An analytical control method based on monitoring data of oral ferrous fumarate solution

Abstract

The present application relates to the technical field of monitoring data analysis, and particularly relates to a monitoring data analysis control method based on protein ferric succinate oral solution, which comprises: determining whether the diffusion rate of raw material medicine is qualified according to the turbidity fluctuation amplitude, and adjusting the stirring speed of the stirring paddle in the liquid preparation tank based on the unqualified condition of the diffusion rate of raw material medicine; under the condition that the diffusion rate of raw material medicine is qualified, determining whether the preliminary dissolution process of raw material medicine is qualified according to the gradient deviation of axial concentration distribution; determining the solid residue at the bottom of the liquid preparation tank based on the unqualified condition of the preliminary dissolution process of raw material medicine, so as to determine the optimization of the speed adjustment coefficient or the adjustment of the grinding time length of the colloid mill; and determining whether the uniformity of the solution in the liquid preparation tank is qualified according to the similarity of a plurality of particle size distribution curves of the solution in the liquid preparation tank, so as to optimize the preset proportion. The present application improves the production efficiency of protein ferric succinate oral solution.

Description

Technical Field

[0001] This invention relates to the field of monitoring data analysis technology, and in particular to an analysis and control method based on monitoring data from oral ferric succinate protein solution. Background Technology

[0002] Ferric protein succinate oral solution, a commonly used organic iron supplement in clinical practice, offers advantages such as minimal gastrointestinal irritation and high bioavailability due to the presence of iron ions in the form of protein succinate complexes, making it widely used for the prevention and treatment of iron deficiency anemia. However, the core technical challenge in the production of this formulation lies in the fact that its active pharmaceutical ingredient (ferric protein succinate) is in powder form. Influenced by intermolecular van der Waals forces, electrostatic attraction, and the drying process during production, it is highly susceptible to forming dense aggregates. This aggregation directly triggers a chain reaction of problems in subsequent solution preparation. During the dispensing stage in the preparation tank, the aggregated active pharmaceutical ingredient is difficult to disperse evenly through conventional stirring, easily forming localized concentration accumulation within the tank, resulting in uneven axial and radial diffusion and a concentration gradient that is less concentrated at the top and more concentrated at the bottom. During the dissolution stage, the active pharmaceutical ingredient particles inside the aggregates cannot fully contact the solvent (purified water and co-solvent system). Solvation only acts on the surface of the aggregates, leading to delayed dissolution of internal particles. Even after colloid milling, micron-sized, incompletely dissociated aggregated particles may remain, resulting in incomplete dissolution.

[0003] The aforementioned uneven diffusion and dissolution issues can further lead to turbidity and localized color variations in the intermediate liquid system. Subsequent filtration processes are prone to clogging of the filter membrane due to undissolved particles, reducing production efficiency. After filling, the finished product may have quality defects such as substandard content uniformity (single-dose iron content deviation exceeding the range specified in the Chinese Pharmacopoeia), particle sedimentation and stratification during storage, and a rough taste. In severe cases, undissolved particles may not be effectively absorbed by the human body, resulting in reduced efficacy or excessive release of free iron ions, increasing the risk of gastrointestinal irritation and ultimately causing the finished product to be substandard.

[0004] Currently, the industry relies heavily on manual visual observation and offline sampling and testing to control such problems. This has limitations such as monitoring lag and insufficient data representativeness, making it difficult to capture diffusion and dissolution anomalies caused by agglomerates in real time. There is an urgent need to establish an analysis and control method based on real-time monitoring data to achieve precise control over the entire process of agglomeration, diffusion and dissolution of active pharmaceutical ingredients, and to ensure the stability of finished product quality.

[0005] Chinese Patent Application Publication No. CN117752768A discloses a formulation and preparation method of an oral solution containing ferric protein succinate. The method first reduces the viscosity of the active component, ferric protein succinate, through concentrated preparation and high-pressure homogenization, increasing the filtration speed of the raw materials. Furthermore, by controlling the temperature of the solution, the protein structure of the ferric protein succinate is preserved, while ultrafiltration is used for sterilization. This patent not only controls the microbial level of the formulation from the source but also optimizes the dosage of antibacterial agents in the formulation, ensuring microbial compliance during formulation stability while guaranteeing clinical efficacy—achieving four benefits in one step. In addition, through the optimization and control of solution parameters, the preparation process is greatly simplified while ensuring product quality attributes. The resulting oral solution formulation and preparation method containing ferric protein succinate meet the needs of commercial production.

[0006] The existing technology also has the following problems: the monitoring of the preparation process of ferric protein succinate oral solution is lagging, which means that the uneven diffusion and dissolution of the raw material due to its easy agglomeration cannot be adjusted in time, resulting in low production efficiency of ferric protein succinate oral solution. Summary of the Invention

[0007] Therefore, this invention provides an analysis and control method based on monitoring data of ferric protein succinate oral solution, which overcomes the problem of lagging monitoring of the preparation process of ferric protein succinate oral solution in the prior art, which leads to the inability to adjust the uneven diffusion and dissolution of the raw material during the production process due to its easy agglomeration characteristics, resulting in low production efficiency of ferric protein succinate oral solution.

[0008] To achieve the above objectives, the present invention provides an analytical control method based on monitoring data from an oral solution of ferric protein succinate, comprising:

[0009] The active pharmaceutical ingredient and solvent of the ferric protein succinate oral solution are mixed in a preset ratio and then added to the dispensing tank.

[0010] The turbidity fluctuation range of the solution at the feeding point is obtained, and the diffusion rate of the active pharmaceutical ingredient is determined to be qualified based on the turbidity fluctuation range. Several speed adjustment coefficients are set based on the condition that the diffusion rate of the active pharmaceutical ingredient is unqualified in order to adjust the stirring speed of the stirring paddle in the mixing tank.

[0011] Under the condition that the diffusion rate of the active pharmaceutical ingredient is qualified, the axial concentration distribution of the solution in the mixing tank is obtained, so as to determine whether the initial dissolution process of the active pharmaceutical ingredient is qualified based on the gradient deviation of the axial concentration distribution.

[0012] Based on the unqualified conditions of the initial dissolution process of the active pharmaceutical ingredient, the solid residue at the bottom of the dispensing tank is determined, and the optimization of the speed adjustment coefficient or the adjustment of the grinding time of the colloid mill is determined based on the distribution difference of the solid residue.

[0013] The particle size distribution curves of the solution at several locations in the mixing tank after grinding with a colloid mill are obtained. The homogeneity of the solution in the mixing tank is determined based on the similarity of the particle size distribution curves. The preset ratio is then optimized based on the condition that the homogeneity of the solution in the mixing tank is not qualified.

[0014] Furthermore, the process of determining whether the diffusion rate of the active pharmaceutical ingredient is qualified based on the turbidity fluctuation amplitude includes:

[0015] The turbidity fluctuation amplitude is compared with the preset fluctuation amplitude;

[0016] Based on the comparison results showing that the turbidity fluctuation amplitude is greater than the preset fluctuation amplitude, it is determined that the diffusion rate of the active pharmaceutical ingredient is unqualified.

[0017] The diffusion rate of the active pharmaceutical ingredient is determined to be qualified based on the comparison results of the turbidity fluctuation amplitude being less than or equal to the preset fluctuation amplitude.

[0018] Furthermore, under the condition that the diffusion rate of the active pharmaceutical ingredient is unqualified, the process of adjusting the stirring speed of the impeller in the mixing tank includes:

[0019] The turbidity difference is obtained by subtracting the turbidity fluctuation amplitude from the preset fluctuation amplitude.

[0020] The turbidity difference is compared with a preset turbidity difference;

[0021] Based on the comparison result between the turbidity difference and the preset turbidity difference, several speed adjustment coefficients are set to increase the stirring speed of the stirring paddle.

[0022] Furthermore, assuming the diffusion rate of the active pharmaceutical ingredient is qualified, the process for determining the gradient deviation of the axial concentration distribution includes:

[0023] Obtain the first distribution concentration of the active pharmaceutical ingredient at the top of the mixing tank, the second distribution concentration of the active pharmaceutical ingredient in the tank, and the third distribution concentration of the active pharmaceutical ingredient at the bottom of the tank;

[0024] The first concentration difference is obtained by subtracting the second distribution concentration from the first distribution concentration, and the second concentration difference is obtained by subtracting the third distribution concentration from the second distribution concentration.

[0025] The absolute concentration difference between the first concentration difference and the second concentration difference is defined as the gradient deviation of the axial concentration distribution.

[0026] Furthermore, the process of determining whether the initial dissolution process of the active pharmaceutical ingredient is qualified based on the gradient deviation includes:

[0027] Compare the gradient deviation with the preset deviation;

[0028] Based on the comparison results of the gradient deviation being greater than the preset deviation, it is determined that the initial dissolution process of the active pharmaceutical ingredient is unqualified.

[0029] Furthermore, under the condition that the initial dissolution process of the active pharmaceutical ingredient is unqualified, the process for determining the distribution difference of solid residues at the bottom of the mixing tank includes:

[0030] Using the geometric center of the bottom of the mixing tank as a reference point, the bottom of the mixing tank is divided into several equally spaced rings;

[0031] Determine the solid residue of any of the aforementioned rings, and determine the standard deviation of several of the solid residues as the distributional difference of the solid residues.

[0032] Furthermore, the process of optimizing the velocity adjustment coefficient based on the distribution differences includes:

[0033] Compare the distribution difference with a preset difference;

[0034] The speed adjustment coefficient is optimized based on the comparison result that the distribution difference is greater than the preset difference;

[0035] The first difference between the distribution difference and the preset difference is compared with the preset difference;

[0036] Based on the comparison result between the first difference and the preset difference, several speed optimization coefficients are set to optimize the speed adjustment coefficient.

[0037] Furthermore, the process of adjusting the grinding time of the colloid mill based on the aforementioned distribution differences includes:

[0038] Compare the distribution difference with a preset difference;

[0039] The grinding time of the colloid mill is adjusted based on the comparison result that the distribution difference is less than or equal to the preset difference;

[0040] Compare the second difference between the preset difference and the distribution difference with the preset difference;

[0041] Based on the comparison result between the second difference and the preset difference, several time adjustment coefficients are set to increase the grinding time of the colloid mill.

[0042] Furthermore, the process of determining whether the homogeneity of the solution in the mixing tank is qualified based on the similarity of several particle size distribution curves includes:

[0043] The similarity is compared with a preset similarity.

[0044] Based on the comparison results where the similarity is less than the preset similarity, it is determined that the homogeneity of the solution in the mixing tank is unqualified.

[0045] Furthermore, samples were taken from several locations in the mixing tank, and the area ratio of the characteristic coordination peaks was determined after the samples were allowed to stand.

[0046] Determine the maximum deviation of the area ratio of several of the aforementioned characteristic coordination peaks;

[0047] Based on the determination result of the maximum deviation of the area ratio of the characteristic coordination peak, several proportional optimization coefficients are set to optimize the preset ratio.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention first determines whether the diffusion rate of the active pharmaceutical ingredient (API) is qualified by measuring the turbidity fluctuation at the feeding point. In the preparation of ferric protein succinate oral solution, the feeding point is the core area where the API just enters the solvent system. Its turbidity fluctuation can be directly correlated with and used to determine whether the diffusion rate of the API is qualified. Ferric protein succinate API is prone to agglomeration. After feeding, it needs to diffuse into the surrounding solvent through stirring. Turbidity is essentially the degree of light scattering by suspended particles (including incompletely dispersed API particles and micro-agglomerates) in the solution. The turbidity value at the feeding point directly reflects the concentration of API particles in that area. If the diffusion rate is qualified, the API will be continuously and uniformly carried away from the feeding point. The particles will not accumulate excessively or be lost too quickly in this area. The local particle concentration is maintained in a stable range, and the turbidity fluctuation is small. If the diffusion rate is unqualified, the API particles accumulate at the feeding point, the local particle concentration rises sharply, and the upper limit of turbidity increases significantly. At the same time, due to uneven particle dispersion, there may be temporary sparseness of local particles, which leads to a decrease in the lower limit of turbidity and ultimately results in excessive turbidity fluctuation. Furthermore, the feeding point, as the starting point of diffusion, is more sensitive to turbidity fluctuations than other areas. Areas far from the feeding point have completed diffusion, resulting in gradual turbidity changes that cannot directly reflect the rate of the initial diffusion stage. However, the turbidity fluctuations at the feeding point can capture the dynamic balance between particle generation and diffusion carry-away in real time, thereby accurately determining whether the diffusion rate meets the qualified standard of uniform dispersion of the active pharmaceutical ingredient (API) without local accumulation. This avoids problems such as uneven dissolution and uneven content of the finished product due to unqualified diffusion rates. Under the condition that the diffusion rate of the API is qualified, the axial concentration distribution of the solution in the mixing tank is further used to determine whether the initial dissolution process of the API is qualified. A qualified diffusion rate ensures that the API particles are uniformly dispersed in all axial regions of the mixing tank, that is, after feeding, the particles do not accumulate or become sparse due to insufficient diffusion, and the initial amount of API particles in each axial position is consistent.At this point, the difference in axial concentration distribution is no longer determined by whether the particles disperse, but by whether the particles dissolve. If the initial dissolution process is satisfactory, the active pharmaceutical ingredient particles at each axial position will dissolve synchronously and uniformly under stirring and solvation. The resulting protein ferric succinate complex will further diffuse evenly with convection within the container. The amount of undissolved residual particles is basically consistent at each axial position, resulting in a gentle axial concentration distribution with minimal gradient deviation. The axial concentration gradient deviation in the initial dissolution stage has predictive value for subsequent processes. Without colloid milling, dissolution relies on the natural contact between particles and solvent. If a significant axial concentration difference has already occurred at this stage... A gradient indicates that particles in some areas have accumulated due to dissolution lag caused by impaired dissolution. Even after subsequent grinding with a colloid mill, undissolved particles may remain after grinding due to poor initial dissolution, ultimately leading to problems such as uneven concentration and substandard clarity in the finished product. Conversely, if the axial concentration gradient deviation is small, it indicates that the initial dissolution progress in each area is consistent and the undissolved particles are evenly distributed. Subsequent colloid milling can efficiently handle residual microparticles, ensuring complete final dissolution. Furthermore, preparation parameters can be specifically adjusted for cases of unqualified diffusion rates and unqualified initial dissolution processes to improve the production efficiency of ferric protein succinate oral solution.

[0049] Furthermore, this invention determines the uniformity of the oral solution by comparing the similarity of the particle size distribution curves of the solution at several locations within the dispensing tank after grinding with a colloid mill. The core function of the colloid mill is to break up aggregates of the active pharmaceutical ingredient, ensuring that any remaining incompletely dissolved particles in the system meet the process requirements of fine particle size and uniform distribution. Although the ferric protein succinate active pharmaceutical ingredient has undergone preliminary soft material preparation, diffusion, and initial dissolution, it may still contain dense aggregates that are not completely dissociated. The colloid mill breaks these aggregates into micron- or even nano-sized particles through high-speed shearing and grinding. If the grinding is thorough and the system is uniformly mixed, these broken particles will form a stable dispersion in the solvent, and the particle size distribution in each region should be uniform. Significant differences exist; conversely, if grinding is insufficient or the particles are not evenly dispersed after crushing, some areas will have a high proportion of large particles and some areas will have a predominance of small particles. This is directly reflected in the low similarity of the particle size distribution curve, which will directly affect subsequent processes and the quality of the finished product. The semi-finished product after colloid milling needs to enter the filtration and filling stages. If the uniformity is not up to standard, the concentrated areas of large particles will easily clog the filter membrane during filtration, reducing production efficiency. It may also cause the iron content to be inconsistent or to easily settle and stratify during storage, affecting the product stability and taste. Therefore, in response to the situation of non-uniformity, the preset ratio of solvent is specifically increased to further improve the production efficiency of ferric protein succinate oral solution. Attached Figure Description

[0050] Figure 1 This is a flowchart of the analysis and control method based on monitoring data from an oral ferric protein succinate solution according to an embodiment of the present invention;

[0051] Figure 2 A flowchart for determining whether the diffusion rate of the active pharmaceutical ingredient is qualified in an embodiment of the present invention;

[0052] Figure 3 A flowchart for determining whether the preliminary dissolution process of the active pharmaceutical ingredient is qualified in an embodiment of the present invention;

[0053] Figure 4 This is a flowchart for determining whether the homogeneity of the solution in the mixing tank is qualified according to an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0055] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0056] Please see Figures 1-4 As shown, Figure 1 This is a flowchart of the analysis and control method based on monitoring data from an oral ferric protein succinate solution according to an embodiment of the present invention; Figure 2 A flowchart for determining whether the diffusion rate of the active pharmaceutical ingredient is qualified in an embodiment of the present invention; Figure 3 A flowchart for determining whether the preliminary dissolution process of the active pharmaceutical ingredient is qualified in an embodiment of the present invention; Figure 4 This is a flowchart for determining whether the homogeneity of the solution in the mixing tank is qualified according to an embodiment of the present invention.

[0057] The present invention provides an analysis and control method based on monitoring data from an oral solution of ferric protein succinate, comprising:

[0058] Step S1: Mix the raw material and solvent of the ferric protein succinate oral solution in a preset ratio and then put them into the dispensing tank.

[0059] Step S2: Obtain the turbidity fluctuation range of the solution at the feeding point, so as to determine whether the diffusion rate of the active pharmaceutical ingredient is qualified based on the turbidity fluctuation range, and set several speed adjustment coefficients based on the unqualified diffusion rate of the active pharmaceutical ingredient to adjust the stirring speed of the stirring paddle in the mixing tank.

[0060] Step S3: Under the condition that the diffusion rate of the active pharmaceutical ingredient is qualified, the axial concentration distribution of the solution in the mixing tank is obtained, so as to determine whether the initial dissolution process of the active pharmaceutical ingredient is qualified based on the gradient deviation of the axial concentration distribution.

[0061] Step S4: Based on the unqualified conditions of the initial dissolution process of the active pharmaceutical ingredient, determine the solid residue at the bottom of the dispensing tank, and determine the optimization of the speed adjustment coefficient or the adjustment of the grinding time of the colloid mill based on the distribution difference of the solid residue.

[0062] Step S5: Obtain the particle size distribution curves of the solution at several locations in the mixing tank after grinding with a colloid mill, so as to determine whether the homogeneity of the solution in the mixing tank is qualified based on the similarity of the particle size distribution curves, and optimize the preset ratio based on the condition that the homogeneity of the solution in the mixing tank is not qualified.

[0063] Specifically, the active pharmaceutical ingredient of the ferric protein succinate oral solution is ferric protein succinate powder, and the preparation process of the ferric protein succinate oral solution is as follows: raw material pretreatment, weighing purified water, stirring and dissolving excipients, stirring and dissolving raw materials, grinding and dissolving raw materials in a colloid mill, adjusting pH, making up to a fixed volume, filtering, filling, and light inspection.

[0064] It is understandable that the pretreatment process of raw materials involves mixing the raw drug powder with a solvent, namely pure water, in a preset ratio to obtain wet granules. The purpose is to solve the problem of uneven iron ion concentration distribution caused by the inherent characteristics of raw drugs, such as easy agglomeration and the need for gradual dissociation to dissolve, by pre-wetting and preliminary dispersion. As an organic iron-protein complex, ferric protein succinate is prone to forming dense hard agglomerates due to the intermolecular forces and particle surface tension of its raw drug powder. If the dried and agglomerated active pharmaceutical ingredient (API) is directly added to the subsequent mixing tank, the interior of the agglomerates will be difficult for the solvent to penetrate. Subsequent stirring or grinding will only act on the surface of the agglomerates, failing to effectively break down the internal particles. This results in large particles remaining in the final product, affecting the uniformity of dissolution and the taste. Pre-mixing allows pure water to gradually penetrate the API agglomerates, disrupting the interparticle forces and loosening the agglomerates into smaller secondary clusters or even monodisperse particles. During subsequent colloid milling, it is no longer necessary to overcome the strong cohesive forces of the hard agglomerates; only fine crushing of the loose particles is required. This improves grinding efficiency and ensures the uniformity of the final particle size. The preset ratio is pure water / API powder mass = 8%.

[0065] Specifically, the process of determining whether the diffusion rate of the active pharmaceutical ingredient is qualified based on the turbidity fluctuation amplitude includes:

[0066] The turbidity fluctuation amplitude is compared with the preset fluctuation amplitude;

[0067] Based on the comparison results showing that the turbidity fluctuation amplitude is greater than the preset fluctuation amplitude, it is determined that the diffusion rate of the active pharmaceutical ingredient is unqualified.

[0068] The diffusion rate of the active pharmaceutical ingredient is determined to be qualified based on the comparison results of the turbidity fluctuation amplitude being less than or equal to the preset fluctuation amplitude.

[0069] Specifically, the feeding point location refers to the instant mixing zone extending into the solution inside the tank, centered on the feeding port. The specific range is proportional to the volume of the mixing tank. For example, for a mixing tank with a volume of 1000L, the feeding point location refers to a cylindrical area with a radius of 10-20cm, 5-15cm below the feeding port. The specific location is not limited.

[0070] Specifically, the turbidity fluctuation range is determined based on the monitoring data of the turbidity sensor in the liquid preparation tank. A real-time turbidity curve is established based on the monitoring data of the turbidity sensor. The maximum and minimum turbidity values ​​are determined every 1 minute. The difference between the maximum and minimum turbidity values ​​is determined as the turbidity fluctuation range.

[0071] Specifically, the preset fluctuation range is set to [5 NTU, 15 NTU], and in this embodiment of the invention, 8 NTU is preferred.

[0072] Specifically, when the diffusion rate of the active pharmaceutical ingredient is determined to be substandard, the process of adjusting the stirring speed of the agitator in the mixing tank includes:

[0073] The turbidity difference is obtained by subtracting the turbidity fluctuation amplitude from the preset fluctuation amplitude.

[0074] The turbidity difference is compared with a preset turbidity difference;

[0075] Based on the comparison result between the turbidity difference and the preset turbidity difference, several speed adjustment coefficients are set to increase the stirring speed of the stirring paddle.

[0076] Specifically, based on the comparison result that the turbidity difference is greater than or equal to the preset turbidity difference, the stirring speed is increased by a first speed adjustment coefficient;

[0077] Based on the comparison result that the turbidity difference is less than the preset turbidity difference, the stirring speed is increased by a second speed adjustment coefficient.

[0078] Specifically, the preset turbidity difference is set to a range of [2 NTU, 5 NTU], preferably 3 NTU in this embodiment of the invention; the first speed adjustment coefficient is set to a range of [1.15, 1.3], preferably 1.2 in this embodiment of the invention; and the second speed adjustment coefficient is set to a range of [1.05, 1.14], preferably 1.1 in this embodiment of the invention.

[0079] Understandably, the problem with the diffusion rate of the active pharmaceutical ingredient (API) is that the diffusion rate of the API from the feeding point to other areas is uneven. Increasing the speed of the agitator can enhance the hydrodynamic effect and improve the mass transfer efficiency of the API.

[0080] Specifically, assuming the diffusion rate of the active pharmaceutical ingredient is qualified, the process for determining the gradient deviation of the axial concentration distribution includes:

[0081] Obtain the first distribution concentration of the active pharmaceutical ingredient at the top of the mixing tank, the second distribution concentration of the active pharmaceutical ingredient in the tank, and the third distribution concentration of the active pharmaceutical ingredient at the bottom of the tank;

[0082] The first concentration difference is obtained by subtracting the second distribution concentration from the first distribution concentration, and the second concentration difference is obtained by subtracting the third distribution concentration from the second distribution concentration.

[0083] The absolute concentration difference between the first concentration difference and the second concentration difference is defined as the gradient deviation of the axial concentration distribution.

[0084] Specifically, the first distribution concentration, the second distribution concentration, and the third distribution concentration all refer to the mass concentration of iron ions, which are measured using an online spectrophotometer.

[0085] Specifically, the process of determining whether the initial dissolution process of the active pharmaceutical ingredient is qualified based on the gradient deviation includes:

[0086] Compare the gradient deviation with the preset deviation;

[0087] Based on the comparison results showing that the gradient deviation is greater than the preset deviation, it is determined that the initial dissolution process of the active pharmaceutical ingredient is unqualified.

[0088] The preliminary dissolution process of the active pharmaceutical ingredient is deemed qualified based on the comparison results where the gradient deviation is less than or equal to the preset deviation.

[0089] Understandably, before grinding with a colloid mill, the solution contains easily agglomerated active pharmaceutical ingredient (API) particles, which can cause high-density materials to settle due to gravity. Particles gradually accumulate from the top and middle of the tank towards the bottom, resulting in significant axial concentration stratification. The concentration is highest at the bottom, lowest at the top, and intermediate in the middle. A satisfactory diffusion rate leads to initial particle dispersion. Even with natural settling, the API is initially dispersed by stirring, resulting in a relatively slow settling rate and a slow, uniform change in axial concentration. Settling does not cause sudden increases or decreases in local concentration, and the particles remain in a relatively uniform dispersion state. Subsequent grinding with a colloid mill allows for rapid dissolution, indicating successful initial dissolution. However, if the gradient deviation exceeds the standard, settling causes severe concentration stratification, leading to larger particle sizes, faster settling rates, and drastic, uneven changes in axial concentration. This can form a sediment layer that is difficult to disperse during subsequent grinding. This directly affects the final dissolution efficiency and product concentration uniformity, resulting in unsatisfactory initial dissolution.

[0090] Specifically, the preset deviation range is set to [0.03 g / L, 0.06 g / L], and in this embodiment of the invention, 0.04 g / L is preferred.

[0091] Specifically, when the initial dissolution process of the active pharmaceutical ingredient is determined to be substandard, the process for determining the distribution differences of solid residues at the bottom of the mixing tank includes:

[0092] Using the geometric center of the bottom of the mixing tank as a reference point, the bottom of the mixing tank is divided into several equally spaced rings;

[0093] Determine the solid residue of any of the aforementioned rings, and determine the standard deviation of several of the solid residues as the distributional difference of the solid residues.

[0094] Specifically, the bottom of the mixing tank is divided into several rings at equal intervals. For example, taking a mixing tank with a radius of 60cm as an example, the bottom of the tank can be divided into 6 rings at intervals of 10cm, and the specific division is not limited.

[0095] Specifically, the equally spaced rings at the bottom of the mixing tank are divided into regions radially (from the center to the edge). The amount of solid residue in each ring directly reflects the uniformity of the radial diffusion capability of the stirring paddle. When the stirring paddle rotates, it will transfer the raw material particles in the tank radially (center → edge, edge → center) through shear force and fluid turbulence. This process is called radial diffusion. Ideally, when radial diffusion is uniform, the amount of solid residue in each ring should be similar. However, in reality, the radial diffusion capacity of the impeller is affected by the distance from the impeller blades. The area closer to the impeller blades has strong fluid turbulence, fast radial diffusion, and less solid residue. The area farther from the blades has weak fluid turbulence, slow radial diffusion, and more solid residue. This ultimately leads to differences in the amount of residue in each ring. If the standard deviation is large, it indicates that the amount of residue in different rings is large (e.g., very little residue in the central ring and a lot in the edge rings). This directly reflects that the radial diffusion capacity of the impeller is seriously uneven, and solid particles cannot be effectively transferred radially, making it impossible for solid particles to be evenly distributed radially at the bottom of the tank. Therefore, the speed adjustment coefficient should be optimized to further enhance the radial fluid turbulence intensity of the impeller. A faster stirring speed will cause the blades to generate stronger shear force, breaking the weak turbulence zone in the edge area and pushing the residual particles in the edge rings to diffuse towards the center, reducing the difference in the amount of residue.

[0096] Specifically, the process of optimizing the velocity adjustment coefficient based on the distribution differences includes:

[0097] Compare the distribution difference with a preset difference;

[0098] The speed adjustment coefficient is optimized based on the comparison result that the distribution difference is greater than the preset difference;

[0099] The first difference between the distribution difference and the preset difference is compared with the preset difference;

[0100] Based on the comparison result between the first difference and the preset difference, several speed optimization coefficients are set to optimize the speed adjustment coefficient.

[0101] Specifically, based on the comparison result that the first difference is greater than the preset difference, the speed adjustment coefficient is increased by the first speed optimization coefficient.

[0102] Based on the comparison result that the first difference is less than or equal to the preset difference, the speed adjustment coefficient is increased by the second speed optimization coefficient.

[0103] Specifically, the detection of solid residue can be achieved by installing a laser emitter and receiver in the target area at the bottom of the mixing tank. When the laser passes through the bottom area of ​​the tank, if there is solid residue, the laser will be reflected / scattered, and the laser intensity detected by the receiver will decrease. The amount of solid residue can then be determined based on the magnitude of the decrease in laser intensity, without any specific limitation.

[0104] Specifically, the preset difference is set to a range of [0.2mg, 0.7mg], preferably 0.4mg in this embodiment of the invention; the first speed optimization coefficient is set to a range of [1.08, 1.14], preferably 1.12 in this embodiment of the invention; and the second speed optimization coefficient is set to a range of [1.03, 1.07], preferably 1.06 in this embodiment of the invention.

[0105] Specifically, the process of adjusting the grinding time of the colloid mill based on the distribution differences includes:

[0106] Compare the distribution difference with a preset difference;

[0107] The grinding time of the colloid mill is adjusted based on the comparison result that the distribution difference is less than or equal to the preset difference;

[0108] Compare the second difference between the preset difference and the distribution difference with the preset difference;

[0109] Based on the comparison result between the second difference and the preset difference, several time adjustment coefficients are set to increase the grinding time of the colloid mill.

[0110] Specifically, based on the comparison result that the second difference is greater than the preset difference, the grinding time is increased by a first time adjustment coefficient.

[0111] Based on the comparison result that the second difference is less than or equal to the preset difference, the grinding time is increased by the second time adjustment coefficient.

[0112] Specifically, the first duration adjustment coefficient is set to a value range of [1.3, 1.6], preferably 1.4 in this embodiment of the invention, and the second duration adjustment coefficient is set to a value range of [1.2, 1.29], preferably 1.25 in this embodiment of the invention.

[0113] It is understandable that the solid residue at the bottom of the mixing tank is caused not only by uneven distribution leading to localized residue, but also by undissolved particles resulting in overall residue. When the distribution of solid residue varies greatly, it means that the amount of residue in different areas at the bottom of the mixing tank differs significantly. The root cause of this difference is insufficient radial diffusion capability of the agitator, preventing the raw material solid particles from being uniformly dispersed within the tank. When the distribution difference is small or equal to the preset difference, it indicates that the solid particles have been uniformly distributed at the bottom of the mixing tank, but solid residue still exists. At this point, the core issue is no longer uneven distribution, but rather that the raw material particles are too large and have insufficient specific surface area, resulting in a slow dissolution rate or incomplete dissolution. In this case, increasing the grinding time of the colloid mill can increase the specific surface area of ​​the particles. The larger the specific surface area of ​​the particles, the larger the contact area with the solvent, and the faster the dissolution rate.

[0114] Specifically, the process of determining whether the homogeneity of the solution in the mixing tank is qualified based on the similarity of several particle size distribution curves includes:

[0115] The similarity is compared with a preset similarity.

[0116] Based on the comparison results where the similarity is less than the preset similarity, it is determined that the homogeneity of the solution in the mixing tank is unqualified.

[0117] The homogeneity of the solution in the mixing tank is determined to be qualified based on the comparison result where the similarity is greater than or equal to the preset similarity.

[0118] Specifically, the process for determining the similarity is as follows:

[0119] All particle size distribution curves are aligned with the origin of the coordinate system.

[0120] The similarity is determined by the ratio of the overlapping area to the area enclosed by the standard particle size distribution curve and the coordinate axis.

[0121] Specifically, the particle size distribution curve is measured using a laser particle size analyzer, but the specific method is not limited.

[0122] Specifically, the preset similarity value range is set to [0.6, 0.8], and 0.7 is preferred in this embodiment of the invention.

[0123] Specifically, the process of optimizing the preset ratio when the homogeneity of the solution in the mixing tank is determined to be unsatisfactory includes:

[0124] Samples were taken from several locations in the mixing tank, and the area ratio of the characteristic coordination peaks was determined after the samples were allowed to stand.

[0125] The difference between the maximum and minimum values ​​of the area ratios of the several characteristic coordination peaks is determined as the maximum deviation of the area ratios of the several characteristic coordination peaks.

[0126] Based on the determination result of the maximum deviation, several proportional optimization coefficients are set to optimize the preset ratio.

[0127] Specifically, the sampling location is determined randomly, without any specific restrictions.

[0128] Specifically, the maximum deviation is compared with a preset area ratio;

[0129] Based on the comparison result that the maximum deviation is greater than the preset area ratio, it is determined to increase the preset ratio by a first ratio optimization coefficient;

[0130] Based on the comparison result that the maximum deviation is less than or equal to the preset area ratio, the preset ratio is increased by a second ratio optimization coefficient.

[0131] Specifically, the characteristic coordination peak area ratio refers to the ratio of the area of ​​the characteristic peak of the target coordination structure to the area of ​​the reference peak in the dissolved target active ingredient (ferric protein succinate) in the oral solution, obtained through a specific detection technique. The characteristic coordination peak refers to the iron ion (Fe) in the ferric protein succinate molecule. 2+ / Fe 3+ The specific signal peak generated by the coordination bond (such as Fe-O bond, Fe-N bond, depending on the coordination mode) between the active pharmaceutical ingredient and protein succinic acid under specific detection conditions. Undissolved active pharmaceutical ingredient particles will not produce this peak. Therefore, this peak only reflects the effective dissolved concentration of the target active ingredient. It can be determined by Fourier transform infrared spectroscopy (FTIR) or ultraviolet-visible spectrophotometry (UV-Vis). This is existing technology and will not be elaborated further.

[0132] Specifically, the preset area ratio is set to a range of [0.2, 0.4], preferably 0.3 in this embodiment of the invention; the first ratio optimization coefficient is set to a range of [1.4, 1.6], preferably 1.5 in this embodiment of the invention; and the second ratio optimization coefficient is set to a range of [1.1, 1.3], preferably 1.2 in this embodiment of the invention.

[0133] It is understandable that the homogeneity of the solution in the mixing tank refers to the uniformity of the distribution of undissolved particles of the active pharmaceutical ingredient in the solvent. If the homogeneity is unqualified, it indicates that there are significant differences in the distribution of undissolved particles at different locations in the solution. If the homogeneity is qualified, it indicates that there are no differences in the distribution of undissolved particles at different locations in the solution. The essence of the dissolution process is the diffusion of solute molecules from the surface of solid particles into the solution. Therefore, the spatial distribution of particles directly determines the density of dissolution sites. If the particle distribution is uniform, the dissolution sites are evenly distributed in the solution, and the solute diffusion areas around each particle are less likely to overlap. Solute molecules can diffuse into the solution more evenly, and the effective dissolution concentration distribution is more likely to be uniform. If the particle distribution is uneven, the dissolution sites in dense areas overlap highly, and the diffusion boundary layers of multiple particles interfere with each other. The solute concentration in this area will rise rapidly. If the rate of diffusion of solute molecules into sparse areas cannot keep up with the local dissolution rate, a concentration gradient difference will be formed, resulting in an uneven distribution of effective dissolution concentration. Therefore, the distribution of the effective dissolution concentration of the solution can be characterized by the uniformity of the distribution of undissolved particles in the mixing tank. In some areas, the active pharmaceutical ingredient (API) is fully dissolved and at a high concentration, while in other areas it is not fully dissolved and at a low concentration. The effective dissolved concentration of the API is positively correlated with the area ratio of the characteristic coordination peak. Therefore, the degree of non-uniformity of the solution in the mixing tank can be determined based on the deviation of the area ratio of the characteristic coordination peak. In this way, the preset ratio can be increased to improve the dissolution kinetic efficiency and thus increase the degree of dissolution of the API.

[0134] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. An analytical control method based on monitoring data from an oral solution of ferric protein succinate, characterized in that, include: The active pharmaceutical ingredient and solvent of the ferric protein succinate oral solution are mixed in a preset ratio and then added to the dispensing tank. The turbidity fluctuation range of the solution at the feeding point is obtained, and the diffusion rate of the active pharmaceutical ingredient is determined to be qualified based on the turbidity fluctuation range. Several speed adjustment coefficients are set based on the condition that the diffusion rate of the active pharmaceutical ingredient is unqualified in order to adjust the stirring speed of the stirring paddle in the mixing tank. Under the condition that the diffusion rate of the active pharmaceutical ingredient is qualified, the axial concentration distribution of the solution in the mixing tank is obtained, so as to determine whether the initial dissolution process of the active pharmaceutical ingredient is qualified based on the gradient deviation of the axial concentration distribution. Based on the unqualified conditions of the initial dissolution process of the active pharmaceutical ingredient, the solid residue at the bottom of the dispensing tank is determined, and the optimization of the speed adjustment coefficient or the adjustment of the grinding time of the colloid mill is determined based on the distribution difference of the solid residue. The particle size distribution curves of the solution at several locations in the mixing tank after grinding with a colloid mill are obtained. The homogeneity of the solution in the mixing tank is determined based on the similarity of the particle size distribution curves. The preset ratio is optimized based on the condition that the homogeneity of the solution in the mixing tank is not qualified. Among them, the process of determining the distribution difference of solid residues at the bottom of the dissolution tank when it is determined that the initial dissolution process of the active pharmaceutical ingredient is unqualified includes: Using the geometric center of the bottom of the mixing tank as a reference point, the bottom of the mixing tank is divided into several equally spaced rings; Determine the solid residue of any of the aforementioned rings, and determine the standard deviation of several of the solid residues as the distributional difference of the solid residues.

2. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 1, characterized in that, The process of determining whether the diffusion rate of the active pharmaceutical ingredient is qualified based on the turbidity fluctuation amplitude includes: The turbidity fluctuation amplitude is compared with the preset fluctuation amplitude; Based on the comparison results showing that the turbidity fluctuation amplitude is greater than the preset fluctuation amplitude, it is determined that the diffusion rate of the active pharmaceutical ingredient is unqualified. The diffusion rate of the active pharmaceutical ingredient is determined to be qualified based on the comparison results of the turbidity fluctuation amplitude being less than or equal to the preset fluctuation amplitude.

3. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 2, characterized in that, When the diffusion rate of the active pharmaceutical ingredient is determined to be substandard, the process of adjusting the stirring speed of the impeller in the mixing tank includes: The turbidity difference is obtained by subtracting the turbidity fluctuation amplitude from the preset fluctuation amplitude. The turbidity difference is compared with a preset turbidity difference; Based on the comparison result between the turbidity difference and the preset turbidity difference, several speed adjustment coefficients are set to increase the stirring speed of the stirring paddle.

4. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 3, characterized in that, Under the condition that the diffusion rate of the active pharmaceutical ingredient is qualified, the process of determining the gradient deviation of the axial concentration distribution includes: Obtain the first distribution concentration of the active pharmaceutical ingredient at the top of the mixing tank, the second distribution concentration of the active pharmaceutical ingredient in the tank, and the third distribution concentration of the active pharmaceutical ingredient at the bottom of the tank; The first concentration difference is obtained by subtracting the second distribution concentration from the first distribution concentration, and the second concentration difference is obtained by subtracting the third distribution concentration from the second distribution concentration. The absolute concentration difference between the first concentration difference and the second concentration difference is defined as the gradient deviation of the axial concentration distribution.

5. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 4, characterized in that, The process of determining whether the initial dissolution process of the active pharmaceutical ingredient is qualified based on the gradient deviation includes: Compare the gradient deviation with the preset deviation; Based on the comparison results of the gradient deviation being greater than the preset deviation, it is determined that the initial dissolution process of the active pharmaceutical ingredient is unqualified.

6. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 5, characterized in that, The process of optimizing the velocity adjustment coefficient based on the distribution differences includes: Compare the distribution difference with a preset difference; The speed adjustment coefficient is optimized based on the comparison result that the distribution difference is greater than the preset difference; The first difference between the distribution difference and the preset difference is compared with the preset difference; Based on the comparison result between the first difference and the preset difference, several speed optimization coefficients are set to optimize the speed adjustment coefficient.

7. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 6, characterized in that, The process of adjusting the grinding time of the colloid mill based on the aforementioned distribution differences includes: Compare the distribution difference with a preset difference; The grinding time of the colloid mill is adjusted based on the comparison result that the distribution difference is less than or equal to the preset difference; Compare the second difference between the preset difference and the distribution difference with the preset difference; Based on the comparison result between the second difference and the preset difference, several time adjustment coefficients are set to increase the grinding time of the colloid mill.

8. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 7, characterized in that, The process of determining whether the homogeneity of the solution in the mixing tank is qualified based on the similarity of several particle size distribution curves includes: The similarity is compared with a preset similarity. Based on the comparison results where the similarity is less than the preset similarity, it is determined that the homogeneity of the solution in the mixing tank is unqualified.

9. The analysis and control method based on monitoring data of ferric protein succinate oral solution according to claim 8, characterized in that, The process of optimizing the preset ratio when the homogeneity of the solution in the mixing tank is determined to be unsatisfactory includes: Samples were taken from several locations in the mixing tank, and the area ratio of the characteristic coordination peaks was determined after the samples were allowed to stand. Determine the maximum deviation of the area ratio of several of the aforementioned characteristic coordination peaks; Based on the determination result of the maximum deviation of the area ratio of the characteristic coordination peak, several proportional optimization coefficients are set to optimize the preset ratio.

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