Application of Absorption Modeling in Rational Design of Drug Product Under Quality-by-Design Paradigm

Abstract

Physiologically based absorption models can be an important tool in understanding product performance and hence implementation of Quality by Design (QbD) in drug product development. In this report, we show several case studies to demonstrate the potential application of absorption modeling in rational design of drug product under the QbD paradigm. The examples include application of absorption modeling—(1) prior to first-in-human studies to guide development of a formulation with minimal sensitivity to higher gastric pH and hence reduced interaction when co-administered with PPIs and/or H2RAs, (2) design of a controlled release formulation with optimal release rate to meet trough plasma concentrations and enable QD dosing, (3) understanding the impact of API particle size distribution on tablet bioavailability and guide formulation design in late-stage development, (4) assess impact of API phase change on product performance to guide specification setting, and (5) investigate the effect of dissolution rate changes on formulation bioperformance and enable appropriate specification setting. These case studies are meant to highlight the utility of physiologically based absorption modeling in gaining a thorough understanding of the product performance and the critical factors impacting performance to drive design of a robust drug product that would deliver the optimal benefit to the patients.

Fig. 1

Projections for total absorption (Fa) for compound A as a function of stomach pH and dose under default precipitation (a) or prolonged precipitation (b) settings

Fig. 2

a Assumed target dissolution profiles of controlled-release formulation showing target 80% (T _80%) release of compound B at 8, 12, and 16 h. b Predicted PK profiles of controlled-release (CR) formulations (6 mg dose) and a comparison of the observed (mean ± standard deviation) and predicted PK profile of immediate-release (IR) formulation at 3 mg dose. c Plot of predicted individual plasma concentration at 24 h (C _24 h) as a function of total intestinal transit time for the three controlled-release formulations

Fig. 3

a Observed (mean) and fitted dissolution profiles of compound C tablets using API with four different particle size distributions. b Observed (mean) vs. model predicted plasma concentration vs. time profiles in fasted health volunteers at different doses

Fig. 4

a Observed (mean ± standard deviation) vs. model predicted plasma concentration vs. time profile for pioglitazone HCl salt at 30 mg in fasted healthy volunteers. The default precipitation settings (900 s) model is also shown as a reference. b Model projected relationship between free base absorption (expressed as % relative Fa to the HCl salt simulation) and stomach pH. c Projected AUC values as a function of free base content and stomach pH. d Simulation of 80:20 HCl salt:free base mixture in healthy Caucasians or Japanese subjects. Exposure is presented as relative bioavailability to a 100% HCl simulation

Fig. 5

Dissolution profiles of 50 mg losartan from three tablet formulations in 250 mL of simulated gastric fluid (SGF)