Quantification Of Active Pharmaceutical Ingredients Research Articles

Quantification of API content in pharmaceutical tablets within milliseconds by time-stretch near-infrared transmission spectroscopy

We explored the feasibility of high-speed and high-accuracy quantification of active pharmaceutical ingredient (API) content in tablet products by near-infrared (NIR) spectroscopy to improve the reliability of pharmaceuticals. For this purpose, we employed a high-power NIR time-stretch transmission spectrometer recently developed by us. By using this transmission spectrometer with a multivariate calibration model, we demonstrated the ability to quantify API content with a short measurement time of 3.9 ms per tablet for model pharmaceuticals. For the model tablet, the quantification ability of our spectrometer was comparable to that achieved by a commonly used Fourier-transform NIR (FT-NIR) spectrometer with a measurement time of several seconds. We also confirmed that the effect of irradiating tablets with the NIR pulses used in our spectrometer was negligible.

The feasibility of Raman spectroscopy for accurate assessment of essential criteria in pharmaceutical industry by investigation of Metformin hydrochloride tableting process

AbstractAnalytical and real‐time technology in pharmaceutical manufacturing process is an important need to ensure that manufactured drugs are safe and effective. Raman spectroscopy is an emerging technique that is able to perform quantitative analysis nondestructively due to the molecular structure of many drugs. Monitoring the content uniformity and quantification of active pharmaceutical ingredient (API) in the tablet preparation process, without the assistance of solvent, is one of the key concerns in the formulation design in order to provide stable, pure, and homogenous finished products. In this study, we investigated the possibility of using Raman data as an analytical method to quantify API, the intra‐ and inter‐sample uniformity of content in the tableting process of Metformin hydrochloride tablets (C4H11N5.HCl). Analysis of all standard samples for prediction of API uniformity represents an acceptable accuracy and precision with a relative standard deviation of 2.55%. Further investigation of tablets regarding to relative Raman intensity of some characteristic peaks demonstrates the amount of API content with an accuracy of ≥96%. These values have a good adaption with pharmacopeia monograph. Findings reveal that the Raman method can be routinely utilized for quantifying API, controlling the content uniformity and the stability of drugs in different stages of manufacturing.

Characterization of famotidine API and simultaneous Quantification of its organic impurities by UPLC

To evaluate the characterization of Famotidine API (active pharmaceutical ingredient) and develop the accurate, precise, linear ultra-performance liquid chromatographic (UPLC) method for quantitating determination of organic impurities (Impurity-A, Impurity-B, and Impurity-C) in Famotidine API, pharmaceutical dosage forms and the method has been validated as per international council of harmonization (ICH) guidelines. The Famotidine API characterization was done by using spectroscopic techniques such as mass, infrared spectroscopy (IR), differential scanning calorimetry (DSC), proton nuclear magnetic resonance (1H-NMR), Carbon-13 nuclear magnetic resonance (C13-NMR), and two-dimensional nuclear magnetic resonance (2D-NMR). The organic impurities (A, B, and C) quantification was done using ACQUITY UPLC CSH C18- 100 mm × 2.1 mm, 1.7 μm column connected to ACQUITY UPLC with PDA detector. The optimized chromatographic conditions were achieved at 0.3 mL/min flow rate using a gradient system with 0.1% Tri fluoro acetic acid in water acetonitrile and Methanol as mobile phase. Three organic impurities are measured at λmax 260 nm at 45°C column temperature. Famotidine structure was confirmed by the appraised complete characterization data. The coefficient of correlation (r2) for the Impurity-A, Impurity-B, and Impurity-C was obtained not less than 0.99. The limit of detection (LOD) obtained 0.12 µg/mL and the limit of quantification (LOQ) obtained 0.4 µg/mL for each impurity concerning Famotidine test concentration. The method was fully validated as precision, accuracy, LOQ precision, LOQ accuracy, ruggedness, and robustness complying with FDA, ICH, AOAC, and European medicines agency (EMEA) guidelines. The characterization study and the proposed UPLC method were specific, accurate, precise, linear, rugged, and robust for the determination of the three organic impurities in Famotidine API and it can be implemented for its intended use in pharmaceutical industries.

Hot Stage Microscopy-based Method for Determination of Particle Size in Reverse Engineering: Establishment of a Platform Technology Employing Carvedilol as a Model Drug

Aim: To develop a hot stage microscopy based method for determination of particle size in reverse engineering and establishment of a platform technology employing carvedilol as a model drug. It was hypothesized that reverse engineering using thermal methods will suggest a logical path in decoding the innovator’s formulation to develop an efficient generic product and preconize the morphology of an active pharmaceutical ingredient (API). Background: To develop a generic formulation, a detailed analysis of identification, quantification and characterization of APIs and excipients present in the innovator product is a mandatory requirement. Identification of actives, excipients, and manufacturing processes involved in innovator product formulation can be facilitated using reverse engineering studies. Objective: The objective of this study was to establish a platform technology for determination of particle size in reverse engineering using hot stage microscopy (HSM). Method: Method: Differential scanning calorimetry (DSC) and HSM techniques were employed for identification of different unit processes that can affect the particle size distribution of API during formulation. Result: Result: DSC technique helped to unwind information about qualitative as well as quantitative nature of the formulation blend. HSM technique helped to reveal the particulate level properties of the drug present in the blend and formulation. Conclusion: The study concluded that the two thermal techniques DSC and HSM together could be effectively used to reverse engineer a given formulation using a very less sample quantity. The study suggested a logical path in decoding innovator’s formulation to develop an efficient generic product. Moreover, this HSM based thermal method of particle size determination will offer new insight into the decoding of an innovator product in a shorter period.

A Mini-Review on Simultaneous Quantification of Active Pharmaceutical Ingredients By UV and Quality by Design Assisted HPLC Method

Objective: Nowadays, most pharmaceutical formulations contain more than one drug because there are numerous advantages to multicomponent formulations, like patient compliance, enhanced efficacy, synergetic effects of both drugs, etc. This review paper describes the simultaneous estimation methods such as UV spectroscopy and high-performance liquid chromatography (HPLC) to determine various drug molecules and active pharmaceutical ingredients (APIs). In addition, the implementation of the quality by design (QbD) principle is used to illustrate how these approaches can be developed and validated. Method: To estimate the drug content in these multicomponent formulations, several UV spectroscopy and HPLC methods have been developed and validated as per the available literature. UV spectrophotometry and HPLC are among the most critical tools in the analysis of drugs in pharmaceutical formulations. The QbD based optimization approach applies to developing the simultaneous estimation method, which could be designed with predefined objectives, that emphasize the product and process to maintain the desired quality. The QbD approach followed the guidelines mentioned in ICH Q8 (R2). Results: This review article gives brief information regarding the various QbD optimized UV and HPLC methods for simultaneous estimation of multicomponent formulations and their recent applications and elaborates on multiple steps in the development of the HPLC method along with their applications. Conclusion: The available information is very informative for multicomponent analysis, and it will open new paradigms in upcoming research in the field of analysis.

Method development and validation of a near-infrared spectroscopic method for in-line API quantification during fluidized bed granulation

Near-infrared spectroscopy (NIRS) is an excellent process analytical technology (PAT) tool for active pharmaceutical ingredient (API) quantification during fluidized granulation. Therefore, a portable near-infrared spectrometer combined with a new innovative method of extended iterative optimization technique (EIOT) was used to in-line monitor the API content uniformity during fluidized bed granulation. The principal component analysis (PCA) and partial least squares regression (PLSR) were also used to characterize and predict API concentration with changes from 75% to 125% of the label claim to prove the superiority of EIOT. The API content prediction accuracy of the EIOT method was verified through offline High Performance Liquid Chromatography (HPLC) measurement. Also, the spatial distribution of API in granules was visualized by Raman imaging technology. The results showed that the established NIRS method was suitable for the prediction of API content in fluidized bed granulation, which provides a new idea for the determination of API content during granulation.

Development of methods of identification and quantitative determination of active substances in semi-solid dosage forms with sapropel extracts

For use in veterinary medicine for the treatment of the wound process and the prevention of mastitis, the composition and technology of an emulsion-based cream, conventionally called “Saprocream”, has been developed. Clinical trial of the drug “Saprocream” proved its effectiveness and safety for use in the healing of microtraumas, erosions and cracks (wounds) of the udders of cows.
 The aim of the research were was the standardization of the cream under the conventional name “Saprocream” for use in veterinary medicine as a wound healing agent, the development of methods of identification and quantification and their validation.
 Materials and methods. Test samples of emulsion cream type o / v, containing 15 % aqueous extract of sapropel (VES), 10 % oil extract of sapropel (OES), 6 % emulsifier No. 1, 1 % cetylstearyl alcohol, preservatives – 0.01 % nisin, 0.1 % euxil K 100 and purified water up to 100 g were made by phase inversion.
 The methods of pharmacopoeial articles of the European Pharmacopoeia of the 10th edition, SPhU 1.0, as well as industry standards were used to develop methods for identification and quantification of active pharmaceutical ingredients (API) in the developed cream and its standardization.
 Results. The chromatographic profile of the acetone extract from the cream coincides with the chromatographic profile of the reference solution ((PRS) β-carotene), which indicates the presence of substances of carotenoid structure. The absorption spectrum of hexane extraction from the cream in the range from 500 nm to 750 nm has a maximum absorption at a wavelength of 670±2 nm, which coincides with the maximum absorption of hexane solution OES, indicating the presence of chlorophyll.
 A method for quantifying the total mass fraction of humic acids (HA) has been developed and it has been established that the total mass fraction of HA in cream samples with sapropel extracts is 0.828 %.
 The results of the validation of the method show that there is a linear relationship between the concentration of the total mass fraction of HA and the mass of the AES sample with a correlation coefficient of 0.9981 (³ 0.9981). The developed technique is precise, because the value of the relative confidence interval is less than the critical value for the convergence of the results: D %=1.34≤1.60 and the criterion of insignificance of systematic error d=0.51 is fulfilled.
 Conclusions. An emulsion-based cream under the conventional name “Saprocream” has been standardized, methods for identification and quantification of active substances have been developed and validation of the developed methods for use in veterinary medicine as a wound-healing and anti-inflammatory agent has been carried out.

Visualizing and Quantifying Pharmaceutical Compounds within Skin using Coherent Raman Scattering Imaging.

Cutaneous pharmacokinetics (cPK) after topical formulation application has been a research area of particular interest for regulatory and drug development scientists to mechanistically understand topical bioavailability (BA). Semi-invasive techniques, such as tape-stripping, dermal microdialysis, or dermal open-flow microperfusion, all quantify macroscale cPK. While these techniques have provided vast cPK knowledge, the community lacks a mechanistic understanding of active pharmaceutical ingredient (API) penetration and permeation at the cellular level. One noninvasive approach to address microscale cPK is coherent Raman scattering imaging (CRI), which selectively targets intrinsic molecular vibrations without the need for extrinsic labels or chemical modification. CRI has two main methods-coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS)-that enable sensitive and selective quantification of APIs or inactive ingredients. CARS is typically utilized to derive structural skin information or visualize chemical contrast. In contrast, the SRS signal, which is linear with molecular concentration, is used to quantify APIs or inactive ingredients within skin stratifications. Although mouse tissue has commonly been utilized for cPK with CRI, topical BA and bioequivalence (BE) must ultimately be assessed in human tissue before regulatory approval. This paper presents a methodology to prepare and image ex vivo skin to be used in quantitative pharmacokinetic CRI studies in the evaluation of topical BA and BE. This methodology enables reliable and reproducible API quantification within human and mouse skin over time. The concentrations within lipid-rich and lipid-poor compartments, as well as total API concentration over time are quantified; these are utilized for estimates of micro- and macroscale BA and, potentially, BE.

Elucidation for Intratumor Localization of a DDS-based Anticancer Drug and Enhancement of Its Therapeutic Effects via Improvement of the Tumor Microenvironment

In the development of drug delivery system (DDS)-based anticancer drugs, the techniques for the intratumor mapping and quantification of active pharmaceutical ingredients (API) in pharmaceuticals must be pivotal for predicting pharmacological effects and adverse events. X-ray fluorescence spectrometry (XRF) is a potent analytical tool for mapping/quantifying platinum pharmaceutics such as oxaliplatin (l-OHP) and its liposomal formulation. In recent studies, we employed XRF to visualize the intratumor micro-distribution of l-OHP in a tumor-bearing model mouse intravenously injected with either free l-OHP or l-OHP liposomes. The intratumor distribution of l-OHP within tumor sections could be determined by XRF to detect platinum atoms. After treatment with the liposomal formulation, the l-OHP was localized near the tumor vessels and, via repeated injections, increasingly accumulated in tumors by a much greater degree than treatment with free l-OHP. The repeated injections of l-OHP liposomes improved the vascular permeability via inducing the apoptosis of tumor cells near the tumor vessels, which should improve the tumor microenvironment and enhance the intratumor accumulation of repeated doses of l-OHP liposomes. The proposed process was also used to visualize the intratumor distribution of l-OHP in rectal cancer specimens resected from a patient who had received l-OHP-based preoperative chemotherapy. We further revealed that neutralization of an acidic tumor microenvironment via oral administration with NaHCO3 could improve the therapeutic efficacy of weakly basic anticancer agent-encapsulating liposomes. Collectively, mapping/quantifying the intratumor API in DDS drugs and/or improving the tumor microenvironment would be an effective means to accelerate the clinical development of DDS-based anticancer drugs.

Validated Simultaneous Gradient Ultra-Performance Liquid Chromatographic Quantification of Some Proton Pump Inhibitor Drug Residues in Saudi Pharmaceutical Industrial Wastewater.

Monitoring and quantification of active pharmaceutical ingredients (APIs) in the environment constitute important and challenging tasks, as they are directly associated with human health. Three commonly used proton pump inhibitors (PPIs), namely, omeprazole sodium (OMP), pantoprazole sodium (PNT), and lansoprazole sodium (LNZ) are well separated and quantified using ultra-performance liquid chromatography (UPLC) in pharmaceutical industrial wastewater. The separation of the studied drugs was performed on a stationary phase with a WatersTM column (100 × 2.1 mm, 1.7 µm). The mobile phase was composed of methanol:0.05 M potassium dihydrogen phosphate buffer (adjusted to pH 7.5 using NaOH) (50:50, v/v). The elution process was done in gradient mode by changing the relative proportions of the mobile phase components with time to get an optimum separation pattern. The flow rate of the developing system was adjusted to 0.8 mL/minute. Detection of the separated drugs was performed at 230 nm. The studied drugs were quantified in the concentration range of 10–200 ng/mL for all drugs. The cited method was fully validated according to the international conference on harmonization (ICH-Q2B) guidelines, then it was applied successfully for quantification of the studied PPIs in real wastewater samples after their solid phase extraction (SPE).

Confocal laser scanning microscopy as a novel tool of hyperspectral imaging for the localization and quantification of fluorescent active principles in pharmaceutical solid dosage forms

Confocal laser scanning microscopy (CLSM) supported with multivariate analysis is proposed as hyperspectral imaging technique to identify, locate, and quantify, in a direct way, active pharmaceutical ingredients (APIs) in synthetic tablets, with the aim of establishing a new analysis methodology that collects qualitative and quantitative information from the surface and inner layers of solid dosage forms. This method is proposed as a novel, non-destructive, rapid, and highly sensitive hyperspectral imaging technique, with an excellent spatial resolution at the microscopic level. Two chemical systems comprising pharmaceutical mixtures of acetaminophen–caffeine–excipients and digoxin–excipients were analyzed by multivariate curve resolution-alternating least squares (MCR-ALS) using emission spectra obtained from microscopic images with the pixel sizes of 512 μm × 512 μm to localize the APIs in the tablets. In addition, partial least squares (PLS) regression models were developed and used for calibration to obtain the concentration of the fluorescent active ingredients. The analysis by MCR-ALS delivered excellent results in localizing the fluorescent compounds; meanwhile, PLS achieved good error parameters for prediction of the external validation set for the quantification of caffeine and less successful quantification of digoxin. The performance of CLSM was evaluated by estimation of the analytical figures of merit of the technique to assess the quantification of APIs, including calculations of the uncertainty in the signal, sensitivity, analytical sensitivity, and ranges of detection and quantification limits. Use of CLSM as hyperspectral imaging attempts to increase the application of this technique in direct analysis of solid samples, showing that autofluorescent compounds can be analyzed for qualitative and quantitative purposes in presence of interferents by application of chemometrics.

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 (RPDP) 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 RMSEP of 0.72 %, R2P of 0.946 and RPDP 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.

Rapid quantification of active pharmaceutical ingredient for sugar-free Yangwei granules in commercial production using FT-NIR spectroscopy based on machine learning techniques

Rapid quantification methods for sugar-free Yangwei granules were developed based on near-infrared (NIR) spectroscopy combined with machine learning approaches as a quality control strategy for Chinese medicine granules (CMGs). Different machine learning approaches-i.e., interval partial least squares optimized by the genetic algorithm (GA-iPLS), the backpropagation artificial neural network (BP-ANN), and the particle swarm optimization-support vector machine (PSO-SVM)-were used to develop prediction models for three active pharmaceutical ingredients (APIs), namely, albiflorin, paeoniflorin, and benzoylpaeoniflorin. The partial least squares (PLS) algorithm was used for linear model calibration and comparison of the prediction performance of these developed models. The performance of the final models was assessed by the correlation coefficient (R), root mean square error of calibration set (RMSEC), and root mean square error of prediction set (RMSEP). All models performed well in model fitting and provided satisfactory prediction accuracy. The results indicate that the machine learning approaches are more stable, predictable, and suitable for CMGs when a high-accuracy analysis is required. In summary, NIR spectroscopy coupled with machine learning techniques is a suitable tool for the straightforward quantification of CMGs.

Surface enhanced infrared absorption spectroscopy (SEIRA) as a green analytical chemistry approach: Coating of recycled aluminum TLC sheets with citrate capped silver nanoparticles for chemometric quantitative analysis of ternary mixtures as a green alternative to the traditional methods

The past two decades have seen the full expansion of all fields of Nanotechnology, Chemometrics, Recycling, and Vibration spectroscopy into most of the research areas. The proposed method involves the harmonization of the previously mentioned fields as a vital tool to fulfill the concepts of sustainability and green analytical chemistry. This may reduce the negative impact of analytical laboratory activities on the surrounding environment and enables the implementation of sustainable development principles to analytical laboratories. This work compares the performance of surface enhanced infrared spectroscopy (SEIRA) with traditional chromatographic techniques for quantification of active pharmaceutical ingredients concerning the twelve principles of green analytical chemistry. The used aluminum TLC slides were recycled to be used as a SEIRA substrate. Citrate capped silver nanoparticles were synthesized via one step chemical reduction method, characterized, and deposited on the surface of the recycled aluminum TLC slides to be used as an active mid-infrared surface for quantification of the active pharmaceutical ingredient’s combinations. SEIRA coupled with PLSR chemometric tool was developed, validated and successfully applied to mixtures having diverged concentration ranges (5, 30 and 500 μg ml−1) of Pholcodine, Pseudoephedrine and Paracetamol, respectively. Pholcodine is a synthetic or semi-synthetic opium alkaloid that derived from morphine. Pseudoephedrine is a sympathomimetic agent that is prohibited in sports competitions by the world antidoping agency at certain concentration levels. Paracetamol has analgesic and antipyretic actions. After optimization of the method parameters and number of latent factors, a good linear calibration model of the PLSR strategy was obtained as indicated by the lowest root mean square error of calibration and prediction obtained and the regression coefficients R2 of 0.9912, 0.9888, and 0.9992, respectively. The calibration ranges for the three drugs in their pharmaceutical combinations was 2.5–12.5, 15–75 and 200–600 μg ml−1, respectively. The method showed high resolving power for the three drugs in presence of excipients and good recoveries were obtained in a range of 97–102% with relative standard deviation < 2. The developed lab on a chip SEIRA analyzer in comparison to the traditional chromatographic techniques does not only fulfill the twelve principles of GAC but also it combines the merits of high throughput straightforward fingerprint analyzers, portable to measure samples on its place, cost effective, reduced sample volume and solvent consumption, coupled with intelligent chemometric tools to analyze multiple samples, reduced trials and time to get results.

Detection and quantification of active pharmaceutical ingredients as adulterants in Garcinia cambogia slimming preparations using NIR spectroscopy combined with chemometrics

A rapid, simple and efficient method with minimal sample treatment was developed for authentication of Garcinia cambogia fruit peel powder, along with determining undeclared active pharmaceutical ingredients (APIs) in its herbal slimming dietary supplements using near infrared spectroscopy combined with chemometrics. Five featured adulterants, including sibutramine, metformin, orlistat, ephedrine, and theophylline are selected as target compounds. The Near infrared spectral data matrix of authentic Garcinia cambogia fruit peel and specimens degraded by intentional contamination with the five selected APIs was subjected to hierarchical clustering analysis to investigate their bundling figure. SIMCA models were established to ensure the genuiness of Garcinia cambogia fruit peel which resulted in perfect classification of all tested specimens. Adulterated samples were utilized for construction of PLSR models based on different APIs contents at minute levels of fraud practices (LOQ < 0.2% w/w).The suggested approach can be applied to enhance and guarantee the safety and quality of Garcinia fruit peel powder as raw material and in dietary supplements.

Are antibiotics substandard in Lebanon? Quantification of active pharmaceutical ingredients between brand and generics of selected antibiotics

BackgroundIn developing countries, brand-generic substitution is not based on validated scientific evidence that confirm the therapeutic equivalence of the generic to the originator. Rather, decisions are made based on the availability of generic medications. Substitution by inappropriate preparations applies to antibiotics, which may increase the risk of resistance in case of underdosing. This analytical study aims to dose and assess for the accuracy of labeling three oral antibiotic preparations, namely ciprofloxacin hydrochloride, amoxicillin trihydrate and amoxicillin trihydrate-clavulanate potassium, the active pharmaceutical ingredients (APIs) found in brand and generic tablets available on the Lebanese market.MethodsOne brand and 4 generics of ciprofloxacin tablets, 3 generic amoxicillin tablets, and 1 brand and 4 generics of amoxicillin-clavulanic acid medications, were quantified, taking 2 batches of each. According to the United States Pharmacopeia (USP) guidelines, ultra-high pressure liquid chromatography was used to measure the APIs content within tablets. The USP required assay limit of the API was taken as the main comparison criteria.ResultsOut of the 5 ciprofloxacin medications tested, all 5 were out of the 2% required range, thus being substandard. For amoxicillin, all 3 medications were within the 20% range. As for amoxicillin-clavulanic acid medications, 4 out of 5 medications met the 30% required range of clavulanic acid and one exceeded the claimed amount of clavulanic acid, while all 5 met the assay limit for amoxicillin.ConclusionThese findings raise safety and efficacy concerns, providing solid grounds for potential correlations of antibiotic resistance/substandard antibiotics.

Raman microimaging as an analytical technique for simultaneous quantification and localization of active principles in pharmaceutical solid dosage forms

AbstractRaman microimaging, as a product of Raman microspectroscopy mapping and multivariate analysis, was used for the localization and quantification of active pharmaceutical ingredients (APIs) in tablets made in laboratory. This was done to develop an analytical strategy to simultaneously recover qualitative and quantitative information of solid dosage forms at a microscopic level by using a nondestructive method. A chemical system, composed of acetaminophen (AMP), caffeine, and one excipient (microcrystalline cellulose), was subjected to chemometric analysis through principal component analysis (PCA) and multivariate curve resolution with alternating least squares (MCR–ALS). This was done by using Raman spectra obtained from microscopic images with pixel sizes of 15 × 15 μm to localize the APIs in the tablets. Partial least squares (PLS) was applied as a calibration method to obtain bulk and single‐pixel concentrations of APIs in the samples. MCR–ALS provided better results than PCA for the localization of APIs. PLS achieved satisfactory root mean standard error values in the external validation set (&lt;4% w/w) in bulk concentration determinations of AMP. This method also achieved concentrations for each pixel of the images, reconstructing images very similar to those obtained by MCR–ALS. Consequently, simultaneous localization and quantification of AMP was possible. Finally, the performance of Raman microimaging was evaluated through estimation of analytical figures of merit (AFOMs) of the technique used to assess the quantification of APIs. This included different calculus of uncertainty in the signal in a technique where the signal/noise ratio is low, and AFOMs for multivariate quantification are not often reported.

Transmission Raman Spectroscopic Quantification of Active Pharmaceutical Ingredient in Coated Tablets of Hot-Melt Extruded Amorphous Solid Dispersion.

Transmission Raman spectroscopy is an emerging technique, capable of quantitative analysis of drug products nondestructively using a multivariate data analysis approach. We developed and validated a chemometric method to quantify the active pharmaceutical ingredient in coated tablets of hot-melt extruded amorphous solid dispersion. A partial least squares regression (PLSR) model was developed and validated based on transmission Raman spectra data collected from coated tablet samples with variations in the content of active pharmaceutical ingredient, excipients, water content, a key oxidative degradant, milled extrudate particle size distribution, and tablet hardness. The method was proven to be accurate, linear, specific, and robust. Our work demonstrates that transmission Raman spectroscopy (TRS) is a viable, cost-effective, secondary method to high-performance liquid chromatography (HPLC) for quantitation of active pharmaceutical ingredient (API) in coated tablets of hot-melt extruded amorphous solid dispersion.

Quantification of Inkjet-Printed Pharmaceuticals on Porous Substrates Using Raman Spectroscopy and Near-Infrared Spectroscopy.

The use of inkjet printing for pharmaceutical manufacturing is gaining interest for production of personalized dosage forms tailored to specific patients. As part of the manufacturing, it is imperative to ensure that the correct dose is printed. The aim of this study was to use inkjet printing for manufacturing of personalized dosage forms combined with the use of near-infrared (NIR) and Raman spectroscopy as complementary analytical techniques for active pharmaceutical ingredient (API) quantification of the inkjet-printed dosage forms. Three APIs, propranolol (0.5-4.1mg), montelukast (2.1-12.1mg), and haloperidol (0.6-4.1mg) were inkjet printed in 1cm2 areas on a porous substrate. The printed doses were non-destructively analyzed by transmission NIR and Raman spectroscopy (both transmission and backscatter). X-ray computed microtomography (μ-CT) analysis was undertaken for porosity measurements of the substrate. The API content was confirmed using high-performance liquid chromatography (HPLC), and the content in the dosage forms was modeled from the NIR and Raman spectra using partial least squares regression (PLS). HPLC analysis revealed a linear correlation of the number of layers printed to the API content. The resulting PLS models for both NIR and Raman had R2 values between 0.95 and 0.99. The best predictive model was obtained using NIR, followed by Raman spectroscopy. μ-CT revealed the substrate to be highly porous and optimal for inkjet printing. In conclusion, NIR and Raman spectroscopic techniques could be used complementary as fast API quantification tools for inkjet-printed medicines.

Quantifying API polymorphs in formulations using X-ray powder diffraction and multivariate standard addition method combined with net analyte signal analysis

The direct quantification of Active Pharmaceutical Ingredients in solid formulations is a challenging open issue. A consolidated analytical technique based on X-ray Powder Diffraction is available, being the definitive test for the identification of polymorphs and crystal phases. However, its application for quantitative analysis is hindered by matrix effects: refinement methods (e.g. Rietveld method) require a complete knowledge of samples' composition, while univariate calibration methods require the matrix effect to be studied and severely suffer from the co-presence of crystalline and amorphous phases in the sample. Multivariate analysis is the only way to bypass problems affecting refinements procedures and univariate calibration. In particular, the multivariate standard addition method (SAM) is promising; however, it is straightforward only when the analytical blank (matrix devoid of analyte) is available: in that case SAM is applied by simply extrapolating the SAM model to the matrix experimental signal. In this work, the quantitative analysis of polymorphic forms of Active Pharmaceutical Ingredients based on X-ray Powder Diffraction is performed for the first time by a method based on multivariate standard addition method combined with net analyte signal procedure; it allows for reliable quantification of polymorphs of active principles in solid formulations, which are rapidly analyzed without any sample pre-treatment. Two test cases are presented: quantification of two polymorphs of piracetam in binary mixtures (forms II and III), and quantification of paracetamol (form I) in Tachifludec®.