The present study evaluates the in vitro release of diclofenac sodium (DFNa) from contact lenses based on poly-2-hydroxyethyl methacrylate (pHEMA) hydrogels containing an embedded microemulsion to extend release duration. The oil (ethyl butyrate)-in-water microemulsion systems are prepared with two non-ionic surfactants, Brij 97 or Tween 80, together with a long-alkyl chain cationic surfactant, cetalkonium chloride (CKC). Without CKC, Brij 97 or Tween 80-based microemulsions showed average droplet sizes of 12 nm and 18 nm, respectively. The addition of CKC decreased the average droplet sizes to 2–5 nm for both non-ionic surfactants. Such significant reduction in the average droplet size corresponds to an increase in the DFNa release duration as revealed by the in vitro experiments. Contact lens characterization showed that important properties such as optical transparency and water content of Brij 97-based contact lenses with cationic microemulsions was excellent. However, the optical transparency of the corresponding Tween 80 based contact lenses was unsatisfactory. The results indicate that cationic microemulsion-laden contact lenses can benefit from combinatory effects of microemulsions and cationic surfactant at low CKC weight percentage, e.g., with the release of 70% of the drug in 45, 10, and 7 h for B97-CKC-0.45%, CKC-0.45%, and control lenses, respectively. However, the microemulsion effect on extending DFNa release became negligible at the highest CKC weight percentage (1.8%).
Continuous manufacturing (CM) is an emerging technology which can improve pharmaceutical manufacturing and reduce drug product quality issues. One challenge that needs to be addressed when adopting CM technology is material traceability through the entire continuous process, which constitutes one key aspect of control strategy. Residence time distribution (RTD) play an important role in material traceability as it characterizes the material spreading through the process. The propagation of upstream disturbances could be predictively tracked through the entire process by convolution of the disturbance and the RTD. The present study sets up the RTD-based modeling framework in a commonly used process modeling environment, gPROMS, and integrates it with existing modules and built-in tools (e.g. parameter estimation). Concentration calculations based on the convolution integral requires access to historical stream property information, which is not readily available in flowsheet modeling platforms. Thus, a novel approach is taken whereby a partial differential equation is used to propagate and store historical data as the simulation marches forward in time. Other stream properties not modeled by an RTD are determined in auxiliary modules. To illustrate the application of the framework, an integrated RTD-auxiliary model for a continuous direct compression manufacturing line was developed. An excellent agreement was found between the model predictions and experiments. The validated model was subsequently used to assess in-process control strategies for feeder and material traceability through the process. Our simulation results show the employed modeling approach facilitates risk-based assessment of the continuous line by promoting our understanding on the process.
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