Investigation of drug distribution in tablets using surface enhanced Raman chemical imaging

Research progress on the application of spectral imaging technology in pharmaceutical tablet analysis

Tablet as a traditional dosage form in pharmacy has the advantages of accurate dosage, ideal dissolution and bioavailability, convenient to carry and transport. The most concerned tablet quality attributes include active pharmaceutical ingredient (API) contents and polymorphic forms, components distribution, hardness, density, coating state, dissolution behavior, etc., which greatly affect the bioavailability and consistency of tablet final products. In the pharmaceutical industry, there are usually industry standard methods to analyze the tablet quality attributes. However, these methods are generally time-consuming and laborious, and lack a comprehensive understanding of the properties of tablets, such as spatial information. In recent years, spectral imaging technology makes up for the shortcomings of traditional tablet analysis methods because it provides non-contact and rich information in time and space. As a promising technology to replace the traditional tablet analysis methods, it has attracted more and more attention. The present paper briefly describes a series of spectral imaging techniques and their applications in tablet analysis. Finally, the possible application prospect of this technology and the deficiencies that need to be improved were also prospected.

A Review of Pharmaceutical Robot based on Hyperspectral Technology

The quality and safety of medicinal products are related to patients’ lives and health. Therefore, quality inspection takes a key role in the pharmaceutical industry. Most of the previous solutions are based on machine vision, however, their performance is limited by the RGB sensor. The pharmaceutical visual inspection robot combined with hyperspectral imaging technology is becoming a new trend in the high-end medical quality inspection process since the hyperspectral data can provide spectral information with spatial knowledge. Yet, there is no comprehensive review about hyperspectral imaging-based medicinal products inspection. This paper focuses on the pivotal pharmaceutical applications, including counterfeit drugs detection, active component analysis of tables, and quality testing of herbal medicines and other medical materials. We discuss the technology and hardware of Raman spectroscopy and hyperspectral imaging, firstly. Furthermore, we review these technologies in pharmaceutical scenarios. Finally, the development tendency and prospect of hyperspectral imaging technology-based robots in the field of pharmaceutical quality inspection is summarized.

Development of distribution maps of spectrally similar degradation products by Raman chemical imaging microscope coupled with a new variable selection technique and SIMCA classifier

The ability to detect degradation products of active pharmaceutical ingredients (API) is an essential performance not only for conducting proper stability studies and subsequently gain regulatory approvals; but as well for detecting degradation products during the manufacturing process (In Process Control). Thus, this study aims to present the ability of using Raman Chemical Imaging (Raman-CI) microscope, with its optimum precision, in combination with appropriate chemometrics algorithms, to detect the spectrally similar Salicylic Acid (SA) in Acetylsalicylic Acid (ASA) powder mixture, and then create a chemical distribution map that reflects the distribution of ASA's main degradation product. The generated Hyperspectral images were processed where, a supervised chemometrics soft classifier, Soft Independent Modeling of Class Analogy (SIMCA), is applied to classify pixels and construct the subsequent distribution maps. In addition, due to the challenge of the high structural and spectral similarity between both substances, this study presents a new variable selection and dimensionality reduction technique, called Variable Strength Coefficient (VSC) to maximize the spectral differences and enhance the model precision and selectivity. A High-performance liquid chromatographic (HPLC) method was applied as a reference separation method to assess the results obtained by the proposed technique. The proposed technique was validated, where the obtained results confirmed that Raman Chemical Imaging Microscope, when coupled with SIMCA and VSC, is a powerful tool with outstanding accuracy. In addition, this approach could be suitable in applications where constructing accurate distribution maps of spectrally similar API's is required.

Carbamazepine polymorphism: a re-visitation using Raman imaging

Raman imaging methods have appeared in the last years as a powerful approach to monitoring the quality of pharmaceutical compounds. Because polymorphism occurs in many crystalline pharmaceutical compounds, it is essential to monitor polymorphic transformations induced by different external stimulus, such as temperature changes, to which those compounds may be submitted. Raman imaging with k-means cluster analysis (CA) is used here as an essential technique to investigate structural and chemical transformations occurring in carbamazepine p-monoclinic (CBZ III) into carbamazepine triclinic (CBZ I) when submitted to temperatures near the melting point of CBZ III (178 °C) and CBZ I (193°C). CBZ III commercial powder and laboratorial prepared CBZ I were analyzed by differential scanning calorimetry, powder X-ray diffraction and Raman spectroscopy with variable temperature. After thermal treatment, the resultant CBZ powder was evaluated by Raman imaging, in which all imaging data was analyzed using CA. Raman imaging allowed the identification of different polymorphs of CBZ (CBZ III and CBZ I) and iminostilbene (IMS), a degradation product of CBZ, in the treated samples, depending on the heating treatment method.

Why should the pharmaceutical industry claim for the implementation of second-order chemometric models-A critical review

Today, pharmaceutical products are submitted to a large number of analytical tests, planned to either ensure or construct their quality. The official methods of analysis used to perform these determinations are very different in nature, but almost all demand the intensive use of reagents and manpower as major drawbacks. Thus, analytical development is continuously evolving to find fast and smart approaches. First-order chemometric models are well-known in the pharmaceutical industry, and are extensively used in many fields. Such is the impact of chemometric models that regulatory agencies include them in guidelines and compendia. However, the mention or practical application of higher-order models in the pharmaceutical industry is rather scarce. Herein, we try to bring a brief introduction to chemometric models and useful literature references, focusing on higher-order chemometric models (HOCM) applied to reduce manpower, reagent consumption, and time of analysis, without sacrificing accuracy or precision, while gaining selectivity and sensitivity. The advantages and drawbacks of HOCM are also discussed, and the comparison to first-order chemometric models is also analyzed. Along the work, HOCM are evidenced as a powerful tool for the pharmaceutical industry; moreover, its implementation is shown during several steps of production, such as identification, purity test and assay, and other applications as homogeneity of API distribution, Process Analytical Technology (PAT), Quality by Design (QbD) or natural product fingerprinting. Among these topics, qualitative and quantitative applications were covered. Experimental approaches of chemometrics coupled to several analytical techniques such as UV-vis, fluorescence and vibrational spectroscopies (NIR, MIR and Raman), and other techniques as hyphenated-chromatography and electrochemical techniques applied to production and analysis are discussed throughout this work.

Towards a spray-coating method for the detection of low-dose compounds in pharmaceutical tablets using surface-enhanced Raman chemical imaging (SER-CI)

Surface-enhanced Raman chemical imaging (SER-CI) is a highly sensitive analytical tool recently used in the pharmaceutical field owing to the possibility to obtain high sensitivity along with spatial information. However, the covering method of the pharmaceutical samples such as tablets with metallic nanoparticles is a major issue for SER-CI analyses due to the difficulty to obtain a homogeneous covering of tablet surface with the SERS substrates. In this context, a spray-coating method was proposed in order to fully exploit the potential of SER-CI. A homemade apparatus has been developed from an electrospray ionization (ESI) probe in order to cover the pharmaceutical tablets with the colloidal suspension in a homogeneous way. The silver substrate was pulled through the airbrush by a syringe pump which was then nebulized into small droplets due to the contact of the solution with the gas flow turbulence. A robust optimization of the process was carried out by adjusting experimental parameters such as the liquid flow rate and the spraying time. Besides, the performances of this spraying technique were compared with two others covering methods found in the literature which are drop casting and absorption coating. A homogeneity study, conducted by SER-CI and matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) applied to the different covering techniques was performed. The influence of the metallic nanoparticles deposit on soluble compounds was also investigated in order to highlight the advantages of using this new spray coating approach.

Multispectral UV imaging for fast and non-destructive quality control of chemical and physical tablet attributes

Monitoring of tablet quality attributes in direct vicinity of the production process requires analytical techniques that allow fast, non-destructive, and accurate tablet characterization. The overall objective of this study was to investigate the applicability of multispectral UV imaging as a reliable, rapid technique for estimation of the tablet API content and tablet hardness, as well as determination of tablet intactness and the tablet surface density profile. One of the aims was to establish an image analysis approach based on multivariate image analysis and pattern recognition to evaluate the potential of UV imaging for automatized quality control of tablets with respect to their intactness and surface density profile. Various tablets of different composition and different quality regarding their API content, radial tensile strength, intactness, and surface density profile were prepared using an eccentric as well as a rotary tablet press at compression pressures from 20MPa up to 410MPa. It was found, that UV imaging can provide both, relevant information on chemical and physical tablet attributes. The tablet API content and radial tensile strength could be estimated by UV imaging combined with partial least squares analysis. Furthermore, an image analysis routine was developed and successfully applied to the UV images that provided qualitative information on physical tablet surface properties such as intactness and surface density profiles, as well as quantitative information on variations in the surface density. In conclusion, this study demonstrates that UV imaging combined with image analysis is an effective and non-destructive method to determine chemical and physical quality attributes of tablets and is a promising approach for (near) real-time monitoring of the tablet compaction process and formulation optimization purposes.

Recent Advances in Solid-State Analysis of Pharmaceuticals

Current analytical techniques for characterizing solid-state pharmaceuticals include powder x-ray diffraction, differential scanning calorimetry, thermogravimetric analysis, infrared spectroscopy, Raman spectroscopy, electron microscopy and nuclear magnetic resonance. Powder x-ray diffraction and differential scanning calorimetry are mainstream techniques but they lack spatial resolution. Scanning electron microscopy and micro-Raman spectroscopy provide good chemical and optical characterization but they are not capable of analysing very small nanoparticles. Transmission electron microscopy and nano-thermal analysis can provide explicit characterization of nanoparticles but they are invasive. Nuclear magnetic resonance offers good spatial resolution but its use is mainly limited by poor sensitivity and high costs. In view of the many challenges posed by existing methods, new and novel techniques are being continually researched and developed to cater to the growing number of solid formulations in the pipeline and in the market. Some of the recent advances attained in the solid-state analysis of pharmaceutical are summarized in this review article.

Determination of acetylsalicylic acid in commercial tablets by SERS using silver nanoparticle-coated filter paper

In this work, filter paper was used as a low cost substrate for silver nanoparticles in order to perform the detection and quantification of acetylsalicylic acid by SERS in a commercial tablet. The reaction conditions were 150mM of ammonium hydroxide, 50mM of silver nitrate, 500mM of glucose, 12min of the reaction time, 45°C temperature, pretreatment with ammonium hydroxide and quantitative filter paper (1-2μm). The average size of silver nanoparticles deposited on the paper substrate was 180nm. Adsorption time of acetylsalicylic acid on the surface of the silver-coated filter paper was studied and an adsorption time of 80min was used to build the analytical curve. It was possible to obtain a calibration curve with good precision with a coefficient of determination of 0.933. The method proposed in this work was capable to quantify acetylsalicylic acid in commercial tablets, at low concentration levels, with relative error of 2.06% compared to the HPLC. The preparation of filter paper coated with silver nanoparticles using Tollen's reagent presents several advantages such as low cost of synthesis, support and reagents; minimum amount of residuals, which are easily treated, despite the SERS spectroscopy presenting fast analysis, with low sample preparation and low amount of reactants as in HPLC analysis.

Applications of surface-enhanced Raman scattering in advanced bio-medical technologies and diagnostics

In this review of the literature on surface-enhanced Raman scattering (SERS), we describe recent developments of this technique in the medical field. SERS has developed rapidly in the last few years as a result of the fascinating advancements in instrumentation and the ability to interpret complex Raman data using high-processional, computer-aided programs. This technique, has many advantages over ordinary spectroscopic analytical techniques - such as extremely high sensitivity, molecular selectivity, intense signal and great precision - that can be leveraged to address complex medical diagnostics problems. This review focuses on the SERS-active substrate, as well as major advances in cancer and bacteria detection and imaging. Finally, we present a perspective on anticipated future advancements in SERS techniques to address some of the most critical challenges in the areas of diagnostics, detection, and sensing.

Epoxy/Polycaprolactone Systems with Triple-Shape Memory Effect: Electrospun Nanoweb with and without Graphene Versus Co-Continuous Morphology

Triple-shape memory epoxy (EP)/polycaprolactone (PCL) systems (PCL content: 23 wt %) with different structures (PCL nanoweb embedded in EP matrix and EP/PCL with co-continuous phase structure) were produced. To set the two temporary shapes, the glass transition temperature (Tg) of the EP and the melting temperature (Tm) of PCL served during the shape memory cycle. An attempt was made to reinforce the PCL nanoweb by graphene nanoplatelets prior to infiltrating the nanoweb with EP through vacuum assisted resin transfer molding. Morphology was analyzed by scanning electron microscopy and Raman spectrometry. Triple-shape memory characteristics were determined by dynamic mechanical analysis in tension mode. Graphene was supposed to act also as spacer between the nanofibers, improving the quality of impregnation with EP. The EP phase related shape memory properties were similar for all systems, while those belonging to PCL phase depended on the structure. Shape fixity of PCL was better without than with graphene reinforcement. The best shape memory performance was shown by the EP/PCL with co-continuous structure. Based on Raman spectrometry results, the characteristic dimension of the related co-continuous network was below 900 nm.