Taste measurement system and taste measurement method for oral pharmaceutical preparations

Abstract

To provide a novel taste evaluation system and a taste evaluation method for assessing taste interactions arising from a combination of bitterness of an active ingredient contained in an oral pharmaceutical preparation and flavorings and sweeteners.SOLUTION: A taste evaluation system for an oral pharmaceutical preparation according to one embodiment of the present invention includes an input layer that measures actual measured values of saltiness, sourness, sweetness, umami, and bitterness generated from an active ingredient, flavorings, and sweeteners contained in the oral pharmaceutical preparation, an intermediate layer that calculates analyzed values of saltiness, sourness, sweetness, umami, and bitterness generated by interactions between the active ingredient and the flavorings and sweeteners by means of a neural network trained using actual performance values of arbitrary flavorings and sweeteners as teacher data based on the measured values, and an output layer that outputs the analyzed values.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a taste measurement system and a taste measurement method for oral pharmaceutical preparations. In particular, the present invention relates to a novel taste measurement system and a novel taste measurement method for evaluating the interaction of taste generated by the combination of the bitter taste of an active ingredient contained in an oral pharmaceutical preparation, a flavor and a sweetener. [Background Art]

[0002] Taste is a sensation perceived in response to substances taken into the mouth. The five basic tastes are saltiness, sourness, sweetness, umami and bitterness. Among the five basic tastes, in particular, the bitter taste exhibited by active ingredients contained in oral pharmaceutical preparations greatly affects medication compliance. As a method for reducing the bitterness of oral pharmaceutical preparations, there is a method of adding a sweetener or a flavor to the preparation. The sweetener itself has a strong sweetness and suppresses bitterness. On the other hand, flavors mainly suppress unpleasant tastes such as bitterness through aroma. Evaluation of the bitterness of oral pharmaceutical preparations is generally performed by sensory testing, but reproducibility is difficult to obtain because there are variations due to individual differences and physical conditions of testers. In addition, in order to obtain reproducibility, sensory tests need to be performed by specially trained personnel, which requires cost and time. Furthermore, for oral pharmaceutical preparations containing highly active drug substances, human sensory testing is not preferable from an ethical point of view.

[0003] Taste sensors are being introduced as a method for safely and objectively evaluating tastes such as bitterness of oral pharmaceutical preparations. For example, Non-Patent Document 1 discloses an objective taste evaluation method that quantifies the bitterness of oral pharmaceutical preparations using a taste sensor, in view of problems such as reproducibility and ethical issues. In addition, Patent Document 1 discloses a taste sensor that imitates human taste by quantitatively evaluating the saltiness, sourness, sweetness, umami and bitterness of a sample respectively, but there has been no track record of evaluating samples of oral pharmaceutical preparations containing flavors. [Prior Art Documents] [Patent Documents]

[0004] [Patent Document 1] Patent No. 4240003 [Non-patent literature]

[0005] [Non-Patent Document 1] Pharmacia, Vol. 51, No. 2, p. 130, "The Science of Drug Taste Using Taste Sensors" [Overview of the project] [Problems that the invention aims to solve]

[0006] One objective of the present invention is to provide a novel taste measurement system and taste measurement method for evaluating the interaction of tastes resulting from the combination of the bitterness of the active ingredient contained in an oral pharmaceutical preparation and flavorings and sweeteners. [Means for solving the problem]

[0007] According to one embodiment of the present invention, a taste measurement system for an oral pharmaceutical preparation is provided, comprising: an input layer for measuring measured values ​​of saltiness, sourness, sweetness, umami, and bitterness arising from the active ingredient, flavorings, and sweeteners contained in the oral pharmaceutical preparation; an intermediate layer that calculates analytical values ​​of saltiness, sourness, sweetness, umami, and bitterness arising from the interaction between the active ingredient, flavorings, and sweeteners using a neural network trained on the measured values ​​using the actual values ​​of arbitrary flavorings and sweeteners as training data; and an output layer for outputting the analytical values.

[0008] In the aforementioned taste measurement system for oral pharmaceutical preparations, the actual values ​​may be the results of a sensory evaluation using any combination of flavorings and sweeteners.

[0009] In the aforementioned taste measurement system for the oral pharmaceutical preparation, the flavoring used in the sensory test may be one selected from the group consisting of yuzu, pineapple, cider, strawberry, peach, orange, lemon, grapefruit, banana, and yogurt flavorings.

[0010] In the taste measurement system for the aforementioned oral pharmaceutical preparation, the fragrance contained in the oral pharmaceutical preparation may be the same fragrance used in the sensory evaluation.

[0011] In the aforementioned taste measurement system for oral pharmaceutical preparations, the sweetener used in the sensory test may be one selected from the group consisting of thaumatin, stevia, sucralose, aspartame, saccharin, acesulfame K, refined sucrose, lactose, and D-mannitol.

[0012] In the aforementioned taste measurement system for the oral pharmaceutical preparation, the sweetener contained in the oral pharmaceutical preparation may be the same sweetener used in the sensory evaluation test.

[0013] In the aforementioned taste measurement system for oral pharmaceutical preparations, the active ingredient may have a bitter taste.

[0014] Furthermore, according to one embodiment of the present invention, a method for measuring the taste of an oral pharmaceutical preparation is provided, which includes measuring actual values ​​of saltiness, sourness, sweetness, umami, and bitterness generated from the active ingredient, flavorings, and sweeteners contained in the oral pharmaceutical preparation, and using a neural network trained with the actual values ​​of arbitrary flavorings and sweeteners as training data to calculate analytical values ​​of saltiness, sourness, sweetness, umami, and bitterness generated by the interaction between the active ingredient and the flavorings and sweeteners, and outputting the analytical values. [Effects of the Invention]

[0015] One embodiment of the present invention provides a novel taste measurement system and taste measurement method for evaluating the interaction of tastes resulting from the combination of the bitterness of the active ingredient contained in an oral pharmaceutical formulation and flavorings and sweeteners. [Brief explanation of the drawing]

[0016] [Figure 1] This diagram shows the configuration of a taste measurement system according to one embodiment of the present invention. [Figure 2]FIG. 1 is a diagram showing combinations of training samples for a taste measurement system according to an embodiment of the present invention. [Figure 3] FIG. 1 is a diagram showing analysis results of Example 1 obtained using the taste measurement system according to an embodiment of the present invention. [Figure 4] FIG. 1 is a diagram showing a radar chart of Example 1 obtained using the taste measurement system according to an embodiment of the present invention. [Figure 5] The sensory test results of Reference Example 1 are shown. [Figure 6] The analysis results of Comparative Example 1 obtained using the taste measurement system before training with teacher data are shown. [Figure 7] A radar chart of Comparative Example 1 obtained using the taste measurement system before training with teacher data is shown. [Figure 8] Analysis results of bitterness scores of Example 1 and Comparative Example 1 obtained using the taste measurement system before and after training with teacher data are shown. [Figure 9] FIG. 1 is a diagram showing analysis results of Example 2 obtained using the taste measurement system according to an embodiment of the present invention. [Figure 10] FIG. 1 is a diagram showing a radar chart of Example 2 obtained using the taste measurement system according to an embodiment of the present invention. [Figure 11] The sensory test results of Reference Example 2 are shown. [Figure 12] The teacher data trained by the taste measurement system according to an embodiment of the present invention is shown. [Figure 13] The teacher data trained by the taste measurement system according to an embodiment of the present invention is shown. [Figure 14] The teacher data trained by the taste measurement system according to an embodiment of the present invention is shown. [Figure 15] The teacher data trained by the taste measurement system according to an embodiment of the present invention is shown. [Figure 16] The teacher data trained by the taste measurement system according to an embodiment of the present invention is shown. [Figure 17] The teacher data trained by the taste measurement system according to an embodiment of the present invention is shown. [Modes for carrying out the invention]

[0017] The following describes a taste measurement system and taste measurement method according to one embodiment of the present invention. However, the taste measurement system and taste measurement method of the present invention are not limited to the embodiments and examples described below.

[0018] The inventors' investigations revealed that the analytical values ​​of saltiness, sourness, sweetness, umami, and bitterness derived from the active ingredients and sweeteners in oral pharmaceutical preparations, as measured by a conventional taste measurement system, correlated with the actual values ​​obtained from human sensory evaluations. On the other hand, the analytical values ​​of saltiness, sourness, sweetness, umami, and bitterness derived from the active ingredients, fragrances, and sweeteners in oral pharmaceutical preparations did not correlate with the actual values ​​obtained from human sensory evaluations. In other words, because fragrances suppress unpleasant tastes with their aromatic components, it was found that simply using a taste sensor and a conventionally known taste measurement method to evaluate samples would not allow for the evaluation of the effect of fragrances in suppressing unpleasant tastes. Therefore, the neural network of the taste measurement system was trained using the actual values ​​of human sensory evaluations of arbitrary fragrances and sweeteners as training data. A taste measurement system equipped with a neural network trained on historical values ​​of flavorings and sweeteners measured the saltiness, sourness, sweetness, umami, and bitterness of active ingredients, flavorings, and sweeteners contained in oral pharmaceutical preparations. The analyzed values ​​correlated with historical values ​​from human sensory evaluations. It was found that the neural network trained on historical values ​​of flavorings and sweeteners can mimic the taste interactions resulting from combinations of flavorings and sweeteners.

[0019] (Taste measurement system) Figure 1 shows the configuration of a taste measurement system according to one embodiment of the present invention. The taste measurement system 1 includes an input layer 10, an intermediate layer 20, and an output layer 30.

[0020] The input layer 10 includes a sensor 100. The sensor 100 acts as a substitute for taste buds. The sensor 100 electrochemically reacts with each of the components that give rise to saltiness, sourness, sweetness, umami, and bitterness, and outputs a quantitative electrical signal. The components that give rise to saltiness may be, for example, NaCl, KCl, LiCl, etc., with NaCl and KCl being preferred. The components that give rise to sourness may be, for example, H derived from hydrochloric acid, acetic acid, citric acid, malic acid, succinic acid, etc. + This is preferable. The sweetening component may be glucose, sucrose, fructose, maltose, glycine, aspartame, etc., with glucose and sucrose being preferred. The umami component may be glutamate, inosinic acid, guanylic acid, etc., with glutamate being preferred. The bittering component may be caffeine, quinine, tannin, phenylalanine, Mg2+, etc., with caffeine being preferred. There may be one or more types of each flavor component. By measuring each of these components, saltiness, sourness, sweetness, umami, and bitterness can be quantified. In the input layer 10, the sensor 100 is used to measure the measured values ​​of saltiness, sourness, sweetness, umami, and bitterness generated from the active ingredients, flavorings, and sweeteners contained in the oral pharmaceutical preparation. The active ingredients contained in the oral pharmaceutical preparation may have a bitter taste.

[0021] The intermediate layer 20 includes a neural network 200. For example, an RBFN can be used as the neural network 200. Preferably, the improved RBFN described in Patent Document 1 is used as the neural network 200. The improved RBFN is a neural network that specializes the RBFN for chemical data analysis and further enhances its generalization ability. The improved RBFN improves the estimation accuracy for chemical data compared to conventional methods by using a basis automatic optimization algorithm. In addition, the generalization ability is improved compared to conventional methods by adding a weight suppression term to the network's evaluation function.

[0022] The neural network 200 first calculates the concentration of each component from the measured values ​​obtained by the sensor 100. Therefore, the neural network 200 may be trained by inputting measured values ​​and the actual concentrations of each taste component. The relationship between the measured values ​​and the actual concentrations of each taste component can be obtained by measuring the measured values ​​using each sensor for a mixture containing each taste component at known concentrations.

[0023] The neural network 200 then calculates analytical values ​​representing the intensity of saltiness, sourness, sweetness, umami, and bitterness perceived by humans, based on the concentrations of each component. Therefore, the neural network 200 may be trained by inputting the concentrations of each component and the perceived intensity of saltiness, sourness, sweetness, umami, and bitterness. The relationship between the concentrations of each component and the perceived intensity of saltiness, sourness, sweetness, umami, and bitterness can be obtained through sensory testing.

[0024] In the sensory evaluation, it is preferable that panelists taste or sample five standard samples, each independently containing one of the following tastes: saltiness, sourness, sweetness, umami, and bitterness. Subsequently, the panelists taste or sample several learning samples, and then sensorily evaluate the intensity of each of the saltiness, sourness, sweetness, umami, and bitterness, comparing it with the intensity of each taste in the standard samples and quantifying the results.

[0025] The sweetness learning sample used in the sensory evaluation may be, for example, one of the sweeteners selected from the group consisting of thaumatin, stevia, sucralose, aspartame, saccharin, acesulfame K, refined sucrose, lactose, and D-mannitol. However, the sweetness learning sample is not particularly limited.

[0026] Figure 2 shows a combination of learning samples for a taste measurement system according to one embodiment of the present invention. The learning samples used in the sensory test may be, for example, a combination of a sweetener and a flavoring. The flavoring to be combined with one of the sweeteners may be one selected from the group consisting of flavorings such as yuzu, pineapple, cider, strawberry, peach, orange, lemon, grapefruit, banana, yogurt, apple, melon, blueberry, grape, white grape, muscat, milk, chocolate, caramel, vanilla, mango, matcha, coffee, cherry, fruit mix, and menthol. Preferably, the flavoring to be combined with one of the sweeteners is one selected from the group consisting of flavorings such as yuzu, pineapple, cider, strawberry, peach, orange, lemon, grapefruit, banana, and yogurt. However, the flavoring to be combined with one of the sweeteners is not particularly limited.

[0027] In this embodiment, it is preferable that the sensory test involves panelists tasting or sampling five standard samples, each independently containing one of the five tastes: saltiness, sourness, sweetness, umami, and bitterness. Then, the panelists tasting or sampling a learning sample containing one of nine sweeteners independently. They then sensorily evaluate the intensity of each of the saltiness, sourness, sweetness, umami, and bitterness, and quantify the results by comparing them to the intensity of each of the standard samples. In this embodiment, it is preferable that the sensory test further involves panelists tasting or sampling five standard samples, each independently containing one of the five tastes: saltiness, sourness, sweetness, umami, and bitterness. Then, the panelists tasting or sampling ten learning samples obtained by combining the sweeteners with ten flavorings. They then sensorily evaluate the intensity of each of the saltiness, sourness, sweetness, umami, and bitterness, and quantify the results by comparing them to the intensity of each of the standard samples.

[0028] More preferably, the standard sample consists of two standard samples of different concentrations for each taste, and the sensory evaluation of the learning sample is quantified based on a five-point scale for each taste: (1) not perceived at all, (2) perceived weaker than the low-concentration standard sample, (3) perceived as equivalent to the low-concentration standard sample, (4) perceived as being of intermediate strength between the low-concentration and high-concentration standard samples, and (5) perceived as equivalent to or stronger than the high-concentration standard sample. Each of these five levels of evaluation may be further subdivided.

[0029] The neural network 200 can learn the intensity of saltiness, sourness, sweetness, umami, and bitterness perceived by humans as a result of the interaction between flavorings and sweeteners by inputting the results obtained from sensory tests using nine training samples containing one of nine sweeteners, and 90 training samples combining each of the nine sweeteners with one of ten flavorings. Furthermore, by having the neural network 200 learn the concentration of each component and the standard deviation of the intensity of saltiness, sourness, sweetness, umami, and bitterness perceived by humans, it can also calculate the variability of the intensity of saltiness, sourness, sweetness, umami, and bitterness perceived by humans.

[0030] The output layer 30 outputs analytical values ​​indicating the intensity of saltiness, sourness, sweetness, umami, and bitterness as perceived by a person, as analyzed in the intermediate layer.

[0031] In the taste measurement system of the present invention, the neural network 200 is trained to learn the intensity of saltiness, sourness, sweetness, umami, and bitterness that humans perceive as resulting from the interaction of flavorings and sweeteners, making it possible to more accurately mimic human taste. As specifically shown in the following examples, surprisingly, the system of the present invention was even able to reproduce the taste illusions that humans perceive, such as the increase or decrease in bitterness of the active ingredients contained in oral pharmaceutical preparations due to changes in the combination of flavorings and sweeteners.

[0032] (Method of measuring taste) The method for measuring the taste of a sample using the taste measurement system described above is explained below.

[0033] Prepare any sample to evaluate its taste. The sample may contain the active ingredient found in an oral pharmaceutical preparation and one sweetener, or one flavoring and one sweetener.

[0034] The sample is input to the input layer 10 of the taste measurement system 1. The input layer 10 uses the sensor 100 to measure the actual values ​​of saltiness, sourness, sweetness, umami, and bitterness in the sample.

[0035] The measured values ​​obtained by the sensor 100 are input to the intermediate layer 20 of the taste measurement system 1. The intermediate layer 20 uses a neural network 200 to calculate the concentration of each component from the obtained measured values.

[0036] The intermediate layer 20 further uses a neural network 200 to calculate analytical values ​​representing the intensity of saltiness, sourness, sweetness, umami, and bitterness as perceived by humans, based on the concentrations of each component obtained.

[0037] The output layer 30 outputs analytical values ​​indicating the intensity of saltiness, sourness, sweetness, umami, and bitterness as perceived by a person, as analyzed in the intermediate layer.

[0038] In the taste measurement method of the present invention, the neural network 200 is trained to learn the intensity of saltiness, sourness, sweetness, umami, and bitterness that humans perceive as resulting from the interaction of flavorings and sweeteners, making it possible to more accurately mimic human taste. As specifically shown in the following examples, surprisingly, the method of the present invention was even able to reproduce the taste illusions that humans perceive, such as the increase or decrease in bitterness of the active ingredient contained in oral pharmaceutical preparations due to changes in the combination of flavorings and sweeteners. [Examples]

[0039] The taste measurement system and taste measurement method for oral pharmaceutical preparations according to the present invention will be explained in more detail by showing specific examples and test results.

[0040] (1) Sensor Na is a component that gives a salty taste. + , and Cl - H + Sensors were created for components that exhibit sweetness, such as glucose and sucrose; components that exhibit umami, such as glutamate; and components that exhibit bitterness, such as caffeine. + Sensor, Cl - Sensor, H + The sensors were ion-selective electrodes. The glucose, sucrose, and glutamate sensors were enzyme electrodes.

[0041] (2) Training with training data To simulate the taste interactions resulting from combinations of flavorings and sweeteners, a sensory evaluation was conducted by six panelists, and the results were used for training. The panelist sensory evaluation was conducted as follows:

[0042] As standard samples for the five basic tastes—salty, sour, sweet, umami, and bitter—five different samples containing each taste independently were prepared in two different concentrations, as shown in Table 1. [Table 1]

[0043] For learning about sweetness, the following samples were used: thaumatin (Sunsweet® T / San-Ei Gen FFI Co., Ltd.) 0.5 mg / 10 mL, stevia (stevioside / Tokyo Chemical Industries, Ltd.) 1.7 mg / 10 mL, sucralose (sucralose / San-Ei Gen FFI Co., Ltd.) 1.0 mg / 10 mL, aspartame (aspartame / Ajinomoto Co., Inc.) 3.3 mg / 10 mL, saccharin sodium (saccharin sodium hydrate BP / Yamato Chemical Co., Ltd.) 1.7 mg / 10 mL, acesulfame potassium (Sanet Pharm Grade Type D (fine powder) / MC Food Specialties Co., Ltd.) 3.0 mg / 10 mL, refined sucrose (refined sucrose / Fujifilm Wako Pure Chemical Industries, Ltd.) 300 mg / 10 mL, lactose (Pharmatose® 200 M / FrieslandCampina DMV) Nine different preparations were used, consisting of either BV) 1000 mg / 10 ml or D-mannitol (Mannit P / Mitsubishi Corporation Life Sciences Co., Ltd.) 500 mg / 10 ml.

[0044] The learning samples for sweeteners and flavorings were created by combining the above-mentioned learning samples for sweetness with flavorings. The ten flavorings that could be combined with each of the above-mentioned learning samples for sweetness were yuzu (SGW-0008 / Shiono Fragrance Co., Ltd.), pineapple (SGW-0018 / Shiono Fragrance Co., Ltd.), cider (SGW-0029 / Shiono Fragrance Co., Ltd.), strawberry (SGW-0013 / Shiono Fragrance Co., Ltd.), peach (SGW-0020 / Shiono Fragrance Co., Ltd.), orange (SGW-0003 / Shiono Fragrance Co., Ltd.), lemon (SGW-0005 / Shiono Fragrance Co., Ltd.), grapefruit (SGW-0004 / Shiono Fragrance Co., Ltd.), banana (SGW-0019 / Shiono Fragrance Co., Ltd.), and yogurt (SGW-0033 / Shiono Fragrance Co., Ltd.). The fragrance concentration was adjusted to 8.5 mg / 10 ml for all products used.

[0045] Each panelist tasted a standard sample and memorized each basic taste. They then sequentially tasted 10 different sweeteners and flavoring samples, including a sweetness learning material and flavorings, and evaluated the intensity of the five basic tastes for each learning sample. Each taste was rated on a 5-point scale and described numerically. All samples were at room temperature, and participants rinsed their mouths with water before tasting the next sample. The mean and standard deviation of the obtained values ​​were calculated.

[0046] By inputting the results obtained from the sensory evaluation into the neural network 200, the intermediate layer 20 was able to learn the intensity of saltiness, sourness, sweetness, umami, and bitterness that people perceive as resulting from the interaction of flavorings and sweeteners. Figures 12 to 14 show the average values ​​learned by the neural network 200, and Figures 15 to 17 show the standard deviations learned by the neural network 200.

[0047] (3) Example 1 Using the taste measurement system according to this embodiment, the salty, sour, sweet, umami, and bitter tastes derived from the active ingredients, flavorings, and sweeteners contained in oral pharmaceutical preparations were analyzed.

[0048] Teneligliptin hydrobromide was used as the active ingredient in the oral pharmaceutical preparation, and sucralose was used as the sweetener. Yuzu, pineapple, cider, strawberry, peach, orange, lemon, grapefruit, banana, or yogurt flavorings were added, and the salty, sour, sweet, umami, and bitter tastes resulting from the active ingredient, flavorings, and sweeteners in the oral pharmaceutical preparation were analyzed. The samples were prepared by adding 31 mg of teneligliptin hydrobromide, 1.4 mg of sucralose, and 12.5 mg of flavoring to 15 mL of water and mixing. The samples were then analyzed using a taste measurement system (Taste Sensor Leo, OISSY Co., Ltd.) that had been trained with training data. Figure 3 shows the analysis results of Example 1 using the taste measurement system according to this embodiment. Figure 4 shows the radar chart of Example 1 using the taste measurement system according to this embodiment.

[0049] (4) Reference example 1 Sensory evaluation was conducted to assess the taste derived from the active ingredients, flavorings, and sweeteners contained in the oral pharmaceutical formulation.

[0050] Teneligliptin hydrobromide was used as the active ingredient in the oral pharmaceutical preparation, and sucralose was used as the sweetener. Yuzu, pineapple, cider, strawberry, or peach flavorings were added, and the taste resulting from the active ingredient, flavoring, and sweetener in the oral pharmaceutical preparation was evaluated. Samples were prepared by adding 31 mg of teneligliptin hydrobromide, 1.4 mg of sucralose, and 12.5 mg of flavoring to 15 mL of water and mixing, and a sensory evaluation was conducted by two panelists. A three-level rating from delicious to unpleasant was used to comprehensively judge the five basic tastes. Figure 5 shows the sensory evaluation results for Reference Example 1.

[0051] (5) Comparative Example 1 Using a taste measurement system prior to training with training data, we analyzed the saltiness, sourness, sweetness, umami, and bitterness derived from the active ingredients, flavorings, and sweeteners contained in oral pharmaceutical preparations.

[0052] Teneligliptin hydrobromide was used as the active ingredient in the oral pharmaceutical formulation, and sucralose was used as the sweetener. Yuzu, pineapple, cider, strawberry, or peach flavorings were added, and the salty, sour, sweet, umami, and bitter tastes resulting from the active ingredient, flavoring, and sweetener in the oral pharmaceutical formulation were analyzed. Samples were prepared by adding 31 mg of teneligliptin hydrobromide, 1.4 mg of sucralose, and 12.5 mg of flavoring to 15 mL of water and mixing. The samples were then analyzed using a taste measurement system (Taste Sensor Leo, OISSY Co., Ltd.) before training with training data. Figure 6 shows the analysis results of Comparative Example 1 using the taste measurement system before training with training data. Figure 7 shows the radar chart of Comparative Example 1 using the taste measurement system before training with training data.

[0053] (6) Comparison results of Example 1, Reference Example 1, and Comparative Example 1 In Example 1, the strawberries and peaches that were perceived as bitter in the sensory test of Reference Example 1 showed a difference compared to the yuzu and pineapple, which were less perceived as bitter. In particular, the strawberries showed a difference of 0.2 or more (a difference that could be recognized by more than 95% of people) compared to the yuzu and pineapple, and a correlation with the sensory test of Reference Example 1 was confirmed. Furthermore, a correlation was confirmed with the sensory test results of analyses using other sweeteners (saccharin).

[0054] In Comparative Example 1, the strawberries and peaches that were perceived as bitter in the sensory test of Reference Example 1 did not show any significant difference compared to the yuzu and pineapple, which were perceived as less bitter. In particular, the peach had the lowest bitterness score. It was found that Comparative Example 1 did not correlate with the sensory test of Reference Example 1.

[0055] Figure 8 shows the analysis results of the bitterness scores for Example 1 and Comparative Example 1. In Comparative Example 1, the bitterness scores for strawberries and peaches, which were perceived as bitter in the sensory test of Reference Example 1, were lower compared to Example 1. In addition, the sourness scores for all fruits except peaches in Comparative Example 1 were higher than in Example 1, resulting in different analysis results before and after training with the training data.

[0056] (7) Example 2 Using the taste measurement system according to this embodiment, we analyzed the saltiness, sourness, sweetness, umami, and bitterness resulting from the active ingredients, flavorings, and sweeteners contained in other oral pharmaceutical preparations.

[0057] Lacosamide was used as the active ingredient in the oral pharmaceutical formulation, and sucralose was used as the sweetener. Yuzu, pineapple, cider, strawberry, peach, orange, lemon, grapefruit, banana, or yogurt flavorings were added, and the salty, sour, sweet, umami, and bitter tastes resulting from the active ingredient, flavorings, and sweeteners in the oral pharmaceutical formulation were analyzed. Samples were prepared by adding 50 mg of lacosamide, 1.4 mg of sucralose, and 12.5 mg of flavoring to 15 mL of water and mixing, and the results were analyzed using a taste measurement system (Taste Sensor Leo, OISSY Co., Ltd.) that had been trained with training data. Figure 9 shows the analysis results of Example 2 using the taste measurement system according to this embodiment. Figure 10 shows the radar chart of Example 2 using the taste measurement system according to this embodiment.

[0058] (8) Reference example 2 Sensory evaluation was conducted to assess the taste derived from the active ingredients, flavorings, and sweeteners contained in the oral pharmaceutical formulation.

[0059] Lacosamide was used as the active ingredient in the oral pharmaceutical preparation, and sucralose was used as the sweetener. Yuzu, strawberry, cider, banana, orange, or lemon flavorings were added, and the taste resulting from the active ingredient, flavoring, and sweetener in the oral pharmaceutical preparation was evaluated. Samples were prepared by adding 50 mg of lacosamide, 1.4 mg of sucralose, and 12.5 mg of flavoring to 15 mL of water and mixing, and a sensory evaluation was conducted by two panelists. A five-point scale was used to comprehensively judge the five basic tastes: 5: Delicious, 4: Better than sweetener alone, 3: About the same as sweetener alone, 2: Worse than sweetener alone, and 1: Unpleasant. Figure 11 shows the sensory evaluation results for Reference Example 2.

[0060] (9) Comparison results of Example 2 and Reference Example 2 In Example 2, the oranges, lemons, and yuzu that performed better with only the sweetener in the sensory test of Reference Example 2 showed lower values ​​(less bitterness perceived) than those with only the sweetener, thus confirming a correlation with the sensory test of Reference Example 2. [Explanation of symbols]

[0061] 1: Taste measurement system, 10: Input layer, 20: Hidden layer, 30: Output layer, 100: Sensor, 200: Neural network

Claims

1. An input layer for measuring the measured values ​​of saltiness, sourness, sweetness, umami, and bitterness in a sample containing the active ingredients, flavorings, and sweeteners found in oral pharmaceutical preparations, Based on the measured values, an intermediate layer calculates analytical values ​​of saltiness, sourness, sweetness, umami, and bitterness resulting from the interaction between the active ingredient and the flavorings and sweeteners, using a neural network trained on the results of sensory tests of arbitrary flavorings and sweeteners that do not contain the active ingredient in the oral pharmaceutical preparation as training data. An output layer that outputs the aforementioned analysis values, A taste measurement system for oral pharmaceutical formulations, including [specific example].

2. The taste measurement system for an oral pharmaceutical preparation according to claim 1, wherein the flavoring used in the sensory test is one selected from the group consisting of yuzu, pineapple, cider, strawberry, peach, orange, lemon, grapefruit, banana, and yogurt flavorings.

3. The taste measurement system for an oral pharmaceutical preparation according to claim 2, wherein the fragrance contained in the oral pharmaceutical preparation is the fragrance used in the sensory test.

4. The taste measurement system for an oral pharmaceutical preparation according to claim 3, wherein the sweetener used in the sensory test is one selected from the group consisting of thaumatin, stevia, sucralose, aspartame, saccharin, acesulfame K, refined sucrose, lactose, and D-mannitol.

5. The taste measurement system for an oral pharmaceutical preparation according to claim 4, wherein the sweetener contained in the oral pharmaceutical preparation is the sweetener used in the sensory evaluation.

6. The taste measurement system for an oral pharmaceutical preparation according to claim 5, wherein the active ingredient has a bitter taste.

7. The measured values ​​of saltiness, sourness, sweetness, umami, and bitterness in samples containing active ingredients, flavorings, and sweeteners found in oral pharmaceutical preparations were measured. Based on the measured values, a neural network trained using the results of sensory tests of arbitrary fragrances and sweeteners that do not contain the active ingredient in the oral pharmaceutical preparation was used to calculate analytical values ​​of saltiness, sourness, sweetness, umami, and bitterness resulting from the interaction between the active ingredient and the fragrances and sweeteners. Output the aforementioned analysis values. A method for measuring the taste of oral pharmaceutical preparations, including [specific example].

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