A microneedle patch customization management method and system

Abstract

The application provides a microneedle patch customization management method and system, and relates to the technical field of microneedle patch customization management. The application constructs a drug release event sequence by acquiring a target drug release curve and identifying feature points; the target curve is decomposed into a plurality of basic release curves according to a microneedle unit drug release model; the manufacturing parameters of each microneedle population are inversely solved by taking the minimum deviation of the superimposed curve and the target curve as the target; then the skin mechanics simulation is verified, the geometric parameters or matrix materials of the population that do not pass the closed loop adjustment are fed back and recalculated until all pass; finally, the number, arrangement area ratio and spatial position of microneedles are calculated according to the drug release events of various populations, and a manufacturing parameter set containing array arrangement rules is generated. The application realizes reverse and accurate design from complex drug release requirements to manufacturable parameters, considers drug release performance and penetration reliability, and effectively avoids parameter conflicts and repeated verification in the traditional trial-and-error process.

Description

Technical Field

[0001] This invention relates to the field of microneedle patch customization management technology, specifically a microneedle patch customization management method and system. Background Technology

[0002] Insulin therapy for diabetic patients requires highly individualized dosing regimens to precisely match the patient's unique glycemic fluctuation patterns. In daily management, postprandial hyperglycemia spikes are a major challenge, and the time to peak, peak height, and duration of hyperglycemia vary significantly among patients. Existing customized management methods for microneedle patches mostly focus on coarse control of single drug release duration or total dose, failing to achieve precise matching with multi-peak, multi-morphological target release curves. The conventional approach involves selecting one or a few microneedles of different heights based on experience and simply mixing them. The resulting superimposed release curve morphology is very limited, making it difficult to actively fit the complex timing requirements defined in the prescription, such as a sharp early peak followed by a gentle late peak. This method is essentially a forward trial-and-error approach, determining the physical parameters of the microneedles before measuring their release results, completely lacking the ability to reverse-engineer the required microneedle array combination and specific manufacturing parameters from the target curve. In particular, when a plateau-shaped peak appears in the target curve, existing technologies cannot automatically identify and properly break it down, resulting in a release curve that deviates significantly from the prescription requirements in terms of peak rate and duration, making it impossible to achieve truly precise drug delivery.

[0003] More importantly, even if several candidate parameters for microneedle populations that meet drug release requirements are obtained through some means, current technologies lack a complete method for the coordinated design and closed-loop verification of drug release performance and insertion reliability. In practice, to meet a complex timing release requirement, some microneedles with very thin or irregular geometric shapes may be calculated. These microneedles may have the theoretical drug release capacity, but when actually inserted into real skin with different elastic moduli and stratum corneum thicknesses, they are prone to buckling or even breakage, leading to drug delivery failure. Existing methods separate drug release design from mechanical verification. Mechanical verification is often carried out only after physical samples are manufactured. Once a problem is found, it is necessary to go back and modify the design, and then re-prepare samples for testing. This method is not only time-consuming and costly, but it also often destroys the previously adjusted drug release performance, causing the entire design to fall into a vicious cycle of neglecting one aspect for another. It is impossible to stably and efficiently generate a set of final manufacturing parameters for a microneedle patch that meets the requirements of complex drug release curves and ensures reliable skin insertion for a specific patient.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a microneedle patch customization management method and system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for customizing and managing microneedle patches, comprising the following steps: Step 1: Obtain the target drug release curve, identify feature points on the target drug release curve, and analyze the temporal sequence of the feature points to form a drug release event sequence of the target drug release curve. The drug release event sequence includes the start time, peak time, peak rate and duration of each drug release peak. Step 2: Call the pre-built microneedle unit drug release model, and decompose the target drug release curve into several basic release curves according to the drug release event sequence. Each basic release curve corresponds to a microneedle population. Step 3: With the goal of minimizing the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve, the manufacturing parameters of each microneedle population are solved by inversion. The manufacturing parameters include the needle geometry parameters and the degradation rate constant of the needle matrix material. Step 4: Input the manufacturing parameters of each microneedle population obtained from the inversion into the skin mechanics simulation model, and perform mechanical simulation verification of the process of each microneedle piercing the skin; if any microneedle population fails the mechanical simulation verification, adjust the manufacturing parameters of that microneedle population, and feed the adjusted manufacturing parameters back to Step 3 to re-invert and solve until it passes the mechanical simulation verification. Step 5: Based on the drug release event sequence corresponding to each microneedle population verified by mechanical simulation, calculate the number of microneedles required for each microneedle population, and determine the arrangement area ratio and spatial position of each microneedle population on the microneedle patch according to the number of microneedles, and generate a set of manufacturing parameters containing the spatial arrangement rules of the microneedle array.

[0007] Furthermore, the target drug release curve contains multiple time-independent drug release peaks, each corresponding to a postprandial blood glucose control requirement. The feature points include start time, peak time, and end time. Feature point identification is performed on the target drug release curve specifically as follows: Scan the target drug release curve, locate the time point when the release rate first exceeds the preset onset threshold as the start time of the drug release peak, locate the inflection point when the release rate changes from rising to falling as the peak time, record the value of the release rate at the inflection point as the peak rate, and locate the time point when the release rate falls back below the preset onset threshold as the end time. The duration is obtained from the difference between the end time and the start time. When the release rate corresponding to the peak time is maintained at the peak rate for a duration exceeding a preset time threshold, the drug release peak is determined to be a plateau peak and is divided into two consecutive sub-peaks. The drug release event sequence of each sub-peak is then re-determined. The drug release event sequence is organized with a single drug release peak as an independent unit, and the sub-peaks after being split are regarded as two independent drug release peaks in the drug release event sequence.

[0008] Furthermore, the manufacturing parameters also include the spatial distribution concentration of the drug within the needle body, and the parameters associated with the microneedle unit drug release model include the needle body geometric parameters, the degradation rate constant of the needle body matrix material, and the spatial distribution concentration of the drug within the needle body; Each drug release peak in the drug release event sequence is taken as an independent decomposition target unit, so that the total number of the decomposed basic release curves is consistent with the total number of drug release peaks. The decomposition employs a non-negative matrix factorization algorithm, and constrains the peak time of each decomposed basic release curve to remain within a preset deviation range from the peak time of the corresponding drug release peak.

[0009] Furthermore, each basic release curve is assigned to an independent microneedle population, which corresponds to a microneedle array region on the microneedle patch, and all microneedles in the microneedle array region have exactly the same manufacturing parameters. Using the manufacturing parameters as variables to be optimized, an iterative optimization algorithm is adopted. In each iteration, the microneedle unit drug release model is called to generate a basic release curve. Using an independent decomposition target unit as a calculation unit, the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve in the drug release event sequence corresponding to the decomposition target unit is calculated. The values ​​of each variable to be optimized are updated in the direction of reducing the deviation until the deviation converges to the preset deviation threshold range.

[0010] Furthermore, the spatial distribution concentration of the drug within the needle body specifically refers to the concentration gradient distribution of the drug along the axial direction of the needle body; During the inversion solution process, the spatial distribution concentration of the drug in the needle body and the degradation rate constant of the needle matrix material are adjusted first. When adjusting these two parameters alone cannot bring the deviation to the preset deviation threshold range, the geometric parameters of the needle body are then adjusted.

[0011] Furthermore, when calculating the deviation, the iterative optimization algorithm assigns a higher weight coefficient to the peak rate and peak time of each drug release peak than to other time periods, so that the microneedle population corresponding to the manufacturing parameters obtained by inversion will preferentially fit the peak rate and peak time defined in the drug release event sequence.

[0012] Furthermore, the mechanical simulation verification refers to the pre-construction or invocation of a skin mechanical simulation model that matches the skin characteristics of the target user. This skin mechanical simulation model defines at least the elastic modulus and stratum corneum thickness of the skin. The skin mechanical simulation model takes the needle geometry parameters and mechanical properties of the needle matrix material of the microneedle population as inputs, and the buckling critical load and fracture critical stress corresponding to the microneedle population as output variables. The needle geometry parameters and mechanical properties of the needle matrix material of each microneedle population obtained by inversion are input into the skin mechanics simulation model to simulate the mechanical behavior of the microneedle population when it is vertically inserted into the skin, so as to verify whether its output variables exceed the corresponding preset maximum threshold. If any microneedle population fails the mechanical simulation verification, the following closed-loop correction process will be executed: Prioritize adjusting the needle geometry parameters of this microneedle population. If adjusting the needle geometry parameters alone cannot make it pass the mechanical simulation verification, then select from the preset material database a replacement material with higher mechanical strength than the current material and a degradation rate constant that is closest to the degradation rate constant obtained from the current inversion as the newly determined needle matrix material type. The adjusted needle geometry parameters or the newly determined needle matrix material type are used as the changed constraints of the manufacturing parameters and fed back into the inversion solution process. Under the condition that the constraints are met, the parameter inversion is re-executed until the deviation between the newly generated set of curves and the target drug release curve meets the preset deviation threshold range. All microneedle populations have been verified through mechanical simulation, and the manufacturing parameters corresponding to each microneedle population at this time are used as the final manufacturing parameters.

[0013] Furthermore, the microneedle array spatial arrangement rule refers to determining the arrangement area ratio and spatial position of the microneedle population corresponding to the drug release peak on the microneedle patch based on the peak rate and duration in the drug release event sequence corresponding to each drug release peak.

[0014] Furthermore, the specific details for determining the layout area ratio are as follows: Obtain the peak rate and duration of each drug release peak, and calculate the total amount of drug released for that peak. The microneedle unit drug release model is invoked to calculate the amount of drug released per unit of a single microneedle in the microneedle population corresponding to the peak drug release; The total number of microneedles required for this microneedle population is determined based on the total drug release and the drug release per unit. Based on the total number of microneedles and the total area of ​​the microneedle patch, determine the distribution area ratio of the microneedle population on the microneedle patch.

[0015] The present invention also provides a microneedle patch customization management system, which is used to implement the above-mentioned microneedle patch customization management method, including: The drug release curve parsing module is used to acquire the target drug release curve, identify feature points of the target drug release curve, and analyze the temporal sequence of the feature points to form a drug release event sequence of the target drug release curve. The drug release event sequence includes the start time, peak time, peak rate and duration of each drug release peak. The drug release curve decomposition module is used to call the pre-built microneedle unit drug release model and decompose the target drug release curve into several basic release curves based on the drug release event sequence. Each basic release curve corresponds to a microneedle population. The manufacturing parameter inversion solution module is used to invert and solve the manufacturing parameters of each microneedle population with the goal of minimizing the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve. The manufacturing parameters include needle geometric parameters and the degradation rate constant of the needle matrix material. The simulation verification and correction module is used to input the manufacturing parameters of each microneedle population obtained by inversion into the skin mechanics simulation model and perform mechanical simulation verification of the process of each microneedle piercing the skin. If any microneedle population fails the mechanical simulation verification, the manufacturing parameters of the microneedle population are adjusted and the adjusted manufacturing parameters are fed back to step 3 to re-invert and solve until the mechanical simulation verification is passed. The microneedle array arrangement generation module is used to calculate the number of microneedles required for each microneedle population based on the drug release event sequence corresponding to each microneedle population verified by mechanical simulation, and to determine the arrangement area ratio and spatial position of each microneedle population on the microneedle patch based on the number of microneedles, thereby generating a set of manufacturing parameters containing the spatial arrangement rules of the microneedle array.

[0016] Compared with the prior art, the technical effects and advantages provided by the present invention are as follows: This invention starts with the target drug release curve, which contains complex forms such as multi-peaks and plateau peaks. Through the automatic identification and decomposition of feature points, it achieves accurate digital analysis of any complex prescription requirements, and solves the defect of existing technologies that can only roughly control the total dose and cannot fit multi-peak time-series curves.

[0017] This invention can also automatically solve a set of manufacturing parameters including needle geometry, matrix material degradation rate and drug spatial distribution concentration, so that the final superimposed release curve can faithfully reproduce each peak height, peak position and peak width defined by the prescription, truly realizing precise drug delivery for each individual.

[0018] This invention actively introduces individualized mechanical constraints such as skin elastic modulus and stratum corneum thickness during the inversion solution process, and adopts a hierarchical correction strategy of first adjusting geometric parameters and then modifying matrix materials. This ensures that the final set of manufacturing parameters can not only meet the complex timing release requirements, but also reliably penetrate the skin of the target user without bending or breaking. This eliminates the pain points of repeated trial and error and parameter conflicts in the traditional serial process, and provides a complete technical solution for the manufacturing of personalized microneedle patches. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a schematic diagram comparing the effects of different spatial distribution concentrations of drugs on the drug release curve in this invention; Figure 3 This is a schematic diagram comparing the effects of different degradation rate constants on the drug release curve in this invention; Figure 4 This is a schematic diagram comparing the effects of different needle geometry parameters on the drug release curve in this invention; Figure 5 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0021] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0022] Example: Please see Figures 1 to 4 The present invention provides a technical solution: A method for customizing and managing microneedle patches, comprising the following steps: Step 1: Obtain the target drug release curve and identify feature points on the target drug release curve. Analyze the temporal sequence of the feature points to form a drug release event sequence for the target drug release curve. The drug release event sequence includes the start time, peak time, peak rate, and duration of each drug release peak.

[0023] The target drug release curve can be directly determined by in vitro release assays or obtained by deconvolution of in vivo blood drug concentration data based on a pharmacokinetic model. After obtaining the target drug release curve, it is preprocessed, including removing baseline drift and random noise, for example, by using moving average filtering or multinomial smoothing filtering; if the original sampling time interval is not uniform, it is first interpolated into a uniform time series, and the interpolation time interval can be 1 minute to 10 minutes; the preprocessed curve is used for subsequent feature point identification.

[0024] In this embodiment, the target drug release curve contains multiple time-independent drug release peaks, and each drug release peak corresponds to a postprandial blood glucose control requirement.

[0025] There is usually an interval between two adjacent drug release peaks where the release rate is lower than the preset onset threshold, to ensure that each peak is independent of each other in time. If adjacent peaks do not drop below the preset onset threshold, they are considered to overlap and curve separation or merging is required.

[0026] The feature points include start time, peak time, and end time. Feature point identification of the target drug release curve is specifically performed as follows: Scan the target drug release curve, locate the time point when the release rate first exceeds the preset onset threshold as the start time of the drug release peak, locate the inflection point when the release rate changes from rising to falling as the peak time, record the value of the release rate at the inflection point as the peak rate, and locate the time point when the release rate falls back below the preset onset threshold as the end time. The duration is obtained from the difference between the end time and the start time.

[0027] The preset onset threshold can be set to 5% to 20% of the maximum peak rate in the target drug release curve, preferably 10%. The preset onset threshold should be significantly higher than baseline noise and measurement fluctuations. Typically, baseline noise should not exceed 5% of the maximum peak rate, while setting it below 20% avoids missing low-amplitude but clinically significant release peaks. Generally, baseline data under blank or zero-release conditions can be collected, and the mean and standard deviation of the baseline can be calculated. The preset onset threshold is set as the baseline mean plus three times the standard deviation; if this value is lower than 5% of the maximum peak rate, then 5% is used; if this value is higher than 20% of the maximum peak rate, then 20% is used. The scan step size can be the preprocessed time interval, for example, 1 minute to 10 minutes.

[0028] When the release rate corresponding to the peak time is maintained at the peak rate for a duration exceeding a preset time threshold, the drug release peak is determined to be a plateau peak and is divided into two consecutive sub-peaks. The drug release event sequence of each sub-peak is then redefined.

[0029] The duration during which the release rate remains at the peak rate refers to the length of time during which the release rate is not less than 90% of the peak rate; this 90% is the fluctuation tolerance ratio. The fluctuation tolerance ratio can be determined based on the measurement accuracy, with 95% for high measurement accuracy and 85% for low measurement accuracy. The preset time threshold can be between 0.5 hours and 2 hours, preferably 1 hour. The rationale for this value is that plateau peaks with a duration of less than 0.5 hours do not need to be split, as their shape can still be approximated by subsequent single-peak basic release curves; however, peaks exceeding 2 hours are difficult to fit with single-peak basic release curves and need to be split. Generally, the preset time threshold is determined based on the single-peak width capability of the basic release curve in subsequent decomposition steps. The narrower the half-peak width of the basic release curve, the smaller the preset time threshold should be. During splitting, the original peak is split into two consecutive sub-peaks at the midpoint of the plateau duration period, based on the start and end times of the plateau duration period; or the splitting point is determined based on the principle of equal release amount, ensuring that the sum of the total drug release of the two sub-peaks is the same as the original plateau peak. After splitting, for each sub-peak, its feature points are re-determined according to the above-mentioned identification method of start time, peak time, and end time.

[0030] The drug release event sequence is organized with a single drug release peak as an independent unit, and the sub-peaks after being split are regarded as two independent drug release peaks in the drug release event sequence.

[0031] The drug release event sequence can be stored in chronological order. Each drug release peak or sub-peak is an entry, and the entry must include at least the start time, peak time, peak rate, duration, and corresponding event number.

[0032] Step 2: Call the pre-built microneedle unit drug release model, and decompose the target drug release curve into several basic release curves according to the drug release event sequence. Each basic release curve corresponds to a microneedle population.

[0033] The microneedle unit drug release model is pre-constructed, and its construction method includes: taking a single microneedle as the object, establishing a drug release kinetic equation based on the needle's geometric parameters, the degradation rate constant of the needle matrix material, and the spatial distribution concentration of the drug within the needle, and obtaining the unit-time release rate curve of the single microneedle under any given manufacturing parameters through numerical solution or analytical approximation. Step 2 calls this model only to generate a single-peak release curve shape that matches each drug release peak, serving as the basic release curve corresponding to that drug release peak, and does not directly determine the final manufacturing parameters; each basic release curve is subsequently assigned to a microneedle population and serves as the target curve for inversion solution in step 3.

[0034] For example, a microneedle unit drug release model can take the following form: The drug release rate is determined by both the degradation of the needle matrix and drug diffusion, and can be expressed by the following formula: in, For the release rate, The drug diffusion coefficient, The surface area of ​​the needle. For local concentration gradients, This is the matrix degradation rate constant. The remaining amount of drug in the needle body; wherein the concentration distribution of the drug along the needle body axis is given as a function of the drug concentration along the needle body axis as defined in step 3.

[0035] This model can be solved numerically using the finite difference method or the finite element method. Alternatively, empirical release equations, such as the Korsmeyer-Peppas equation or the Higuchi equation, can be used, as long as a single-peak release curve can be output based on the manufacturing parameters.

[0036] In this embodiment, the manufacturing parameters also include the spatial distribution concentration of the drug within the needle body, and the parameters associated with the microneedle unit drug release model include the needle body geometric parameters, the degradation rate constant of the needle body matrix material, and the spatial distribution concentration of the drug within the needle body.

[0037] The needle geometry parameters include at least one of the following: needle length, base diameter, tip diameter, cone angle, needle shape, and surface microstructure dimensions. The degradation rate constant of the needle matrix material can be a first-order degradation rate constant. The spatial distribution concentration of the drug within the needle refers to the concentration distribution function of the drug along the needle axis, which can be represented by discrete nodal concentration values ​​or by a parameterized function, such as a linear gradient, exponential gradient, or Gaussian distribution. The microneedle unit drug release model receives the above parameters and outputs a time series of the release rate of a single microneedle within a specified time period.

[0038] Each drug release peak in the drug release event sequence is used as an independent decomposition target unit, so that the total number of the decomposed basic release curves is consistent with the total number of drug release peaks.

[0039] The time range of each decomposition target unit is limited to the start and end time of the drug release peak. Within this time range, the target drug release curve only includes the contribution of that peak. Since each drug release peak is independent of each other in time, the decomposition can be performed one peak at a time in chronological order, and there is no overlap between the decomposition target units. For the sub-peaks obtained after the plateau peak is split in step 1, they are also treated as independent decomposition target units.

[0040] The decomposition employs a non-negative matrix factorization algorithm, and constrains the peak time of each decomposed basic release curve to remain within a preset deviation range from the peak time of the corresponding drug release peak.

[0041] In practice, the target drug release curve and each candidate basic release curve are first discretized into non-negative time series with the same time step. The candidate basic release curves consist of a set of single-peak curves generated by the microneedle unit drug release model within a preset parameter range, with each candidate curve corresponding to a decomposition target unit. The objective function of the non-negative matrix factorization algorithm is to minimize the mean square error between the weighted superposition result of the target drug release curve and each basic release curve, and a peak time deviation penalty term is added. Since each drug release peak is independent in time, after decomposition, each drug release peak is contributed only by its corresponding basic release curve. Therefore, only one element in the weight vector is 1, and the rest are 0, thus ensuring that the total number of basic release curves is consistent with the total number of drug release peaks.

[0042] The preset deviation range for the peak release time deviation can be ±10 minutes to ±30 minutes, preferably ±15 minutes. The rationale for this value is that this deviation range is smaller than the time scale of the rising or falling phase of the drug release peak, preventing misalignment of the release peak, while also avoiding overly strict constraints that prevent decomposition. Generally, it is taken as 3 to 5 times the sampling interval of the target drug release curve, or 10% to 20% of the time of the rising phase of the drug release peak.

[0043] The iterative solution of nonnegative matrix factorization can be achieved using alternating least squares or multiplicative update rules. The maximum number of iterations can be set to 500 to 2000, and the convergence condition is that the change in the objective function value between two consecutive iterations is less than 0.1%. In addition, a smoothing regularization term can be added, with a regularization coefficient of 0.01 to 0.1, to avoid unreasonable oscillations in the basic release curve.

[0044] Step 3: With the goal of minimizing the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve, the manufacturing parameters of each microneedle population are solved by inversion. The manufacturing parameters include the needle geometry parameters and the degradation rate constant of the needle matrix material.

[0045] The deviation can be quantified using root mean square error (RMSE) or mean absolute percentage error (MAS). The preset deviation threshold range can be set to a RMSE less than or equal to 10% of the maximum peak rate in the target drug release curve, or an MAS less than or equal to 5%. This ensures that when the RMSE of the release curve does not exceed 10% of the maximum peak rate, the cumulative drug release error can be controlled within a clinically acceptable dose deviation range. Generally, the allowable upper limit of release rate error is derived from the clinically effective dose range of the drug corresponding to the target drug release curve, serving as the deviation threshold.

[0046] In this embodiment, each basic release curve is assigned to an independent microneedle population, which corresponds to a microneedle array region on the microneedle patch. All microneedles in the microneedle array region have the same manufacturing parameters.

[0047] A non-microneedle isolation zone or physical partition can be set on the microneedle patch substrate between array areas of different microneedle populations to prevent uncontrolled cross-diffusion of drugs released by different populations within the skin. The number of microneedle populations is consistent with the total number of baseline release curves, typically 1 to 5, preferably 1 to 3.

[0048] Using the manufacturing parameters as variables to be optimized, an iterative optimization algorithm is adopted. In each iteration, the microneedle unit drug release model is called to generate a basic release curve. Using an independent decomposition target unit as a calculation unit, the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve in the drug release event sequence corresponding to the decomposition target unit is calculated. The values ​​of each variable to be optimized are updated in the direction of reducing the deviation until the deviation converges to the preset deviation threshold range.

[0049] The needle's geometric parameters, the degradation rate constant of the needle matrix material, and the spatial distribution concentration of the drug within the needle are all considered as variables to be optimized. The iterative optimization algorithm can be one of the following: gradient descent, quasi-Newton method, genetic algorithm, particle swarm optimization algorithm, or simulated annealing algorithm; preferably, a constrained sequential quadratic programming method or interior point method is used to handle the constraints on the range of manufacturing parameters.

[0050] The value ranges of each variable to be optimized are limited according to the actual manufacturing process: In the needle geometry parameters, the needle length ranges from 50 micrometers to 1500 micrometers, the base diameter ranges from 50 micrometers to 500 micrometers, and the tip diameter ranges from 1 micrometer to 100 micrometers; the degradation rate constant of the needle matrix material ranges from 0.001 / hour to 1 / hour; the range of the spatial distribution concentration of the drug within the needle body is determined based on the drug loading capacity and saturated solubility of the needle matrix material. For example, when using discrete segments, the drug concentration in each segment ranges from 0 to the saturated solubility of the drug in the matrix material at the corresponding position of that segment, and the total drug loading of all segments does not exceed 50% of the total mass of the needle matrix material; when using a parameterized function, the spatial distribution concentration of the drug within the needle body can be specifically described by any of the following functional forms: Linear gradient distribution: positioning the needle body along the axial direction ( Indicates the tip of a needle. Indicates the base of the needle body. Drug concentration at the needle length Defined as ,in, This refers to the drug concentration at the needle tip. This is the concentration change rate coefficient. When... The concentration of the drug increases towards the base, when The concentration increases towards the needle tip. The preferred value range is -0.5 to 0.5, in order to balance the burst release requirement in the initial stage and the sustained release capability in the later stage; Exponential decay / growth distribution: defined as ,in, The attenuation index is preferably in the range of -5 to 5, and is used to simulate the nonlinear distribution of the drug due to diffusion and migration during the solidification process of the needle. Gaussian local distribution: defined as ,in, Location of drug enrichment center For the distribution width parameter, The value range is 0 to , The range of values ​​is to It is used to achieve pulsed release at a specific time point.

[0051] The specific values ​​of the above parameters are used as variables to be optimized in the inversion solution process of step 3. Their initial values ​​can be preset according to the drug loading capacity and saturated solubility of the needle matrix material, and adjusted within the above value range during the optimization iteration.

[0052] Initial values ​​can be selected from a pre-set manufacturing parameter database, using intermediate or commonly used values. The initial value for the spatial distribution concentration of the drug can be an intermediate value from a uniform distribution or a linear gradient distribution. Since each decomposition target unit is independent in time, iterative optimization can be performed separately for each decomposition target unit, i.e., the manufacturing parameters of the corresponding microneedle population are inverted individually. Within the time range of a single decomposition target unit, the release contribution of other microneedle populations is approximately zero; therefore, the set of superimposed curves simplifies to the basic release curve corresponding to that microneedle population. In each iteration, a basic release curve is generated based on the current manufacturing parameters using the microneedle unit drug release model. The weighted deviation between this curve and the target drug release curve within the time range of that decomposition target unit is calculated. Then, the manufacturing parameters are updated using the selected optimization algorithm until the deviation is less than a preset deviation threshold or the maximum number of iterations is reached. The maximum number of iterations can be between 200 and 1000. Convergence conditions may also include a deviation change of less than 0.1% between two adjacent iterations.

[0053] In this embodiment, the spatial distribution concentration of the drug within the needle body specifically refers to the concentration gradient distribution of the drug along the axial direction of the needle body. This concentration gradient distribution can be described parametrically, for example, by dividing the needle body along the axial direction into 3 to 10 equal segments, with the drug concentration in each segment as an independent variable; or by using a linear gradient function, an exponential decay function, or a Gaussian distribution function, with the function parameters as variables to be optimized. Generally, the distribution type is selected based on the peak shape characteristics of the target release curve. A peak-shaped release corresponds to the drug being concentrated at the needle tip, while a sustained-release plateau-shaped release corresponds to the drug being evenly distributed along the axial direction of the needle body or distributed near the base.

[0054] During the inversion solution process, the spatial distribution concentration of the drug in the needle body and the degradation rate constant of the needle matrix material are adjusted first. When adjusting these two parameters alone cannot bring the deviation to the preset deviation threshold range, the geometric parameters of the needle body are then adjusted.

[0055] In practice, the inversion process is divided into two stages: In the first stage, only the spatial distribution concentration of the drug and the degradation rate constant are used as variables to be optimized, while the needle geometry parameters remain at their initial preset values. If the deviation still exceeds the preset deviation threshold after the first stage, the process proceeds to the second stage, where the needle geometry parameters are also added as variables to be optimized for further iteration. The rationale for this approach is that adjusting the needle geometry parameters alters the mechanical properties and skin penetration ability of the microneedle, and unnecessary changes should be avoided as much as possible; while the drug distribution and degradation rate constant significantly affect the release curve, and their adjustment does not affect the mechanical properties. A general determination method is as follows: if the deviation in the first stage does not converge within the preset maximum number of iterations, it is determined that the needle geometry parameters need to be adjusted.

[0056] In this embodiment, under the condition of keeping other variables fixed, single-factor comparative simulation experiments were conducted on the spatial distribution concentration of the drug within the needle, the degradation rate constant of the needle matrix material, and the geometric parameters of the needle. The spatial distribution concentration of the drug was set to three typical distribution patterns: tip enrichment, uniform distribution, and matrix enrichment; the degradation rate constant was set to a high value (0.15). ), Middle (0.08) Low (0.03) Three levels; the needle geometry parameters are adjusted by changing the needle base diameter to control the needle's slenderness ratio, corresponding to three configurations: thin needle, standard needle, and thick needle. The simulation is based on a single microneedle drug release kinetic model. Generate, time range is 0 The sampling time was 12 hours, with a step size of 0.4 hours, and a total of 31 sampling points. The simulated drug release rate data for each of the three parameters at three different levels are shown in Table 1 below: Table 1: Example table comparing the effects of three manufacturing parameters on drug release profiles: Based on the data in Table 1 above, Figures 2 to 4 It can be seen that, in the spatial distribution concentration data of the drug, the peak time of the drug release curve in the needle tip enrichment mode (A1) is about 3.2 h, and the peak rate is about 110; the peak time of the uniform distribution mode (A2) is about 4 h, and the peak rate is about 100; and the peak time of the base enrichment mode (A3) is about 5 h, and the peak rate is about 85. The three curves differ in peak time by about 1.8 h and peak rate by about 25, and the peak shape gradually becomes wider (A3) from sharp (A1). This indicates that the concentration gradient distribution of the drug along the needle axis has a significant regulatory ability on the peak time and peak shape of the drug release curve.

[0057] In the matrix degradation rate constant dataset, the peak time for the high degradation rate (B1) curve was approximately 3 hours, with a peak rate of approximately 120; the peak time for the medium degradation rate (B2) curve was approximately 4 hours, with a peak rate of approximately 100; and the peak time for the low degradation rate (B3) curve was approximately 5.5 hours, with a peak rate of approximately 70. The three curves differed by approximately 2.5 hours in peak time and approximately 50 in peak rate. Furthermore, the low degradation rate curve still maintained a release margin of approximately 24.4 after 12 hours, indicating that the degradation rate constant not only determines the release rate but also significantly affects the total drug release duration and peak position.

[0058] Among the needle geometry parameters, the differences in peak time between the three curves of the fine needle (C1), standard needle (C2), and coarse needle (C3) do not exceed 0.4 h, and the differences in peak rate do not exceed ±5. The three curves almost overlap, indicating that under the same drug distribution and degradation rate conditions, the direct influence of needle geometry parameters (base diameter) on the drug release curve is much smaller than that of the former two.

[0059] A comprehensive comparison of the three subplots reveals that the spatial distribution concentration of the drug and the matrix degradation rate constant all have a significant order of magnitude impact on the peak position, peak value, and peak shape of the drug release curve (the peak value can vary by up to 25%). 50, peak time offset can reach 1.8. The 2.5h adjustment handle is an efficient adjustment handle for inverting and fitting the target drug release curve; while the perturbation amplitude of the drug release curve by the needle geometry parameters is less than one-fifth of the former two, but it plays a decisive role in the mechanical properties (buckling critical load and fracture critical stress) of the microneedle piercing the skin.

[0060] The above comparative results also quantitatively demonstrate the rationality of the inversion strategy in this embodiment, which requires adjusting the spatial distribution concentration and the degradation rate constant of the needle matrix material first. During the inversion process, the two parameters with the strongest ability to control the drug release curve (drug distribution and degradation rate) should be prioritized to achieve accurate fitting of the drug release curve. Geometric parameters that directly affect mechanical performance should be reserved as a margin for adjustment to ensure mechanical safety, and only adjusted when the drug release fitting fails to meet the requirements. This hierarchical optimization strategy avoids blindly adjusting geometric parameters in the early stages of inversion, which could compromise the reliability of microneedle insertion. It ensures that the drug release performance design and mechanical reliability design converge synergistically during the inversion stage, thereby guaranteeing that the final output manufacturing parameter set can accurately reproduce the target drug release curve and ensure reliable microneedle insertion into the target user's skin.

[0061] In this embodiment, when calculating the deviation, the iterative optimization algorithm assigns a higher weight coefficient to the peak rate and peak time of each drug release peak than to other time periods, so that the microneedle population corresponding to the manufacturing parameters obtained by inversion will preferentially fit the peak rate and peak time defined in the drug release event sequence.

[0062] The weighting coefficients can be set to 5 to 20 for time points near the peak rate and peak time, and 1 for other time points. For example, within a 10-minute time window before and after the peak time, the weighting coefficient is set to 10, and the weighting coefficient for other time points is set to 1. The rationale for this setting is that the peak rate and peak time directly affect the maximum exposure level and onset time of the drug, which are crucial to the therapeutic effect and safety, and the fitting accuracy needs to be prioritized; while small deviations in other time periods can be compensated for by adjusting the number of microneedles in subsequent steps. A general method for determining the weighting coefficients is to determine the degree of influence of the peak characteristics on the objective function through sensitivity analysis. If the deviation of the peak rate or peak time has a significant impact on the efficacy, the weight of the corresponding time window is increased; alternatively, the weights can be set according to the clinically acceptable error range so that the peak error is amplified to the same order of magnitude as the total error.

[0063] Step 4: Input the manufacturing parameters of each microneedle population obtained from the inversion into the skin mechanics simulation model, and perform mechanical simulation verification of the process of each microneedle piercing the skin; if any microneedle population fails the mechanical simulation verification, adjust the manufacturing parameters of that microneedle population, and feed the adjusted manufacturing parameters back to Step 3 to re-invert and solve until the mechanical simulation verification is passed.

[0064] The mechanical simulation verification is performed after the inversion in step 3. The verification objects are the needle geometry parameters and mechanical properties of the needle matrix material corresponding to each microneedle population. If the mechanical simulation verification fails, only the microneedle population that failed the verification is adjusted, without affecting other microneedle populations that have passed the verification.

[0065] In this embodiment, the mechanical simulation verification refers to the pre-construction or invocation of a skin mechanical simulation model that matches the skin characteristics of the target user. The skin mechanical simulation model defines at least the elastic modulus and stratum corneum thickness of the skin. The skin mechanical simulation model takes the needle geometry parameters and mechanical properties of the needle matrix material of the microneedle population as inputs, and the buckling critical load and fracture critical stress corresponding to the microneedle population as output variables.

[0066] The skin mechanics simulation model can be constructed using the finite element method, simplifying the skin into a three-layer structure: stratum corneum, active epidermis, and dermis. The reference values ​​for stratum corneum thickness are 10 to 40 micrometers, active epidermis thickness is 50 to 150 micrometers, and dermis thickness is 1 to 3 millimeters. The reference values ​​for stratum corneum elastic modulus are 10 to 1000 MPa, and for dermis elastic modulus are 0.1 MPa to 10 MPa, with specific values ​​determined based on the target user's skin location, age, and stratum corneum condition. The mechanical properties of the needle matrix material include elastic modulus, Poisson's ratio, yield strength, and fracture strength. Elastic modulus and Poisson's ratio are used for linear elasticity analysis, while yield strength and fracture strength are used to determine whether the material undergoes plastic deformation or fracture. The buckling critical load is determined by simulating the axial compressive force during lateral buckling instability of the microneedle under vertical pressure. The fracture critical stress is determined by monitoring the maximum equivalent stress within the needle during insertion and combining it with the fracture strength of the needle matrix material.

[0067] The needle geometry parameters and mechanical properties of the needle matrix material of each microneedle population obtained by inversion are input into the skin mechanics simulation model to simulate the mechanical behavior of the microneedle population when it is vertically inserted into the skin, so as to verify whether its output variables exceed the corresponding preset maximum threshold.

[0068] During simulation, microneedles are placed above the skin surface, and a downward displacement load is applied at a speed of 0.01 mm / s to 10 mm / s, preferably 0.1 mm / s to 1 mm / s, to simulate the process from contact with the skin surface to the needle tip penetrating the superficial dermis. During verification, the simulated buckling critical load and fracture critical stress are compared with their respective safety thresholds; if either value is lower than its safety threshold, the microneedle population is deemed to have failed the mechanical simulation verification.

[0069] In this embodiment, the preset maximum threshold refers to the lower limit of the safety threshold: the safety threshold for the buckling critical load can be taken as 2 to 3 times, preferably 2.5 times, the maximum puncture force required for the microneedle population during vertical skin insertion; the safety threshold for the fracture critical stress can be taken as 1.5 to 2.5 times, preferably 2 times, the yield strength of the needle matrix material. The rationale for these values ​​is that individual differences and testing errors exist in skin mechanical properties, and the safety factor can cover dynamic load fluctuations and local stress concentrations during insertion. Generally, the maximum puncture force of the target user's skin is first obtained through ex vivo skin puncture experiments or preliminary finite element simulations. The sum of the average value and standard deviation is taken as the required maximum puncture force, and then multiplied by the safety factor. The fracture safety threshold is determined by dividing the lower confidence limit of the yield strength by the safety factor based on the mechanical test data of the needle matrix material.

[0070] If any microneedle population fails the mechanical simulation verification, the following closed-loop correction process will be executed: Prioritize adjusting the needle geometry parameters of this microneedle population. If adjusting the needle geometry parameters alone cannot make it pass the mechanical simulation verification, then select a replacement material from the preset material database that has higher mechanical strength than the current material and whose degradation rate constant is closest to the degradation rate constant obtained by the current inversion as the newly determined needle matrix material type.

[0071] Specific methods for prioritizing the adjustment of needle geometry parameters include: increasing the needle base diameter, decreasing the needle aspect ratio, increasing the needle tip cone angle, shortening the needle length, or increasing the needle cross-sectional moment of inertia. If, through the above adjustments, the simulated buckling critical load and fracture critical stress are not lower than their respective safety thresholds, then the mechanical simulation verification is considered successful. If the verification still fails after adjustment, material replacement is triggered. The preset material database contains at least the type, elastic modulus, yield strength, fracture strength, degradation rate constant, and biocompatibility level of each candidate material; commonly used candidate materials include polylactic acid, polylactic acid-glycolic acid copolymer, polyvinyl alcohol, hyaluronic acid, and their blends. When screening alternative materials, first screen candidate materials whose yield strength and fracture strength are not lower than 1.1 times the corresponding values ​​of the current material; then sort them in ascending order according to the absolute value of the deviation between the degradation rate constant of the candidate material and the degradation rate constant of the current material, and prioritize the one with the smallest deviation. The allowable range of degradation rate constant deviation can be no more than 20% of the current value, preferably 10%, to ensure that the influence of the alternative material on the drug release curve is as small as possible.

[0072] The rationale for prioritizing the adjustment of needle geometry parameters lies in the fact that these parameters directly determine the buckling critical load and fracture critical stress of the microneedle. Increasing the base diameter, decreasing the aspect ratio, or increasing the tip cone angle can effectively improve mechanical strength. Furthermore, the impact of these geometric adjustments on the drug release curve is mainly reflected in changes in the release area and diffusion path, which can be compensated for by re-optimizing the spatial distribution concentration and degradation rate constant of the drug within the needle in step 3, ensuring that the adjusted release curve still meets the target drug release requirements. Replacing the needle matrix material, in addition to altering mechanical properties, also changes the degradation rate constant and drug release behavior. Moreover, the available materials are limited by biocompatibility, degradation product safety, and drug compatibility; materials with higher mechanical strength and degradation rate constants close to the current material may not exist. Therefore, to minimize disturbances to drug release performance and avoid introducing additional constraints, we first attempt to adjust only the needle geometry parameters; only when the geometric parameter adjustments fail to meet mechanical safety requirements should the needle matrix material be replaced.

[0073] The adjusted needle geometry parameters or the newly determined needle matrix material type are used as modified constraints on the manufacturing parameters and fed back into the inversion solution process. Specifically, when the needle geometry parameters are adjusted, they are directly fed back into the inversion solution process as fixed constraints. When the needle matrix material type is changed, all parameters related to the new material in the microneedle unit drug release model (including but not limited to degradation rate constant, drug diffusion coefficient, and mechanical properties) must be updated synchronously first to ensure that the model can accurately reflect the drug release behavior of the new material. Then, the fixed degradation rate constant of the material is fed back into the inversion solution process as a constraint. Under the condition that this constraint is met, the parameter inversion is re-executed until the deviation between the newly generated curve set and the target drug release curve meets the preset deviation threshold range.

[0074] Once the needle geometry parameters are adjusted and verified through mechanical simulation, during the re-inversion in step 3, these parameters are fixed to the adjusted values. Only the spatial distribution concentration of the drug within the needle and the degradation rate constant of the needle matrix material are re-optimized. When the material type is replaced, the degradation rate constant of the new material is fixed to the known value of the new material, and the spatial distribution concentration of the drug and the needle geometry parameters are allowed to be re-optimized under the constraints of mechanical simulation verification. The termination condition for the re-inversion remains that the deviation between the newly generated curve set and the target drug release curve meets the preset deviation threshold range, which is the same as that used in step 3.

[0075] All microneedle populations have been verified through mechanical simulation, and the manufacturing parameters corresponding to each microneedle population at this time are used as the final manufacturing parameters.

[0076] If, after one round of closed-loop correction, there are still microneedle populations that fail the mechanical simulation verification, then the above adjustment-feedback-inversion process is repeated until all microneedle populations pass the mechanical simulation verification and the deviation between the curve set and the target drug release curve meets the preset deviation threshold range.

[0077] Step 5: Based on the drug release event sequence corresponding to each microneedle population verified by mechanical simulation, calculate the number of microneedles required for each microneedle population, and determine the arrangement area ratio and spatial position of each microneedle population on the microneedle patch according to the number of microneedles, and generate a set of manufacturing parameters containing the spatial arrangement rules of the microneedle array.

[0078] In this embodiment, the spatial arrangement rule of the microneedle array refers to determining the distribution area ratio and spatial position of the microneedle population corresponding to each drug release peak on the microneedle patch based on the peak rate and duration in the drug release event sequence corresponding to each drug release peak.

[0079] The spatial positioning principle is as follows: microneedle populations with high peak rates or large total drug release are preferentially placed in the central area of ​​the microneedle patch, while microneedle populations with low peak rates or small total drug release are placed in the peripheral area; a non-microneedle isolation zone is set between each microneedle population area, with a reference width of 0.5 mm to 2 mm, preferably 1 mm. The rationale for this arrangement is that the central area of ​​the microneedle patch has closer contact with the skin and a more uniform insertion depth, which is conducive to the stable release of drugs by populations with large release amounts; the width of the isolation zone can prevent lateral diffusion and crosstalk of different drug populations within the skin, and its general method is to estimate the diffusion distance based on the drug diffusion coefficient and release time, and take a safety factor of 2 to 3 times.

[0080] In this embodiment, the specific method for determining the layout area ratio is as follows: Obtain the peak rate and duration of each drug release peak, and calculate the total drug release required for that peak. The total drug release is equal to the peak rate of the drug release peak multiplied by the duration, and then multiplied by the peak shape factor. The peak shape factor is recommended to be between 0.3 and 0.7, preferably 0.5. This value is reasonable because the basic release curve obtained in step 2 is usually a single-peak curve, and its area is between the area of ​​a triangle and the area of ​​a rectangle, with a peak shape factor of 0.5 for triangles. A general method for determining the peak shape factor is to numerically integrate the basic release curve corresponding to the drug release peak in step 2 over the duration, and divide the integrated area by the product of the peak rate and the duration to obtain the peak shape factor of the drug release peak.

[0081] The microneedle unit drug release model is invoked to calculate the unit drug release amount per microneedle in the microneedle population corresponding to the drug release peak within a specified duration. The unit drug release amount is the cumulative release amount of a single microneedle simulated from the start time to the end time using the microneedle unit drug release model under the manufacturing parameters of the microneedle population finally determined in step 3. The duration is taken as the duration of the drug release peak. If the duration of the drug release peak exceeds the time range that the microneedle unit drug release model can simulate, it is calculated using model extrapolation and a conservative estimate is adopted.

[0082] The total number of microneedles required for this microneedle population is determined based on the total drug release and the drug release per unit. The total number of microneedles is equal to the total drug release divided by the drug release per unit, rounded up, and then multiplied by a redundancy factor. The reference value for the redundancy factor is 1 to 1.2, with a preferred value of 1.1. This value is reasonable because actual manufacturing and drug delivery processes may involve deviations in needle shaping, individual differences in skin penetration, and some microneedle insertion failures. The redundancy factor ensures that the actual total drug release is not less than the target total drug release. A general method for determining this value is based on the upper limit of the confidence interval of the microneedle insertion success rate and the in vitro-in vivo drug release correlation test for this microneedle population, typically not exceeding 1.2.

[0083] Based on the total number of microneedles and the total area of ​​the microneedle patch, determine the area ratio of the microneedle population on the microneedle patch. Specifically: first, determine the required array area of ​​the microneedle population based on the total number of microneedles and the base area occupied by a single microneedle. The base area occupied by a single microneedle is calculated as 1.5 to 3 times, preferably 2 times, the microneedle spacing of the needle base diameter. The maximum reference value for the microneedle array density is 100 to 1000 microneedles per square centimeter, preferably 300 microneedles. Then, divide the required array area by the total usable area of ​​the microneedle patch to obtain the area ratio of the microneedle population. The sum of the area ratios of all microneedle populations should not exceed 1. If it exceeds 1, prioritize reducing the redundancy coefficient, or return to step 3 to adjust the manufacturing parameters to reduce the total number of microneedles. The rationality of the maximum density of the microneedle array is that too low a density will lead to an excessively large microneedle patch size, while too high a density will increase skin puncture resistance and manufacturing difficulty. The general method for determining this density is based on the base strength of the microneedle patch, the required microneedle spacing, and the target user's skin's tolerance to puncture point density.

[0084] Please see Figure 5 The present invention also provides a microneedle patch customization management system, which is used to implement the above-mentioned microneedle patch customization management method, including: The drug release curve parsing module is used to acquire the target drug release curve, identify feature points of the target drug release curve, and analyze the temporal sequence of the feature points to form a drug release event sequence of the target drug release curve. The drug release event sequence includes the start time, peak time, peak rate and duration of each drug release peak. The drug release curve decomposition module is used to call the pre-built microneedle unit drug release model and decompose the target drug release curve into several basic release curves based on the drug release event sequence. Each basic release curve corresponds to a microneedle population. The manufacturing parameter inversion solution module is used to invert and solve the manufacturing parameters of each microneedle population with the goal of minimizing the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve. The manufacturing parameters include needle geometric parameters and the degradation rate constant of the needle matrix material. The simulation verification and correction module is used to input the manufacturing parameters of each microneedle population obtained by inversion into the skin mechanics simulation model and perform mechanical simulation verification of the process of each microneedle piercing the skin. If any microneedle population fails the mechanical simulation verification, the manufacturing parameters of the microneedle population are adjusted and the adjusted manufacturing parameters are fed back to step 3 to re-invert and solve until the mechanical simulation verification is passed. The microneedle array arrangement generation module is used to calculate the number of microneedles required for each microneedle population based on the drug release event sequence corresponding to each microneedle population verified by mechanical simulation, and to determine the arrangement area ratio and spatial position of each microneedle population on the microneedle patch based on the number of microneedles, thereby generating a set of manufacturing parameters containing the spatial arrangement rules of the microneedle array.

[0085] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0086] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0087] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for customized management of microneedle patches, characterized in that, The specific steps include: Step 1: Obtain the target drug release curve, identify feature points on the target drug release curve, and analyze the temporal sequence of the feature points to form a drug release event sequence of the target drug release curve. The drug release event sequence includes the start time, peak time, peak rate and duration of each drug release peak. Step 2: Call the pre-built microneedle unit drug release model, and decompose the target drug release curve into several basic release curves according to the drug release event sequence. Each basic release curve corresponds to a microneedle population. Step 3: With the goal of minimizing the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve, the manufacturing parameters of each microneedle population are solved by inversion. The manufacturing parameters include the needle geometry parameters and the degradation rate constant of the needle matrix material. Step 4: Input the manufacturing parameters of each microneedle population obtained from the inversion into the skin mechanics simulation model, and perform mechanical simulation verification of the process of each microneedle piercing the skin; if any microneedle population fails the mechanical simulation verification, adjust the manufacturing parameters of that microneedle population, and feed the adjusted manufacturing parameters back to Step 3 to re-invert and solve until it passes the mechanical simulation verification. Step 5: Based on the drug release event sequence corresponding to each microneedle population verified by mechanical simulation, calculate the number of microneedles required for each microneedle population, and determine the arrangement area ratio and spatial position of each microneedle population on the microneedle patch according to the number of microneedles, and generate a set of manufacturing parameters containing the spatial arrangement rules of the microneedle array.

2. The microneedle patch customization management method according to claim 1, characterized in that, The target drug release curve contains multiple time-independent drug release peaks, each corresponding to a postprandial blood glucose control requirement. The feature points include start time, peak time, and end time. Feature point identification of the target drug release curve is specifically performed as follows: Scan the target drug release curve, locate the time point when the release rate first exceeds the preset onset threshold as the start time of the drug release peak, locate the inflection point when the release rate changes from rising to falling as the peak time, record the value of the release rate at the inflection point as the peak rate, and locate the time point when the release rate falls back below the preset onset threshold as the end time. The duration is obtained from the difference between the end time and the start time. When the release rate corresponding to the peak time is maintained at the peak rate for a duration exceeding a preset time threshold, the drug release peak is determined to be a plateau peak and is divided into two consecutive sub-peaks. The drug release event sequence of each sub-peak is then re-determined. The drug release event sequence is organized with a single drug release peak as an independent unit, and the sub-peaks after being split are regarded as two independent drug release peaks in the drug release event sequence.

3. The microneedle patch customization management method according to claim 2, characterized in that, The manufacturing parameters also include the spatial distribution concentration of the drug within the needle body, and the parameters associated with the microneedle unit drug release model include the needle body geometric parameters, the degradation rate constant of the needle body matrix material, and the spatial distribution concentration of the drug within the needle body; Each drug release peak in the drug release event sequence is taken as an independent decomposition target unit, so that the total number of the decomposed basic release curves is consistent with the total number of drug release peaks. The decomposition employs a non-negative matrix factorization algorithm, and constrains the peak time of each decomposed basic release curve to remain within a preset deviation range from the peak time of the corresponding drug release peak.

4. The microneedle patch customization management method according to claim 3, characterized in that, Each basic release curve is assigned to an independent microneedle population, which corresponds to a microneedle array region on the microneedle patch, and all microneedles in the microneedle array region have exactly the same manufacturing parameters. Using the manufacturing parameters as variables to be optimized, an iterative optimization algorithm is adopted. In each iteration, the microneedle unit drug release model is called to generate a basic release curve. Using an independent decomposition target unit as a calculation unit, the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve in the drug release event sequence corresponding to the decomposition target unit is calculated. The values ​​of each variable to be optimized are updated in the direction of reducing the deviation until the deviation converges to the preset deviation threshold range.

5. The microneedle patch customization management method according to claim 4, characterized in that, The spatial distribution concentration of the drug within the needle body is specifically the concentration gradient distribution of the drug along the axial direction of the needle body. During the inversion solution process, the spatial distribution concentration of the drug in the needle body and the degradation rate constant of the needle matrix material are adjusted first. When adjusting these two parameters alone cannot bring the deviation to the preset deviation threshold range, the geometric parameters of the needle body are then adjusted.

6. The microneedle patch customization management method according to claim 4, characterized in that, When calculating the deviation, the iterative optimization algorithm assigns a higher weight coefficient to the peak rate and peak time of each drug release peak than to other time periods, so that the microneedle population corresponding to the manufacturing parameters obtained by inversion will preferentially fit the peak rate and peak time defined in the drug release event sequence.

7. The microneedle patch customization management method according to claim 2, characterized in that, The mechanical simulation verification refers to the pre-construction or invocation of a skin mechanical simulation model that matches the skin characteristics of the target user. The skin mechanical simulation model defines at least the elastic modulus and stratum corneum thickness of the skin. The skin mechanical simulation model takes the needle geometry parameters and mechanical properties of the needle matrix material of the microneedle population as inputs, and the buckling critical load and fracture critical stress corresponding to the microneedle population as output variables. The needle geometry parameters and mechanical properties of the needle matrix material of each microneedle population obtained by inversion are input into the skin mechanics simulation model to simulate the mechanical behavior of the microneedle population when it is vertically inserted into the skin, so as to verify whether its output variables exceed the corresponding preset maximum threshold. If any microneedle population fails the mechanical simulation verification, the following closed-loop correction process will be executed: Prioritize adjusting the needle geometry parameters of this microneedle population. If adjusting the needle geometry parameters alone cannot make it pass the mechanical simulation verification, then select from the preset material database a replacement material with higher mechanical strength than the current material and a degradation rate constant that is closest to the degradation rate constant obtained from the current inversion as the newly determined needle matrix material type. The adjusted needle geometry parameters or the newly determined needle matrix material type are used as the changed constraints of the manufacturing parameters and fed back into the inversion solution process. Under the condition that the constraints are met, the parameter inversion is re-executed until the deviation between the newly generated set of curves and the target drug release curve meets the preset deviation threshold range. All microneedle populations have been verified through mechanical simulation, and the manufacturing parameters corresponding to each microneedle population at this time are used as the final manufacturing parameters.

8. The microneedle patch customization management method according to claim 4, characterized in that, The microneedle array spatial arrangement rule refers to determining the area ratio and spatial position of the microneedle population corresponding to each drug release peak on the microneedle patch based on the peak rate and duration in the drug release event sequence corresponding to each drug release peak.

9. The microneedle patch customization management method according to claim 8, characterized in that, The specific method for determining the layout area ratio is as follows: Obtain the peak rate and duration of each drug release peak, and calculate the total amount of drug released for that peak. The microneedle unit drug release model is invoked to calculate the amount of drug released per unit of a single microneedle in the microneedle population corresponding to the peak drug release; The total number of microneedles required for this microneedle population is determined based on the total drug release and the drug release per unit. Based on the total number of microneedles and the total area of ​​the microneedle patch, determine the distribution area ratio of the microneedle population on the microneedle patch.

10. A microneedle patch customization management system, characterized in that, The aforementioned microneedle patch customization management system is used to implement the microneedle patch customization management method according to any one of claims 1-9, comprising: The drug release curve parsing module is used to acquire the target drug release curve, identify feature points of the target drug release curve, and analyze the temporal sequence of the feature points to form a drug release event sequence of the target drug release curve. The drug release event sequence includes the start time, peak time, peak rate and duration of each drug release peak. The drug release curve decomposition module is used to call the pre-built microneedle unit drug release model and decompose the target drug release curve into several basic release curves based on the drug release event sequence. Each basic release curve corresponds to a microneedle population. The manufacturing parameter inversion solution module is used to invert and solve the manufacturing parameters of each microneedle population with the goal of minimizing the deviation between the set of curves formed by superimposing the basic release curves and the target drug release curve. The manufacturing parameters include needle geometric parameters and the degradation rate constant of the needle matrix material. The simulation verification and correction module is used to input the manufacturing parameters of each microneedle population obtained by inversion into the skin mechanics simulation model and perform mechanical simulation verification of the process of each microneedle piercing the skin. If any microneedle population fails the mechanical simulation verification, the manufacturing parameters of the microneedle population are adjusted and the adjusted manufacturing parameters are fed back to step 3 to re-invert and solve until the mechanical simulation verification is passed. The microneedle array arrangement generation module is used to calculate the number of microneedles required for each microneedle population based on the drug release event sequence corresponding to each microneedle population verified by mechanical simulation, and to determine the arrangement area ratio and spatial position of each microneedle population on the microneedle patch based on the number of microneedles, thereby generating a set of manufacturing parameters containing the spatial arrangement rules of the microneedle array.

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