Method for on-line monitoring of drug application rate of pellet coating through combination of near infrared spectroscopy and real-time weighing

Abstract

The invention belongs to the technical field of quality control, and relates to a method for on-line monitoring of the drug application rate of a pellet coating by combining near infrared spectroscopy with real-time weighing. The method comprises the following steps: (a) providing an active pharmaceutical ingredient (API) content model, detecting a real-time near infrared spectrum in a pellet coating process in real time, and predicting the real-time API content according to the real-time near infrared spectrum by adopting the API content model; (b) the coating liquid is weighed in real time in the pellet coating process, the real-time coating liquid weight is obtained, the obtaining time point of the real-time coating liquid weight is the same as the obtaining time point of the real-time near infrared spectrum, and the real-time total coating weight is obtained according to the real-time coating liquid weight technology; and (c) calculating the real-time pellet coating drug application rate according to the real-time API content and the real-time total coating weight. According to the invention, the drug application rate of the pellets can be accurately monitored in real time in the coating process.

Description

Technical Field

[0001] The invention belongs to the technical field of quality control and relates to a method for online monitoring of micropill coating drug application rate by combining near infrared spectroscopy with real-time weighing. Background Art

[0002] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention, and should not necessarily be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art.

[0003] In the fluidized bed coating process, the drug application rate refers to the ratio of the weight of the drug applied in the coating to the total coating weight, usually expressed as a percentage. This parameter is very important in the pharmaceutical process because it is directly related to the efficacy, release characteristics and production efficiency of the drug. Accurate drug application rate monitoring can ensure product consistency and quality while reducing resource waste. Therefore, improving the online monitoring capability of pellet coating drug application rate is an indispensable part of modern pharmaceutical technology.

[0004] At present, the detection method of drug coating rate of micropellet is mainly based on offline sampling. Common methods include chemical analysis, chromatography technology and weighing method. Although these traditional methods can provide relatively accurate drug content data, their limitations are also very obvious. Offline detection not only requires a long analysis time, which may cause delays in the production process, but also fails to reflect the changes in drug content in the coating process in real time, affecting the timeliness and effectiveness of process control. In addition, the sample processing process may cause the loss or change of the drug, thereby reducing the reliability of the test results. Summary of the invention

[0005] In order to address the deficiencies of the prior art, the purpose of the present invention is to provide a method for online monitoring of the drug application rate of micropill coating by near-infrared spectroscopy combined with real-time weighing. Near-infrared spectroscopy (NIR) can be used to quickly and non-destructively analyze the surface and internal components of the micropills, and to evaluate the drug content in real time, thereby achieving dynamic process control. At the same time, combined with real-time weighing, the drug application rate of the micropills can be monitored in real time and accurately during the coating process.

[0006] In order to achieve the above technical objectives, the technical solution adopted by the present invention is as follows:

[0007] In the first aspect, a method for online monitoring of pellet coating drug loading rate using near infrared spectroscopy combined with real-time weighing comprises the following steps:

[0008] (a) providing a pharmaceutical active ingredient (API) content model, detecting the real-time near infrared spectrum during the pellet coating process in real time, and using the API content model to predict the real-time API content based on the real-time near infrared spectrum;

[0009] (b) weighing the coating liquid in real time during the pellet coating process to obtain the real-time coating liquid weight, and the time point for obtaining the real-time coating liquid weight is the same as the time point for obtaining the real-time near-infrared spectrum, and obtaining the real-time total coating weight according to the real-time coating liquid weight technology;

[0010] (c) calculating the real-time pellet coating rate based on the real-time API content and the real-time total coating weight;

[0011] The construction process of the API content model is:

[0012] NIR spectra and pellet samples were collected simultaneously at different time points during the pellet coating process;

[0013] Detecting the API content in the pellet sample;

[0014] The API content model was established based on the near-infrared spectra at different time points and the API content at the corresponding time points.

[0015] The present invention collects near infrared spectra and micropill samples at different time points during the micropill coating process, ensures that the time of collecting the near infrared spectra and the micropill samples is the same, thereby ensuring a one-to-one correspondence between the near infrared spectra and the API content in the detected micropill samples, and then uses the near infrared spectra and the API content at the corresponding time point to establish an API content model, through which the relationship between the near infrared spectra and the API content at the time point can be established, thereby achieving real-time API content in the micropill coating process by real-time monitoring of the near infrared spectra of the micropill coating process, then obtaining the real-time total coating weight by real-time weighing, and obtaining the real-time micropill coating drug application rate by calculating the real-time API content and the real-time total coating weight, thereby achieving online monitoring of the micropill coating drug application rate by combining the near infrared spectra with the real-time weighing.

[0016] In the second aspect, a system for online monitoring of the drug application rate of micro-pellet coating by near infrared spectroscopy combined with real-time weighing is used to implement the above method, comprising:

[0017] A spectral data acquisition module, which is configured to: acquire a real-time near infrared spectrum during the pellet coating process;

[0018] A coating data acquisition module, which is configured to: obtain the real-time coating liquid weight during the pellet coating process;

[0019] The output module is configured to: convert the real-time coating liquid weight into the real-time total coating weight of the micropellet coating, input the real-time near-infrared spectrum into the API content model to obtain the real-time API content, and then calculate the real-time API content and the real-time total coating weight to obtain the real-time micropellet coating drug application rate.

[0020] The beneficial effects of the present invention are:

[0021] The present invention constructs an API content model of the relationship between near-infrared spectrum and API content by introducing near-infrared spectroscopy technology, and can realize real-time detection of API content by detecting near-infrared spectrum. At the same time, the introduction of real-time weighing technology can detect the total coating weight of micropills in real time, and then calculate the micropill drug application rate by the real-time detected API content and the real-time detected total coating weight of micropills, thereby realizing real-time and accurate monitoring of the micropill drug application rate. The present invention not only breaks the limitation of the lag of traditional offline detection methods, but also avoids the detection reliability problems caused by the loss or change of drugs during sample processing, and can further improve the automation and intelligence level of the production process, providing new ideas for drug quality control and optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0023] Figure 1 This is the original near-infrared spectrum detected by Example 1 of the present invention;

[0024] Figure 2 This is the interface diagram of the online weighing technology EasyDirect Balance of Example 1 of the present invention;

[0025] Figure 3 This is the API content prediction diagram of Example 1 of the present invention;

[0026] Figure 4 1 is a comparison chart of the predicted and actual values ​​of the drug application rate of Example 1 of the present invention, (a) is the first batch, (b) is the second batch, and (c) is the third batch. DETAILED DESCRIPTION

[0027] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0028] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0029] In view of the problems that the existing methods for detecting the drug application rate of micro-pill coating have long time and detection lag, the present invention proposes a method for online monitoring the drug application rate of micro-pill coating by combining near-infrared spectroscopy with real-time weighing.

[0030] A typical embodiment of the present invention provides a method for online monitoring of pellet coating drug loading rate by near infrared spectroscopy combined with real-time weighing, comprising the following steps:

[0031] (a) providing a pharmaceutical active ingredient (API) content model, detecting the real-time near infrared spectrum during the pellet coating process in real time, and using the API content model to predict the real-time API content based on the real-time near infrared spectrum;

[0032] (b) weighing the coating liquid in real time during the pellet coating process to obtain the real-time coating liquid weight, and the time point for obtaining the real-time coating liquid weight is the same as the time point for obtaining the real-time near-infrared spectrum, and obtaining the real-time total coating weight according to the real-time coating liquid weight technology;

[0033] (c) calculating the real-time pellet coating rate based on the real-time API content and the real-time total coating weight;

[0034] The construction process of the API content model is:

[0035] NIR spectra and pellet samples were collected simultaneously at different time points during the pellet coating process;

[0036] Detecting the API content in the pellet sample;

[0037] The API content model was established based on the near-infrared spectra at different time points and the API content at the corresponding time points.

[0038] The method provided by the present invention is suitable for drug application rate detection in all micro-pill coating processes, and is more suitable for drug application rate detection in a fluidized bed micro-pill coating process.

[0039] In some embodiments, the near infrared spectrum is collected in diffuse reflectance mode. The near infrared spectrum is collected throughout the entire pellet coating process, once every 8 to 12 seconds. In order to prevent the near infrared probe from being contaminated, compressed air is blown every 30 seconds.

[0040] In some embodiments, before using near-infrared spectroscopy, a polytetrafluoroethylene white board is used as a background spectrum; specifically, the integration time is adjusted to 8.1 ms, the wavelength range is 908.1 to 1676.0 nm, and the number of scans for each spectrum is 100.

[0041] In some embodiments, ultraviolet spectrophotometry is used to detect the API content in the micropellet sample.

[0042] For API content analysis, a certain weight of drug-coated pellets was randomly selected from each sample. The pellets were fully dissolved in an ultrasonic bath. The solution was filtered through a 0.45 μm filter and the absorbance was measured at the corresponding API absorption wavelength using a UV-visible spectrophotometer (EU-2800D, Zhongke Ruijie, China). A standard calibration curve was developed and used to calculate the API concentration in each solution. The API content was then determined as the ratio of the API mass to the mass of the pill containing the drug, that is, the API content (w / w).

[0043] In some embodiments, the partial least squares (PLS) method is used to establish the API content model. Specifically, the established API content model is verified, wherein the model evaluation parameters include: the coefficient of determination (R 2 ), root mean square error (RMSE), and performance to deviation ratio (RPD) to evaluate model performance. Generally speaking, a good model will have a higher R 2 and RPD and lower RMSE.

[0044] In some embodiments, the API content model is constructed after preprocessing the near infrared spectrum. The reliability of constructing the API content model is increased by preprocessing the near infrared spectrum. Specifically, the near infrared spectrum is preprocessed using the first derivative (SG1) and standard normal variable transformation (SNV) methods. Studies have shown that the use of the SG1+SNV preprocessing method can make the constructed API content model more reliable, thereby providing the accuracy of the micropill coating drug loading rate.

[0045] In some embodiments, the weight of the API in the coating liquid, the weight of the solid content in the coating liquid, and the weight of the liquid content in the coating liquid are obtained, and the real-time total coating weight is calculated based on the real-time coating liquid weight and the obtained weight of the API in the coating liquid, the weight of the solid content in the coating liquid, and the weight of the liquid content in the coating liquid.

[0046] In one or more embodiments, the total weight of the blank pill cores is obtained, and the real-time theoretical total weight of the drug-containing micro-pellets is obtained based on the real-time coating liquid weight, the weight of the solid content in the coating liquid, the weight of the liquid content in the coating liquid, and the total weight of the blank pill cores.

[0047] Specifically, the real-time pellet coating drug application rate is calculated based on the real-time API content, the real-time total coating weight, and the real-time theoretical total weight of the drug-containing pellets.

[0048] In some embodiments, the process of calculating the real-time pellet coating rate includes:

[0049] Calculation of theoretical API weight coated on micropellets; the calculation formula is as follows:

[0050]

[0051] Among them, M api_lilun (i) is the total weight of API entering the fluidized bed at time i (g), M in (i) is the total weight of the coating liquid entering the fluidized bed at time i (g), which can be obtained through real-time balance data, M api is the weight of API in the coating solution (g), M solid is the weight of the solid content in the coating solution (g), M liquid is the weight of the liquid content in the coating solution (g);

[0052] Calculation of the total weight of the theoretical drug-containing pellets coated on the pellets; the calculation formula is as follows:

[0053]

[0054] Among them, M z_lilun (i) is the theoretical total weight of drug-containing pellets in the fluidized bed at time i (g), M pellet is the total weight of blank pellet core (g);

[0055] Calculation of drug application rate; the calculation formula is as follows:

[0056] Among them, AP n (i) is the drug loading rate of drug-containing pellets in the fluidized bed at time i (%), W n (i) is the actual API content (w / w) coated on the micropellets predicted by the API content model established by near infrared spectroscopy.

[0057] In some embodiments, the real-time near infrared spectrum is pre-processed and input into the API content model to obtain the real-time API content. Specifically, the pre-processing method is SG1 and SNV.

[0058] Another embodiment of the present invention provides a system for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing, which is used to implement the above method, including:

[0059] A spectral data acquisition module, which is configured to: acquire a real-time near infrared spectrum during the pellet coating process;

[0060] A coating data acquisition module, which is configured to: obtain the real-time coating liquid weight during the pellet coating process;

[0061] The output module is configured to: convert the real-time coating liquid weight into the real-time total coating weight of the micropellet coating, input the real-time near-infrared spectrum into the API content model to obtain the real-time API content, and then calculate the real-time API content and the real-time total coating weight to obtain the real-time micropellet coating drug application rate.

[0062] In some embodiments, a preprocessing module is included, which is configured to: preprocess the real-time near infrared spectrum obtained during the micropill coating process, and the output module inputs the preprocessed real-time near infrared spectrum into the API content model to obtain the real-time API content. Specifically, the preprocessing method performed by the preprocessing module is SG1 and SNV.

[0063] In some embodiments, a near infrared spectrometer (Micro NIR PATU) is inserted into a micro-pellet coating device. Specifically, the micro-pellet coating device is a fluidized bed. More specifically, the near infrared spectrometer is inserted into a fluidized bed cavity.

[0064] In order to enable those skilled in the art to more clearly understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below in conjunction with specific embodiments.

[0065] Example

[0066] (1) Collect near-infrared spectra of the entire fluidized bed coating process.

[0067] Before each coating batch, preheat the fluidized bed for half an hour to make the fluidized bed granulate in a relatively stable state. After preheating, put the materials in, mix for 10 minutes, and then start spraying the coating liquid.

[0068] During the coating process, the Micro NIR PATU near-infrared spectrometer was inserted into the fluidized bed cavity, and the spectrum was collected in diffuse reflection mode. Before inserting the near-infrared probe, a polytetrafluoroethylene white plate was collected as the background spectrum, the integration time was adjusted to 8.1ms, the wavelength range was 908.1-1676.0nm, and the number of scans for each spectrum was 100. The spectrum was collected throughout the entire fluidized bed coating process, and a spectrum was collected every 10s. In order to prevent the near-infrared probe from being contaminated, compressed air was blown every 30s. See the spectrum diagram. Figure 1 shown.

[0069] (2) Use an online electronic balance capable of transmitting data in real time to collect weight data of the coating liquid during the entire fluidized bed coating process.

[0070] 1) Use an Ethernet cable to connect the balance to the network (LAN);

[0071] 2) Activate LAN: General Configuration and Data -> Network and Bluetooth;

[0072] 3) General Configuration and Data -> Devices and Services -> Add EasyDirect Balance as a new service item via LAN;

[0073] 4) General Configuration and Data -> Publish -> Send Data -> Select Network Transmission -> Set to transmit every 10 seconds;

[0074] EasyDirect Balance transmits balance weight data in real time such as Figure 2 shown.

[0075] (3) Samples were collected at different time points during the fluidized bed coating process (corresponding to the spectral sequence) and the API content (w / w) was measured offline using a UV spectrophotometer.

[0076] For API content analysis, approximately 50 mg of drug-containing pellets were randomly selected from each sample. The pellets were dissolved in pure water in an ultrasonic bath for 20 minutes. The solution was filtered through a 0.45 μm filter and the absorbance was measured at the corresponding API absorption wavelength using a UV-visible spectrophotometer (EU-2800D, Zhongke Ruijie, China). A standard calibration curve was developed and used to calculate the API concentration in each solution. The API content was then determined as the ratio of the API mass to the mass of the pills containing the drug, that is, the API content (w / w).

[0077] (4) Combining the near infrared spectroscopy data with the offline measured API content data, the partial least squares (PLS) method was used to establish the API content model. The established API content model was verified. The model evaluation parameters included: determination coefficient (R 2 ), root mean square error (RMSE) and performance to deviation ratio (RPD) to evaluate the model performance, and the calculation formulas are shown in formula (1), formula (2) and formula (3) respectively.

[0078]

[0079] where y i , actual represents the reference value of the i-th sample, y i , predicted represents the predicted value of the i-th sample, represents the mean of the actual value, and m is the number of samples. Generally speaking, a good model will have a higher R 2 and RPD and lower RMSE.

[0080] The results are shown in Table 1. The best result is when the spectrum preprocessing method is SG1+SNV. 2 C ,RMSEC,R 2 V ,RMSEP,RPD,R 2 T, RMSET are 0.97, 0.008, 0.97, 0.009, 5.37, 0.94, and 0.012, respectively, which indicates that the API content model is reliable and can be used for the subsequent prediction of API content.

[0081] Table 1 Results of the near infrared spectroscopy prediction model for API content under different pretreatment methods

[0082]

[0083]

[0084] SNV: standard normal variate transformation; SG1: Savitzky-Golay first-order derivative; SG2: Savitzky-Golay second-order derivative; the optimal model results are underlined.

[0085] (5) The established API content model is used to predict the changes in API content in real time during the entire fluidized bed coating process. The prediction graph of one batch of API content is shown in the figure below: Figure 3 As shown in the figure, it can be seen that the API content shows a continuous growth trend, but it is not a straight line, indicating that there may be some loss in the drug application process.

[0086] (6) Calculate the ratio of the API content predicted by the near infrared spectroscopy model to the theoretical API content calculated based on the online weighing data, which is the real-time change in the drug loading rate during the coating process. The specific calculation formula is as follows:

[0087] Theoretical API weight calculation of entering the fluidized bed and coated on the micropellets:

[0088]

[0089] Among them, M api_lilun (i) is the total weight of API entering the fluidized bed at time i (g), M in (i) is the total weight of the coating liquid entering the fluidized bed at time i (g), which can be obtained through real-time balance data, M api is the weight of API in the coating solution (g), M solid is the weight of the solid content in the coating solution (g), M liquid is the weight (g) of the liquid content in the coating solution.

[0090] Theoretical solid polymer weight entering the fluidized bed and coated on the micropellets is calculated as follows:

[0091]

[0092] Among them, M z_lilun (i) is the total weight of the drug-containing pellets in the fluidized bed at time i (g), M pelletis the total weight of blank pellets (g).

[0093]

[0094] Among them, AP n (i) is the drug loading rate of drug-containing pellets in the fluidized bed at time i (%), W n (i) is the actual API content (w / w) coated on the micropellets predicted by the API content model established by near infrared spectroscopy.

[0095] In this embodiment, the weight of API in the coating solution is M api The solid content of the coating liquid is 200g. solid The weight is 204g, and the liquid content in the coating liquid is M liquid The weight is 800g, blank pellet core M pellet The total weight is 1000g. The drug loading rate of three validation batches (the API of the three validation batches is metformin) varies as follows: Figure 4 As shown, through endpoint offline verification, the red circle coincides with the blue line, proving the accuracy of the method.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing, characterized in that: The steps include: (a) providing an API content model, detecting the real-time near infrared spectrum during the pellet coating process in real time, and using the API content model to predict the real-time API content based on the real-time near infrared spectrum; (b) weighing the coating liquid in real time during the pellet coating process to obtain the real-time coating liquid weight, and the time point for obtaining the real-time coating liquid weight is the same as the time point for obtaining the real-time near-infrared spectrum, and obtaining the real-time total coating weight according to the real-time coating liquid weight technology; (c) calculating the real-time pellet coating rate based on the real-time API content and the real-time total coating weight; The construction process of the API content model is: NIR spectra and pellet samples were collected simultaneously at different time points during the pellet coating process; Detecting the API content in the pellet sample; The API content model was established based on the near-infrared spectra at different time points and the API content at the corresponding time points.

2. The method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 1, characterized in that: The near-infrared spectrum was collected in diffuse reflectance mode.

3. The method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 1, characterized in that: Before using near-infrared spectroscopy, a polytetrafluoroethylene white board was used as the background spectrum.

4. The method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 1, characterized in that: The API content in the micropellet sample was detected by ultraviolet spectrophotometry.

5. The method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 1, characterized in that: The partial least squares method was used to establish the API content model.

6. The method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 1, characterized in that: The API content model is constructed after preprocessing the near infrared spectrum; preferably, the near infrared spectrum is preprocessed by using the first derivative and standard normal variable transformation method.

7. The method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 1, characterized in that: The process of calculating real-time pellet coating drug loading includes: Calculation of theoretical API weight coated on micropellets; the calculation formula is as follows: Among them, M api_lilun (i) is the total weight of API entering the fluidized bed at time i, M in (i) is the total weight of the coating liquid entering the fluidized bed at time i, which can be obtained through real-time balance data, M api is the weight of API in the coating solution, M solid is the weight of the solid content in the coating solution, M liquid is the weight of the liquid content in the coating solution; Calculation of the theoretical solid polymer weight coated on the micropellets; the calculation formula is as follows: Among them, M z_lilun (i) is the total weight of the drug-containing pellets in the fluidized bed at time i, M pellet is the total weight of blank pellet core; Calculation of drug application rate; the calculation formula is as follows: Among them, AP n (i) is the drug loading rate of drug-containing pellets in the fluidized bed at time i, W n (i) The actual API content coated on the micropellets predicted by the API content model constructed by near infrared spectroscopy.

8. The method for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 1, characterized in that: The real-time near-infrared spectrum is preprocessed and input into the API content model to obtain the real-time API content; preferably, the preprocessing method is SG1 and SNV.

9. A system for online monitoring of pellet coating rate using near infrared spectroscopy combined with real-time weighing, characterized in that: The method for implementing claim 1 comprises: A spectral data acquisition module, which is configured to: acquire a real-time near infrared spectrum during the pellet coating process; A coating data acquisition module, which is configured to: obtain the real-time coating liquid weight during the pellet coating process; The output module is configured to: convert the real-time coating liquid weight into the real-time total coating weight of the micropellet coating, input the real-time near-infrared spectrum into the API content model to obtain the real-time API content, and then calculate the real-time API content and the real-time total coating weight to obtain the real-time micropellet coating drug application rate.

10. The system for online monitoring of pellet coating rate by near infrared spectroscopy combined with real-time weighing as claimed in claim 9, characterized in that: It includes a preprocessing module, which is configured to: preprocess the real-time near-infrared spectrum obtained during the micropill coating process, and input the preprocessed real-time near-infrared spectrum into the API content model in the output module to obtain the real-time API content; preferably, the preprocessing method performed by the preprocessing module is SG1 and SNV.

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