Clémence Fauteux-Lefebvre

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.

Biodiesel reforming with a NiAl2O4/Al2O3-YSZ catalyst for the production of renewable SOFC fuel.

Biodiesel’s contribution as a renewable energy carrier is increasing continuously. Fuel cell market penetration, although slow, is now an irreversible reality. The combination of solid oxide fuel cells (SOFC) with biodiesel offers considerable advantages because it entails both high energy conversion efficiency and nearzero atmospheric carbon emissions. This work is aimed at proving the efficiency of a newly-developed (patent pending), Al2O3/YSZ-supported NiAl2O4 spinel catalyst to steam reform biodiesel. Reforming converts biodiesel into a gaseous mixture, mainly composed of H2 and CO, used directly as SOFC fuel. The work is performed in a test rig comprising a lab-scale, fixed-bed isothermal reactor and a product-conditioning train. The biodiesel/water mixtures are emulsified prior to their spray injection in the reactor preheating zone, where they are instantaneously vaporized and rapidly brought to the desired reaction temperature to avoid thermal cracking. Reforming takes place at gas hourly space velocities equal to or higher than those in industrial reforming units. The products are analysed by at-line gas chromatography. The results show that biodiesel conversion is complete at steady state. Thermodynamic calculations reveal that the fast reforming reaction reaches chemical equilibrium. The catalyst’s performance is very efficient and prevents carbon formation and deactivation.

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

Abstract 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.

Determining the Number of Components for Multivariate Curve Resolution: Case Study Using Raman Mapping of Pharmaceutical Tablets

Raman chemical imaging of pharmaceutical tablets can be used to determine particle morphology, active pharmaceutical ingredient (API) concentration, sample heterogeneity, as well as for impurity detection. Raman imaging generally requires simple and fast sample preparation and offers μm-scale spatial resolutions. The probe used in this study (mPATTM Raman system from H2Optx) also performs 3D analysis of solid samples. In pharmaceutical tablet composition analysis, there is an increased interest for Raman mapping using chemometric tools such as multivariate curve resolution (MCR) [1].