Dissolution medium pH value dynamic regulation and control method and system based on dissolution instrument

Abstract

The invention provides a dissolution medium pH value dynamic regulation and control method and system based on a dissolution instrument. According to the method, the real-time pH value and the dynamic change trend of the release rate of the active component are obtained, then the pH dynamic compensation instruction is generated according to the offset between the dynamic change trend of the release rate of the active component and the preset stage release target curve, and then the release rate of the active component is calculated based on the pH dynamic compensation instruction and the real-time pH value. The injection parameter combination of the buffer solution is calculated, and then the buffer solution corresponding to the concentration of the buffer solution is injected into the corresponding dissolution cup according to the accurate injection amount in the dynamic time window through a multi-channel accurate fluid controller, so that the pH value of the liquid environment is dynamically matched with the transfer stage of the medicine in the gastrointestinal tract of the human body; according to the technical scheme provided by the invention, the problem of measurement drift caused by the fact that a sensor is easily interfered by drug residues or organic solvents in the prior art is effectively solved, and electrolysis errors of a single electrode in a complex medium are also avoided.

Description

Technical Field

[0001] This application relates to the field of intelligent pharmaceutical equipment technology, and in particular to a method and system for dynamic control of the pH value of the dissolution medium based on a dissolution apparatus. Background Technology

[0002] In the field of drug development and quality control, dissolution testing is a key step in evaluating the release behavior of drug formulations in specific media. Its main applications include dissolution experiments that simulate the pH environment of the human gastrointestinal tract (such as gastric juice pH of about 1.5-2.0 and small intestine pH of about 6.8) to predict the release kinetics of drugs in vivo.

[0003] To address the aforementioned technical requirements, a widely adopted solution is the closed-loop electrochemical feedback control system. This system integrates a highly sensitive pH sensor (such as a glass electrode) and a microprocessor controller to monitor real-time pH changes in the dissolution medium. When a pH deviation from the set value is detected, the microprocessor calculates the dosage requirement based on a pre-programmed sequence and drives a peristaltic pump to precisely add a small amount of acidic or alkaline titrant (such as HCl or NaOH solution), achieving automatic pH correction. This solution features automated and continuous operation, seamlessly integrates with standard dissolution testing platforms, and significantly improves testing accuracy and operational efficiency.

[0004] Although this closed-loop electrochemical control system represents a significant improvement over manual methods, it suffers from several drawbacks: First, the sensor is susceptible to interference from drug residues or dissolved particles in the medium (such as protein precipitates adsorbing onto the electrode surface), leading to response drift and requiring frequent calibration (at least once a day), affecting long-term stability. Second, the response delay is significant, especially under low flow rate regulation, where the time for the pH value to recover to the target value often exceeds 2 minutes, making it difficult to meet the needs of rapid pH switching scenarios. Finally, the system integration cost is high (pH sensors and associated pump consumables are expensive), and electrolytic errors may occur in complex media (such as those containing organic solvents) (pH reading deviations can be as high as 0.3 units), limiting its widespread applicability in multi-component testing. Summary of the Invention

[0005] This application provides a method and system for dynamic control of pH value of dissolution medium based on a dissolution apparatus, which solves the problems in the prior art such as sensor drift caused by medium interference, response delay that is difficult to meet the requirements of rapid switching, insufficient control accuracy in complex media, and high system integration cost.

[0006] In a first aspect, this application provides a method for dynamically controlling the pH value of the dissolution medium based on a dissolution apparatus, including: The real-time pH value of the liquid environment inside the dissolution vessel and the dynamic trend of the release rate of active ingredients are monitored simultaneously using an acid-resistant sensor. Based on the offset between the dynamic trend of the release rate of the active ingredient and the preset phased release target curve, a dynamic pH compensation command is generated. Based on the pH dynamic compensation command and the real-time pH value, the injection parameter combination of the buffer solution is calculated, wherein the injection parameter combination includes a buffer solution concentration matching the current drug release phase, a precise injection volume based on the slope of the release rate change, and a dynamic time window to maintain the target pH stability. By using a multi-channel precision fluid controller, the buffer solution corresponding to the concentration of the buffer solution is injected into the corresponding dissolution vessel at the precise injection volume within the dynamic time window, so that the pH value of the liquid environment is dynamically matched to the drug transport stage in the human gastrointestinal tract.

[0007] Optionally, the real-time pH value of the liquid environment inside the dissolution vessel and the dynamic trend of the release rate of the active ingredient are simultaneously monitored using an acid-resistant sensor, including: Multiple measurement units are arranged in a ring along the depth direction on the side wall of the dissolution vessel, wherein each measurement unit includes a hydrogen ion sensing part and a light signal capturing part; At each predetermined acquisition time point, all measurement units are activated simultaneously by a synchronous trigger signal, causing the hydrogen ion sensing part of the measurement unit to generate an electrical signal, and at the same time, the optical signal capture part of the measurement unit to generate an optical signal. The electrical signal is converted into a real-time pH value, and the optical signal is converted into a concentration value of the active ingredient. By connecting the active ingredient concentration data points from consecutive time points in chronological order, a curve of active ingredient concentration variation is generated. Calculate the difference between the concentration values ​​of two adjacent collection time points on the active ingredient concentration change curve, and divide the difference by the time length between adjacent collection time points to obtain the active ingredient release rate value at each collection time point; The release rate values ​​of the active ingredients are arranged in chronological order of the collection time points to generate an active ingredient release rate sequence. Identify the consistency of the increasing or decreasing direction of multiple consecutive release rate values ​​in the release rate sequence of the active ingredient, so as to extract the continuous change characteristics of the release rate sequence of the active ingredient as a dynamic change trend.

[0008] Optionally, based on the offset between the dynamic trend of the release rate of the active ingredient and the preset staged release target curve, a pH dynamic compensation command is generated, including: Based on the dynamic trend of the release rate of the active ingredient, the time boundary of the current drug release stage is defined. Obtain the reference change profile of the preset phased release target curve within the time boundary; By comparing the actual change profile of the release rate of the active ingredient with the reference change profile, the difference results are obtained. Analyze the persistent offset component and sudden fluctuation component in the difference results; The compensation benchmark value is determined based on the continuous offset component, and the compensation adjustment factor is adjusted based on the sudden fluctuation component. The aforementioned compensation benchmark value and the adjusted compensation regulation factor are combined to form a dynamic pH compensation command that includes the direction and intensity of action.

[0009] Optionally, determining a compensation benchmark value based on the persistent offset component and adjusting the compensation adjustment factor based on the sudden fluctuation component includes: Calculate the linear cumulative amount of the continuous offset component as a function of time, and input the linear cumulative amount into a predefined relational table to output the compensation reference value; Extract the peak intensity and duration of the sudden fluctuation component, and multiply the peak intensity by the duration to obtain the fluctuation energy value; Based on the weight coefficients matched with the fluctuation energy values ​​in the pre-stored mapping set, the weight coefficients are multiplied by the initial value of the compensation adjustment factor to obtain the adjusted compensation adjustment factor.

[0010] Optionally, based on the pH dynamic compensation command and the real-time pH value, a combination of injection parameters for the buffer solution is calculated, wherein the combination of injection parameters includes a buffer solution concentration matching the current drug release phase, a precise injection volume based on the slope of the release rate change, and a dynamic time window for maintaining target pH stability, including: Based on the dynamic trend of the release rate of the active ingredient, the slope of the release rate change is calculated; Extract the direction identifier and force value from the pH dynamic compensation command; Based on the action direction identifier and the target human gastrointestinal segment corresponding to the current drug release stage, select the buffer solution concentration value from the preset concentration mapping table; Convert the sign and absolute value of the slope of the release rate change to the baseline injection volume. Based on the product relationship between the applied force value and the baseline injection volume, a precise injection volume is generated; Based on the deviation and trend of the real-time pH value from the target pH range, a dynamic time window for maintaining the stability of the target pH is generated. The selected buffer solution concentration value, the generated precise injection volume, and the dynamic time window are combined into an injection parameter set.

[0011] Optionally, based on the action direction identifier and the target human gastrointestinal segment corresponding to the current drug release stage, a buffer solution concentration value is selected from a preset concentration mapping table, including: Obtain the target human gastrointestinal segment identifier corresponding to the current drug release stage, wherein the target human gastrointestinal segment identifier includes a stomach segment identifier, a small intestine segment identifier, or a large intestine segment identifier. Based on the target human gastrointestinal tract segment identifier, the type of the action direction identifier is identified. If the action direction identifier is a first type of instruction, the acid concentration selection process is initiated; if the action direction identifier is a second type of instruction, the alkali concentration selection process is initiated. When executing the acid concentration selection process, the corresponding acid buffer solution concentration range is extracted from the preset concentration mapping table based on the target human gastrointestinal tract segment identifier. The specific concentration value is calculated within the range of the acidic buffer solution concentration based on the proportion of the duration of the current drug release phase to the total duration of the target human gastrointestinal tract. When executing the alkaline concentration selection process, the corresponding alkaline buffer solution concentration range is extracted from the preset concentration mapping table based on the target human gastrointestinal tract segment identifier. Based on the proportion of the cumulative release of the active ingredient at the current drug release stage to the target release amount in the target human gastrointestinal tract segment, the specific concentration value is calculated within the concentration range of the alkaline buffer solution. The calculated specific concentration value will be output as the buffer solution concentration value.

[0012] Optionally, the sign and absolute value of the slope of the release rate change are converted to a baseline injection volume, including: The sign attribute of the release rate change slope is determined. When the release rate change slope is greater than a preset zero mark, it is a positive sign; when the release rate change slope is less than the preset zero mark, it is a negative sign. Calculate the absolute value of the slope of the change in the release rate; The absolute value is matched with multiple preset consecutive value intervals, and the basic quantity adjustment coefficient is obtained based on the matching results, wherein each value interval corresponds to a basic quantity adjustment coefficient. When the symbol attribute is a positive symbol, the basic quantity adjustment coefficient is multiplied by the preset positive reference unit quantity to obtain the basic injection quantity reference value; When the symbol attribute is negative, the basic quantity adjustment coefficient is multiplied by the preset negative benchmark unit quantity to obtain the basic injection quantity benchmark value.

[0013] Secondly, this application provides a dynamic pH control system for the dissolution medium based on a dissolution apparatus, comprising: The monitoring module is used to simultaneously monitor the real-time pH value of the liquid environment inside the dissolution cup and the dynamic trend of the release rate of active ingredients through an acid-resistant sensor. The generation module is used to generate a dynamic pH compensation command based on the offset between the dynamic trend of the release rate of the active ingredient and the preset phased release target curve. The calculation module is used to calculate the injection parameter combination of the buffer solution based on the pH dynamic compensation command and the real-time pH value, wherein the injection parameter combination includes a buffer solution concentration matching the current drug release stage, a precise injection volume based on the slope of the release rate change, and a dynamic time window to maintain the target pH stability. The execution module is used to inject the buffer solution corresponding to the concentration of the buffer solution into the corresponding dissolution vessel at the precise injection volume within the dynamic time window through a multi-channel precision fluid controller, so that the pH value of the liquid environment is dynamically matched to the drug transport stage in the human gastrointestinal tract.

[0014] Thirdly, embodiments of this application provide a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are to be invoked and executed by the processing component to realize a method for dynamic control of the pH value of a dissolution medium based on a dissolution apparatus as described in the first aspect above.

[0015] Fourthly, embodiments of this application provide a computer storage medium storing a computer program, which, when executed by a computer, implements a method for dynamic pH control of a dissolution medium based on a dissolution apparatus as described in the first aspect.

[0016] This application embodiment utilizes an acid-resistant sensor to simultaneously monitor the real-time pH value of the dissolution medium and the dynamic trend of the release rate of the active ingredient. Combined with a dynamic selection mechanism of buffer concentration based on the slope of the release rate change and matching the human gastrointestinal tract segment, it effectively overcomes the measurement drift problem caused by drug residues or organic solvent interference in existing technologies. Specifically, the application of acid-resistant materials resists the corrosion and loss of strong acid media, while the decoupled acquisition of synchronous optical and electrochemical signals (such as calculating concentration through spectral absorption peaks) avoids electrolytic errors of a single electrode in complex media. At the same time, the buffer concentration is dynamically mapped according to the proportion of drug release time in the target gastrointestinal segment (such as the small intestine), achieving adaptive compensation of the ionic strength of the medium, enabling the system to maintain high accuracy and stability even in dissolution solutions containing organic solvents or high protein components.

[0017] Furthermore, by using the dynamic trend of the active ingredient release rate as a feedforward factor to generate pH compensation instructions, and based on a sign-based grading algorithm of the release rate change slope and dynamic time window constraints, the shortcomings of existing schemes in terms of lag response and accuracy control are completely solved. The positive or negative sign of the release rate change slope drives the direction prediction of the basic injection volume (e.g., injecting alkaline buffer in advance when the slope increases positively), while the product of the effect strength and the slope generates a precise injection volume at the nanoliter level. Combined with the synchronous control of the buffer injection rhythm by the dynamic time window (e.g., three pulse injections within 1.5 seconds), the pH adjustment response speed is shortened to less than 10 seconds, and the fluctuation amplitude is stably controlled within the range required by the target human gastrointestinal tract segment (e.g., stomach pH 1.8±0.03, small intestine pH 6.8±0.02), providing a high-fidelity human simulation environment for drug release behavior in vivo.

[0018] These or other aspects of this application will become more apparent from the description of the following embodiments. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart of a method for dynamically controlling the pH value of the dissolution medium based on a dissolution apparatus, provided in this application, is shown. Figure 2 This invention provides a schematic diagram of a dynamic pH control system for dissolution media based on a dissolution apparatus. Figure 3 A schematic diagram of the structure of a computing device provided in this application is shown. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0022] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] Figure 1 This application provides a flowchart of a method for dynamically controlling the pH value of the dissolution medium based on a dissolution apparatus, as shown in the embodiments of this application. Figure 1 As shown, the method includes: Step 101: Simultaneously monitor the real-time pH value of the liquid environment inside the dissolution cup and the dynamic trend of the release rate of active ingredients using an acid-resistant sensor.

[0025] In this step, the acid-resistant sensor is a detection device with an acid-resistant material coating (such as a ceramic matrix composite) that can stably measure liquid data in a strong acid environment; the real-time pH value refers to the acidity or alkalinity value output by the sensor electrode in real time, which directly reflects the acidity or alkalinity of the current liquid environment; the active ingredient release rate is the amount of mass change of the drug's active ingredient dissolved into the liquid per minute, used to quantify the speed of drug release; the dynamic change trend is identified by analyzing the release rate data at continuous time points to determine the regular pattern of the release rate change over time (such as continuous acceleration, gradual slowdown, or remaining stable).

[0026] In this embodiment, firstly, a ring-shaped array of sensor units (each unit containing an acid-base electrode and an optical detector) is fixed to the inner wall of the dissolution vessel. When the system triggers a synchronous acquisition command: all acid-base electrodes simultaneously contact the liquid, generating an electrical signal reflecting the hydrogen ion concentration, which is converted by the circuit to output a pH value; all optical detectors simultaneously emit light beams and measure the light transmittance of the liquid, which is converted into a drug concentration value through a preset concentration mapping table. Subsequently, the system captures the concentration values ​​at two adjacent time points and calculates the concentration increment per unit time as the release rate value. Finally, multiple release rate values ​​from the continuously acquired time period are arranged sequentially, and the overall trend is determined by a change direction analysis algorithm (such as continuously comparing the difference between adjacent rates). If the rate value sequence continues to increase, it is determined to be an accelerated release trend.

[0027] For example, in a test simulating the human stomach environment, experimenter Xiao Zhang injected artificial gastric acid (initial acidity 1.5) into a dissolution vessel and placed a sustained-release capsule inside. After monitoring was initiated, the ring sensor collected data every half minute. The initial acidity was 1.52 and the drug concentration was 15 mg / mL. After 30 seconds, the acidity changed to 1.55 and the concentration rose to 25 mg / mL. The system calculated the release rate at this stage to be (25-15)÷0.5=20 mg / min. At 60 seconds, the concentration reached 38 mg / mL, and the release rate increased to (38-25)÷0.5=26 mg / min. The rate values ​​(20, 26, 33) all showed an upward trend, indicating that the drug release was in a stable and accelerating trend. This conclusion provides a core basis for the next step of intelligent acid-base regulation.

[0028] Step 102: Generate a pH dynamic compensation command based on the offset between the dynamic trend of the release rate of the active ingredient and the preset phased release target curve.

[0029] In this step, the preset phased release target curve refers to the ideal release rate change trajectory model set according to the different transport stages of the drug in the human gastrointestinal tract (such as slow and uniform release in the stomach for 0-2 hours and stepped accelerated release in the intestine for 2-6 hours); the offset refers to the numerical deviation (including continuous deviation from the baseline value and sudden instantaneous fluctuation value) calculated by comparing the dynamic change trend data with the target curve in real time; the generated pH dynamic compensation instruction is a computer-executable instruction code that includes acid-base adjustment direction indicators (such as increasing acidity or decreasing alkalinity) and intensity levels (such as intensity levels 1-5) to guide the precise control of subsequent buffer solutions.

[0030] In this embodiment, the system first divides the time boundary of the current drug release stage based on the dynamic trend of the release rate of the active ingredient (such as the continuous acceleration curve output in step 101). For example, 0-90 seconds is identified as the stomach simulation stage. Then, it retrieves the preset target curve corresponding to this time period (such as the ideal uniform release model in the stomach stage). By comparing the difference between the actual rate value and the target value at each time point, it separates two types of offset components: sudden instantaneous fluctuation components caused by equipment errors (such as abnormal values ​​in a certain concentration collection) and continuous trend offset components caused by drug characteristics (such as the release rate being higher than the target value throughout the process). Finally, it assigns a basic compensation value to the continuous offset component (such as the need to enhance the acidic environment for continuous excessively rapid release) and adds a dynamic correction factor to the sudden component (such as the need to weaken the adjustment amplitude for instantaneous fluctuations). After merging, it generates a compensation instruction containing a direction identifier and an intensity level (such as "Direction: Enhance acidity, Intensity level: 3").

[0031] For example, following the test results of the sustained-release capsules in step 101: the system detected that during the gastric simulation phase (0-3 minutes), the actual release rate continuously increased from 20 mg / min to 33 mg / min, while the preset target curve required a constant rate of 22 mg / min during this phase. The actual curve was higher than the target value throughout (maximum deviation of 50%), and a brief surge occurred at 1.5 minutes (instantaneous rate reaching 29 mg / min). The system determined that the continuous deviation accounted for 80% and the sudden fluctuation accounted for 20%, and accordingly generated a compensation instruction (enhanced acidity, intensity level 3); this instruction indicated that an appropriate amount of acidic buffer solution needed to be injected to prolong the drug's residence time in the gastric environment and correct the deviation of excessively rapid release.

[0032] Step 103: Based on the pH dynamic compensation command and the real-time pH value, calculate the injection parameter combination of the buffer solution, wherein the injection parameter combination includes a buffer solution concentration matching the current drug release phase, a precise injection volume based on the slope of the release rate change, and a dynamic time window to maintain target pH stability.

[0033] In this step, the combination of buffer solution injection parameters includes three core elements: buffer solution concentration refers to the acid-base ratio strength required to match the human physiological environment according to the current drug release stage (e.g., stomach / intestine) (e.g., a strong acid solution is required for the stomach environment), and its concentration range is determined by a preset physiological mapping model; precise injection volume refers to the buffer solution volume dynamically calculated based on the slope of the release rate of the active ingredient (i.e., the instantaneous rate of change of the release rate, which is faster or slower), and the adjustment direction is predicted by the positive or negative sign of the slope (e.g., a positive slope requires increased acidity), and the basic dosage is calculated by converting the absolute value; dynamic time window refers to the buffer solution action period set to maintain the stability of the target pH (e.g., three pulse injections within 5 seconds), and its duration is determined by the deviation and rate of change between the real-time pH value and the target value.

[0034] In this embodiment, the system first parses the pH dynamic compensation command (such as "Enhanced Acidity, Intensity Level 3" output in step 102), extracts the action direction identifier (such as "Enhanced Acidity") and the action intensity value ("Level 3"). Simultaneously, it reads the dynamic trend of the active ingredient release rate and calculates the slope of the release rate change in the latest time period (such as obtaining the curvature using a three-point difference algorithm). Next, based on the action direction identifier and the current drug release stage identifier (such as "gastric segment"), it locks the buffer solution concentration range from a preset mapping table (such as 0.05-0.1M hydrochloric acid solution corresponding to the stomach). Then, combining the sign attribute (positive / negative) and absolute value of the release rate change slope, it matches a preset coefficient table to calculate the baseline injection volume (if the slope is large, the baseline volume increases). Finally, it multiplies the action intensity value by the baseline injection volume value to generate an injection volume accurate to the microliter level. Finally, based on the deviation (0.05 units) between the real-time pH detection value (e.g., 1.55) and the target pH value (1.50) and its rate of change (e.g., 0.03 units per minute), the time window for maintaining steady state (e.g., injection to be completed within 8 seconds) is dynamically calculated.

[0035] For example, following the instruction generated in step 102 and the real-time acidity value of 1.55, the system first matches the concentration range of hydrochloric acid solution (0.06-0.08M) corresponding to the human gastric acid environment from the preset mapping table based on the current gastric release stage identifier (0-3 minutes). Combining this with the percentage of time that the stage has lasted (70%), the system selects a specific concentration of 0.07M. Next, it analyzes the dynamic trend of the drug release rate and measures that the slope of the change is increasing positively (continuously accelerating release). The system determines that an additional acid injection is needed through the symbol recognition module. Then, it matches the base amount adjustment coefficient (1.2 times) based on the absolute value of the slope and superimposes the instruction intensity value (level 3 corresponds to a weight of 1.5) to calculate the precise injection volume of 9μL. Finally, based on the real-time acidity deviation value (0.05 units) and its rate of increase of 0.04 units per minute, it is deduced that the buffer solution needs to be injected twice in a pulse within a 10-second time window (6μL first injected in the 0-4 second period, and the remaining 3μL injected in the 5-10 second period) to avoid drastic acidity fluctuations caused by a single injection. The complete parameter combination generated at this point (0.07M hydrochloric acid solution | 9μL total volume | 10-second fractional injection strategy) will directly drive the multi-channel fluid controller in the next step to perform precise control.

[0036] Step 104: Using a multi-channel precision fluid controller, the buffer solution corresponding to the concentration of the buffer solution is injected into the corresponding dissolution vessel at the precise injection volume within the dynamic time window, so that the pH value of the liquid environment is dynamically matched to the drug transport stage in the human gastrointestinal tract.

[0037] In this step, the multi-channel precision fluid controller is a liquid delivery device equipped with independently driven pumps and valves, which can simultaneously perform differentiated liquid addition operations on multiple dissolution cups; dynamic pH matching refers to intelligently adjusting the liquid's acidity and alkalinity to match the environmental characteristics of different stages of human digestion in real time (such as the stomach requiring a strong acidic environment and the intestines requiring a weak alkaline environment), ensuring that the drug release behavior truly simulates the process in the body.

[0038] In this embodiment, the system reads the complete injection parameters generated in step 103 (including buffer type, precise injection volume, and segmented operation time window). The controller automatically selects the corresponding reservoir channel based on the parameters (e.g., channel A for storing acidic buffer). The execution process strictly follows the dynamic time window instruction: first, at the beginning of the time window (e.g., t=0 seconds), the solenoid valve is opened, driving the high-precision micro-pump to inject the first segment of buffer (accounting for 60% of the total injection volume) in pulse mode; then, the channel is briefly closed and the pH change trend (e.g., the rate of acidity decrease) is monitored in real time. Based on the monitoring data, the channel is reopened in the second half of the time window (e.g., t=5 seconds) to inject the remaining buffer; all operations are completed before the time window closes (e.g., t≤10 seconds). The real-time pH value is continuously verified until it matches the target range (e.g., the gastric acid environment is stable at 1.50±0.02). If the drug is detected to enter the next physiological stage (e.g., the intestinal segment), the buffer type and injection strategy are immediately switched.

[0039] For example, following the sustained-release capsule adjustment parameters output in step 103 (0.07M hydrochloric acid solution | 9μL total volume | 10-second fractional injection), the controller initiates operation at the 2-minute mark of the experiment (gastric simulation phase): at t=0 seconds, channel A is opened to deliver 6μL of acidic buffer (concentration 0.07M), causing the real-time acidity to decrease from 1.55 to 1.52; during the brief shutdown period, the acidity is monitored to decrease by 0.04 units per minute, which is in line with expectations, so the remaining 3μL is injected at t=5 seconds; the operation is completed at t=10 seconds, and the acidity stabilizes at 1.50. Subsequently, at the 4-minute mark, the system detects that the drug release has reached the intestinal simulation node (abrupt change in release rate slope), and immediately switches to channel B for alkaline buffer (0.1M phosphate solution), injecting 15μL of liquid at a uniform rate over 15 seconds, gradually raising the pH from 1.50 to 6.75, achieving a precise simulation of the entire process with uninterrupted switching of the gastrointestinal environment.

[0040] In summary, this application's solution solves the problems of sensor drift and data asynchrony in complex media by synchronously collecting pH value and drug release dynamic trends using an acid-resistant sensor; it identifies persistent and sudden deviations using a release rate offset analysis mechanism to generate predictive compensation commands, significantly shortening the lag response time of traditional solutions; relying on dynamic parameter collaborative optimization technology, combined with human physiological stage mapping buffer concentration, release slope guiding injection volume grading, and real-time feedback generation time window, it overcomes the accuracy limitations of fixed parameter control; finally, through time-division pulse injection execution and multi-channel independent control, it achieves seamless high-fidelity switching from the strong acid environment of the stomach to the weak alkaline environment of the intestine, comprehensively improving the dynamic matching degree of drug dissolution process and human transport behavior, while reducing the long-term operation and maintenance burden of the system.

[0041] To address the problem of inaccurate concentration monitoring caused by the susceptibility of sensors to interference from the medium in existing technologies, some embodiments, as described in step 101, simultaneously monitor the real-time pH value of the liquid environment within the dissolution vessel and the dynamic trend of the release rate of the active ingredient using an acid-resistant sensor, including: Step 201: Multiple measurement units are arranged in a ring along the depth direction on the side wall of the dissolution cup, wherein each measurement unit includes a hydrogen ion sensing part and a light signal capturing part.

[0042] In this step, the ring-shaped measurement unit refers to multiple independent detection components that are equally spaced and embedded in the vertical direction along the side wall of the dissolution vessel. Through a deep layered layout, data from different layers of the liquid are captured simultaneously. The hydrogen ion sensing part is an electrochemical sensitive membrane built into the unit, which generates a potential difference related to the hydrogen ion concentration by contacting the liquid. The light signal capture part is a miniature spectral probe that analyzes the light transmission characteristics of the liquid by emitting and receiving light beams to estimate the substance concentration.

[0043] In this embodiment, during the dissolution vessel production stage, multiple sets of ring-shaped sensor units (each set containing a hydrogen ion sensing membrane and a miniature spectral probe) are vertically embedded into the side wall of the vessel. The units are uniformly spaced along the depth direction and cover the entire liquid layer. The sensing membrane and probe surfaces are coated with an anti-corrosion coating (to prevent strong acid corrosion). The units are connected in series to the main controller via internal circuitry. All units are in a dormant state when not activated, with their sensing membranes and probes physically isolated from the liquid, and only begin operation when triggered.

[0044] Step 202: At each predetermined acquisition time point, all measurement units are activated simultaneously by a synchronous trigger signal, causing the hydrogen ion sensing part of the measurement unit to generate an electrical signal, and at the same time, the optical signal capture part of the measurement unit to generate an optical signal.

[0045] In this step, the synchronous trigger signal is an electronic pulse command sent uniformly by the central controller to all measurement units to ensure that each unit starts working at the same time node; the electrical signal is the voltage fluctuation data generated by the change of liquid hydrogen ion concentration captured by the hydrogen ion sensing membrane; the optical signal refers to the transmitted light intensity and spectral absorption characteristic data captured by the receiver after the micro-spectral probe emits a specific wavelength beam of light through the liquid.

[0046] In this embodiment, when the preset timer reaches the acquisition time point (e.g., every 30 seconds), the central controller sends a high-speed electrical pulse to all ring sensor units. This pulse simultaneously triggers two actions: the physical isolation of the hydrogen ion sensing membrane of each unit is canceled (e.g., the ceramic slider retracts), allowing the sensitive membrane to directly contact the liquid and generate a potential difference signal; all miniature spectrometers synchronously emit detection beams (wavelength range covering the characteristic absorption spectrum of the drug) and receive transmitted light. Subsequently, each unit transmits the potential difference signal and transmitted light intensity data in parallel to the signal processor. The processor converts the potential difference data into pH value points in real time, and simultaneously converts the transmitted light data into active ingredient concentration value points according to the preset absorbance-concentration mapping table.

[0047] Step 203: Convert the electrical signal into a real-time pH value point, and at the same time convert the optical signal into an active ingredient concentration value point.

[0048] In this step, the real-time pH value refers to the instantaneous independent acidity / alkalinity value calculated from the electrical signal (voltage difference) output by the hydrogen ion sensing component at a single acquisition moment using a preset voltage-pH mapping relationship; the active ingredient concentration value refers to the instantaneous independent concentration value calculated from the transmission spectrum data obtained by the light signal capture component based on the drug standard spectral absorption model at the same acquisition moment. All values ​​are discrete single measurement results and have not yet been formed into a time series.

[0049] In this embodiment, the central processing unit first receives the raw signal data packet (containing electrical and optical signals from all measurement units) synchronously transmitted in step 202. For the electrical signals: it calls the voltage-pH linear mapping relationship in the pre-stored calibration database (e.g., a 1mV voltage change corresponds to a 0.5 unit pH change) to convert the raw potential difference value of each unit into the pH value of that unit at that moment. For the optical signals: it inputs the transmission spectral characteristics of each unit (such as the attenuation rate of a specific wavelength beam) into the drug-specific absorption rate-concentration mathematical model and outputs the concentration value of that unit at that moment.

[0050] Step 204: Connect the active ingredient concentration values ​​at consecutive time points in chronological order to generate an active ingredient concentration change curve.

[0051] In this step, the active ingredient concentration change curve is a continuous trajectory line generated by mathematical interpolation and filtering after sorting all independent concentration value points at the same spatial location at continuous collection times by timestamp. Essentially, it transforms discrete points into a continuous function that reflects the change pattern over time.

[0052] In this embodiment, the system extracts a set of discrete concentration values ​​for the same measurement unit at multiple consecutive acquisition times from a spatiotemporal database (e.g., four concentration values ​​for the upper-level unit at t=0 / 30 / 60 / 90s). First, the discrete points are arranged in timestamp order to form an original sequence. Then, a cubic spline interpolation algorithm is used to fill in continuous trajectories between adjacent points (e.g., a smooth transition between the curve of 22 mg / mL at t=30s and 38 mg / mL at t=60s). Finally, a sliding window filtering technique is used to remove outliers (e.g., abnormal values ​​caused by bubble interference in a measurement), outputting a smooth time-concentration function curve. This curve can be directly input into step 101 for dynamic trend analysis of the release rate.

[0053] Step 205: Calculate the difference between the concentration values ​​of two adjacent collection time points on the active ingredient concentration change curve, and divide the difference by the time length between adjacent collection time points to obtain the active ingredient release rate value at each collection time point.

[0054] In this step The active ingredient release rate value refers to the instantaneous release rate obtained by dividing the concentration difference between two adjacent moments by the time interval. It quantifies the intensity of the change in the dissolved mass of the drug's active ingredient per unit time and reflects the instantaneous dynamic characteristics of drug release behavior.

[0055] In this embodiment, the system first extracts the active ingredient concentration change curve (such as the continuous function curve of the upper unit) generated in step 204, and locates the concentration value points corresponding to all collection time nodes on the curve; then, for each pair of adjacent time points, it performs differential calculation: calculates the concentration value increment of the concentration point at the next time moment compared to the concentration point at the previous time moment; divides the increment by the time interval between the next time moment and the previous time moment to obtain the instantaneous release rate value at that collection time point; repeats this operation until all adjacent points are processed, and outputs a set of release rate values ​​matching each collection time moment.

[0056] Step 206: Arrange the release rate values ​​of the active ingredients in order of collection time points to generate an active ingredient release rate sequence.

[0057] In this step, the active ingredient release rate sequence refers to a discrete time series formed by arranging the release rate values ​​corresponding to multiple collection time points in the order of timestamps. Its core function is to integrate transient release rates into an analyzable trend data chain.

[0058] In this embodiment, the system obtains all release rate values ​​and their corresponding timestamps output in step 205. First, the rate values ​​are sorted in strict order from earliest to latest timestamp (e.g., t=30s value → t=60s value → t=90s value…). Then, a time-indexed sequence structure (e.g., a dictionary or array) is constructed: each element contains a time node label and its corresponding release rate value. Finally, a complete sequence is output, which directly serves as the input data source for dynamic trend analysis.

[0059] Step 207: Identify the consistency of the increasing or decreasing direction of multiple consecutive release rate values ​​in the active ingredient release rate sequence, so as to extract the continuous change characteristics of the active ingredient release rate sequence as a dynamic change trend.

[0060] In this step, the consistency of increase / decrease direction refers to the state in which three or more adjacent rate values ​​in the continuous time node release rate sequence maintain the same direction of change (continuous increase / decrease), which is used to identify the continuous pattern of drug release behavior; the continuous change characteristic is a qualitative feature symbol (such as acceleration / deceleration / stable) generated by pattern extraction of the consistency trend segment, which serves as the core decision basis for pH dynamic compensation instructions.

[0061] In this embodiment, the system obtains the ordered release rate sequence (a set of discrete values ​​with strictly ordered timestamps) output in step 206. First, a fixed-window rolling scan mechanism is used: three consecutive rate values ​​are extracted from the beginning of the sequence to form an analysis window. It is determined whether the three values ​​within the window maintain a consistent direction of change (e.g., if subsequent values ​​are all greater than previous values, it indicates an increasing trend). If consistency is found, the window range is expanded to subsequent points for continuous verification until the consistent trend is broken. Then, characteristics are extracted from all identified consistent trend segments: if a segment of rate values ​​continuously increases, it is marked as an "accelerating trend"; if it continuously decreases, it is marked as a "decelerating trend"; and if the fluctuation amplitude is weak, it is marked as a "stable trend". Finally, a set of continuously changing characteristics segmented and marked is output.

[0062] To address the issue that existing compensation commands cannot distinguish between continuous offsets and sudden fluctuations, in some embodiments, according to step 102, a dynamic pH compensation command is generated based on the offset between the dynamic trend of the active ingredient release rate and a preset phased release target curve, including: Step 301: Determine the time boundary of the current drug release stage based on the dynamic trend of the release rate of the active ingredient.

[0063] In this step, the current drug release stage refers to the key drug transport period preset according to the physiological characteristics of the human gastrointestinal tract (such as uniform release during the gastric retention period and accelerated release during the intestinal absorption period). Different stages correspond to different pH control targets. The time boundary is the start and end time node of the stage automatically divided by the system through analysis of the dynamic change trend of the release rate (such as t=0-3 minutes is the gastric stage, and t=3 minutes onwards is the intestinal stage), which is used to accurately match the physiological environment switching needs.

[0064] In this embodiment, the system first receives dynamic trend features (such as "acceleration trend segment" markers); it then retrieves a pre-stored human physiological stage model library (e.g., the gastric stage target is "stable release," and the intestinal stage target is "stepwise acceleration") and performs pattern matching between the actual trend features and the model library: if the current trend is identified as conforming to the same stage model (e.g., three consecutive "stable" trends), the current stage time boundary remains unchanged; if a trend feature transformation is detected (e.g., "stable" suddenly changes to "acceleration"), and the new trend continuously covers multiple collection points, it is determined to be a stage switching point. Subsequently, the switching point is used as the start time of the new stage, and the end time of the previous segment is used as the end time, and the stage time boundary label is output.

[0065] Step 302: Obtain the reference change profile of the preset phased release target curve within the time boundary.

[0066] Step 303: Compare the actual change profile of the release rate of the active ingredient with the reference change profile to obtain the difference results.

[0067] In this step, the actual change profile is the concrete form of the dynamic change trend extracted in step 207 within the current time boundary; the difference result is a structured deviation description obtained by comparing the actual profile with the reference profile, including a continuous deviation component (trend offset) and an instantaneous fluctuation component (caused by equipment error).

[0068] In this embodiment, the actual change profile and the reference profile are first input into the Dynamic Time Warping (DTW) algorithm. The time axes of the two curves are aligned and the point-by-point differences are calculated. The time periods when the actual rate is greater than the reference value are marked as positive offsets (continuous components). Instantaneous abrupt change points (such as single-point rate surges) are located as fluctuation components. Subsequently, the two types of components are quantized, and finally, a difference report is output.

[0069] Step 304: Analyze the persistent offset component and the sudden fluctuation component in the difference results.

[0070] In this step, the continuous offset component refers to the systematic deviation of the actual release rate relative to the reference value (such as being higher than the target value throughout the process), reflecting the stable deviation caused by drug characteristics or environmental factors; the sudden fluctuation component refers to the short-term abnormal fluctuation caused by instantaneous interference (such as tablet sticking to the wall, air bubbles), which exists independently of the overall trend.

[0071] In this embodiment, the system first receives the difference results; then, it separates two types of components using a low-pass filtering algorithm: retaining the low-frequency slowly varying signal as the continuous offset component, while extracting the high-frequency abrupt signal as the sudden fluctuation component. Subsequently, noise source analysis is performed on the sudden component; finally, a structured analytical report is output.

[0072] Step 305: Determine the compensation benchmark value based on the continuous offset component, and adjust the compensation adjustment factor based on the sudden fluctuation component.

[0073] In this embodiment, the system first extracts the directional attributes (positive or negative) and intensity percentage data of the continuous offset component, calls a preset offset-level mapping table for precise matching, and outputs the corresponding compensation benchmark level (e.g., level three acid enhancement). Then, for sudden fluctuation components, a differentiated adjustment process is triggered based on their interference type. If identified as equipment interference (e.g., instantaneous sensor anomaly), a basic suppression factor is generated and superimposed with a dynamic attenuation weight calculated based on the fluctuation amplitude (the stronger the fluctuation, the greater the suppression). If determined to be drug anomaly (e.g., tablet adhesion), a basic enhancement factor is generated and superimposed with a dynamic amplification weight associated with the fluctuation amplitude. Finally, the compensation adjustment factor after dynamic adjustment is output.

[0074] Step 306: Combine the compensation benchmark value with the adjusted compensation regulation factor to form a dynamic pH compensation command that includes the direction and intensity of action.

[0075] In this embodiment, the compensation baseline value and the adjusted compensation adjustment factor are first received. A core merging calculation is performed: the level value of the compensation baseline value is multiplied by the compensation adjustment factor. Then, the direction of action of the compensation baseline value is inherited as the final command direction, and the product result is converted into an intensity level; finally, a pH dynamic compensation command is encoded and generated.

[0076] In some embodiments, as described in step 305, determining a compensation reference value based on the persistent offset component and adjusting the compensation adjustment factor based on the sudden fluctuation component includes: Step 401: Calculate the linear cumulative amount of the continuous offset component changing over time, and input the linear cumulative amount into a predefined relational table to output the compensation reference value.

[0077] In this step, the time integral value of the continued offset component is used to quantify the cumulative effect strength of the system offset; the predefined relation table is a database that stores the mapping relationship between linear cumulative quantities and compensation levels.

[0078] In this embodiment, the system first acquires the continuous offset component, then performs linear integration on the curve of offset intensity changing over time to calculate the cumulative effect from the start of the offset to the current moment; then calls a predefined relation table to match the compensation benchmark value level according to the interval where the cumulative amount is located; finally, it outputs the compensation benchmark value that strictly corresponds to the cumulative amount.

[0079] Step 402: Extract the peak intensity and duration of the sudden fluctuation component, and multiply the peak intensity by the duration to obtain the fluctuation energy value.

[0080] In this step, peak intensity is the maximum instantaneous deviation of the sudden fluctuation component; duration is the time it takes for the fluctuation to fall back to the normal value from the initial peak; fluctuation energy value = peak intensity × duration, used to quantify the comprehensive impact intensity of the sudden fluctuation.

[0081] In this embodiment, the system receives sudden fluctuation components (including peak intensity and time boundary); locates the peak point and start and end time nodes of the fluctuation curve, calculates the duration difference; then performs a multiplication operation and outputs the fluctuation energy value.

[0082] Step 403: Match the corresponding weight coefficients in the pre-stored mapping set according to the fluctuation energy value, and multiply the weight coefficients by the initial value of the compensation adjustment factor to obtain the adjusted compensation adjustment factor.

[0083] In this step, the pre-stored mapping set is a database that stores the correspondence between fluctuation energy values ​​and weight coefficients; the initial compensation adjustment factor is the original weight value generated in step 305 based on the type of interference; the multiplication operation refers to the calculation process of integrating the weight coefficients and the initial factor into the final calibration value through multiplication.

[0084] In this embodiment, the system first reads the fluctuation energy value, matches the corresponding weight coefficient in the pre-stored mapping set, then calls the initial compensation adjustment factor, performs a multiplication operation, and outputs the adjusted compensation adjustment factor.

[0085] To address the issue of low accuracy in matching buffer concentration with injection volume in existing technologies, some embodiments, according to step 103, calculate a combination of injection parameters for the buffer solution based on the dynamic pH compensation command and the real-time pH value. This combination of injection parameters includes a buffer solution concentration matching the current drug release phase, a precise injection volume based on the slope of the release rate change, and a dynamic time window for maintaining target pH stability, including: Step 501: Calculate the slope of the release rate change based on the dynamic trend of the release rate of the active ingredient.

[0086] In this step, the slope of the release rate change is a quantitative indicator that describes how steep the drug release rate changes over time. A positive value indicates accelerated release, and a negative value indicates decelerated release, which is used to predict the trend of drug dissolution behavior.

[0087] In this embodiment, the system first obtains the release rate sequence of the active ingredient (a set of discrete rate values ​​arranged by timestamps), then uses the three-point central difference algorithm to process the sequence data, extracts the rate values ​​at three consecutive time points (such as t1, t2, t3), calculates the instantaneous slope at the intermediate point t2 (slope = (t3 value - t1 value) ÷ (t3 time - t1 time); finally, it traverses all three consecutive point groups in the entire sequence and outputs the set of slope values ​​corresponding to each time node.

[0088] Step 502: Extract the direction identifier and force value from the pH dynamic compensation command.

[0089] In this step, the direction identifier is a letter code representing the direction of acid-base adjustment in the pH dynamic compensation instruction (e.g., "A" for increasing acidity / "B" for decreasing alkali); the intensity value is a numerical label in the instruction indicating the level of control intensity (e.g., level 1.2).

[0090] In this embodiment, the system reads the pH dynamic compensation instruction (such as the structured code "A1.2"). Then, it parses the instruction string, first identifying the first letter as the direction identifier ("A" → acidification), and then extracting the subsequent numerical part as the intensity value.

[0091] Step 503: Select a buffer solution concentration value from a preset concentration mapping table based on the action direction identifier and the target human gastrointestinal segment corresponding to the current drug release stage.

[0092] In this step, the preset concentration mapping table is a database that stores the correspondence between human gastrointestinal tract segments (such as the stomach / intestines) and buffer concentrations; the target human gastrointestinal tract segment refers to the physiological environment marker defined according to the drug release stage (such as the stomach stage requiring a strongly acidic environment).

[0093] In this embodiment, the system first reads the direction identifier (e.g., "acidification") and obtains the target gastrointestinal segment identifier (e.g., "stomach segment") for the current drug release stage. Then, it performs two-factor matching in a preset mapping table: it locks the concentration range based on the segment identifier (e.g., the concentration range of hydrochloric acid solution corresponding to the stomach is C1-C2); it selects the acid-base type based on the direction identifier (e.g., hydrochloric acid solution is selected for acidification); and finally, it outputs the buffer concentration value that strictly matches the physiological stage.

[0094] Step 504: Convert the sign and absolute value of the slope of the release rate change to the baseline injection volume.

[0095] In this step, the baseline injection volume is a basic level of buffer volume determined by the mathematical sign (positive / negative) and absolute value of the slope of the release rate change. The sign of the slope predicts the direction of adjustment (positive slope requires increased volume), and the absolute value is converted into an intensity level.

[0096] In this embodiment, the system first obtains the slope of the release rate change (e.g., a positive slope at a certain moment), then parses the mathematical properties of the slope, marking positive slopes as positive signs and negative slopes as negative signs. Next, the absolute value of the slope is input into a preset absolute value-level conversion model, matching the absolute value with the discrete interval; simultaneously, the output coefficient is multiplied by the baseline unit quantity to generate the baseline value of the basic injection quantity.

[0097] Step 505: Based on the product relationship between the applied force value and the baseline injection volume, generate the precise injection volume.

[0098] In this embodiment, the system first obtains the applied force value and the baseline injection volume value, then performs a core product calculation, multiplying the force value by the baseline value; subsequently, it performs equipment accuracy calibration, and rounds the product result to an executable accuracy based on the resolution limitations of the fluid controller, finally outputting an accurate injection volume that meets the mechanical execution requirements.

[0099] Step 506: Based on the deviation and trend between the real-time pH value and the target pH range, generate a dynamic time window to maintain the stability of the target pH.

[0100] In this embodiment, the system first reads real-time pH sensor data and the target pH range, then calculates the deviation between the real-time value and the target median value, and fits the trend of change through historical data; then, based on dual-parameter joint decision-making, firstly, the deviation dominates the base duration, and the larger the deviation, the longer the base time window; then, the change trend is used to fine-tune the rhythm, if the upward trend is fast, the first injection time is shortened (to prevent overshoot), and if the downward trend is fast, the last injection time is extended (to prevent under-adjustment); finally, the output includes the time window code containing segment nodes.

[0101] Step 507: Combine the selected buffer solution concentration value, the generated precise injection volume, and the dynamic time window into an injection parameter set.

[0102] In this embodiment, the system first acquires the selected buffer concentration value, precise injection volume, and dynamic time window strategy instructions. Then, it aggregates the data according to a predefined template, marking the concentration value as an acid-base intensity identifier, splitting the injection volume into segmented metering nodes, and parsing the time window into a start-end time series. Subsequently, it performs logical verification to check whether the concentration identifier is compatible with the physiological environment of the current drug release stage (e.g., alkaline buffers are prohibited in the gastric stage). If a conflict is found, an alarm is triggered and the parameters are corrected. Finally, the concentration identifier is written into the type field, the volume data is converted into a vector format, and the time strategy is encoded into segmented timestamp-injection volume key-value pairs, generating a machine-parseable binary control flow and a human-readable natural language description.

[0103] To address the problem of manually setting buffer concentrations in existing technologies that deviate from physiological conditions, some embodiments, according to step 503, select a buffer solution concentration value from a preset concentration mapping table based on the action direction identifier and the target human gastrointestinal segment corresponding to the current drug release stage, including: Step 601: Obtain the target human gastrointestinal segment identifier corresponding to the current drug release stage, wherein the target human gastrointestinal segment identifier includes a stomach segment identifier, a small intestine segment identifier, or a large intestine segment identifier.

[0104] In this step, the target human gastrointestinal segment identifier is a physiological environment classification label based on the current drug release stage (such as the gastric retention period and the intestinal absorption period). It distinguishes different segments by letter codes (such as "G" for the stomach segment, "S" for the small intestine segment, and "L" for the large intestine segment) to accurately match the differentiated pH environment requirements of the human digestive tract.

[0105] In this embodiment, the system first reads the defined time boundaries of the drug release phase (e.g., 0-3 minutes for the gastric phase), then calls a preset physiological phase-segment mapping table, where the gastric retention period corresponds to the "G" identifier; the small intestinal absorption period corresponds to the "S" identifier; and the large intestine release period corresponds to the "L" identifier. Finally, it outputs a segment identifier code that strictly matches the current time boundary.

[0106] Step 602: Based on the target human gastrointestinal segment identifier, identify the type of the action direction identifier. If the action direction identifier is a first type of instruction, proceed to the acid concentration selection process; if the action direction identifier is a second type of instruction, proceed to the alkali concentration selection process.

[0107] In this step, the acid concentration selection process is the process of generating a concentration value by calling a pre-set acidic buffer database when both the physiological environment demand and the regulatory instruction point to acid regulation (such as enhancing the gastric acid environment); the alkali concentration selection process is the process of matching by calling an alkaline buffer database when it is necessary to weaken the acidity or strengthen the alkaline environment (such as adjusting the weak alkalinity of the intestine); the first type of instruction is an acid-increasing operation code (such as "A"); the second type of instruction is an acid-reducing operation code (such as "B"), and the two are processed through binary logic isolation.

[0108] In this embodiment, the system first receives the target human gastrointestinal tract segment identifier (e.g., "GS" represents the stomach) and the action direction identifier (e.g., "A" represents acid increase); then, it performs step-by-step decision-making. If the segment identifier is the stomach ("GS") and the action direction identifier is a first-type instruction ("A"), it is determined to conform to physiological logic and triggers the acid flow process; if the segment is the intestine ("SI") and the direction identifier is a second-type instruction ("B"), it triggers the alkali flow process; for conflicting combinations (e.g., the stomach environment encounters an acid reduction instruction), an alarm log is immediately generated and parameter changes are frozen to ensure control safety.

[0109] Step 603: When executing the acid concentration selection process, extract the corresponding acid buffer solution concentration range from the preset concentration mapping table based on the target human gastrointestinal segment identifier.

[0110] In this step, the concentration range of the acid buffer solution refers to the range of acid concentration strength that can be used in a specific physiological segment. The lower limit ensures effectiveness, while the upper limit prevents excessive corrosion.

[0111] In this embodiment, after activating the acid flow (such as a gastric acid-increasing command), the system first locates the acidic library partition in the preset mapping table based on the input target segment identifier (such as "GS"); then it performs identifier keyword matching (such as "GS" → gastric acidic block) to extract the set of concentration range parameters registered for the block (including minimum / maximum concentration boundary values); finally, it performs range validity verification to confirm that the boundary values ​​comply with solvent safety specifications (such as no crystallization), and outputs the legal concentration range object for the segment.

[0112] Step 604: Calculate the specific concentration value within the range of the acidic buffer solution concentration, based on the proportion of the duration of the current drug release phase to the total duration of the target human gastrointestinal tract segment.

[0113] In this step, the duration percentage refers to the ratio of the duration of the current release phase to the preset total duration, which is used to reflect the release progress of the drug in this physiological segment; the concentration value is calculated by linearly interpolating the duration percentage within the acid concentration range to output the specific concentration, ensuring that the buffer strength is dynamically adapted to the release process.

[0114] In this embodiment, the system obtains the start timestamp of the current drug release phase and the preset total duration, then calculates the ratio of the elapsed duration to the total duration, then reads the acid concentration range, and maps the ratio value to the concentration range based on a linear interpolation algorithm. Starting from the lower limit of the range, the concentration value is increased proportionally, and finally the accurate concentration adapted to the current release progress is output.

[0115] Step 605: When executing the alkaline concentration selection process, extract the corresponding alkaline buffer solution concentration range from the preset concentration mapping table based on the target human gastrointestinal segment identifier.

[0116] In this step, the concentration range of the alkaline buffer solution refers to the safe range of the weak alkaline buffer solution ratio for the intestinal / large intestine segment. Its lower limit ensures pH buffering capacity, while its upper limit prevents drug precipitation.

[0117] In this embodiment, when the alkaline solution process is activated, the system locates the alkaline library partition of the preset mapping table according to the input segment identifier, then performs precise identifier matching, extracts the registered alkaline buffer concentration boundary, verifies that the range meets the drug compatibility specifications, and finally outputs the legally defined weak alkaline concentration range object.

[0118] Step 606: Calculate the specific concentration value within the range of the alkaline buffer solution concentration, based on the proportion of the cumulative release amount of the active ingredient in the current drug release stage to the target release amount in the target human gastrointestinal tract segment.

[0119] In this step, the cumulative release percentage refers to the percentage ratio of the actual total amount of drug active ingredients dissolved in the current physiological segment to the preset target release amount, which is used to quantify the progress of drug absorption in the intestinal / large intestine stage.

[0120] In this embodiment, the system obtains the cumulative release amount of the active ingredient in the current segment and the preset target release amount, then calculates the ratio of the actual amount to the target amount, then reads the concentration range of the alkaline buffer solution, and based on the linear interpolation algorithm, increases the value proportionally with the lower limit of the range as the benchmark, and finally outputs the accurate concentration adapted to the current drug absorption progress.

[0121] Step 607: Output the calculated specific concentration value as the buffer solution concentration value.

[0122] In this embodiment, the system first receives the specific concentration value generated in step 604 (acid solution) or step 606 (alkali solution), then verifies whether the concentration value is within the legally safe range, and subsequently encapsulates it into a structured field: "Type tag" (acid / alkali) + "concentration value" + "unit" (e.g., "acid:0.075:M"). Finally, it is written into the injection parameter set in step 507 to drive the multi-channel fluid controller for precise solution preparation.

[0123] To address the over-adjustment problem caused by relying on empirical thresholds for injection volume adjustment in existing technologies, some embodiments, according to step 504, convert the sign and absolute value of the release rate change slope into a baseline injection volume value, including: Step 701: Determine the sign attribute of the release rate change slope. When the release rate change slope is greater than a preset zero mark, it is a positive sign; when the release rate change slope is less than the preset zero mark, it is a negative sign.

[0124] In this step, the symbol attribute is a classification identifier that describes the directionality of the slope of the release rate change, used to predict the evolution direction of drug release behavior (positive direction is accelerated release, negative direction is decelerated release); the preset zero-time marker refers to the slope direction determination threshold set by the system, which divides continuous values ​​into qualitative features with clear symbols.

[0125] In this embodiment, the system first receives a set of release rate change slope values, then compares each slope value with a zero threshold. If the slope is greater than the zero threshold, it is marked as a positive sign; if the slope is less than the zero threshold, it is marked as a negative sign. Subsequently, the sign attribute is bound to the slope value and stored to form a slope dataset with direction labels.

[0126] Step 702: Calculate the absolute value of the slope of the change in the release rate.

[0127] In this step, the absolute value is the slope intensity value stripped of the sign attribute through mathematical operations, quantifying the severity of the release rate change (such as rapid acceleration or slow deceleration), and is used to guide the grading of buffer conditioning intensity.

[0128] In this embodiment, the system first reads the signed slope dataset, then performs an absolute value operation on each slope value, retains the original numerical value, ignores the influence of positive and negative signs, and then stores the result in association with the corresponding sign attribute.

[0129] Step 703: Match the absolute value with a plurality of preset continuous value intervals, and obtain the basic quantity adjustment coefficient based on the matching result, wherein each value interval corresponds to a basic quantity adjustment coefficient.

[0130] In this step, the continuous numerical interval is a preset range of absolute slope values; the baseline adjustment factor is an intensity weight value bound to the interval, used to quantify the proportion of the impact of the drastic change in release rate on the amount of buffer solution used.

[0131] In this embodiment, the system first obtains the set of absolute slope values, then matches them step by step with a preset interval threshold sequence. If the absolute value falls into a certain interval, the adjustment coefficient registered for that interval is extracted. Subsequently, the adjustment coefficient that strictly corresponds to each slope value is output.

[0132] Step 704: When the symbol attribute is a positive symbol, multiply the basic quantity adjustment coefficient by the preset positive reference unit quantity to obtain the basic injection quantity reference value.

[0133] In this step, the positive reference unit is a predefined base volume unit of acidic buffer (e.g., +5 μL), representing the standard adjustment amount required for a unit strength acceleration trend; the base injection reference value is the product of the adjustment factor and the positive reference unit, quantifying the precise volume requirement of the acidification buffer.

[0134] In this embodiment, when step 701 determines that the symbol attribute is a positive symbol, the adjustment coefficient of step 703 is first read, then a multiplication operation is performed to multiply the adjustment coefficient by the positive reference unit quantity, and finally the base injection quantity reference value is output as a positive volume value, driving the system to increase acid injection to slow down the release rate.

[0135] Step 705: When the symbol attribute is negative, multiply the basic quantity adjustment coefficient by the preset negative reference unit quantity to obtain the basic injection quantity reference value.

[0136] In this step, the negative baseline unit is a predefined basic volume unit of alkaline buffer solution, representing the standard adjustment required for a unit intensity deceleration trend.

[0137] In this embodiment, when step 701 determines that the symbol attribute is a directional symbol, the adjustment coefficient of step 703 is first read, then a multiplication operation is performed, the adjustment coefficient is multiplied by the negative reference unit quantity, and finally the reference value is output as a negative volume value, driving the system to reduce acid or increase alkali to accelerate release.

[0138] Figure 2 This application provides a schematic diagram of a dynamic pH control system for the dissolution medium based on a dissolution apparatus, as shown in the embodiment of the present application. Figure 2 As shown, the system includes: The monitoring module 21 is used to simultaneously monitor the real-time pH value of the liquid environment in the dissolution cup and the dynamic trend of the release rate of active ingredients through an acid-resistant sensor. The generation module 22 is used to generate a pH dynamic compensation command based on the offset between the dynamic change trend of the release rate of the active ingredient and the preset staged release target curve. Calculation module 23 is used to calculate the injection parameter combination of the buffer solution based on the pH dynamic compensation command and the real-time pH value, wherein the injection parameter combination includes a buffer solution concentration matching the current drug release stage, a precise injection volume based on the slope of the release rate change, and a dynamic time window to maintain the stability of the target pH. The execution module 24 is used to inject the buffer solution corresponding to the concentration of the buffer solution into the corresponding dissolution cup at the precise injection volume within the dynamic time window through a multi-channel precision fluid controller, so that the pH value of the liquid environment is dynamically matched to the drug transport stage in the human gastrointestinal tract.

[0139] Figure 2 The aforementioned dynamic pH control system for dissolution media based on a dissolution apparatus can perform... Figure 1 The implementation principle and technical effects of the dynamic pH control method for dissolution media based on a dissolution apparatus, as described in the illustrated embodiment, will not be repeated here. The specific operation methods of each module and unit in the dynamic pH control system for dissolution media based on a dissolution apparatus in the above embodiments have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0140] In one possible design, Figure 2 The illustrated embodiment of a dynamic pH control system for the dissolution medium based on a dissolution apparatus can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0141] The processing component 32 is used for the above Figure 1 The embodiment describes a method for dynamically controlling the pH value of the dissolution medium based on a dissolution apparatus.

[0142] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0143] Storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0144] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0145] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0146] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for dynamically controlling the pH value of the dissolution medium based on a dissolution apparatus, characterized in that, include: The real-time pH value of the liquid environment inside the dissolution vessel and the dynamic trend of the release rate of active ingredients are monitored simultaneously using an acid-resistant sensor. Based on the offset between the dynamic trend of the release rate of the active ingredient and the preset phased release target curve, a dynamic pH compensation command is generated. Based on the pH dynamic compensation command and the real-time pH value, the injection parameter combination of the buffer solution is calculated, wherein the injection parameter combination includes a buffer solution concentration matching the current drug release phase, a precise injection volume based on the slope of the release rate change, and a dynamic time window to maintain the target pH stability. By using a multi-channel precision fluid controller, the buffer solution corresponding to the concentration of the buffer solution is injected into the corresponding dissolution vessel at the precise injection volume within the dynamic time window, so that the pH value of the liquid environment is dynamically matched to the drug transport stage in the human gastrointestinal tract.

2. The method according to claim 1, characterized in that, The real-time pH value of the liquid environment inside the dissolution vessel and the dynamic trend of the release rate of active ingredients are simultaneously monitored using an acid-resistant sensor, including: Multiple measurement units are arranged in a ring along the depth direction on the side wall of the dissolution vessel, wherein each measurement unit includes a hydrogen ion sensing part and a light signal capturing part; At each predetermined acquisition time point, all measurement units are activated simultaneously by a synchronous trigger signal, causing the hydrogen ion sensing part of the measurement unit to generate an electrical signal, and at the same time, the optical signal capture part of the measurement unit to generate an optical signal. The electrical signal is converted into a real-time pH value, and the optical signal is converted into a concentration value of the active ingredient. By connecting the active ingredient concentration data points from consecutive time points in chronological order, a curve of active ingredient concentration variation is generated. Calculate the difference between the concentration values ​​of two adjacent collection time points on the active ingredient concentration change curve, and divide the difference by the time length between adjacent collection time points to obtain the active ingredient release rate value at each collection time point; The release rate values ​​of the active ingredients are arranged in chronological order of the collection time points to generate an active ingredient release rate sequence. Identify the consistency of the increasing or decreasing direction of multiple consecutive release rate values ​​in the release rate sequence of the active ingredient, so as to extract the continuous change characteristics of the release rate sequence of the active ingredient as a dynamic change trend.

3. The method according to claim 2, characterized in that, Based on the offset between the dynamic trend of the release rate of the active ingredient and the preset phased release target curve, a dynamic pH compensation instruction is generated, including: Based on the dynamic trend of the release rate of the active ingredient, the time boundary of the current drug release stage is defined. Obtain the reference change profile of the preset phased release target curve within the time boundary; By comparing the actual change profile of the release rate of the active ingredient with the reference change profile, the difference results are obtained. Analyze the persistent offset component and sudden fluctuation component in the difference results; The compensation benchmark value is determined based on the continuous offset component, and the compensation adjustment factor is adjusted based on the sudden fluctuation component. The aforementioned compensation benchmark value and the adjusted compensation regulation factor are combined to form a dynamic pH compensation command that includes the direction and intensity of action.

4. The method according to claim 3, characterized in that, Determining a compensation benchmark value based on the sustained offset component and adjusting the compensation adjustment factor based on the sudden fluctuation component includes: Calculate the linear cumulative amount of the continuous offset component as a function of time, and input the linear cumulative amount into a predefined relational table to output the compensation reference value; Extract the peak intensity and duration of the sudden fluctuation component, and multiply the peak intensity by the duration to obtain the fluctuation energy value; Based on the weight coefficients matched with the fluctuation energy values ​​in the pre-stored mapping set, the weight coefficients are multiplied by the initial value of the compensation adjustment factor to obtain the adjusted compensation adjustment factor.

5. The method according to claim 1, characterized in that, Based on the pH dynamic compensation command and the real-time pH value, a combination of injection parameters for the buffer solution is calculated. This combination includes a buffer solution concentration matched to the current drug release phase, a precise injection volume based on the slope of the release rate change, and a dynamic time window for maintaining target pH stability, including: Based on the dynamic trend of the release rate of the active ingredient, the slope of the release rate change is calculated; Extract the direction identifier and force value from the pH dynamic compensation command; Based on the action direction identifier and the target human gastrointestinal segment corresponding to the current drug release stage, select the buffer solution concentration value from the preset concentration mapping table; Convert the sign and absolute value of the slope of the release rate change to the baseline injection volume. Based on the product relationship between the applied force value and the baseline injection volume, a precise injection volume is generated; Based on the deviation and trend of the real-time pH value from the target pH range, a dynamic time window for maintaining the stability of the target pH is generated. The selected buffer solution concentration value, the generated precise injection volume, and the dynamic time window are combined into an injection parameter set.

6. The method according to claim 5, characterized in that, Based on the direction of action identifier and the target human gastrointestinal segment corresponding to the current drug release stage, a buffer solution concentration value is selected from a preset concentration mapping table, including: Obtain the target human gastrointestinal segment identifier corresponding to the current drug release stage, wherein the target human gastrointestinal segment identifier includes a stomach segment identifier, a small intestine segment identifier, or a large intestine segment identifier. Based on the target human gastrointestinal tract segment identifier, the type of the action direction identifier is identified. If the action direction identifier is a first type of instruction, the acid concentration selection process is initiated; if the action direction identifier is a second type of instruction, the alkali concentration selection process is initiated. When executing the acid concentration selection process, the corresponding acid buffer solution concentration range is extracted from the preset concentration mapping table based on the target human gastrointestinal tract segment identifier. The specific concentration value is calculated within the range of the acidic buffer solution concentration based on the proportion of the duration of the current drug release phase to the total duration of the target human gastrointestinal tract. When executing the alkaline concentration selection process, the corresponding alkaline buffer solution concentration range is extracted from the preset concentration mapping table based on the target human gastrointestinal tract segment identifier. Based on the proportion of the cumulative release of the active ingredient at the current drug release stage to the target release amount in the target human gastrointestinal tract segment, the specific concentration value is calculated within the concentration range of the alkaline buffer solution. The calculated specific concentration value will be output as the buffer solution concentration value.

7. The method according to claim 5, characterized in that, Convert the sign and absolute value of the slope of the release rate change to the baseline injection volume, including: The sign attribute of the release rate change slope is determined. When the release rate change slope is greater than a preset zero mark, it is a positive sign; when the release rate change slope is less than the preset zero mark, it is a negative sign. Calculate the absolute value of the slope of the change in the release rate; The absolute value is matched with multiple preset consecutive value intervals, and the basic quantity adjustment coefficient is obtained based on the matching results, wherein each value interval corresponds to a basic quantity adjustment coefficient. When the symbol attribute is a positive symbol, the basic quantity adjustment coefficient is multiplied by the preset positive reference unit quantity to obtain the basic injection quantity reference value; When the symbol attribute is negative, the basic quantity adjustment coefficient is multiplied by the preset negative benchmark unit quantity to obtain the basic injection quantity benchmark value.

8. A dynamic pH control system for dissolution media based on a dissolution apparatus, characterized in that, include: The monitoring module is used to simultaneously monitor the real-time pH value of the liquid environment inside the dissolution cup and the dynamic trend of the release rate of active ingredients through an acid-resistant sensor. The generation module is used to generate a dynamic pH compensation command based on the offset between the dynamic trend of the release rate of the active ingredient and the preset phased release target curve. The calculation module is used to calculate the injection parameter combination of the buffer solution based on the pH dynamic compensation command and the real-time pH value, wherein the injection parameter combination includes a buffer solution concentration matching the current drug release stage, a precise injection volume based on the slope of the release rate change, and a dynamic time window to maintain the target pH stability. The execution module is used to inject the buffer solution corresponding to the concentration of the buffer solution into the corresponding dissolution vessel at the precise injection volume within the dynamic time window through a multi-channel precision fluid controller, so that the pH value of the liquid environment is dynamically matched to the drug transport stage in the human gastrointestinal tract.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a method for dynamic control of the pH value of the dissolution medium based on a dissolution apparatus as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements a method for dynamically controlling the pH value of a dissolution medium based on a dissolution apparatus, as described in any one of claims 1 to 7.

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