Prediction of Drug Dissolution from Tablets Using Near‐Infrared Diffuse Reflectance Spectroscopy as a Nondestructive Method

Regulatory Experience with Continuous Manufacturing and Real Time Release Testing for Dissolution in New Drug Applications

Regulatory submissions involving the use of continuous manufacturing (CM)1 and/or real-time release testing for dissolution (RTRT-D) to the United States Food and Drug Administration (FDA) were identified spanning several years. The submissions were for orally administered IR tablets and they were examined from a biopharmaceutics perspective to highlight commonly occurring issues which the FDA's assessment teams identified with the proposed use of CM and/or RTRT-D. The objective of this study is to provide recommendations for best practices that will help advance the field by (i) generating greater opportunities for (drug) Applicants2 to benefit from the implementation of advanced manufacturing approaches, (ii) improving high quality regulatory submissions involving CM and RTRT-D, and thus (iii) lessening the regulatory review burden. This paper has identified several common deficiencies, such as inadequate strategies for stratified sampling of drug product (DP) units, inappropriate design of experiments (DoE), inability of the proposed RTRT-D model to account for dissolution variability and to predict the entire time course of dissolution, insufficient documentation, and unsuitable in vitro dissolution methods.

Imaging techniques for studying solid dosage formulation: Principles and applications

Classic methods for evaluating the disintegration and dissolution kinetics of solid dosage forms are no longer sufficient to meet the growing demands in the pharmaceutical field. Hence, scientists have turned to imaging techniques and computer technology to develop innovative visualization methods. These methods allow for a visual understanding of the disintegration or dissolution process and offer valuable insights into the drug release kinetics. This article aims to provide an overview of the commonly used imaging techniques and their applications in studying the disintegration or dissolution of solid dosage forms. Therefore, imaging presents a novel and alternative approach to understanding the mechanisms of disintegration and dissolution in the formulation study of solid dosages.

Releasing fast and slow: Non-destructive prediction of density and drug release from SLS 3D printed tablets using NIR spectroscopy

Selective laser sintering (SLS) 3D printing is a revolutionary 3D printing technology that has been found capable of creating drug products with varied release profiles by changing the laser scanning speed. Here, SLS 3D printed formulations (printlets) loaded with a narrow therapeutic index drug (theophylline) were produced using SLS 3D printing at varying laser scanning speeds (100-180 mm/s). The use of reflectance Fourier Transform - Near Infrared (FT-NIR) spectroscopy was evaluated as a non-destructive approach to predicting 3D printed tablet density and drug release at 2 h and 4 h. The printed drug products formulated with a higher laser speed exhibited an accelerated drug release and reduced density compared with the slower laser scanning speeds. Univariate calibration models were developed based on a baseline shift in the spectra in the third overtone region upon changing physical properties. For density prediction, the developed univariate model had high linearity (R² value = 0.9335) and accuracy (error < 0.029 mg/mm³). For drug release prediction at 2 h and 4 h, the developed univariate models demonstrated a linear correlation (R² values of 0.9383 and 0.9167, respectively) and accuracy (error < 4.4%). The predicted vs. actual dissolution profiles were found to be statistically similar (f₂ > 50) for all of the test printlets. Overall, this article demonstrates the feasibility of SLS 3D printing to produce drug products containing a narrow therapeutic index drug across a range of drug release profiles, as well as the potential for FT-NIR spectroscopy to predict the physical characteristics of SLS 3D printed drug products (drug release and density) as a non-destructive quality control method at the point-of-care.

Comparative study on the real-time monitoring of a fluid bed drying process of extruded granules using near-infrared spectroscopy and audible acoustic emission

The process of fluidized bed drying of granules was comparatively evaluated by on-line real-time measurements of granule moisture content (MC) using near-infrared spectroscopy (NIR) and audible acoustic emission (AAE). The extruded granules were prepared by kneading a powder blend containing lactose, starch, crystalline cellulose, and riboflavin, with water. The MC of the granules (while they were dried at 35 °C in a fluidized bed dryer) was monitored simultaneously with NIR and AAE. The prediction accuracy of the NIR and AAE using partial least squares (PLS) was verified by measuring MC of the granules. The best calibration models following NIR and AAE evaluations consisted of five latent variables with correlation coefficients of 1.000 and 0.998 and root mean square error of 0.259 and 0.615, respectively. As a result of external verification, the accuracy of MC analysis by AAE was slightly lower than that of NIR; however, it was still applicable in practice. Furthermore, the end point of fluidized bed drying process was automatically determined using the PLS discriminant analysis. From the above results, it can be concluded that the AAE-mediated granule drying process can be monitored with sufficient accuracy (compared with NIR).

Simple analytical total diffuse reflectance over a reduced-scattering-pathlength scaled dimension of [10-5, 10-1] from a medium with HG scattering anisotropy

Model approximation is necessary for reflectance assessment of tissue at sub-diffusive to non-diffusive scale. For tissue probing over a sub-diffusive circular area centered on the point of incidence, we demonstrate simple analytical steady-state total diffuse reflectance from a semi-infinite medium with the Henyey-Greenstein (HG) scattering anisotropy (factor $g$g). Two physical constraints are abided to: (1) the total diffuse reflectance is the integration of the radial diffuse reflectance; (2) the radial and total diffuse reflectance at $g \gt {0}$g>0 analytically must resort to their respective forms corresponding to isotropic scattering as $g$g becomes zero. Steady-state radial diffuse reflectance near the point of incidence from a semi-infinite medium of $g \approx 0$g≈0 is developed based on the radiative transfer for isotropic scattering, then integrated to find the total diffuse reflectance for $g \approx 0$g≈0. The radial diffuse reflectance for $g \ge 0.5$g≥0.5 is semi-empirically formulated by comparing to Monte Carlo simulation results and abiding to the second constraint. Its integration leads to a total diffuse reflectance for $g \ge 0.5$g≥0.5 that is also bounded by the second constraint. Over a collection diameter of the reduced-scattering pathlength ($1/\mu _s^{ \prime}$1/μs') scaled size of [${{10}^{ - 5}}$10^-5, ${{10}^{ - 1}}$10^-1] for $g = [{0.5},{0.95}]$g=[0.5,0.95] and the absorption coefficient as strong as the reduced scattering coefficient, the simple analytical total diffuse reflectance is found to be accurate, with an average error of 16.1%.

Fast, Spectroscopy-Based Prediction of In Vitro Dissolution Profile of Extended Release Tablets Using Artificial Neural Networks

The pharmaceutical industry has never seen such a vast development in process analytical methods as in the last decade. The application of near-infrared (NIR) and Raman spectroscopy in monitoring production lines has also become widespread. This work aims to utilize the large amount of information collected by these methods by building an artificial neural network (ANN) model that can predict the dissolution profile of the scanned tablets. An extended release formulation containing drotaverine (DR) as a model drug was developed and tablets were produced with 37 different settings, with the variables being the DR content, the hydroxypropyl methylcellulose (HPMC) content and compression force. NIR and Raman spectra of the tablets were recorded in both the transmission and reflection method. The spectra were used to build a partial least squares prediction model for the DR and HPMC content. The ANN model used these predicted values, along with the measured compression force, as input data. It was found that models based on both NIR and Raman spectra were capable of predicting the dissolution profile of the test tablets within the acceptance limit of the f2 difference factor. The performance of these ANN models was compared to PLS models using the same data as input, and the prediction of the ANN models was found to be more accurate. The proposed method accomplishes the prediction of the dissolution profile of extended release tablets using either NIR or Raman spectra.

Prediction of Dissolution of Sustained Release Coated Ciprofloxacin Beads Using Near-infrared Spectroscopy and Process Parameters: a Data Fusion Approach

The aim of the work is to develop a data fusion model using near-infrared (NIR) and process parameters for the predictions of drug dissolution from controlled release multiparticulate beads. Using a design of experiments, ciprofloxacin-coated beads were manufactured and critical process parameters such as air volume, product temperature, curing temperature, and curing time were measured; environmental humidity was monitored using a Pyrobuttons®. The NIR spectra were decomposed using principal component analysis (PCA). The PCA scores were fused with process measurements and all variables were autoscaled. The autoscaled variables were regressed against measured dissolution data at 1 h and 2 h time points; the PLS regression used quadratic and cross terms. The NIR spectra only model using data collected at the end of bead curing generated a PLS model using 5 latent variables with R² equal to 0.245 and 0.299 and RMSECV 13.23 and 13.12 for the 1 h and 2 h dissolution time points, respectively. The low R² and high root mean square error of cross validation (RMSECV) values indicate that NIR spectra alone were insufficient to model the drug release. Similar results were obtained for NIR model using data collected at the end of spraying phase. Models with fused spectral and process data yielded better prediction with R² above 0.88 and RMSECV less than 5% for the 1 h and 2 h dissolution time points. The data fusion model predicted dissolution profiles with an error less than 10%.

First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing

This manuscript represents the perspective of the Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) and of two focus groups of the American Association of Pharmaceutical Scientists (AAPS): Process Analytical Technology (PAT) and In Vitro Release and Dissolution Testing (IVRDT). The intent of this manuscript is to show recent progress in the field of in vitro predictive dissolution modeling and to provide recommended general approaches to developing in vitro predictive dissolution models for both early- and late-stage formulation/process development and batch release. Different modeling approaches should be used at different stages of drug development based on product and process understanding available at those stages. Two industry case studies of current approaches used for modeling tablet dissolution are presented. These include examples of predictive model use for product development within the space explored during formulation and process optimization, as well as of dissolution models as surrogate tests in a regulatory filing. A review of an industry example of developing a dissolution model for real-time release testing (RTRt) and of academic case studies of enabling dissolution RTRt by near-infrared spectroscopy (NIRS) is also provided. These demonstrate multiple approaches for developing data-rich empirical models in the context of science- and risk-based process development to predict in vitro dissolution. Recommendations of modeling best practices are made, focused primarily on immediate-release (IR) oral delivery products for new drug applications. A general roadmap is presented for implementation of dissolution modeling for enhanced product understanding, robust control strategy, batch release testing, and flexibility toward post-approval changes.

3D printed medicines: A new branch of digital healthcare

Three-dimensional printing (3DP) is a highly disruptive technology with the potential to change the way pharmaceuticals are designed, prescribed and produced. Owing to its low cost, diversity, portability and simplicity, fused deposition modeling (FDM) is well suited to a multitude of pharmaceutical applications in digital health. Favourably, through the combination of digital and genomic technologies, FDM enables the remote fabrication of drug delivery systems from 3D models having unique shapes, sizes and dosages, enabling greater control over the release characteristics and hence bioavailability of medications. In turn, this system could accelerate the digital healthcare revolution, enabling medicines to be tailored to the individual needs of each patient on demand. To date, a variety of FDM 3D printed medical products (e.g. implants) have been commercialised for clinical use. However, within pharmaceuticals, certain regulatory hurdles still remain. This article reviews the current state-of-the-art in FDM technology for medical and pharmaceutical research, including its use for personalised treatments and interconnection within digital health networks. The outstanding challenges are also discussed, with a focus on the future developments that are required to facilitate its integration within pharmacies and hospitals.

Spectroscopic insight for tablet compression

Tablet compression process has been studied over the years from various perspectives. However what exactly happens to material during compression is still unknown. In this study a novel compression die which enables real-time spectroscopic measurements during the compression of material is represented. Both near infrared and Raman spectroscope probes can be attached to the die. In this study the usage of the die is demonstrated by using Raman spectroscopy. Eicosane, d-glucose anhydrate, α-lactose monohydrate and xylitol were used in the study because their compression behavior and bonding properties during compression were assumed to be different. The intensity of the Raman signal changed during compression with all of the materials. However, the intensity changes were different within the materials. The biggest differences were within the xylitol spectra. It was noticed that some peaks disappeared with higher compression pressures indicating that the pressure affected variously on different bonds in xylitol structure. These reversible changes were supposed to relate the changes in conformation and crystal structure. As a conclusion, the die was found to be a significant addition for studying compression process in real-time. It can help to reveal Process induced transformations (PITs) occurring during powder compaction.

Analytical technologies for real-time drug dissolution and precipitation testing on a small scale

Objectives

This review focuses on real-time analytics of drug dissolution and precipitation testing on a comparatively small scale.

Key findings

Miniaturisation of test equipment is an important trend in pharmaceutics, and several small-scale experiments have been reported for drug dissolution and precipitation testing. Such tests typically employ analytics in real-time. Fibre optic ultraviolet (UV) analytics has become a well-established method in this field. Novel imaging techniques are emerging that use visible or UV light; also promising is Fourier transform infrared imaging based on attenuated total reflection. More information than just a rate constant is obtained from these methods. The early phase of a dissolution process can be assessed and drug precipitation may eventually be observed. Some real-time techniques are particularly well suited to studying drug precipitation during formulation dispersion; for example, turbidity, focused beam reflectance measurement and Raman spectroscopy.

Summary

Small-scale dissolution tests equipped with real-time analytics have become important to screen drug candidates as well as to study prototype formulations in early development. Future approaches are likely to combine different analytical techniques including imaging. Miniaturisation started with mini-vessels or small vials and future assays of dissolution research will probably more often reach the level of parallel well plates and microfluidic channels.

Real-time monitoring of the drying of extruded granules in a fluid-bed dryer using audible acoustic emission chemometrics

The purpose of this study was an attempt to adapt the audible acoustic emission (AAE) sound measurement method for the on-line monitoring of the fluid-bed drying process of pharmaceutical granules.

Pharmaceutical Applications of Chemometric Techniques

Chemometrics involves application of various statistical methods for drawing vital information from various manufacturing-related processes. Multiway chemometric models like parallel factor analysis (PARAFAC), Tucker-3, N-partial least square (N-PLS), and bilinear models like principle component regression (PCR) and partial least squares (PLS) have been discussed in the paper. Chemometric approaches can be used to analyze the data obtained from various instruments including near infrared (NIR), attenuated total reflectance Fourier transform infrared (ATR-FTIR), high-performance liquid chromatography (HPLC), and terahertz pulse spectroscopy. The technique has been used in the quality assurance and quality control of pharmaceutical solid dosage forms. Moreover, application of chemometric methods in the evaluation of properties of pharmaceutical powders and tablet parametric tests has also been discussed in the review. It has been suggested as a useful method for the real-time in-process testing and is a valuable process analytical tool.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed.

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories. This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.

Prediction of drug dissolution profiles from tablets using NIR diffuse reflectance spectroscopy: A rapid and nondestructive method

A comparison between dissolution profiles obtained by using a dissolution apparatus (conventional method) and the NIR diffuse reflectance spectra of a series of clonazepam-containing batches is reported. Ten different formulations with fixed amount of clonazepam and varying proportions of excipients were analyzed at seven dissolution times and three different media. The percentages of dissolution of each sample were correlated with the NIR spectra of three tablets of each batch, through a multivariate analysis using the PLS regression algorithm. The squared correlation coefficients for the plots of percentages of dissolution from the equipment laboratory (dissolution apparatus and HPLC determination) versus the predicted values, in the leave-one-out cross-validation, varied from 0.80 to 0.92, indicating that the NIR diffuse reflectance spectroscopy method is an alternative, nondestructive tool for measurement of drug dissolution from tablets.