Evaluation of NIR and Raman spectroscopies for the quality analytical control of a solid pharmaceutical formulation with three active ingredients

Seasonal variation of antioxidant bioactive compounds in southern highbush blueberry leaves and non-destructive quality prediction in situ by a portable near-infrared spectrometer

Blueberry leaves (BBL) are a natural source with strong antioxidant activity, but bioactive compounds and their seasonal variation remain vague. Here, two major classes of compounds including four caffeoylquinic acids and eight flavonoids were identified in two southern highbush cultivars ("Lanmei" #1 and "Jewel") grown in China. Major bioactive compounds were discovered using an online HPLC post-column derivatization system and determined as neochlorogenic acid (NeoCA), chlorogenic acid (CA), rutin, hyperoside, and isoquercitrin. CA contributed the most to the BBL antioxidant activity. "Lanmei" showed significant advantages in terms of rutin content and antioxidant activity over "Jewel" (P < 0.05). The highest CA content (CAC) of juvenile "Jewel" leaves reached 17.9%. July was the optimum harvest time for both cultivars after fruiting stage. Total phenolic content (TPC) and Trolox equivalent antioxidant capacity (TEAC) of fresh BBL were accurately predicted by a portable near-infrared (NIR) device in a rapid, low-cost, and non-destructive way in situ.

Mixing uniformity effect on leaching behaviour of cement-based solidified contaminated clay

Mixing uniformity is essential for the quality control of the contaminated clay's solidification. To investigate the effect of the mixing uniformity on the leaching behaviour of the cement-based solidified contaminated clay, this study proposed a quantitative method to characterize the mixing uniformity and investigated the leaching behaviour by the leaching toxicity tests and semi-dynamic leaching tests. X-ray computed tomography (X-CT) was employed to reveal the internal mesoscopic structure. In this case, Pb2+ was selected as a tagged pollutant because of the widespread attention at heavy metal-contaminated sites. The leaching toxicity indicates the significant Pb2+ concentration deviation among the parallel specimens and non-association with the mixing uniformity. However, the Pb2+ cumulative leaching mass and observed diffusion coefficient by the semi-dynamic leaching tests both decrease with the mixing uniformity. X-CT image analysis reveals that the high cement zones wrap the low cement zones with different dimensions in the heterogeneous solidified matrix. Moreover, the specimen pretreatment method in the existing leaching toxicity standards may be inadequate because of the overall encapsulation destruction by the crushing process and representativeness uncertainty when sampling. However, for semi-dynamic leaching, the Pb2+ migration depends on the uniformity, reflecting the continuous distribution of high cement zones.

Towards a real-time release of blends and tablets using NIR and Raman spectroscopy at commercial scales

Near Infrared and Raman spectroscopy-based Process Analytical Technology tools were used for monitoring blend uniformity (BU) and content uniformity (CU) for solid oral formulations. A quantitative Partial Least Square model was developed to monitor BU as real-time release testing at a commercial scale. The model having the R2, and root mean square error of 0.9724 and 2.2047, respectively can predict the target concentration of 100% with a 95% confidence interval of 101.85-102.68% even after one year. The tablets from the same blends were investigated for CU using NIR and Raman techniques both in reflection and transmission mode. Raman reflection technique was found to be the best and the PLS model was developed using tablets compressed at different concentrations, hardness, and speed. The model with R2 and RMSE of 0.9766 and 1.9259, respectively was used for the quantification of CU. Both the BU and CU models were validated for accuracy, precision, specificity, linearity, and robustness. The accuracy was proved against the HPLC method with a relative standard deviation of less than 3%. The equivalency for BU by NIR and CU by Raman was evaluated using Schuirmann's Two One-sided tests and found equivalent to HPLC within a 2% acceptable limit.

Emerging analytical techniques for pharmaceutical quality control: Where are we in 2022?

Quality control is a fundamental and critical activity in the pharmaceutical industry that guarantees the quality of medicines. QC analyses are currently performed using several well-known techniques, mainly liquid and gas chromatography. However, current trends are focused on the development of new techniques to reduce analysis time and cost, to improve the performances and decrease ecological footprint. In this context, analytical scientists developed and studied emerging technologies based on spectroscopy and chromatography. The present review aims to give an overview of the recent development of vibrational spectroscopy, supercritical fluid chromatography and multi-dimensional chromatography. Selected emerging techniques are discussed using SWOT analysis and published pharmaceutical QC applications are discussed.

Quantitative analysis of blend uniformity within a Three-Chamber feed frame using simultaneously Raman and Near-Infrared spectroscopy

This study reports the use of Raman and Near-infrared (NIR) spectroscopy to simultaneously monitor the drug concentration in flowing powder blends within a three-chamber feed frame. The Raman probe was located at the top of the dosing chamber, while the NIR probe was located at the top of the filling chamber. The Raman and NIR spectra were continuously acquired while the powder blends flowed through the feed frame. Calibration models were developed with spectra from a total of five calibration blends ranging in caffeine concentration among 3.50 and 6.50% w/w. These models were optimized to predict three test set blends of 4.00, 5.00, and 6.00% w/w caffeine. The results showed a high predictive ability of the models based on root mean square error of predictions of 0.174 and 0.235% w/w for NIR and Raman spectroscopic models, respectively. Concentration profiles with higher variability were observed for the Raman spectroscopy predictions. An estimate of the mass analyzed by each spectrum showed that a NIR spectrum analyzes approximately 4.5 times the mass analyzed by a Raman spectrum; despite these differences in the mass analyzed, blend uniformity results are equivalent between techniques. Variographic analysis demonstrated that both techniques have significantly low sampling errors for the real-time monitoring process of drug concentration within the feed frame.

Spectrophotometry and pharmaceutical PAT/RTRT: Practical challenges and regulatory landscape from development to product lifecycle

European Pharmacopoeia includes dedicated chapters for Raman, NIR and Chemometrics, as well as there is a lot of Academia research on the matter. Despite that, the word innovation is often associated to such tools and there is a still slow implementation at industry. The paper is the outcome of the Associazione Farmaceutici dell'Industria (AFI) Study Group on Process Innovation and Product Lifecycle; the aim is to describe some case studies referring to practical approaches in pharmaceutical industry, in order to depict challenges and opportunities for the implementation of spectroscopic techniques. Case studies include: feasibility and pre-screening evaluations, chemometric model development approaches, way for the method maintenance during commercial manufacturing, challenges for implementation on existing equipment and on sterile processes. Case studies refer to oral solid products, liquid products and sterile Active Pharmaceutical Ingradient (API) manufacturing. There are already successful and robust spectroscopic applications in pharmaceutical industry and the technology is mature: this is the outcome of a strong applied research performed at pharmaceutical production departments. It is necessary to acknowledge efforts done by industry as Research for strengthening the cooperation with Academia, so that advantage of process innovation might reach the patients in a fastest way.

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.

Calibration transfer between modelled and commercial pharmaceutical tablet for API quantification using backscattering NIR, Raman and transmission Raman spectroscopy (TRS)

Backscattering NIR, Raman (BSR) and transmission Raman spectroscopy (TRS) coupled with chemometrics have shown to be rapid and non-invasive tools for the quantification of active pharmaceutical ingredient (API) content in tablets. However, the developed models are generally specifically related to the measurement conditions and sample characteristics. In this study, a number of calibration transfer methods, including DS, PDS, DWPDS, GLSW and SST, were evaluated for the spectra correction between modelled tablets produced in the laboratory and commercial samples. Results showed that the NIR and BSR spectra of commercial tablet corrected by DWPDS and PDS, respectively, enabled accurate API predictions with the high ratio of prediction error to deviation (RPD_P) values of 2.33 and 3.03. The most successfully approach was achieved with DS corrected TRS data and SiPLS modelling (161 variables) and yielded RMSE_P of 0.72 %, R²_P of 0.946 and RPD_P of 4.35. The proposed calibration transfer strategy offers the opportunities to analyse samples produced in different conditions; in the future, its implication will find extensively process control and quality assurance applications and benefit all possible users in the entire pharmaceutical industry.