TGA and NMR relaxation measurement of nonmesoporous silica to investigate the amount of hydrolysis product in acetylsalicylic acid adsorbed on silica.

This study investigated a crucial surface property of silica that contributes to the chemical stability of acetylsalicylic acid (ASA) physically adsorbed on silica. Hydrophilic nonmesoporous types of silica were selected, and the number of hydroxyl groups on silica (N(OH)) was evaluated using thermogravimetric analysis (TGA). The ASA-containing silica was stored at 40 °C in drying conditions, and the amount of ASA degradation was quantified based on salicylic acid. From the scatterplots between the number of hydroxyl groups per unit weight (specific surface area (SSA) × N(OH)) and the amount of ASA degradation, it was clarified that in ASA adsorbed on silica, the ASA chemical stability was determined by the formula (the SSA × N(OH)). In addition, a time-domain nuclear magnetic resonance measurement verified the N(OH) result by estimating the interaction between the silica surface and water in an aqueous silica suspension. The N(OH) result was found to be reasonable.

Use of Time-Domain NMR for 1H T1 Relaxation Measurement and Fitting Analysis in Homogeneity Evaluation of Amorphous Solid Dispersion.

This study examined the usefulness of 1H T1 relaxation measurements for evaluating the homogeneity of amorphous solid dispersion (ASD). Indomethacin and polyvinylpyrrolidone were used to prepare two kinds of ASDs. One was inhomogeneous ASD (ASDmelt) prepared by a melt-quenching method, and the other was homogeneous ASD (ASDsolvent) prepared by a solvent evaporation method. The T1 relaxation was measured by the time-domain NMR (TD-NMR) technique using a low-field NMR system. Curve-fitting analysis of T1 relaxation plots was conducted using the Akaike information criterion. This fitting analysis revealed that the T1 relaxation of ASDmelt and ASDsolvent was biphasic and monophasic, respectively. ASDmelt and ASDsolvent were inhomogeneous and homogeneous on a nanometer scale, respectively, considering the spin diffusion of 1H nuclei. These T1 results were consistent with the Raman mapping of ASDs. From the fitting analysis of 1H T1 relaxation, we conclude that TD-NMR is a promising technique for evaluating ASD homogeneity.

Determination of the Solid Content of Active Pharmaceutical Ingredient Powders in Suspension-Type Pharmaceutical Oral Jelly Using Time-Domain NMR.

This study determined the content of solid active pharmaceutical ingredient (API) powders dispersed in suspension-type pharmaceutical oral jellies using a low-field time-domain NMR (TD-NMR). The suspended jellies containing a designated API content were prepared and tested. Acetaminophen (APAP), indomethacin (IMC) and L-valine were used as test APIs. First, this study measured the T2 relaxation rate (the reciprocal of T2 relaxation time) by the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence, and then evaluated whether the API content could be determined by the acquired T2 relaxation rate. The T2 relaxation rate negatively correlated with API content to a certain extent, but their correlation was not sufficient for achieving a precise determination. Subsequently, the solid-echo pulse sequence measurement was adopted for this study. We found that NMR signals corresponding to solid components strongly correlated with API content. Thus, this method achieved a precise determination of API contents in suspended jellies. In addition, this study confirmed the effect of API particle size on the T2 relaxation rate by using an L-valine-containing jelly: the T2 relaxation rate became faster when a smaller API size was incorporated into the suspended jelly, while there was no difference in terms of the NMR signals measured by solid-echo pulse sequence. From these findings, TD-NMR could be a powerful tool for evaluating the API dispersion state in suspended oral jellies.

[Time-Domain NMR Study to Evaluate Physical Properties of Pharmaceutical Dosage Forms for Process Analysis].

Here, we sought to investigate the usefulness of time-domain NMR (TD-NMR) for evaluating the physical properties of drug formulations. TD-NMR measures NMR relaxation and is mainly performed using a bench-top low-field NMR system (e.g., 20 MHz); thus, it does not require any specific sample shape for measurement if the sample is not gas. Taking advantage of these features, TD-NMR has been widely used for quality control in food science. However, it has rarely been used in the pharmaceutical field. The T1 and T2 relaxations are not spectra like those obtained by a high-field NMR system (e.g., 300-600 MHz) but only curves in which the NMR signal recovers or decays according to a specific rule. Therefore, selecting the equation used in the fitting analysis is crucial to estimate the time constants, T1 and T2 relaxation times. As the result of a series of studies, the T1 relaxation measurement by TD-NMR was shown to help evaluate the crystallinity of drugs in solid dosage forms and the miscibility of a drug and excipient in a binary mixture. The T2 relaxation measurement was also helpful for quantitatively evaluating the solid form of drugs in a physical mixture with or without moisture adsorption. TD-NMR is an excellent technique widely applied to evaluating the physical properties of various formulations, whether solid or liquid, and is expected to be applied to process analysis and quality control in the pharmaceutical field.

Continuous Monitoring of the Agglomeration and Sedimentation of Indomethacin Nanosuspensions Using T2 Relaxation Time with Time-Domain NMR.

The time-domain NMR technique was utilized to monitor precisely the physicochemical stability of indomethacin (IMC) nanosuspensions using T2 relaxation time (T2). We investigated whether T2 values can distinguish between agglomeration and sedimentation. Nanosuspensions of IMC were prepared using aqueous wet bead milling with polyvinylpyrrolidone as a stabilizer. Prepared nanosuspensions were divided into two fractions: one was stored in the NMR equipment for continuous T2 measurements and the other was stored in the dispersion analyzer. Measurements of both nanosuspensions were carried out, without dilution, over a period of 24 h at 10-min intervals. Transmission profiles based on multilight scattering technology showed that agglomeration predominantly occurred at 25 and 35 °C immediately after wet bead milling up to 4 h, followed by sedimentation from 4 to 24 h. Upon measuring the T2 relaxation, T2 values at both 25 and 35 °C showed a two-step change-there was a significant prolongation in T2 values immediately after preparation of nanosuspensions up to approx. 4 h and a gradual prolongation in T2 values from approx. 4 to 24 h. Considering the results of transmission profiles, these two-step T2 changes correspond to agglomeration and sedimentation. In other words, this study established that monitoring the T2 values of nanosuspensions could be used to evaluate the agglomeration and sedimentation of contained drug particles. This technique does not directly observe the nanoparticles themselves, but the water molecules. Thus, measurement of T2 relaxation is considered to be a general-purpose technique, independent of the type of drug or polymer.

Continuous Monitoring of the Hydration Behavior of Hydrophilic Matrix Tablets Using Time-Domain NMR.

Time-domain NMR (TD-NMR) was used for continuous monitoring of the hydration behavior of hydrophilic matrix tablets. The model matrix tablets comprised high molecular weight polyethylene oxide (PEO), hydroxypropyl methylcellulose (HPMC), and polyethylene glycol (PEG). The model tablets were immersed in water. Their T2 relaxation curves were acquired by TD-NMR with solid-echo sequence. A curve-fitting analysis was conducted on the acquired T2 relaxation curves to identify the NMR signals corresponding to the nongelated core remaining in the samples. The amount of nongelated core was estimated from the NMR signal intensity. The estimated values were consistent with the experiment measurement values. Next, the model tablets immersed in water were monitored continuously using TD-NMR. The difference in hydration behaviors of the HPMC and PEO matrix tablets was then characterized fully. The nongelated core of the HPMC matrix tablets disappeared more slowly than that of the PEO matrix tablets. The behavior of HPMC was significantly affected by the PEG content in the tablets. It is suggested that the TD-NMR method has potential to be utilized to evaluate the gel layer properties, upon replacement of the immersion medium: purified (nondeuterated) water is replaced with heavy (deuterated) water. Finally, drug-containing matrix tablets were tested. Diltiazem hydrochloride (a highly water-soluble drug) was employed for this experiment. Reasonable in vitro drug dissolution profiles, which were in accordance with the results from TD-NMR experiments, were observed. We concluded that TD-NMR is a powerful tool to evaluate the hydration properties of hydrophilic matrix tablets.

Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales.

The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and data were collected according to the design of experiments at different scales. In total, 38 different tablets were prepared, and the tensile strength (TS) and dissolution rate after 10 min (DS10) were measured. In addition, 15 material attributes (MAs) related to particle size distribution, bulk density, elasticity, plasticity, surface properties, and moisture content of granules were evaluated. By using unsupervised learning including principal component analysis and hierarchical cluster analysis, the regions of tablets produced at each scale were visualized. Subsequently, supervised learning with feature selection including partial least squares regression with variable importance in projection and elastic net were applied. The constructed models could predict the TS and DS10 from the MAs and the compression force with high accuracy (R2= 0.777 and 0.748, respectively), independent of scale. In addition, important factors were successfully identified. ML can be used for better understanding of similarity/dissimilarity between scales, for constructing predictive models of critical quality attributes, and for determining critical factors.

A Data-Driven Approach to Predicting Tablet Properties after Accelerated Test Using Raw Material Property Database and Machine Learning.

The purpose of this study was to develop a model for predicting tablet properties after an accelerated test and to determine whether molecular descriptors affect tablet properties. Tablets were prepared using 81 types of active pharmaceutical ingredients, with the same formulation and three different levels of compression pressure. The tablet properties measured were the tensile strength and disintegration time of tablets after two weeks of accelerated test. The material properties measured were the change in tablet thickness before and after the accelerated test, maximum swelling force, swelling time, and swelling rate. The acquired data were added to our previously constructed database containing a total of 20 material properties and 3381 molecular descriptors. The feature importance values of molecular descriptors, material properties and the compression pressure for each tablet property were calculated by random forest, which is one type of machine learning (ML) that uses ensemble learning and decision trees. The results showed that more than half of the top 25 most important features were molecular descriptors for both tablet properties, indicating that molecular descriptors are strongly related to tablet properties. A prediction model of tablet properties was constructed by eight ML types using 25 of the most important features. The results showed that the boosted neural network exhibited the best prediction accuracy and was able to predict tablet properties with high accuracy. A data-driven approach is useful for discovering intricate relationships hidden within complex and large data sets and predicting tablet properties after an accelerated test.

Usefulness of Applying Partial Least Squares Regression to T2 Relaxation Curves for Predicting the Solid form Content in Binary Physical Mixtures.

This study applied partial least squares (PLS) regression to nuclear magnetic resonance (NMR) relaxation curves to quantify the free base of an active pharmaceutical ingredient powder. We measured the T2 relaxation of intact and moisture-absorbed physical mixtures of tetracaine free base (TC) and its hydrochloride salt (TC·HCl). The obtained T2 relaxation curves were analyzed by two methods, one using a previously reported T2 relaxation time (T2), and the other using PLS regression. The accuracy of estimating TC was inadequate when using previous T2 values because the moisture-absorbed physical mixtures showed biphasic T2 relaxation curves. By contrast, the entire measured whole of the T2 relaxation curves was used as input variables and analyzed by PLS regression to quantify the content of TC in the moisture-absorbed TC/TC·HCl. Based on scatterplots of theoretical versus predicted TC, the obtained PLS model exhibited acceptable coefficients of determination and relatively low root mean squared error values for calibration and validation data. The statistical values confirmed that an accurate and reliable PLS model was created to quantify TC in even moisture-absorbed TC/TC·HCl. The bench-top low-field NMR instrument used to apply PLS regression to the T2 relaxation curve may be a promising tool in process analytical technology.

Low-Field NMR to Characterize the Crystalline State of Ibuprofen Confined in Ordered or Nonordered Mesoporous Silica.

The crystalline state of ibuprofen (IBU) confined in mesoporous silica was characterized using low-field time-domain nuclear magnetic resonance (TD-NMR). IBU was loaded into ordered (Santa Barbara Amorphous-15 [SBA-15]; SBA) or nonordered mesoporous silica (Sylysia 320; SYL) using a well-known incipient wetness impregnation method. The dissolution profile of IBU from the silica was measured. The IBU-loaded SBA showed a relatively higher drug concentration at 10 and 20 min, which was typical of a supersaturated solution. However, it did not maintain that concentration. By contrast, the IBU-loaded SYL did not show such a dissolution profile in the early stage. To characterize the crystalline state of IBU confined in silica, the T1 relaxation time of IBU-loaded silica powder was measured and analyzed by curve fitting. Monophasic T1 relaxation was observed for IBU-loaded SBA. This may indicate that the amorphous phase, which has various molecular mobilities, was close to within the length of 1H spin diffusion. The TD-NMR technique, even if the sample is powder, can rapidly and easily measure NMR relaxation. Therefore, it can be useful toward fully characterizing the crystalline state of drugs confined in mesopores.

Determination of Hardness of a Pharmaceutical Oral Jelly by Using T2 Relaxation Behavior Measured by Time-Domain NMR.

Hardness is a critical quality characteristic of pharmaceutical oral jelly. In this study, the hardness was determined by using the T2 relaxation curves measured by time-domain NMR. For sample preparation, kappa- and iota-carrageenans, and locust bean gum, were used as gel-forming agents. Ten test jellies with different gel-forming agent composition were prepared, and their hardness and T2 relaxation curves were measured by a texture analyzer and time-domain NMR (TD-NMR). A negative correlation between T2 relaxation time (T2) and hardness was observed; however, it was difficult to determine the hardness directly from the T2 value. That is probably because the T2 relaxation curve contains information about molecular states, not only of water but also of the solute, and T2 values calculated by single-exponential curve fitting only express one property of the test jelly. By considering this issue, partial least squares (PLS) regression analysis was performed on the T2 relaxation curves for hardness determination of the test jellies. According to the analysis, an accurate and reliable PLS model was created that enabled accurate assessment of the hardness of the test jellies. TD-NMR enables the measurement of samples nondestructively and rapidly with low cost, and so could be a promising method for evaluation of the hardness of pharmaceutical oral jellies.

Characterization of the Salt and Free Base of Active Pharmaceutical Ingredients Based on NMR Relaxometry Measured by Time Domain NMR.

NMR relaxometry measurement by time domain NMR (TD-NMR) is a promising technique for characterizing the properties of active pharmaceutical ingredients (APIs). This study is dedicated to identifying the salt and free base of APIs by NMR relaxometry measured by the TD-NMR technique. Procaine (PC) and tetracaine (TC) were selected as model APIs to be tested. By using conventional methods including powder X-ray diffraction and differential scanning calorimetry, this study first confirmed that the salt and free base of the tested APIs differ from each other in their crystalline form. Subsequently, measurements of T1 and T2 relaxation were performed on the tested APIs using TD-NMR. The results demonstrated that these NMR relaxometry measurements have sufficient capacity to distinguish the difference between the free base and salt of the tested APIs. Furthermore, quantification of the composition of the binary powder blends consisting of salt and free bases was conducted by analyzing the acquired T1 and T2 relaxation curves. The analysis of the T1 relaxation curves provided a partly acceptable estimation: a good estimation of the composition was observed from PC powders, whereas for TC powders the estimation accuracy changed with the free base content in the binary blends. For the analysis on T2 relaxation curves, a precise estimation of the composition was observed from all the samples. From these findings, the NMR relaxometry measurement by TD-NMR, in particular the T2 relaxation measurement, is effective for evaluating the properties of APIs having different crystalline forms.

Application of machine learning to a material library for modeling of relationships between material properties and tablet properties.

This study investigates the usefulness of machine learning for modeling complex relationships in a material library. We tested 81 types of active pharmaceutical ingredients (APIs) and their tablets to construct the library, which included the following variables: 20 types of API material properties, one type of process parameter (three levels of compression pressure), and two types of tablet properties (tensile strength (TS) and disintegration time (DT)). The machine learning algorithms boosted tree (BT) and random forest (RF) were applied to analysis of our material library to model the relationships between input variables (material properties and compression pressure) and output variables (TS and DT). The calculated BT and RF models achieved higher performance statistics compared with a conventional modeling method (i.e., partial least squares regression), and revealed the material properties that strongly influence TS and DT. For TS, true density, the tenth percentile of the cumulative percentage size distribution, loss on drying, and compression pressure were of high relative importance. For DT, total surface energy, water absorption rate, polar surface energy, and hygroscopicity had significant effects. Thus, we demonstrate that BT and RF can be used to model complex relationships and clarify important material properties in a material library.

Effects of Manufacturing Process Variables on the Tablet Weight Variation of Mini-tablets Clarified by a Definitive Screening Design.

This study investigated the effect of manufacturing process variables of mini-tablets, in particular, the effect of process variables concerning fluidized bed granulation on tablet weight variation. Test granules were produced with different granulation conditions according to a definitive screening design (DSD). The five evaluated factors assigned to DSD were: the grinding speed of the sample mill at the grinding process of the active pharmaceutical ingredient (X1), microcrystalline cellulose content in granules (X2), inlet air temperature (X3), binder concentration (X4) and the spray speed of the binder solution (X5) at the granulation process. First, the relationships between the evaluated factors and the granule properties were investigated. As a result of the DSD analysis, the mode of action of granulation parameters on the granule properties was fully characterized. Subsequently, the variation in tablet weight was examined. In addition to mini-tablets (3 mm diameter), this experiment assessed regular tablets (8 mm diameter). From the results for regular tablets, the variation in tablet weight was affected by the flowability of granules. By contrast, regarding the mini-tablets, no significant effect on the variation of tablet weight was found from the evaluated factors. From this result, this study further focused on other important factors besides the granulation process, and then the effect of the die-hole position of the multiple-tip tooling on tablet weight variation was proven to be significant. Our findings provide a better understanding of manufacturing mini-tablets.

Nondestructive Investigation of the Agglomeration Process for Nanosuspensions via NMR Relaxation of Water Molecules.

This study investigated an agglomeration of nanoparticles in a suspension using nuclear magnetic resonance (NMR) relaxation. The nanosuspension was prepared by wet bead milling using indomethacin and polyvinylpyrrolidone as an active pharmaceutical ingredient (API) and stabilizer, respectively. Transmission profiles using a dispersion analyzer based on multilight scattering technology confirmed that agglomeration occurred at 25 °C immediately after wet bead milling. In this study, we focused on the water molecules, not nanoparticles, and obtained the T2 relaxation time (T2) of the water molecules using the time-domain NMR (TD-NMR) technique. During the storage period, the T2 value rapidly increased at the beginning of the storage. In a suspension system, because the T2 value of water molecules is known to reflect the surface area of the particle, the observed rapid increase in T2 value indicated an agglomeration of nanoparticles. Therefore, it was shown that the measurement of T2 relaxation of a nanosuspension could evaluate the agglomeration process. This technique directly observes water molecules as opposed to nanoparticles. Thus, we believe that TD-NMR is a general-purpose technique that is independent of the type of API or polymer.

Time-domain NMR analysis for the determination of water content in pharmaceutical ingredients and wet granules.

The application of time-domain NMR (TD-NMR) analysis to quantify water content in pharmaceutical ingredients is demonstrated. The initial phase of the study employed a range of disintegrants with defined amounts of added water (0-30% of the total weight) as samples; the disintegrants included croscarmellose sodium, corn starch, low-substituted hydroxypropyl cellulose, and crospovidone. After acquisition of the T2 relaxation curves of the samples by TD-NMR measurements, these curves were analyzed by partial least squares (PLS) regression. According to the analysis, accurate and reliable PLS models were created that enabled accurate assessment of water content in the samples. A powder blend consisting of acetaminophen (paracetamol) and tablet excipients was also examined. Both a physical mixture of the powder blend and a wet granule prepared with a high-speed granulator were tested as samples in this study. Precise determination of water content in the powder blend was achieved by using the TD-NMR method. The accuracy of water content determination was equivalent to or better than that of the conventional loss on drying method. TD-NMR analysis samples were measured nondestructively and rapidly with low cost; thus, it could be a powerful quantitative method for determining water content in pharmaceuticals.

Incompatibility of remimazolam besylate with Ringer's acetate infusion resulting in total occlusion of an intravenous catheter.

Remimazolam besylate is an ultra-short-acting benzodiazepine derivative recently approved in Japan for general anaesthesia. However, less attention has been paid to the compatibility of remimazolam with infusion solutions, and the mechanism underlying the incompatibility remains unknown. The patient was a 65-year-old man who underwent a high tibial osteotomy. After the induction of general anaesthesia using remimazolam solution (5 mg/mL), we noticed precipitate completely blocking the lumen of the intravenous tube connected to a Ringer's acetate Physio140 drip. The mixture of remimazolam solution (5 mg/mL) with Physio140 solution immediately resulted in the formation of substantial precipitate. Nuclear magnetic resonance analysis revealed that the precipitate was remimazolam. Ultraviolet spectrophotometry revealed that the mixture of remimazolam solution with higher ratios of Physio140 resulted in significantly lower solubility, concomitant with an increase in pH. It would be important to consider the remimazolam concentration and infusion solution pH to avoid the production of precipitates.

Effect of Different Direct Compaction Grades of Mannitol on the Storage Stability of Tablet Properties Investigated Using a Kohonen Self-Organizing Map and Elastic Net Regression Model.

This study tested 15 direct compaction grades to identify the contribution of different grades of mannitol to the storage stability of the resulting tablets. After preparing the model tablets with different values of hardness, they were stored at 25 °C, 75% relative humidity for 1 week. Then, measurement of the tablet properties was conducted on both pre- and post-storage tablets. The tablet properties were tensile strength (TS), friability, and disintegration time (DT). The experimental data were analyzed using a Kohonen self-organizing map (SOM). The SOM analysis successfully classified the test grades into three distinct clusters having different changes in the behavior of the tablet properties accompanying storage. Cluster 1 showed an obvious rise in DT induced by storage, while cluster 3 showed a substantial change in mechanical strength of the tablet including a reduction in the TS and a rise in friability. Furthermore, the data were analyzed using an Elastic net regression technique to investigate the general relationships between the powder properties of mannitol and the change behavior of the tablet properties. Consequently, we succeeded in identifying the crucial powder properties for the storage stability of the resulting tablets. This study provides advanced technical knowledge to characterize the effect of different direct compaction grades of mannitol on the storage stability of tablet properties.

Effect of the molecular mobility of water adsorbed by disintegrants on storage-induced hydrolytic degradation of acetylsalicylic acid incorporated into tablets under humid conditions.

The purpose of this study was to investigate the effect of molecular mobility of water adsorbed by disintegrants on the hydrolytic degradation of active pharmaceutical ingredients (APIs). Fourteen different disintegrants were tested. First, powdered disintegrants were stored at conditions of 40 °C/75% relative humidity ("humid conditions") and their T2 relaxation times were measured by time-domain nuclear magnetic resonance for examination of the molecular mobility of water adsorbed by the disintegrant. From the observed T2 values, the water molecular mobility was fully characterized. In particular, the molecular mobility of water adsorbed by crospovidones was much higher than the molecular mobility of water adsorbed by the other test disintegrants because of longer T2 values. The next study examined the hydrolytic degradation of acetylsalicylic acid (ASA), a model moisture-sensitive API, stored under humid conditions. Physical mixtures of ASA and disintegrants or their model tablets were used as test samples, and they were stored for 7 d. The disintegrants contained in the samples clearly affected the ASA degradation: the most significant ASA degradation was observed for the crospovidone-containing samples. Finally, we analyzed the effect of the molecular mobility of water adsorbed by disintegrants on the ASA degradation by the least absolute shrinkage and selection operator (Lasso) regression techniques. As in the T2 experiment, various properties of disintegrants (i.e., water content, pH, and water activity) were used in this experiment as the explanatory variables. From the Lasso analysis, we successfully showed that the higher molecular mobility of water adsorbed by disintegrants significantly enhanced ASA degradation. These findings provide profound insights into the chemical stability of moisture-sensitive APIs in tablets.

A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets.

We previously reported a novel method for the precise prediction of tablet properties (e.g., tensile strength (TS)) using a small number of experimental data. The key technique of this method is to compensate for the lack of experimental data by using data of placebo tablets collected in a database. This study provides further technical knowledge to discuss the usefulness of this prediction method. Placebo tablets consisting of microcrystalline cellulose, lactose, and cornstarch were prepared using the design of an experimental method, and their TS and disintegration time (DT) were measured. The response surfaces representing the relationship between the formulation and the tablet properties were then created. This study investigated tablets containing four different active pharmaceutical ingredients (APIs) with a drug load ranging from 20-60%. Overall, the TS of API-containing tablets could be precisely predicted by this method, while the prediction accuracy of the DT was much lower than that of the TS. These results suggested that the mode of action of APIs on the DT was more complicated than that on the TS. Our prediction method could be valuable for the development of tablet formulations.