A multivariate ANN-CCD integrative model using cellulose based polymers for the development of osmotically controlled push-pull dexibuprofen tablets and its predictive pharmacokinetic modeling.

The biocompatible macromolecules play a pivotal role in enhancing the performance of various drug delivery systems. In the current work, cellulose acetate (Opadry® CA), microcrystalline cellulose and an intrinsically uncharged polymer, polyethylene oxide (Polyox WSR N 80 and Polyox WSR 303), were evaluated for developing a bilayer push-pull osmotic tablet for dexibuprofen. The drug layer was comprised of Polyox WSR N 80, osmogen, microcrystalline cellulose and magnesium stearate. The push layer consisted of Polyox WSR 303 and pigments (Fe 2O3) in addition to osmogen and lubricant. The optimum levels of the input variables, osmogen (sodium chloride), orifice size, and percent coating weight gain were determined using the simultaneous multivariate techniques of Artificial Neural Network (ANN) and Central Composite Design (CCD) to achieve the targeted drug release profile. The ANN model's prediction profiler was cross-validated using the CCD-optimized formulation. The tabletability of the poorly compressible drug, dexibuprofen, was improved by incorporating microcrystalline cellulose as a diluent. The ANN- and CCD-driven trial and optimized formulations were tested for both critical and pharmaceutical quality attributes. Additionally, the optimized formulations FANN was also tested for thermal and chemical stability, physicochemical interactions, and surface morphology. Physiologically Based Pharmacokinetic (PBPK) models for optimized formulations were developed using GastroPlus™ to simulate in vivo plasma profiles and compare with the real-time human pharmacokinetic data. The study demonstrates the promising role of biocompatible macromolecules in compressing the poorly compressible molecule, dexibuprofen, and modulating its release and in vivo pharmacokinetic performance from an osmotically controlled push-pull system for 12 h.