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.

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.

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.

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.

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.

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.

A Novel Approach to Evaluate Amorphous-to-Crystalline Transformation of Active Pharmaceutical Ingredients in Solid Dispersion Using Time-Domain NMR.

The aim of this study was to demonstrate the usefulness of the time-domain NMR (TD-NMR) method to characterize the crystalline state of active pharmaceutical ingredients (APIs) containing a solid dispersion. In this study, indomethacin (IMC) was used as a model for poorly water-soluble API. Solid dispersions of IMC were prepared with polyvinylpyrrolidone (PVP) at different weight ratios. First, we measured the T1 relaxation behavior of solid dispersions. From the result, the T1 relaxation time (T1) changed according to the API content; the T1 tended to increase with increasing API content because the T1 value of amorphous IMC was longer than that of PVP. Next, we tried to monitor the amorphous-to-crystalline transformation of IMC in the solid dispersion during the thermal stress test. In the case of solid dispersion containing 90% IMC, a clear prolongation of the T1 could be observed during the thermal stress test. From the powder X-ray diffraction patterns, the change in T1 relaxation behavior must be caused by the IMC transformation from amorphous to crystalline. From these findings, we were successful in monitoring the IMC amorphous-to-crystalline transformation by the changes in T1 relaxation behavior. Our findings led us to conclude that TD-NMR is a novel approach for the evaluation of crystalline state of APIs in solid dispersions.

T2 Relaxation Study to Evaluate the Crystalline State of Indomethacin Containing Solid Dispersions Using Time-Domain NMR.

The aim of this study was to demonstrate the usefulness of T2 measurements conducted with a time-domain NMR (TD-NMR) for the characterization of active pharmaceutical ingredients (APIs) containing solid dosage forms. A solid dispersion (SD) and a physical mixture (PM) consisting of indomethacin (IMC) and polyvinylpyrrolidone (PVP) were prepared at different weight ratios as test samples, and then their T2 relaxation curves were measured by TD-NMR. The T2 relaxation curve of IMC was quite different from that of PVP by nature. T2 values of the SD and PM samples became gradually shortened with increasing IMC content. No difference in T2 relaxation curves was observed between SD and PM. By analyzing the T2 relaxation curves in detail, we succeeded in precisely quantifying the IMC contents incorporated in the samples. Next, this study evaluated the T2 relaxation curves of amorphous and crystalline states of powdered IMC. T2 relaxation rate of crystalline IMC was slightly but significantly higher than that of amorphous IMC, proving that the T2 measurement was sensitive enough to detect these differences. Finally, a thermal stress was imposed on SD and PM samples at 60°C for 7 d, and then an amorphous-to-crystalline transformation occurred in IMC in the PM sample and was successfully monitored by T2 measurement. We believe that T2 measurement by TD-NMR is a promising analysis for the characterization of APIs in solid dosage forms, including SD-based pharmaceuticals.

A Time-Domain NMR Study of the State of Water in Wet Granules with Different Fillers and Its Contribution to the Wet Granulation Process and to the Characteristics of Granules.

The different states of water incorporated in wet granules were studied by a low-field benchtop 1H-NMR time-domain NMR (TD-NMR) instrument. Wet granules consisting different fillers [cornstarch (CS), microcrystalline cellulose (MCC), and D-mannitol (MAN)] with different water contents were prepared using a high-speed granulator, and then their spin-spin relaxation time (T2) was measured using the NMR relaxation technique. The experimental T2 relaxation curves were analyzed by the two-component curve fitting, and then the individual T2 relaxation behaviors of solid and water in wet granules were identified. According to the observed T2 values, it was confirmed that the molecular mobility of water in CS and MCC granules was more restricted than that in the MAN granule. The state of water appeared to be associated with the drying efficiency and moisture absorption capacity of wet granules. Thus, it was confirmed that the state of water significantly affected the wet granulation process and the characteristics of the resultant granules. In the final phase of this study, the effects of binders on the molecular mobility of water in granulation fluids and wet granules were examined. The state of water in granulation fluids was substantially changed by changing the binders. The difference was still detected in wet granules prepared by addition of these fluids to the fillers. In conclusion, TD-NMR can offer valuable knowledge on wet granulation from the viewpoint of molecular mobility of water.

Modeling of quantitative relationships between physicochemical properties of active pharmaceutical ingredients and tensile strength of tablets using a boosted tree.

OBJECTIVES: The aim of this study was to explore the potential of boosted tree (BT) to develop a correlation model between active pharmaceutical ingredient (API) characteristics and a tensile strength (TS) of tablets as critical quality attributes. METHODS: First, we evaluated 81 kinds of API characteristics, such as particle size distribution, bulk density, tapped density, Hausner ratio, moisture content, elastic recovery, molecular weight, and partition coefficient. Next, we prepared tablets containing 50% API, 49% microcrystalline cellulose, and 1% magnesium stearate using direct compression at 6, 8, and 10 kN, and measured TS. Then, we applied BT to our dataset to develop a correlation model. Finally, the constructed BT model was validated using k-fold cross-validation. RESULTS: Results showed that the BT model achieved high-performance statistics, whereas multiple regression analysis resulted in poor estimations. Sensitivity analysis of the BT model revealed that diameter of powder particles at the 10th percentile of the cumulative percentage size distribution was the most crucial factor for TS. In addition, the influences of moisture content, partition coefficients, and modal diameter were appreciably meaningful factors. CONCLUSIONS: This study demonstrates that BT model could provide comprehensive understanding of the latent structure underlying APIs and TS of tablets.

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.

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.

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.

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.

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.

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.

Quantitative Evaluation of the Crystallinity of Indomethacin Using 1H T2 Relaxation Behaviors Measured by Time Domain NMR.

We sought to demonstrate the usefulness of the T2 relaxation behaviors measured by time domain NMR (TD-NMR) for the quantitative evaluation of the crystallinity of an active pharmaceutical ingredient (API). This study used indomethacin as a model API. After blending amorphous and crystalline indomethacin powders at a designated ratio, T2 relaxation curves were measured by TD-NMR. Subsequently, we acquired a calibration curve to quantify crystallinity by curve fitting analysis. Validation demonstrated a good correlation between the theoretical and experimental percentage of crystallinity. Thus, this study succeeded in a precise estimation of crystallinity of indomethacin using TD-NMR. We also investigated whether the technique is practical by testing indomethacin powders with unknown proportion of crystallinity, and then compared their estimated crystallinity with that found using conventional evaluation techniques. The quantitative performance of the TD-NMR technique was comparable to that of Raman spectroscopy. Furthermore, indomethacin powder blended with excipients, which can be used to produce tablets, was tested. The TD-NMR technique was still able to quantify the crystallinity of indomethacin, even when excipients were incorporated into the sample. Therefore, the present study expands the horizon for evaluating the crystallinity of APIs in pharmaceutical sciences.

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.

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.

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.