Pharmaceutical gel analysis by NIR spectroscopy

Preliminary Study on the Determination of ppm-Level Concentration of Histamine in Tuna Fish Using a Dry Extract System for Infrared Coupled with Near-Infrared Spectroscopy

Rapid and simple methods to determine histamine in tuna fish have been examined. A dry extract system for infrared (DESIR) was coupled with near-infrared spectroscopy in order to obtain the absorption of histamine in tuna fish at the ppm level. The result showed that the optimal extraction solvent for preparing DESIR samples was 75% methanol and boiling water (100 °C). Calibration equations were developed and tested by independent validation set samples. The calibration equation developed from boiling water as solvent extraction was slightly better than the equation developed from 75% methanol solvent with a coefficient of determination (R ²) of 0.79, a standard error of calibration of 2.45 ppm, a standard error of prediction of 2.94 ppm, and a bias of 0.10 ppm. Furthermore, the predicted values from both equations were not significantly different from the reference values obtained from the standard method at the 95% confidence interval. Compared to the current AOAC fluorometric official method, the proposed technique simplified and reduced the preparation time.

Simultaneous quantitative analysis of indomethacin and benzoic acid in gel using ultra-violet-visible spectrophotometry and chemometrics

BACKGROUND

In order to manufacture pharmaceutical products, real-time monitoring in the manufacturing process is necessary, but large equipment cost is required to achieve it.

OBJECTIVE

The aim of this research is to use ultra-violet-visible spectroscopy along with chemometrics procedure to simultaneously carry out quantitative analysis of indomethacin (IMC) and benzoic acid (BA) in the gel during pharmaceutical manufacturing process.

METHODS

The gel preparations contained 0.1-1.5% IMC, 0.015-0.225% BA, 2% carbopol® 941 and 95% ethanol solution. The calibration models were constructed using the partial least square regression (PLS).

RESULTS

The relationships of the measured and predicted concentrations for both IMC and BA had linear plots. The developed PLS calibration models were used to monitor the IMC and BA concentrations during mixing of the gels by the planetary centrifugal and conventional mixers, respectively. IMC and BA were gradually dispersed, dissolved and completely homogeneous within 30 min by the centrifugal mixer. In contrast, IMC and BA were slowly dispersed, dissolved and completely homogeneous at more than 60 min by the conventional mixer.

CONCLUSIONS

The ultra-violet-visible spectrophotometric method couples with multivariate chemometric techniques for quantitative data analysis were successfully applied for the simultaneous determination of major component IMC and trace component BA in the gel.

Real-time simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by near-infrared spectroscopy

This paper proposes and proves a real-time and non-destructive strategy for sensitive and simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by near-infrared (NIR) spectroscopy. In this experiment, 88 samples of tazarotene gel (0.41–0.65 mg g⁻¹ of tazarotene) were prepared using the standard addition method. Among them, 47 samples were inoculated with 50 μl of different concentrations of Escherichia coli (E. coli) DH5a in Luria–Bertani (LB) broth to give 1–4 log CFU g⁻¹ of E. coli DH5a in the gel, 6 samples with 50 μl of LB broth, and 35 samples with nothing. Based on the gel NIR transflectance spectra, E. coli DH5a in the gel was detected by the counter propagation artificial neural network (CP-ANN) model with a classification accuracy of 100.0%, while tazarotene in the gel was simultaneously determined by the partial least squares regression (PLS) model with a root mean square error of cross-validation of 0.0232 mg g⁻¹. Furthermore, 9 samples of real tazarotene gel were used to verify the practicality of the established NIR spectroscopy. The developed NIR strategy can be used to correctly and quickly release the pharmaceutical gels, required for sensitive and simultaneous control of microbial contamination and the active pharmaceutical ingredient (API) content, to the next stage.

This paper proposes a real-time and non-destructive strategy for sensitive and simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by NIR spectroscopy.

Active content determination of pharmaceutical tablets using near infrared spectroscopy as Process Analytical Technology tool

The aim of this study was to develop Near infrared (NIR) methods to determine the active content of non-coated pharmaceutical tablets manufactured from a proportional tablet formulation. These NIR methods intend to be used for the monitoring of the active content of tablets during the tableting process. Firstly, methods were developed in transmission and reflection modes to quantify the API content of the lowest dosage strength. Secondly, these methods were fully validated for a concentration range of 70-130% of the target active content using the accuracy profile approach based on β-expectation tolerance intervals. The model using the transmission mode showed a better ability to predict the right active content compared to the reflection one. However, the ability of the reflection mode to quantify the API content in the highest dosage strength was assessed. Furthermore, the NIR method based on the transmission mode was successfully used to monitor at-line the tablet active content during the tableting process, providing better insight of the API content during the process. This improvement of control of the product quality provided by this PAT method is thoroughly compliant with the Quality by Design (QbD) concept. Finally, the transfer of the transmission model from the off-line to an on-line spectrometer was efficiently investigated.

Near-infrared spectroscopy for the detection and quantification of bacterial contaminations in pharmaceutical products

Accurate detection and quantification of microbiological contaminations remains an issue mainly due the lack of rapid and precise analytical techniques. Standard methods are expensive and time-consuming being associated to high economic losses and public health threats. In the context of pharmaceutical industry, the development of fast analytical techniques able to overcome these limitations is crucial and spectroscopic techniques might constitute a reliable alternative. In this work we proved the ability of Fourier transform near infrared spectroscopy (FT-NIRS) to detect and quantify bacteria (Bacillus subtilis, Escherichia coli, Pseudomonas fluorescens, Salmonella enterica, Staphylococcus epidermidis) from 10 to 10(8) CFUs/mL in sterile saline solutions (NaCl 0.9%). Partial least squares discriminant analysis (PLSDA) models showed that FT-NIRS was able to discriminate between sterile and contaminated solutions for all bacteria as well as to identify the contaminant bacteria. Partial least squares (PLS) models allowed bacterial quantification with limits of detection ranging from 5.1 to 9 CFU/mL for E. coli and B. subtilis, respectively. This methodology was successfully validated in three pharmaceutical preparations (contact lens solution, cough syrup and topic anti-inflammatory solution) proving that this technique possess a high potential to be routinely used for the detection and quantification of bacterial contaminations.

Development of NIRS method for quality control of drug combination artesunate-azithromycin for the treatment of severe malaria

Near infrared spectroscopy (NIRS) methods were developed for the determination of analytical content of an antimalarial-antibiotic (artesunate and azithromycin) co-formulation in hard gelatin capsule (HGC). The NIRS consists of pre-processing treatment of spectra (raw spectra and first-derivation of two spectral zones), a unique principal component analysis model to ensure the specificity and then two partial least-squares regression models for the determination content of each active pharmaceutical ingredient. The NIRS methods were developed and validated with no reference method, since the manufacturing process of HGC is basically mixed excipients with active pharmaceutical ingredients. The accuracy profiles showed β-expectation tolerance limits within the acceptance limits (±5%). The analytical control approach performed by reversed phase (HPLC) required two different methods involving two different preparation and chromatographic methods. NIRS offers advantages in terms of lower costs of equipment and procedures, time saving, environmentally friendly.

Critical review of near-infrared spectroscopic methods validations in pharmaceutical applications

Based on the large number of publications reported over the past five years, near-infrared spectroscopy (NIRS) is more and more considered an attractive and promising analytical tool regarding Process Analytical Technology and Green Chemistry. From the reviewed literature, few of these publications present a thoroughly validated NIRS method even if some guidelines have been published by different groups and regulatory authorities. However, as any analytical method, the validation of NIRS method is a mandatory step at the end of the development in order to give enough guarantees that each of the future results during routine use will be close enough to the true value. Besides the introduction of PAT concepts in the revised document of the European Pharmacopoeia (2.2.40) dealing with near-infrared spectroscopy recently published in Pharmeuropa, it agrees very well with this mandatory step. Indeed, the latter suggests to use similar analytical performance characteristics than those required for any analytical procedure based on acceptance criteria consistent with the intended use of the method. In this context, this review gives a comprehensive and critical overview of the methodologies applied to assess the validity of quantitative NIRS methods used in pharmaceutical applications.

Simultaneous diffuse reflectance infrared determination of clavulanic acid and amoxicillin using multivariate calibration techniques

A method for simultaneous determination of clavulanic acid (CA) and amoxicillin (AMO) in commercial tablets was developed using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and multivariate calibration. Twenty-five samples (10 commercial and 15 synthetic) were used as a calibration set and 15 samples (10 commercial and 5 synthetic) were used for a prediction set. Calibration models were developed using partial least squares (PLS), interval PLS (iPLS), and synergy interval PLS (siPLS) algorithms. The best algorithm for CA determination was siPLS model with spectra divided in 30 intervals and combinations of 2 intervals. This model showed a root mean square error of prediction (RMSEP) of 5.1 mg g(-1). For AMO determination, the best siPLS model was obtained with spectra divided in 10 intervals and combinations of 4 intervals. This model showed a RMSEP of 22.3 mg g(-1). The proposed method was considered as a suitable for the simultaneous determination of CA and AMO in commercial pharmaceuticals products.

Measurement of total flavone content in snow lotus (Saussurea involucrate) using near infrared spectroscopy combined with interval PLS and genetic algorithm

NIR spectroscopy technique was attempted to measure total flavone content in snow lotus in this work. Interval partial least square with genetic algorithm (iPLS-GA) was used to select the efficient spectral regions and variables in model calibration. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R(c)) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R(p)) in prediction set. The optimal iPLS-GA model was obtained with 6 PLS factors, when 5 spectral regions and 53 variables were selected. The measurement results of final model were achieved as follow: RMSEC (%)=0.8347/R(c)=0.9444 in the calibration set, and RMSEP (%)=1.0766/R(p)=0.9006 in the prediction set. Finally, iPLS-GA moded showed its excellent performance, when compared with other 5 different PLS models. This work demonstrated that total flavone content in snow lotus could be measured by NIR spectroscopy technique, and iPLS-GA revealed its superiority in model calibration.