Prediction of in vivo performance of oral extended release formulations prior to clinical evaluation: A case study for enteric coated polymeric beads formulation.

To reduce cost and time for product development, an ideal strategy for the development of oral extended release (ER) product is to identify the desired formulation with minimum needsfor clinical evaluation. The aim of this work was to demonstrate the feasibility of adopting a "prediction-then-validation" strategy for the development of oral ER formulations. Instead of the traditional approach using multiple ER formulations for IVIVC development, an enteric-coated fast release formulation was successfully utilized for the development of a biopredictive tool to estimate the drug release from enteric coated polymeric ER formulations in the intestine. A TS1 (time scale factor between Tvitro and Tvivo equals to 1) system was designed and developed, based on which the in vivo pharmacokinetic (PK) performance of ER formulations in dog and in human were well predicted prior to in vivo evaluations. The model further passed a posteriori validation using the criteria for level A IVIVC and, as designed, provided a Tscale value of 1 for the IVIVC model.

A pre-clinical quantitative model predicts the pharmacokinetics/pharmacodynamics of an anti-BDCA2 monoclonal antibody in humans.

BIIB059 is a novel humanized monoclonal antibody (mAb) that is currently under development for the treatment of Systemic Lupus Erythematosus and Cutaneous Lupus Erythematosus. BIIB059 is targeted against the blood dendritic cell antigen 2 (BDCA2), a receptor exclusively expressed on the surface of plasmacytoid dendritic cells (pDCs). Herein, we utilized pre-clinical pharmacokinetic (PK) and pharmacodynamic (PD) data to develop a non-human primate (NHP) model and to address whether the NHP model can be successfully scaled to predict the human PK/PD. In particular, PK data from 17 cynomolgus monkeys were utilized for PK model development, wherein BIIB059 was administered intravenously (1 and 10 mg/kg single-dosing and 5 mg/kg multiple-dosing) or subcutaneously (0.2 and 7.5 mg/kg single-dosing). Additionally, PD data (BDCA2 receptor density on pDCs) from 6 cynomolgus monkeys were used for the development of the PD model. The developed NHP two-compartment PK model, linked with an indirect response PD model, was subsequently scaled to humans by combining traditional allometric PK scaling with sensitivity-analysis-driven scaling of the PD. The scaled PK/PD model was then used to simulate the human PK/PD for different dose levels. When clinical data from the BIIB059 Phase I study became available, they were used to evaluate the predictability of the scaled PK/PD model and the model simulations were in agreement with the clinical data. Therefore, the presented approach is suggested to be employed in scaling pre-clinical mAb models to support the selection of safe first-in-human doses and, more broadly, the prediction of PK/PD in the clinic.

Quantitation and pharmacokinetic modeling of therapeutic antibody quality attributes in human studies.

A thorough understanding of drug metabolism and disposition can aid in the assessment of efficacy and safety. However, analytical methods used in pharmacokinetics (PK) studies of protein therapeutics are usually based on ELISA, and therefore can provide a limited perspective on the quality of the drug in concentration measurements. Individual post-translational modifications (PTMs) of protein therapeutics are rarely considered for PK analysis, partly because it is technically difficult to recover and quantify individual protein variants from biological fluids. Meanwhile, PTMs may be directly linked to variations in drug efficacy and safety, and therefore understanding of clearance and metabolism of biopharmaceutical protein variants during clinical studies is an important consideration. To address such challenges, we developed an affinity-purification procedure followed by peptide mapping with mass spectrometric detection, which can profile multiple quality attributes of therapeutic antibodies recovered from patient sera. The obtained data enable quantitative modeling, which allows for simulation of the PK of different individual PTMs or attribute levels in vivo and thus facilitate the assessment of quality attributes impact in vivo. Such information can contribute to the product quality attribute risk assessment during manufacturing process development and inform appropriate process control strategy.

Modeling the exposure-response relationship of etanercept in the treatment of patients with chronic moderate to severe plaque psoriasis.

Modeling exposure-response relationships adds significant value to comprehending and interpreting both efficacy and safety data. An exposure-response model was developed using generalized nonlinear mixed-effects methodologies to correlate etanercept exposure with a 75% or greater reduction from baseline in the psoriasis area and severity index (PASI75). Three randomized trials of psoriasis patients were pooled for analysis. Three empirical exposure measures-cumulative dose, predicted cumulative area under the curve, and predicted trough concentration-were evaluated for their predictive capabilities. The predicted cumulative area under the curve model demonstrated the best ability via simulation to reproduce the data and was used to assess the following covariates: age, baseline psoriasis area and severity index, duration of psoriasis disease, prior systemic or phototherapy, race, sex, and weight. The final model was composed by scrutinizing the confidence intervals of a nonparametric bootstrap and included race and sex effects on baseline logit, baseline psoriasis area and severity index and prior systemic or phototherapy effects on maximum drug effect, a weight effect on apparent potency, and an age effect on the rate of drug effect. The model identified covariates predictive of data trends and adequately characterized by simulation the PASI75 over the entire clinical trial design space. In combination with a statistical subgroup analysis, the exposure-response model indicated that dose adjustment was not necessary for etanercept in any patient subpopulation with moderate to severe plaque psoriasis.