Individualized slow-release or quick-release oral preparation selection method and system

Abstract

The invention relates to an individualized slow-release or quick-release oral preparation selection method and system. According to the method, individual pharmacokinetic parameters of a patient are estimated based on group pharmacokinetic characteristics of drugs and clinical characteristic information of the patient, and a Monte Carlo method is creatively combined with a medicine taking behavior to simulate a blood concentration-time curve of a sustained-release or quick-release dosage form drug respectively; the target concentration standard-reaching rate of different dosage forms and the deviation time of the treatment window are estimated, clinical doctors can be helped to optimize the medication scheme design of patients, reliable guidance suggestions are provided, the treatment effect is improved, and adverse reactions are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of administration information processing, and relates to a method and system for selecting an individualized sustained-release or immediate-release oral preparation. Background Art

[0002] Medication compliance is one of the key factors for the success of drug treatment, which is the consistency between patients' taking medications and clinical prescriptions. In the real world, the phenomenon of non-compliance with medications is very common. According to literature reports, among adult patients with chronic diseases such as diabetes and hypertension, the proportion of those who do not take medications as prescribed is as high as 20 - 50%. Poor medication compliance is one of the main reasons leading to severe deterioration of diseases, death, and increased medical costs. Non-compliance is common, with a proportion ranging from 2% to 68%. Among various types of non-compliance behaviors, taking medications late or missing doses accounts for more than 50%.

[0003] One of the common strategies to improve drug compliance is to reduce the dosing frequency. Research shows that compared with the twice-daily dosing regimen, the once-daily dosing regimen can increase compliance by 10% on average. However, missing one dose in the QD dosing regimen is equivalent to missing 100% of the daily dose, and missing one dose in the BID or TID dosing regimen is equivalent to missing 50% and 33.3% of the daily dose respectively. Theoretically, missing 100% of the daily dose is expected to cause more significant fluctuations in the plasma concentration of the drug, leading to more severe clinical consequences. Another view is contrary to this, believing that sustained-release preparations are a way to reduce the impact of non-compliance on the plasma concentration of drugs. Due to the slower absorption rate, sustained-release preparations may maintain the plasma concentration of the drug at the therapeutic level for a long time.

[0004] Existing recommended dose methods based on population pharmacokinetic models usually rely on professional modeling software such as NONMEM, which is complex to operate and requires frequent modification of data files, making it difficult for non-professionals to use. In addition, these methods often rely on idealized medication scenarios and fail to consider the behavioral changes of patients in actual medication use (such as missing or taking medications late), deviating from the real clinical situation. (See the Chinese patent with the application number CN 116469514 A, which discloses "a method and system for optimizing antibacterial drug dosing regimens" and see the Chinese patent with the application number CN 114765076 A, which discloses "a method for calculating individualized fluconazole dosage for neonates and a dosing regimen recommendation system").

[0005] The present invention aims to evaluate the exposure of immediate-release and sustained-release dosage form drugs under non-compliant dosing behaviors and provide a reference for optimizing the selection of preparations. Summary of the Invention

[0006] The object of the present invention is to overcome the disadvantages and deficiencies of the prior art, and to provide a method and system for selecting individualized sustained-release or immediate-release oral preparations. Based on the population pharmacokinetic characteristics of drugs, combined with the clinical characteristic information and medication behavior of patients, the present invention estimates the target concentration attainment rate and the deviation time of the therapeutic window of different dosage forms, which can help clinicians optimize the design of patients' medication regimens and provide reliable guidance to improve the treatment effect and reduce the occurrence of adverse reactions.

[0007] The object of the present invention can be achieved by the following solutions:

[0008] In the first aspect, the present invention provides a method for selecting individualized sustained-release or immediate-release oral preparations, including the following steps:

[0009] S1. Collect the clinical characteristic information and medication behavior of patients;

[0010] S2. Use the population pharmacokinetic models of sustained-release and immediate-release dosage form drugs to process the clinical characteristic information in step S1 respectively, and estimate the individual pharmacokinetic parameters of patients;

[0011] S3. Based on the individual pharmacokinetic parameters in step S2 and the medication behavior in step S1, apply the Monte Carlo method to simulate the plasma concentration-time curves of sustained-release or immediate-release dosage form drugs respectively;

[0012] S4. Calculate the target concentration attainment rate and the deviation time of the therapeutic window of sustained-release or immediate-release dosage form drugs according to the plasma concentration-time curves;

[0013] S5. Select the dosage form with the highest target concentration attainment rate and the shortest deviation time of the therapeutic window as the best dosing regimen.

[0014] As an embodiment of the present invention, the method provides dosage form selection suggestions by developing an interactive web computing tool; the development of the interactive web computing tool is based on RxODE2 and Shiny of R software.

[0015] Furthermore, the developed interactive web computing tool includes a clinical characteristic information module, a medication information module, and an evaluation module; wherein the clinical characteristic information module and the medication-related information module are used for users to input patients' basic information, clinical characteristics, medication information, treatment range, and medication behavior; the evaluation module presents the calculation results of the target concentration attainment rate and the deviation time of the therapeutic window, and the plasma concentration-time curve in the form of charts.

[0016] As an embodiment of the present invention, in step S1, the clinical characteristic information includes one or more of basic information, clinical characteristics, medication information, and treatment range. Among them, the basic information includes one or more of age, weight, gender, transplantation type, and time after transplantation (POD); the clinical characteristics include one or more of estimated glomerular filtration rate (eGFR), liver function, total cholesterol content (Cholesterol), liver function, hematocrit (Haematocrit), haptoglobin content (Haptoglobin), aspartate aminotransferase content (AST), and albumin content (ALB); the medication information includes one or more of concomitant medications, medication regimens, and food intake; the medication regimen includes one or more of mycophenolic acid usage, dosage form selection, daily dose (Dose), and dosing interval.

[0017] As an embodiment of the present invention, in step S1, the medication-taking behaviors include one or more of taking medicine late and missing doses.

[0018] As an embodiment of the present invention, in step S2, the population pharmacokinetic model is specifically to conduct a systematic literature search on the population pharmacokinetic models of different dosage forms of the drug that have been published currently in medical databases such as PubMed, Web of Science, Embase, CNKI, and Wanfang Data, screen the population pharmacokinetic models of different dosage forms according to the principles of systematic evaluation, and obtain the population pharmacokinetic models of immediate-release dosage form and sustained-release dosage form drugs that meet the PRISMA principles for subsequent steps.

[0019] Furthermore, the population pharmacokinetic model includes the tacrolimus population pharmacokinetic model.

[0020] Even further, the calculation formulas for the individual pharmacokinetic parameters in the tacrolimus population pharmacokinetic model are as follows:

[0021] Apparent oral clearance CL = 257.6 × (Haematocrit / 39) 0.49 × (eGFR / 51) 0.07 ;

[0022] Apparent volume of distribution V = 213.2 × (Haptoglobin / 1.4) 0.13 ;

[0023] Bioavailability F of the immediate-release dosage form = 0.25 × (Dose / 2.5) -0.64 × (1 + e -0.32 × (POD / 1000));

[0024] Bioavailability F of the sustained-release dosage form = 0.25 × (Dose / 2.5)-0.62 ;

[0025] The maximum plasma concentration B bound to red blood cells max = 35.7×(Haematocrit / 39) -0.43 ×(Cholesterol / 4.6) -0.18 ×(Haptoglobin / 1.4) -0.05 ×1.14;

[0026] Absorption rate constant k a = 3.5 h -1 ;

[0027] Dissociation constant K d = 0.24 ng / mL;

[0028] Wherein, Haematocrit is the hematocrit, eGFR is the estimated glomerular filtration rate, Haptoglobin is the content of haptoglobin, Dose is the daily dose, POD is the time after transplantation, and Cholesterol is the total cholesterol content.

[0029] The units and formulas of the parameters of the tacrolimus population pharmacokinetic model of the present invention are specifically as follows in the table:

[0030]

[0031] In the above formula, Haematocrit is the hematocrit, eGFR is the estimated glomerular filtration rate, Haptoglobin is the content of haptoglobin, Dose is the daily dose, POD is the time after transplantation, Cholesterol is the total cholesterol content, BSV is the inter-individual variability, ka is the absorption rate constant, and Kd is the dissociation constant.

[0032] As an embodiment of the present invention, in step S2, the individual pharmacokinetic parameters include apparent oral clearance CL, apparent volume of distribution V, bioavailability F, the maximum plasma concentration B bound to red blood cells max , absorption rate constant k a , dissociation constant K d One or more of them.

[0033] As an embodiment of the present invention, in step S3, the number of simulations is 1000 times. That is, the Monte Carlo method is used to simulate the plasma concentration-time curve of patients taking sustained-release or immediate-release dosage forms of drugs 1000 times, and to simulate the time-course change and its variability of the plasma concentration in patients; among them, the variability includes inter-individual variability and intra-individual variability, and the common mathematical expression of inter-individual variability is the exponential model: P iThe pharmacokinetic parameters for individual i (such as clearance CL i ), P pop is the population mean (population median), η i is the random effect of individual i, assumed to follow a normal distribution with a mean of 0 and a variance of ω 2 . When calculating the magnitude of inter-individual variability, the coefficient of variation is usually used. When performing Monte Carlo simulation, intra-individual variability is generally handled with relatively small values, ≈0, such as: additive residuals set to 0.1 ng / m or proportional residuals of 1%.

[0034] As an embodiment of the present invention, in step S4, the calculation formula for the target concentration attainment rate is as follows:

[0035]

[0036] The calculation formula for the deviation time of the therapeutic window is as follows:

[0037] The deviation time DT (deviation time) of the therapeutic window = ∑ the time when the blood drug concentration is outside the therapeutic range.

[0038] Furthermore, the calculation of the target concentration attainment rate: Monte Carlo simulation generally simulates the blood drug concentrations of 1000 virtual patients. The percentage of the number of virtual patients with blood drug concentrations within the target range in the total number of virtual patients is the target concentration attainment rate;

[0039] The deviation time of the therapeutic window: The time when the pharmacokinetic curve formed by the median of the blood drug concentrations of the 1000 virtual patients simulated is outside the target range during the dosing period.

[0040] In the present invention, the target concentration attainment rate refers to the proportion of the blood drug concentration reaching the target concentration; the relative deviation time (i.e., the proportion of the time deviating from the therapeutic window) can be further normalized to the percentage of the deviation time of the therapeutic window in the total treatment time, that is, its calculation formula is as follows:

[0041]

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] 1. The present invention substitutes the clinical characteristic information of patients into the population pharmacokinetic model to estimate the individual pharmacokinetic parameters of patients, and creatively combines the medication-taking behaviors of patients to estimate the target concentration attainment rates and the time deviated from the treatment window of immediate-release dosage forms and sustained-release dosage forms of drugs, solving the limitations of empirically selecting drug dosage forms and the problem of being unable to scientifically quantify the impact of medication-taking behaviors on treatment effects. It can help clinicians optimize the design of patients' medication regimens, provide reliable guiding opinions, provide a basis for the rational selection of dosage forms, and make the treatment effects of patients more guaranteed.

[0044] 2. The present invention realizes a comprehensive assessment of patients' medication-taking behaviors and pharmacokinetic characteristics by developing an interactive visualization platform. This platform supports users to input dosage regimens, patient characteristics, treatment window ranges, actual medication records, etc. The platform completes the calculation of the target attainment rate and the deviation time within seconds, obtains a reasonable dosage form recommendation plan, and can greatly improve the efficiency of rational medication decision-making. Users can quickly obtain the blood drug concentration changes and index evaluation results under different medication-taking scenarios through this platform, providing a scientific basis for individualized dosage form selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objectives, and advantages of the present invention will become more obvious:

[0046] Figure 1 Flow chart for individualized selection of drug dosage forms;

[0047] Figure 2 Principle diagram for calculation of target attainment rate and deviation time;

[0048] Figure 3 Blood drug concentration-time curves after missing IR-T and ER-T within 0 - 3 months after transplantation;

[0049] Figure 4 Blood drug concentration-time curves after missing IR-T and ER-T within 4 - 6 months after transplantation;

[0050] Figure 5 Blood drug concentration-time curves after missing IR-T and ER-T within 7 - 12 months after transplantation;

[0051] Figure 6 Blood drug concentration-time curves after missing IR-T and ER-T within > 12 months after transplantation;

[0052] Figure 7 Target attainment rates of immediate-release dosage form and sustained-release dosage form tacrolimus after taking the drug late or missing the drug;

[0053] Figure 8For the deviation time of immediate-release and extended-release tacrolimus after a late or missed dose;

[0054] Figure 9 For an interactive web interface for individualized dosage form selection. Detailed implementation mode

[0055] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. The following examples are implemented on the premise of the technical solution of the present invention, providing detailed implementation modes and specific operation processes, which will help those skilled in the art to further understand the present invention. It should be noted that the protection scope of the present invention is not limited to the following embodiments. Several adjustments and improvements made under the premise of the concept of the present invention all fall within the protection scope of the present invention.

[0056] Example 1

[0057] In this embodiment, the method of the present invention is used to illustrate by taking the immunosuppressive drug tacrolimus as an example in the specific implementation process. Refer to Figure 1 The flow chart of individualized selection of drug dosage forms shown, and the specific process of implementing the dosage form selection for this drug is as follows:

[0058] Systematic literature search of the population pharmacokinetic models of immediate-release dosage form (IR-T) and extended-release dosage form of tacrolimus (ER-T), using "tacrolimus" or "Prograf" or "Astagraf" or "kidney transplant" and "population pharmacokinetics" or "pharmacokinetic modeling" or "nonlinear mixed effect model" or "NONMEM" or "Pmetrics" or "WINNONMIX" or "P-PHARM" or "nlmixed" or "NLME" or "MONOLIX" as search terms, and conducting literature searches in databases such as PubMed, Embase, and Web of Science. Finally, 3 studies on the population pharmacokinetic models of tacrolimus that met the inclusion criteria were included to provide support for the model construction of the present invention. When there are multiple eligible studies, preference is given to: prospective multi-center studies and studies including intensive sampling. The population pharmacokinetic model used in this example is shown in Table 1:

[0059] Table 1 Population pharmacokinetic models of immediate-release and extended-release tacrolimus

[0060]

[0061] In the above formula, BSV is the inter-individual variability, k aKa is the absorption rate constant, CL is the apparent oral clearance, V is the apparent volume of distribution, F is the bioavailability, and B max is the maximum plasma concentration bound to red blood cells, and K d is the dissociation constant, Haematocrit is the hematocrit, Haptoglobin is the haptoglobin, Dose is the tacrolimus dose, eGFR is the estimated glomerular filtration rate, POD is the number of days after surgery (i.e., the time after transplantation), and Cholesterol is the total cholesterol;

[0062] The basic information and clinical characteristics of the patients were collected. The patient information is as follows: 50 years old, 70 kg, eGFR of 49 mL / min / 1.73 m 2 , cholesterol of 4.7 mmol / L, hematocrit of 39.5%, haptoglobin of 1.5 g / L, the therapeutic range is 4 - 12 ng / mL, and the treatment regimens used at different times after transplantation are shown in Table 2 (i.e., including the time after transplantation and the tacrolimus dose):

[0063] Table 2 Medication regimens at different times after transplantation

[0064]

[0065] The mathematical expression of inter-individual variability is an exponential model: P i is the pharmacokinetic parameter of individual i (such as clearance CL i , etc.), P pop is the population mean (population median), η i is the random effect of individual i, assumed to follow a normal distribution with a mean of 0 and a variance of ω 2 . When calculating the magnitude of inter-individual variability, the coefficient of variation is usually used.

[0066] The individualized pharmacokinetic parameters of this patient were calculated. CL was 258.3 mL / min, V was 215.1 L, and B max was 50.2 ng / mL. The F1 of immediate-release and extended-release tacrolimus was affected by the time after transplantation and the dose, as shown in Table 3 below:

[0067] Table 3

[0068] Time after transplantation (months) Daily dose (mg) F1 0-3 IR = 11; ER = 13 IR: 0.1981; ER: 0.1741 4-6 IR = 8; ER = 9.5 IR: 0.2380; ER: 0.2128 7-12 IR = 6; ER = 7.5 IR: 0.2784; ER: 0.2475 >12 IR = 5; ER = 7 IR: 0.3058; ER: 0.2587

[0069] Using the individual pharmacokinetic parameters of this patient and the corresponding dosing regimens, the plasma concentration-time curve was plotted (the plasma concentration-time curves at 0 - 3 months, 4 - 6 months, 7 - 12 months after transplantation and after missing IR-T and ER-T within > 12 months are shown respectively as Figures 3 - 6 shown). The calculation principles of the target concentration attainment rate and the deviation time from the therapeutic window are referred toFigure 2 , Figure 2 In:

[0070] Concentration-time curve: (a) Concentration curve of tacrolimus sustained-release formulation under complete compliance; (b) Concentration curve of tacrolimus sustained-release formulation after missing one dose. It is assumed that the patient takes the drug multiple times and reaches a steady state.

[0071] The dashed line represents the therapeutic concentration range;

[0072] The thick black line represents the deviation time when the blood drug concentration exceeds the therapeutic range;

[0073] Solid capsules represent normal dosing, and hollow capsules represent missed doses;

[0074] The dark gray line segment represents the median of the simulated concentration-time curve.

[0075] The gray shaded band represents the 5%-95% percentile range of the simulated concentration distribution.

[0076] The gray bar graph represents the proportion of patients within the therapeutic range, and the white bar graph represents the proportion of patients outside the therapeutic range.

[0077] The target achievement rates of the two formulations when patients take late or miss IR-T and ER-T at different times after transplantation are as Figure 7 shown. As the late dosing time increases, the target achievement rate gradually decreases, but IR-T always performs better than ER-T. Especially when the late dosing time does not exceed 15 hours, the advantage of IR-T is more significant. The proportion of time when the blood drug concentration deviates from the therapeutic window after late dosing or missed dosing of the two formulations can be seen Figure 8 . As the late dosing time increases, the proportion of time deviating from the therapeutic window gradually rises, and IR-T performs better than ER-T in maintaining the blood drug concentration within the therapeutic window. When the late dosing time is less than 7 hours, the difference in the proportion of time deviating from the therapeutic window between IR-T and ER-T is not obvious. However, after the delay time exceeds 7 hours, the advantage of IR-T in maintaining the therapeutic concentration is more prominent. Therefore, considering the target achievement rate and the proportion of time deviating from the therapeutic window, IR-T is the recommended formulation for this patient.

[0078] Example 2

[0079] The present invention has developed an online interactive platform for evaluating the individualized formulation selection of immediate-release and sustained-release tacrolimus formulations, and the interface is as Figure 9 shown. Patient basic information module: used to input the patient's basic information, such as age, weight, gender, type of transplantation, time after transplantation, etc., clinical index module: such as eGFR, cholesterol, hematocrit, etc., medication-related information module: such as concomitant medications, medication regimens, and therapeutic ranges;

[0080] Result Output Module: It is used to output the target achievement rate and deviation time of an individual patient under a certain medication behavior, as well as the corresponding plasma concentration-time curve, visually showing the change in drug concentration of the patient under a certain medication behavior.

[0081] A 50-year-old, 70-kg male renal transplant patient 120 days after surgery. Two optional dosage regimens are: IR-T, 4 mg, twice a day, or ER-T, 9.5 mg, once a day. The therapeutic window range is set at 4 - 12 ng / mL. Three different medication behavior scenarios were evaluated through the platform, and the results are shown in Table 4:

[0082] Table 4

[0083]

[0084] If the situation of the patient taking the medicine late or missing the dose is not considered, assuming the patient is fully compliant, then the recommended dosage forms obtained are:

[0085] Table 5

[0086]

[0087] The results are shown in Table 5. If the situation of the patient taking the medicine late or missing the dose is not considered, then the conclusion is that there is no difference between IR-T and ER-T, and the purpose of selecting the dosage form cannot be achieved.

[0088] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a kind of hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as both software modules for implementing the method and the structures within the hardware component.

[0089] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various deformations or modifications within the scope of the claims, which does not affect the essence of the present invention.

Claims

1. A method for selecting an individualized sustained-release or immediate-release oral preparation, characterized in that, It includes the following steps: S1. Collect the clinical characteristic information and medication-taking behavior of the patient; S2. Use the population pharmacokinetic models of sustained-release and immediate-release dosage forms of drugs to process the clinical characteristic information in step S1 respectively, and estimate the individual pharmacokinetic parameters of the patient; S3. Based on the individual pharmacokinetic parameters in step S2 and the medication-taking behavior in step S1, apply the Monte Carlo method to simulate the plasma concentration-time curves of the sustained-release or immediate-release dosage form of drugs respectively; S4. Calculate the target concentration attainment rate and the deviation time from the therapeutic window of the sustained-release or immediate-release dosage form of drugs according to the plasma concentration-time curve; S5. Select the dosage form with the highest target concentration attainment rate and the shortest deviation time from the therapeutic window as the optimal dosing regimen.

2. The method according to claim 1, wherein The method provides dosage form selection suggestions by developing an interactive web-based calculation tool; the development of the interactive web-based calculation tool is based on RxODE2 and Shiny of R software.

3. The method according to claim 1, wherein In step S1, the clinical characteristic information includes one or more of basic information, clinical characteristics, medication information, and treatment range.

4. The method according to claim 3, wherein The basic information includes one or more of age, weight, gender, transplant type, and time after transplantation; The clinical characteristics include one or more of estimated glomerular filtration rate, liver function, total cholesterol content, hematocrit, haptoglobin content, aspartate aminotransferase content, and albumin content; The medication information includes one or more of concomitant medications, medication regimens, and food intake; the medication regimen includes one or more of mycophenolic acid usage, dosage form selection, daily dose, and dosing interval.

5. The method according to claim 1, wherein In step S1, the medication-taking behavior includes one or more of taking the medicine late and missing the dose.

6. The method according to claim 1, characterized in that, In step S2, the population pharmacokinetic model includes the tacrolimus population pharmacokinetic model.

7. The method according to claim 6, wherein The calculation formula for the individual pharmacokinetic parameters in the tacrolimus population pharmacokinetic model is as follows: Apparent oral clearance CL = 257.6 × (Haematocrit / 39) 0.49 × (eGFR / 51) 0.07 ; Apparent volume of distribution V = 213.2 × (Haptoglobin / 1.4) 0.13 ; The bioavailability F of the immediate-release dosage form = 0.25 × (Dose / 2.5) -0.64 × (1 + e -0.32 × (POD / 1000)); The bioavailability F of the sustained-release dosage form = 0.25 × (Dose / 2.5) -0.62 ; Maximum plasma concentration B bound to red blood cells max = 35.7 × (Haematocrit / 39) -0.43 × (Cholesterol / 4.6) -0.18 × (Haptoglobin / 1.4) -0.05 × 1.14; Absorption rate constant k a = 3.5 h -1 ; Dissociation constant K d = 0.24 ng / mL; where Haematocrit is hematocrit, eGFR is estimated glomerular filtration rate, Haptoglobin is haptoglobin content, Dose is daily dose, POD is time after transplantation, and Cholesterol is total cholesterol content.

8. The method according to claim 1, wherein In step S2, the individual pharmacokinetic parameters include apparent oral clearance CL, apparent volume of distribution V, bioavailability F, and maximum plasma concentration B bound to red blood cells max , absorption rate constant k a , dissociation constant K d , or one or more of them.

9. The method according to claim 1, wherein In step S4, the calculation formula for the target concentration attainment rate is as follows: Target concentration achievement rate The calculation formula for the deviation time from the therapeutic window is as follows: The deviation time from the therapeutic window DT = ∑ the time when the plasma concentration is outside the therapeutic range.

10. A system for selecting an individualized sustained-release or immediate-release oral preparation, characterized in that, It includes: Module M1. Collect the clinical characteristic information and medication-taking behavior of the patient; Module M2. Use the population pharmacokinetic models of sustained-release and immediate-release dosage forms of drugs to process the clinical characteristic information in Module M1 respectively, and estimate the individual pharmacokinetic parameters of the patient; Module M3. Based on the individual pharmacokinetic parameters in Module M2 and the medication-taking behavior in Module M1, apply the Monte Carlo method to simulate the plasma concentration-time curves of the sustained-release or immediate-release dosage form of drugs respectively; Module M4. Calculate the target concentration attainment rate and the deviation time from the therapeutic window of the sustained-release or immediate-release dosage form of drugs according to the plasma concentration-time curve; Module M5. Select the dosage form with the highest target concentration attainment rate and the shortest deviation time from the therapeutic window as the optimal dosing regimen.

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