drug exposure was evaluated. Results: By incorporating EHC, the model adequately described the PK profiles of regorafenib, M-2 and M-5 after single and multiple doses in patients from phase 1 studies. Individual exposure in phase 3 studies was adequately described based on assumptions on the time and frequency of food intake, although exact food intake data are recommended to improve the estimation. Covariate analysis identified sex and body mass index (BMI) as impacting exposure to regorafenib, and sex as strongly impacting exposure to M-2 and M-5 (also influenced by the BMI effect on parent regorafenib in the joint model developed); however, these factors accounted for a small portion of the overall variability in exposure. Conclusions: The adequate description of regorafenib PK after multiple dosing requires the incorporation of EHC. Neither single nor combined covariates predicted exposures that would warrant a priori regorafenib dose adjustment.

Pharmaceutical sciences experts and regulators acknowledge that pharmaceutical development as well as drug usage requires more than scientific advancements to cope with current attrition rates/therapeutic failures. Drug disease modeling and simulation (DDM&S) creates a paradigm to enable an integrated and higher-level understanding of drugs, (diseased)systems, and their interactions (systems pharmacology) through mathematical/statistical models (pharmacometrics)1—hence facilitating decision making during drug development and therapeutic usage of medicines. To identify gaps and challenges in DDM&S, an inventory of skills and competencies currently available in academia, industry, and clinical practice was obtained through survey. The survey outcomes revealed benefits, weaknesses, and hurdles for the implementation of DDM&S. In addition, the survey indicated that no consensus exists about the knowledge, skills, and attributes required to perform DDM&S activities effectively. Hence, a landscape of technical and conceptual requirements for DDM&S was identified and serves as a basis for developing a framework of competencies to guide future education and training in DDM&S.

After considering the baseline risk factors: ECOG performance status, alpha-fetoprotein levels, and hepatic function for OS and age for TTP, the ER analysis in regorafenib-treated patients showed similar efficacy over the entire predicted exposure range in RESORCE. This supports the selected regorafenib dose of 160mg once daily (3weeks on/1week off in a 4-week cycle) in patients with intermediate or advanced HCC who have experienced disease progression on sorafenib.

320 Background: REG is approved for refractory metastatic colorectal cancer (CRC) and gastrointestinal stromal tumors (GIST). In the phase 3 RESORCE trial (N = 573), REG (160 mg QD, 3 weeks on/1 week off) significantly (P < 0.001) improved overall survival (OS) vs placebo in HCC patients who progressed on sorafenib (HR 0.63; 95% CI 0.50‒0.79). We evaluated REG PK in RESORCE using a popPK model and the influence of intrinsic and extrinsic factors (covariates) on REG PK. Methods: The average concentrations of REG and its pharmacologically active metabolites (M-2, M-5) were estimated based on sparse PK sampling in cycles 1–2. A covariate analysis was conducted using exposure and covariate data in 16 clinical REG trials in CRC, GIST, and HCC (1337 subjects) using a graphical and generalized additive modeling (GAM) approach. Results: eGFR, total plasma protein, hematocrit, total bilirubin, AST, ALP, and Asians vs non-Asians did not significantly (p > 0.05) influence exposure, whereas covariates significantly (p < 0.05) influencing exposure in 16 studies including RESORCE were: being a healthy volunteer vs a patient, sex, age, hemoglobin at baseline, plasma albumin at baseline, BMI, and body weight. The identified covariate effects were considered small compared with observed overall variability in exposure. Visual comparison of the exposure estimates in RESORCE showed these were comparable to those in phase 3 studies in CRC and GIST. Exposure in Asians was comparable to that in the rest of the world (ROW) and there was no apparent difference in exposure between Japanese, Chinese, and ROW and between patients with mild/moderate hepatic impairment vs normal hepatic function. Only small numerical differences in exposure across different age categories were observed, with a tendency towards higher exposure in patients ≥ 65 years of age. Conclusions: The RESORCE data confirm previous observations that the identified covariates that significantly (P < 0.05) correlated with exposure only describe a small fraction ( < 10%) of the overall variability in exposure and, thus, are not expected to have a clinically relevant impact on REG exposure. Clinical trial information: NCT01774344.