Mafalda C. Sarraguça

Bioreactor monitoring with spectroscopy and chemometrics: a review.

Biotechnological processes are crucial to the development of any economy striving to ensure a relevant position in future markets. The cultivation of microorganisms in bioreactors is one of the most important unit operations of biotechnological processes, and real-time monitoring of bioreactors is essential for effective bioprocess control. In this review, published material on the potential application of different spectroscopic techniques for bioreactor monitoring is critically discussed, with particular emphasis on optical fiber technology, reported for in situ bioprocess monitoring. Application examples are presented by spectroscopy type, specifically focusing on ultraviolet–visible, near-infrared, mid-infrared, Raman, and fluorescence spectroscopy. The spectra acquisition devices available and the major advantages and disadvantages of each spectroscopy are discussed. The type of information contained in the spectra and the available chemometric methods for extracting that information are also addressed, including wavelength selection, spectra pre-processing, principal component analysis, and partial least-squares. Sample handling techniques (flow and sequential injection analysis) that include transport to spectroscopic sensors for ex-situ on-line monitoring are not covered in this review.

Evaluation of green coffee beans quality using near infrared spectroscopy: A quantitative approach

Characterisation of coffee quality based on bean quality assessment is associated with the relative amount of defective beans among non-defective beans. It is therefore important to develop a methodology capable of identifying the presence of defective beans that enables a fast assessment of coffee grade and that can become an analytical tool to standardise coffee quality. In this work, a methodology for quality assessment of green coffee based on near infrared spectroscopy (NIRS) is proposed. NIRS is a green chemistry, low cost, fast response technique without the need of sample processing. The applicability of NIRS was evaluated for Arabica and Robusta varieties from different geographical locations. Partial least squares regression was used to relate the NIR spectrum to the mass fraction of defective and non-defective beans. Relative errors around 5% show that NIRS can be a valuable analytical tool to be used by coffee roasters, enabling a simple and quantitative evaluation of green coffee quality in a fast way.

The use of net analyte signal (NAS) in near infrared spectroscopy pharmaceutical applications: Interpretability and figures of merit

Near infrared spectroscopy (NIRS) has been extensively used as an analytical method for quality control of solid dosage forms for the pharmaceutical industry. Pharmaceutical formulations can be extremely complex, containing typically one or more active product ingredients (API) and various excipients, yielding very complex near infrared (NIR) spectra. The NIR spectra interpretability can be improved using the concept of net analyte signal (NAS). NAS is defined as the part of the spectrum unique to the analyte of interest. The objective of this work was to compare two different methods to estimate the APIs NAS vector of different pharmaceutical formulations. The main difference between the methods is the knowledge of API free formulations NIR spectra. The comparison between the two methods was assessed in a qualitative and quantitative way. Results showed that both methods produced good results in terms of the similarity between the NAS vector and the pure API spectrum, as well as in the ability to predict the API concentration of unknown samples. Moreover, figures of merit such as sensitivity, selectivity, and limit of detection were estimated in a straightforward manner.

Determination of flow properties of pharmaceutical powders by near infrared spectroscopy.

The physical properties of pharmaceutical powders are of upmost importance in the pharmaceutical industry. The knowledge of their flow properties is of critical significance in operations such as blending, tablet compression, capsule filling, transportation, and in scale-up operations. Powders flow properties are measured using a number of parameters such as, angle of repose, compressibility index (Carrs index) and Hausner ratio. To estimate these properties, specific and expensive equipment with time-consuming analysis is required. Near infrared spectroscopy is a fast and low-cost analytical technique thoroughly used in the pharmaceutical industry in the quantification and qualification of products. To establish the potential of this technique to determine the parameters associated with the flow properties of pharmaceutical powders, blended powders based on paracetamol as the active pharmaceutical ingredient were constructed in pilot scale. Spectra were recorded on a Fourier-transform near infrared spectrometer in reflectance mode. The parameters studied were the angle of repose, aerated and tapped bulk density. The correlation between the reference method values and the near infrared spectrum was performed by partial least squares and optimized in terms of latent variables using cross-validation. The near infrared based properties predictions were compared with the reference methods results. Prediction errors, which varied between 2.35% for the angle of repose, 2.51% for the tapped density and 3.18% for the aerated density, show the potential of NIR spectroscopy in the determination of physical properties affecting the flowability of pharmaceutical powders.

A UV spectrophotometric method for the determination of folic acid in pharmaceutical tablets and dissolution tests

Folic acid (FA) or pteroyl-L-glutamic acid, chemically known as N-[4-[[(2-amino-1,4-dihydro-4-oxo-6-pteridinyl)methyl]amino]benzoyl]-L-glutamic acid, is a water-soluble B vitamin that helps build healthy cells. In this study, a new, simple, easy, accurate, precise, economic and sensitive UV spectrophotometric method for the determination of folic acid in commercial tablets and during dissolution tests is presented. Using a phosphate buffer solution at pH 9.0 it was possible to determine the concentration of folic acid in commercial tablets at a λmax of 282.5 nm in a linear range of 1.0–17.5 μg ml−1 with a R2 > 0.9999 and recovery between 100.6 and 101.1%. The method was also optimized for the quantification of folic acid in dissolution tests in the same linear concentration range. The pH effect on the UV spectra of folic acid solutions was eliminated with a first derivative. This procedure allowed the direct measurement of samples from the dissolution vessel (pH approximately equal to 6) without any pH correction. This method was based on the first derivative of the absorbance at λ = 377.2 nm, yielding an R2 > 0.9997 with recovery percentages similar to those presented before. The statistical comparison between the proposed and the HPLC reference method showed excellent agreement and indicates no statistically significant difference in accuracy and precision at a 0.05 significance level.

A PAT approach for the on-line monitoring of pharmaceutical co-crystals formation with near infrared spectroscopy.

Cocrystals represent a class of crystalline solids consisting of two or more molecular species usually held together by non-covalent bonds. Pharmaceutical cocrystals can alter the physicochemical properties of the active pharmaceutical ingredient to improve solubility, dissolution rate, particle properties and stability. This work presents a process analytical technology (PAT) approach to monitor on-line the cocrystallization of furosemide and adenine by solvent evaporation using near infrared spectroscopy (NIRS). Furosemide and adenine were added to a small volume of methanol in a beaker and stirred on an orbital stirring table during 8h at room temperature. The on-line monitoring was performed with a FT-NIR spectrometer fitted with a reflectance fiber optic probe. Monitoring was performed with the probe tip placed 1cm above the cocrystallization medium to avoid interference with the cocrystallization process. Cocrystals were vacuum dried to remove residual solvent and characterized off-line by NIRS, MIRS, DSC and XRPD. Results demonstrate that it was possible to follow the main cocrystallization events on-line.

Online monitoring of P(3HB) produced from used cooking oil with near-infrared spectroscopy.

Online monitoring process for the production of polyhydroxyalkanoates (PHA), using cooking oil (UCO) as the sole carbon source and Cupriavidus necator, was developed. A batch reactor was operated and hydroxybutyrate homopolymer was obtained. The biomass reached a maximum concentration of 11.6±1.7gL(-1) with a polymer content of 63±10.7% (w/w). The yield of product on substrate was 0.77±0.04gg(-1). Near-infrared (NIR) spectroscopy was used for online monitoring of the fermentation, using a transflectance probe. Partial least squares regression was applied to relate NIR spectra with biomass, UCO and PHA concentrations in the broth. The NIR predictions were compared with values obtained by offline reference methods. Prediction errors to these parameters were 1.18, 2.37 and 1.58gL(-1) for biomass, UCO and PHA, respectively, which indicate the suitability of the NIR spectroscopy method for online monitoring and as a method to assist bioreactor control.

Comparison of different chemometric and analytical methods for the prediction of particle size distribution in pharmaceutical powders

This work compares the estimation of the particle size distribution of a pharmaceutical powder using near-infrared spectroscopy (NIRS), powder flowability properties, and components concentration. The estimations were made by considering the former data blocks separately and together using a multi-block approach. The powders were based on a formulation of paracetamol as the pharmaceutical active ingredient. The reference method used to determine particle size distribution was sieving. Partial least squares methods were used to estimate the multivariate regression models, and the results were compared in terms of figures of merit. It was shown that the partial least squares methods gave similar prediction errors. Regarding the data blocks used, the NIRS block was proven the most advantageous to estimate the particle size distribution. The prediction error of the NIRS block was similar to the other data blocks with additional advantages such as less generalization problems and the possibility of its use to predict additional physical and chemical properties with an improvement to analysis time. The multi-block approach produced the worst results but nevertheless allowed a deeper understanding of the individual contributions of the data blocks in the prediction of the particle size distribution.

A batch modelling approach to monitor a freeze-drying process using in-line Raman spectroscopy

Freeze-drying or lyophilisation is a batch wise industrial process used to remove water from solutions, hence stabilizing the solutes for distribution and storage. The objective of the present work was to outline a batch modelling approach to monitor a freeze-drying process in-line and in real-time using Raman spectroscopy. A 5% (w/v) D-mannitol solution was freeze-dried in this study as model. The monitoring of a freeze-drying process using Raman spectroscopy allows following the product behaviour and some process evolution aspects by detecting the changes of the solutes and solvent occurring during the process. Herewith, real-time solid-state characterization of the final product is also possible. The timely spectroscopic measurements allowed the differentiation between batches operated in normal process conditions and batches having deviations from the normal trajectory. Two strategies were employed to develop batch models: partial least squares (PLS) using the unfolded data and parallel factor analysis (PARAFAC). It was shown that both strategies were able to developed batch models using in-line Raman spectroscopy, allowing to monitor the evolution in real-time of new batches. However, the computational effort required to develop the PLS model and to evaluate new batches using this model is significant lower compared to the PARAFAC model. Moreover, PLS scores in the time mode can be computed for new batches, while using PARAFAC only the batch mode scores can be determined for new batches.

Batch Statistical Process Monitoring Approach to a Cocrystallization Process

Cocrystals are defined as crystalline structures composed of two or more compounds that are solid at room temperature held together by noncovalent bonds. Their main advantages are the increase of solubility, bioavailability, permeability, stability, and at the same time retaining active pharmaceutical ingredient bioactivity. The cocrystallization between furosemide and nicotinamide by solvent evaporation was monitored on-line using near-infrared spectroscopy (NIRS) as a process analytical technology tool. The near-infrared spectra were analyzed using principal component analysis. Batch statistical process monitoring was used to create control charts to perceive the process trajectory and define control limits. Normal and non-normal operating condition batches were performed and monitored with NIRS. The use of NIRS associated with batch statistical process models allowed the detection of abnormal variations in critical process parameters, like the amount of solvent or amount of initial components present in the cocrystallization.