Building Process Understanding of Fluid Bed Taste Mask Coating of Microspheres.

Taste is routinely cited as one of the major contributing factors that negatively influence pediatric patient compliance. A promising solution is coated microsphere systems, which provide doses of active pharmaceutical ingredients (API) subdivided into a plurality of small dosage units. In this work, the microspheres were coated with Kollicoat® Smartseal, a reverse enteric polymer, which acts to minimize or prevent the release of API in the neutral pH of the oral cavity, which results in a masking effect of the unpleasant taste of the API. A screening of seven key variables in a Wurster coating process was evaluated by D-optimal design and by analysis of variance. The percentage of API released at pH 6.2 was used as a surrogate method for the taste-masking performance evaluation of Kollicoat® Smartseal. The seven studied variables were: product bed temperature, inlet airflow, atomizing air pressure, spray rate (process parameters), coating level, plasticizer level, solids in coating suspension (material attributes), and curing. Results show that coating level, plasticizer level, product bed temperature, and spray rate are the critical process parameters and reinforce the importance of curing to reduce the overall variability within the batch by promoting complete film formation. The link between material attributes, process parameters, and quality attributes were demonstrated to allow a better understanding of the parameters that affect the API release profile at neutral pH (in vitro) while not injuring release at acidic pH (in vitro). It was demonstrated that not only thickness but also coating morphology have an impact on the dissolution in 50 mM potassium phosphate buffer, pH 6.2.

Specificity of process analytical tools in the monitoring of multicomponent pharmaceutical powders.

The application of Process Analytical Technologies in pharmaceutical manufacturing has been the subject of many studies. Active pharmaceutical ingredient monitoring in real time throughout the manufacturing process is commonly the target of many such implementations. The tools in place must be sensitive to, and selective of, the parameter(s) to be monitored, i.e. in the case of component quantification, they must respond to the component in question and be robust against all others. In this study, four different ingredients (riboflavin, ferrous fumarate, ginseng, and ascorbic acid) in a multi-component blend were monitored by three different tools (near infrared spectroscopy, laser-induced fluorescence and red-green-blue camera) using a full factorial design. The goal was to develop efficient and robust concentration-reading/prediction models able to assess and monitor component interference. Despite relatively high complexity of the blend studied, the three tools demonstrated reasonable specificity for the tracked ingredients (and showed advantages when combined), taking into account larger acceptance criteria typical of dietary products. In certain cases, some interference might lead to biased predictions, highlighting the importance of good calibration. The tools tested and the methodology proposed has divulged their potential in monitoring these components, despite the complexity of the 31-component blend.

A Hierarchical Multivariate Curve Resolution Methodology To Identify and Map Compounds in Spectral Images.

The use of spectroscopic methods, such as near-infrared or Raman, for quality control applications combined with the constant search for finer details leads to the acquisition of increasingly complex data sets. This should not prevent the user from characterizing a sample by identifying and mapping its chemical compounds. Multivariate data analysis methods make it possible to obtain qualitative and quantitative information from such data sets. However, samples containing a large (and/or unknown) number of species, segregated trace compounds (present in few pixels), low signal-to-noise ratios (SNR), and often insufficient spatial resolutions still represent significant hurdles for the analyst.

Using multiple Process Analytical Technology probes to monitor multivitamin blends in a tableting feed frame.

As Process Analytical Technology (PAT) implementation grows in the pharmaceutical industry, more studies are being performed to evaluate its suitability in new applications and processes within the manufacturing chain. As the last step in tablet production, the compression stage represents a critical phase that ensures product quality. In-line control put in place at this stage has the potential to detect powder blends that are out of specification limits and, thus, help to improve product quality. The objectives of the present project are to quantify the composition of a commercial 31-component multivitamin powder blend in real time on an industrial feed frame, using 3 different PAT tools: light-induced fluorescence spectroscopy, near infrared spectroscopy and red, green and blue color imaging. To do so, the concentrations of 5 components (Beta-Carotene, Riboflavin, Ferrous Fumarate, Ginseng and Ascorbic Acid) were alternately changed and monitored with one or many probes. Transition periods between batches served to quantify different powder flow dynamics with sequential composition step changes. The results showed that 4 out of 5 components, each present in commercially-relevant concentrations, could be monitored by one or more tools. Flow dynamics were measured and found to vary significantly in different powder blends.