Near infra red spectroscopy: a tool for solid state characterization

Assessing Polymorphic Purity of Rifampicin in Double and Triple-Drug Fixed-Dose Combination Products

First-line tuberculostatic agents, Rifampicin (RIF), Isoniazid (ISH), Ethambutol (ETB), and Pyrazinamide (PZA) are generally administered as a fixed-dose combination (FDC) for improving patient adherence. The major quality challenge of these FDC products is their variable bioavailability, where RIF and its solid state are key factors. In this work, the analysis of the impact of the polymorphism in the performance of RIF in RIF-ISH and PZA-RIF-ISH combined products was carried out by an overall approach that included the development and validation of two methodologies combining near-infrared (NIR) spectroscopy and partial least squares (PLS) to the further evaluation of commercial products. For NIR-PLS methods, training and validation sets were prepared with mixtures of Form I/Form II of RIF, and the appropriate amount of ISH (for double associations) or ISH-PZA (for triple associations). The corresponding matrix of the excipients was added to the mixture of APIs to simulate the environment of each FDC product. Four PLS factors, reduced spectral range, and the combination of standard normal variate and Savitzky-Golay 1st derivative (SNV-D') were selected as optimum data pre-treatment for both methods, yielding satisfactory recoveries during the analysis of validation sets (98.5±2.0%, and 98.7±1.8% for double- and triple-FDC products, respectively). The NIR-PLS model for RIF-ISH successfully estimated the polymorphic purity of Form II in double-FDC capsules (1.02 ± 0.02w/w). On the other hand, the NIR-PLS model for RIF-ISH-PZA detected a low purity of Form II in triple FDC tablets (0.800 ± 0.021w/w), these results were confirmed by X-ray powder diffraction. Nevertheless, the triple-FDC tablets showed good performance in the dissolution test (Q=99-102%), implying a Form II purity about of 80% is not low enough to affect the safety and efficacy of the product.

Crystallinity: A Complex Critical Quality Attribute of Amorphous Solid Dispersions

Does the performance of an amorphous solid dispersion rely on having 100% amorphous content? What specifications are appropriate for crystalline content within an amorphous solid dispersion (ASD) drug product? In this Perspective, the origin and significance of crystallinity within amorphous solid dispersions will be considered. Crystallinity can be found within an ASD from one of two pathways: (1) incomplete amorphization, or (2) crystal creation (nucleation and crystal growth). While nucleation and crystal growth is the more commonly considered pathway, where crystals originate as a physical stability failure upon accelerated or prolonged storage, manufacturing-based origins of crystallinity are possible as well. Detecting trace levels of crystallinity is a significant analytical challenge, and orthogonal methods should be employed to develop a holistic assessment of sample properties. Probing the impact of crystallinity on release performance which may translate to meaningful clinical significance is inherently challenging, requiring optimization of dissolution test variables to address the complexity of ASD formulations, in terms of drug physicochemical properties (e.g., crystallization tendency), level of crystallinity, crystal reference material selection, and formulation characteristics. The complexity of risk presented by crystallinity to product performance will be illuminated through several case studies, highlighting that a one-size-fits-all approach cannot be used to set specification limits, as the risk of crystallinity can vary widely based on a multitude of factors. Risk assessment considerations surrounding drug physicochemical properties, formulation fundamentals, physical stability, dissolution, and crystal micromeritic properties will be discussed.

Amorphous Solid Dispersion as Drug Delivery Vehicles in Cancer

Cancer treatment has improved over the past decades, but a major challenge lies in drug formulation, specifically for oral administration. Most anticancer drugs have poor water solubility which can affect their bioavailability. This causes suboptimal pharmacokinetic performance, resulting in limited efficacy and safety when administered orally. As a result, it is essential to develop a strategy to modify the solubility of anticancer drugs in oral formulations to improve their efficacy and safety. A promising approach that can be implemented is amorphous solid dispersion (ASD) which can enhance the aqueous solubility and bioavailability of poorly water-soluble drugs. The addition of a polymer can cause stability in the formulations and maintain a high supersaturation in bulk medium. Therefore, this study aimed to summarize and elucidate the mechanisms and impact of an amorphous solid dispersion system on cancer therapy. To gather relevant information, a comprehensive search was conducted using keywords such as "anticancer drug" and "amorphous solid dispersion" in the PubMed, Scopus, and Google Scholar databases. The review provides an overview and discussion of the issues related to the ASD system used to improve the bioavailability of anticancer drugs based on molecular pharmaceutics. A thorough understanding of anticancer drugs in this system at a molecular level is imperative for the rational design of the products.

Characterization of the hydrochloride salt hemihydrate as a new salt of the antifungal agent tioconazole

Tioconazole is an effective antifungal agent, which has a very low solubility in aqueous media, that limits its bioavailability and efficacy. In an effort to overcome the drug limitations by improving its solubility, the hydrochloride salt was prepared in methanolic 1M HCl and obtained as the hemihydrate, as demonstrated by elemental analysis. Single crystals were grown by slow evaporation from an aqueous 1M HCl solution and their structure was determined using single-crystal X-ray diffraction at 302 K. The structures resulting from dehydration and further rehydration were also assessed, at 333 and 283 K, respectively. The morphology of the crystal, which exhibited birefringence under polarized light, was verified by hot stage microscopy. The solid was characterized by additional means, including thermal analysis (melting point, differential scanning calorimetry and thermogravimetry), spectroscopic methods (mid infrared, near infrared, ¹H, ¹³C and ¹⁵N nuclear magnetic resonance in solution, as well as ¹³C and ¹⁵N solid state with spinning at the magic angle) and X-ray diffraction techniques. Functional evaluation tests, including the intrinsic dissolution rate and the dissolution of powders were also performed. In the intrinsic dissolution rate test, the salt proved to dissolve over 2000 times faster than tioconazole. The results suggest that the new salt has physicochemical and performance properties which may support its use as a replacement of the free base in certain applications, especially where improved dissolution rate, solubility or bioavailability of the drug would be desired.

Machine Learning-Enabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data

An increasingly large dataset of pharmaceutics disciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy. The preceding article (Muthudoss et al.. in AAPS PharmSciTech 23, 2022) describes a workflow for leveraging near infrared (NIR) spectroscopy to obtain reliable and robust data on pharmaceutical samples. This study describes the systematic and structured procedure for selecting subsamples from the historical data. We offer a wide range of in-depth quality measures, diagnostic tools, and visualization techniques. A real-world, well-researched NIR dataset was employed to demonstrate this approach. This open-source tablet dataset ( http://www.models.life.ku.dk/Tablets ) consists of different doses in milligrams, different shapes, and sizes of dosage forms, slots in tablets, three different manufacturing scales (lab, pilot, production), coating differences (coated vs uncoated), etc. This sample is appropriate; that is, the model was developed on one scale (in this research, the lab scale), and it can be great to investigate how well the top models are transferable when tested on new data like pilot-scale or production (full) scale. A literature review indicated that the PLS regression models outperform artificial neural network-multilayer perceptron (ANN-MLP). This work demonstrates the selection of appropriate hyperparameters and their impact on ANN-MLP model performance. The hyperparameter tuning approaches and performance with available references are discussed for the data under investigation. Model extension from lab-scale to pilot-scale/production scale is demonstrated. HIGHLIGHTS: • We present a comprehensive quality metrics and visualization strategy in selecting subsamples from the existing studies • A comprehensive assessment and workflow are demonstrated using historical real-world near-infrared (NIR) data sets • Selection of appropriate hyperparameters and their impact on artificial neural network-multilayer perceptron (ANN-MLP) model performance • The choice of hyperparameter tuning approaches and performance with available references are discussed for the data under investigation • Model extension from lab-scale to pilot-scale successfully demonstrated.

Near-infrared spectroscopy combined with chemometrics to classify cosmetic foundations from a crime scene

Cosmetic smears are a form of trace evidence that can link the crime scene, suspects, and victims. Foundation and lipstick are the most common sources of cosmetics that can easily smear, with most current research focused on the evidential analysis of lipsticks. This research aims to create a database of cosmetic foundations on different materials and to access the robustness of using Near-infrared with chemometrics as a non-destructive technique to identify unknown samples collected from a crime scene. Small amounts of six shades of three brands of foundations were smeared on clothing materials, which were then analysed with a combination of Near-infrared with chemometric analysis. Principle component analysis (PCA) was used to reduce data dimensionality and explore potential patterns in sample separation and Linear Discriminant Analysis (LDA) was utilised to assign unknown samples to one of the established classes. The selected techniques proved to be promising for database construction and as a preliminary method of analysis, with 93% of the spectra being correctly classified. Notably, darker foundation shades were less likely to be correctly classified (90% classified correctly) compared to lighter ones (96.7% classified correctly). This could not be improved with Standard Normal Variate (SNV) data pre-treatment or selecting specific NIR regions. This finding is of particular importance; according to the Crime Survey for England and Wales (year ending March 2020) police recorded sexual offences demonstrated that those in Mixed and Black or Black British ethnic groups were significantly more likely to be a victim of sexual assault compared to White, Asian or Other ethnic groups. It is, therefore, crucial to add a wide range of foundation shades, particularly of darker tones, to the future database.

Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy

Selective laser sintering (SLS) 3D printing is capable of revolutionising pharmaceutical manufacturing, by producing amorphous solid dispersions in a one-step manufacturing process. Here, 3D-printed formulations loaded with a model BCS class II drug (20% w/w itraconazole) and three grades of hydroxypropyl cellulose (HPC) polymer (-SSL, -SL and -L) were produced using SLS 3D printing. Interestingly, the polymers with higher molecular weights (HPC-L and -SL) were found to undergo a uniform sintering process, attributed to the better powder flow characteristics, compared with the lower molecular weight grade (HPC-SSL). XRPD analyses found that the SLS 3D printing process resulted in amorphous conversion of itraconazole for all three polymers, with HPC-SSL retaining a small amount of crystallinity on the drug product surface. The use of process analytical technologies (PAT), including near infrared (NIR) and Raman spectroscopy, was evaluated, to predict the amorphous content, qualitatively and quantitatively, within itraconazole-loaded formulations. Calibration models were developed using partial least squares (PLS) regression, which successfully predicted amorphous content across the range of 0–20% w/w. The models demonstrated excellent linearity (R² = 0.998 and 0.998) and accuracy (RMSEP = 1.04% and 0.63%) for NIR and Raman spectroscopy models, respectively. Overall, this article demonstrates the feasibility of SLS 3D printing to produce solid dispersions containing a BCS II drug, and the potential for NIR and Raman spectroscopy to quantify amorphous content as a non-destructive quality control measure at the point-of-care.

Industry White Paper: Contemporary Opportunities and Challenges in Characterizing Crystallinity in Amorphous Solid Dispersions

Members of the IQ Consortium ″Working Group on Characterization on Amorphous Solid Dispersions″ shares here a perspective on the analytical challenges, and limitations of detecting low levels of crystalline drug substance in amorphous solid dispersions (ASDs) and associated drug products. These companies aim to employ highly sensitive commercially available analytical technologies to guide development, support control strategies, and enable registration of quality products. We hope to promote consistency in development and registration approaches and guide the industry in development of "characterization best practices" in the interest of providing high quality products for patients. The first half of this perspective highlights the unique challenges of analytical methodologies to monitor crystalline drug substance in ASDs and their associated drug products. Challenges around use of limit tests, analyte spiking experiments, and method robustness are also underscored. The latter half describes the merits and limitations of the diverse analytical "toolbox" (such as XRPD, NIR and DSC), which can be readily applied during development and, in some cases, considered for potential application and validation in the commercial QC setting when necessary.

Injection-Molded Coamorphous Tablets: Analysis of Intermolecular Interaction and Crystallization Propensity

The processing steps involved in converting from a powder to a tablet entail numerous operations in a which the coamorphous system is recrystallized and dissociated easily. This research focused on (i) a single-step preparation of a coamorphous tablet during injection molding (IM) from the bulk powder, and (ii) a mechanistic characterization of the coamorphous formulation. We selected several organic acids [citric acid, succinic acid, tartaric acid, and malic acid] in an effort to compound with basic loratadine (a poorly water-soluble drug). Loratadine-acids coamorphous tablets were produced via an IM process, and the dissolution was more enhanced than in the pure loratadine amorphous. The interaction was analyzed by FT-IR and terahertz spectroscopies. Each tablet was stored at 40 °C/75%RH, and then XRD patterns were acquired at the desired timepoints. In summary, loratadine exhibited ionic interaction with each acid, and the physical stability of the coamorphous tablet was in proportion to the loratadine-acids interaction strength. Terahertz spectra detected the molecular mobility, which plays an important role in the crystallization propensity of a coamorphous system. This understanding offers a framework for robust coamorphous tablet formulation using the IM methodology.

Principles and Applications of Miniaturized Near-Infrared (NIR) Spectrometers

This review article focuses on the principles and applications of miniaturized near-infrared (NIR) spectrometers. This technology and its applicability has advanced considerably over the last few years and revolutionized several fields of application. What is particularly remarkable is that the applications have a distinctly diverse nature, ranging from agriculture and the food sector, through to materials science, industry and environmental studies. Unlike a rather uniform design of a mature benchtop FTNIR spectrometer, miniaturized instruments employ diverse technological solutions, which have an impact on their operational characteristics. Continuous progress leads to new instruments appearing on the market. The current focus in analytical NIR spectroscopy is on the evaluation of the devices and associated methods, and to systematic characterization of their performance profiles.

Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models

The present paper reports a thorough continuous powder blending process design of acetylsalicylic acid (ASA) and microcrystalline cellulose (MCC) based on the Process Analytical Technology (PAT) guideline. A NIR-based method was applied using multivariate data analysis to achieve in-line process monitoring. The process dynamics were described with residence time distribution (RTD) models to achieve deep process understanding. The RTD was determined using the active pharmaceutical ingredient (API) as a tracer with multiple designs of experiment (DoE) studies to determine the effect of critical process parameters (CPPs) on the process dynamics. To achieve quality control through material diversion from feeding data, soft sensor-based process control tools were designed using the RTD model. The operation block model of the system was designed to select feasible experimental setups using the RTD model, and feeder characterizations as digital twins, therefore visualizing the output of theoretical setups. The concept significantly reduces the material and instrumental costs of process design and implementation.

Quantitative Microscopy: Particle Size/Shape Characterization, Addressing Common Errors Using 'Analytics Continuum' Approach

Particle size/shape characterization of active pharmaceutical ingredient (API) is integral to successful product development. It is more of a correlative property than a decision-making measure. Though microscopy is the only technique that provides a direct measure of particle properties, it is neglected for reasons like non-repeatability and non-reproducibility which is often attributed to a) fundamental error, b) segregation error, c) human error, d) sample randomness, e) sample representativeness etc. Using the "Sucrose" as model sample, we propose "analytics continuum" approach that integrates optical microscope PSD measurements complimented by NIR spectroscopy-based trending analysis as a prescreening tool to demonstrate sample randomness and representativeness. Furthermore, plethora of statistical tests are utilized to infer population statistics. Subsequently, an attribute-based control chart and bootstrap-based confidence interval was developed to monitor product performance. A flowchart to serve as an elementary guideline is developed, which is then extended to handle more complex situations involving API crystallized from two different solvent systems. The results show that the developed methodology can be utilized as a quantitative procedure to assess the suitability of API/excipients from different batches or from alternate vendors and can significantly help in understanding the differences between material even on a minor scale.

Amorphous solid dispersions: An update for preparation, characterization, mechanism on bioavailability, stability, regulatory considerations and marketed products

Amorphous solid dispersions (ASDs) are being employed frequently to improve bioavailability of poorly soluble molecules by enhancing the rate and extant of dissolution in drug product development process. These systems comprise of an amorphous active pharmaceutical ingredient stabilized by a polymer matrix to provide enhanced stability. This review discussed the methodologies of preparation and characterization of ASDs with an emphasis on understanding and predicting stability. Rational selection of polymers, preparation techniques with its advantages and disadvantages and characterization of polymeric amorphous solid dispersions have discussed. Stability aspects have been described as per ICH guidelines which intend to depend on selection of polymers and preparation methods of ASD. The mechanism involved on improvement of bioavailability also considered. Regulatory importance of ASD and current evolving details of QBD approach were reviewed. Amorphous products and particularly ASDs are currently most emerging area in the pharmaceutical field. This strategic approach presents huge impact and advantageous features concerning the overall improvement of drug product performance in clinical settings which ultimately lead to drug product approval by leading regulatory agencies into the market.

Manipulation of Pharmaceutical Polymorphic Transformation Process Using Excipients

BACKGROUND

In the pharmaceutical field, it is vital to ensure a consistent product containing a single solid-state form of the active pharmaceutical ingredient (API) in the drug product. However, some APIs are suffering from the risk of transformation of their target forms during processing, formulation and storage.

METHODS

The purpose of this review is to summarize the relevant category of excipients and demonstrate the availability and importance of using excipients as a key strategy to manipulate pharmaceutical polymorphic transformation.

RESULTS

The excipient effects on solvent-mediated phase transformations, solid-state transitions and amorphous crystallization are significant. Common pharmaceutical excipients including amino acids and derivatives, surfactants, and various polymers and their different manipulation effects were summarized and discussed.

CONCLUSION

Appropriate use of excipients plays a role in manipulating polymorphic transformation process of corresponding APIs, with a promising application of guaranteeing the stability and effectiveness of drug dosage forms.