Method and apparatus for pbpk modeling of inhaled formulations across species and across disease

Abstract

The method and device of PBPK modeling of inhaled drug across species and across diseases are helpful to the effective dose determination of inhaled drug in the development of COPD drug and clinical trials. The method includes: (1) constructing the physiological pharmacokinetic PBPK model at animal level; (2) constructing the PBPK model of healthy people; (3) constructing the PBPK model of disease state; (4) model application and prediction.

Description

Technical Field

[0001] This invention belongs to the technical field of pharmaceutical science, and particularly relates to a PBPK modeling method for cross-species and cross-disease administration of inhaled formulations, as well as a PBPK modeling device for cross-species and cross-disease administration of inhaled formulations. Background Technology

[0002] Obstructive pulmonary diseases, represented by asthma and chronic obstructive pulmonary disease (COPD), are significant respiratory diseases in my country and globally. Their high prevalence, hospitalization rates, disability rates, and mortality rates have made them a serious social problem, imposing a heavy burden on patients, families, and society. Currently, treatment for stable COPD is mainly divided into two categories: bronchodilators and anti-inflammatory drugs, typically employing a step-down combination therapy strategy. Clinically used medications mainly include short-acting (SABA) and long-acting (LABA) β2-receptor agonists; short-acting (SAMA) and long-acting (LAMA) anticholinergic drugs; and inhaled corticosteroids.

[0003] Inhalation therapy is the cornerstone of COPD management. Its core objective is to deliver medication directly to the airways, achieving high local efficacy with low systemic side effects. COPD medications are primarily administered via oral inhalation. Depending on the device and its mechanism of action, commonly used inhaled formulations include pressurized metered-dose inhalers, dry powder inhalers, soft fog inhalers, and nebulized inhalers. The first three are often used for long-term maintenance therapy, while nebulized inhalers are frequently used for acute exacerbations or for critically ill patients for whom other devices are difficult to operate. Inhaled formulations are also the mainstream dosage form in COPD medication development, designed to achieve the lung selectivity advantage of "increased deposition at the target site in the lungs and reduced systemic exposure." By delivering drugs such as LABA and LAMA directly to the airways for local efficacy, this formulation ensures effective drug concentrations at the site of lung lesions while significantly reducing the risk of systemic adverse reactions caused by drug entry into the bloodstream.

[0004] During drug development, it has been discovered that only a small portion of inhaled medications reaches the lung target tissues, with the majority depositing in the oropharynx or being exhaled. Studies have shown that lung deposition rates vary significantly among different formulations and devices, ranging from 4% to 50%. This difference in lung deposition rate can lead to several-fold variations in systemic exposure. Such variations may result in overestimating or underestimating the effective dose, leading to erroneous dose-response inferences, and even causing clinical trial failures or safety issues.

[0005] Human lung deposition data serves as a bridge between in vitro and clinical evaluations, and accurate quantitative data is crucial for determining the dosage of any inhaled drug product. The lung tissue / blood flow ratio is a key parameter for predicting the residence time and systemic exposure of inhaled drugs in the lungs. Accurate determination of the tissue distribution coefficient (Kp) is essential for predicting drug concentration in lung tissue and thus determining the dosage. Furthermore, changes in pulmonary blood flow under different pathological conditions (such as COPD) significantly affect drug deposition and tissue distribution in the lungs. Currently, no literature has been found related to cross-species and cross-disease dosing regimens for inhaled formulations modeled with PBPK. Therefore, there is an urgent need to develop a translational computational method that bridges preclinical and clinical research, quantitatively characterizes the pharmacokinetic properties of inhaled drugs, collects and integrates precise pulmonary physiological parameters, bridges and transcends species differences, and combines COPD disease and physiological states to calculate and obtain parameters such as the lung tissue / plasma partition coefficient, pulmonary blood flow, and lung surface area across species and pathophysiological states. This would provide a new method for determining the effective dosage of inhaled drugs for COPD treatment in clinical trials. Summary of the Invention

[0006] To overcome the shortcomings of existing technologies, the technical problem to be solved by this invention is to provide a PBPK modeling method for cross-species and cross-disease administration of inhaled formulations. This method is a translational computational method that connects preclinical and clinical research, quantitatively characterizes the pharmacokinetic characteristics of inhaled drugs, collects and integrates precise parameters of pulmonary physiological processes, connects and transcends species differences, and calculates and obtains parameters across species and pathophysiological states by combining COPD disease and physiological states. This is helpful for the development of inhaled formulations for the treatment of COPD and the determination of effective doses in clinical trials.

[0007] The technical solution of this invention is: a PBPK modeling method for cross-species and cross-disease administration of inhaled formulations, comprising the following steps: (1) Constructing a physiological pharmacokinetic (PBPK) model at the animal level: Based on oral and nasal inhalation administration data of rats and dogs, the absorption kinetics of drugs in animal lungs were fitted and verified by optimizing alveolar interstitial permeability, systemic absorption rate constant and tissue plasma partition coefficient Kp using the GastroPlus software platform. (2) Constructing a PBPK model of healthy human: Based on the animal pharmacokinetic parameters obtained in step (1), the allometric scaling method was used to extrapolate between species to construct a PBPK model for the first human oral inhalation administration, and the absorption rate and clearance rate of the drug in each compartment of the lung of healthy human were obtained. (3) Construct a PBPK model for disease states: obtain the differences in pulmonary pharmacokinetic characteristic parameters under pathological states; optimize the permeability and clearance rate of alveolar interstitium based on the PBPK model of healthy individuals, and fit the pharmacokinetic characteristics of inhaled formulations in patients based on the PBPK model of healthy individuals, so as to build a PBPK model of inhaled formulations for patients. (4) Model application and prediction: Based on the PBPK model of the inhaled preparation in step (3), the systemic and pulmonary exposure of the inhaled preparation in the patient under different dosages is predicted; at the same time, based on the physicochemical properties of the drug, the deposition ratio and deposition rate in the lungs are calculated.

[0008] This invention utilizes the GastroPlus software platform, a physiological pharmacokinetic (PBPK) simulation software, to construct all pharmacokinetic models and predict blood drug concentration-time curves, as well as inputting corresponding modeling parameters and outputting prediction results. This method serves as a translational computational approach bridging preclinical and clinical research, quantitatively characterizing the pharmacokinetic features of inhaled drugs, collecting and integrating precise parameters of pulmonary physiological processes, bridging and transcending species differences, and combining COPD disease and physiological states to calculate and obtain parameters across species and pathophysiological states. This is helpful for the development of inhaled formulations for COPD treatment and the determination of effective dosages in clinical trials.

[0009] A PBPK modeling device for cross-species and cross-disease administration of inhaled formulations is also provided, the device comprising: The first modeling module is configured to construct an animal-level physiological pharmacokinetic (PBPK) model: based on oral and nasal inhalation administration data of rats and dogs, the absorption kinetics of the drug in the animal lungs are fitted and validated by optimizing alveolar interstitial permeability, systemic absorption rate constant, and tissue-plasma partition coefficient Kp using the GastroPlus software platform. The second modeling module is configured to construct a PBPK model of a healthy human: based on the animal pharmacokinetic parameters obtained from the first modeling module, the allometric scaling method is used to perform interspecies extrapolation to build a PBPK model for the first human oral inhalation administration, and to obtain the absorption rate and clearance rate of the drug in each compartment of the lungs of a healthy human. The third modeling module is configured to construct a PBPK model of the disease state: obtain the differences in pulmonary pharmacokinetic characteristic parameters under pathological conditions; optimize the permeability and clearance rate of alveolar interstitium based on the PBPK model of healthy individuals, and fit the pharmacokinetic characteristics of the inhaled formulation in the patient's body according to the PBPK model of healthy individuals, so as to build a PBPK model of the inhaled formulation for the patient. The application and prediction module is configured based on the inhaled formulation PBPK model of the third modeling module to predict the systemic and pulmonary exposure of the inhaled formulation in the patient at different dosages; at the same time, based on the physicochemical properties of the drug, it calculates the deposition ratio and deposition rate in the lungs. Attached Figure Description

[0010] Figure 1 This is an overall flowchart of the PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to the present invention.

[0011] Figure 2 This is a flowchart of a specific embodiment of the PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to the present invention.

[0012] Figure 3 The results of the PBPK model simulation of intravenous administration of 1 mg / kgrryz001 are shown. (1) shows the results of the PBPK model simulation of rats with intravenous administration of 1 mg / kgrryz001, and (2) shows the results of the PBPK model simulation of beagle dogs with intravenous administration of 1 mg / kgrryz001.

[0013] Figure 4 The results of the PBPK model simulation of rats receiving inhaled rryz001 are shown. (1) 1.448 mg / kg was given to rats by inhalation, (2) 0.471 mg / kg was given to rats by inhalation, and (3) 0.146 mg / kg was given to rats by inhalation.

[0014] Figure 5 The results of the PBPK model simulation of rats receiving inhaled rryz001 are shown. (1) 2.039 mg / kg for rats, (2) 0.571 mg / kg for rats, and (3) 0.236 mg / kg for rats.

[0015] Figure 6 The results of the PBPK model simulation of inhalation administration of rryz001 to healthy individuals are shown. (1) 800 mg / kg for healthy individuals, (2) 1200 mg / kg for healthy individuals, and (3) 1600 mg / kg for healthy individuals.

[0016] Figure 7 The results of the PBPK model simulation of COPD patients receiving inhaled rryz001 are shown. (1) COPD patients receiving inhaled 600 mg / kg, (2) COPD patients receiving inhaled 800 mg / kg. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] To make the description of this disclosure more detailed and complete, illustrative descriptions of embodiments and specific examples of the present invention are provided below; however, these are not the only forms of implementing or utilizing the specific examples of the present invention. The embodiments cover features of multiple specific examples and methods and steps for constructing and operating these specific examples, and their order. However, other specific examples may also be used to achieve the same or equivalent functions and order of steps.

[0019] like Figure 1 As shown, this PBPK modeling method for cross-species and cross-disease administration of inhaled formulations includes the following steps: (1) Constructing a physiological pharmacokinetic (PBPK) model at the animal level: Based on oral and nasal inhalation administration data of rats and dogs, the absorption kinetics of drugs in animal lungs were fitted and verified by optimizing alveolar interstitial permeability, systemic absorption rate constant and tissue plasma partition coefficient Kp using the GastroPlus software platform. (2) Constructing a PBPK model of healthy human: Based on the animal pharmacokinetic parameters obtained in step (1), the allometric scaling method was used to extrapolate between species to construct a PBPK model for the first human oral inhalation administration, and the absorption rate and clearance rate of the drug in each compartment of the lung of healthy human were obtained. (3) Construct a PBPK model for disease states: obtain the differences in pulmonary pharmacokinetic characteristic parameters under pathological states; optimize the permeability and clearance rate of alveolar interstitium based on the PBPK model of healthy individuals, and fit the pharmacokinetic characteristics of inhaled formulations in patients based on the PBPK model of healthy individuals, so as to build a PBPK model of inhaled formulations for patients. (4) Model application and prediction: Based on the PBPK model of the inhaled preparation in step (3), the systemic and pulmonary exposure of the inhaled preparation in the patient under different dosages is predicted; at the same time, based on the physicochemical properties of the drug, the deposition ratio and deposition rate in the lungs are calculated.

[0020] This invention utilizes the GastroPlus software platform, a physiological pharmacokinetic (PBPK) simulation software, to construct all pharmacokinetic models and predict blood drug concentration-time curves, as well as inputting corresponding modeling parameters and outputting prediction results. This method serves as a translational computational approach bridging preclinical and clinical research, quantitatively characterizing the pharmacokinetic features of inhaled drugs, collecting and integrating precise parameters of pulmonary physiological processes, bridging and transcending species differences, and combining COPD disease and physiological states to calculate and obtain parameters across species and pathophysiological states. This is helpful for the development of inhaled formulations for COPD treatment and the determination of effective dosages in clinical trials.

[0021] Preferably, before step (1), the method further includes: collecting and organizing the physicochemical and biopharmaceutical properties of the inhaled drug, including molecular weight Mw, oil-water partition coefficient logP, acid-base dissociation constant pKa, solubility, particle density, particle size, permeability, whole blood / plasma drug concentration ratio Rbp, and plasma protein free fraction solubility Fup; collecting or calculating the systemic clearance rate CL of the compound at the animal level through preclinical pharmacokinetic experiments, and calculating the tissue plasma partition coefficient Kp.

[0022] Preferably, Kp is calculated using the Lukacova method: , : Extracellular water volume fraction in tissues; : Intracellular water volume fraction; : Volume fraction of neutral lipids in tissues; : Volume fraction of neutral phospholipids in tissues; The proportion of the drug in the neutral form in intracellular water (pH 7); The proportion of the drug in the water of tissue cells in its cationic form; The proportion of drugs without positive charge in plasma; : The proportion of positively charged drugs in plasma; K: Solvent / water partition coefficient; Ka: Binding constant between basic drugs and acidic phospholipids; Concentration of acidic phospholipids in tissues; The ratio of albumin concentration in tissues to albumin concentration in plasma; The proportion of unbound drugs in plasma.

[0023] Preferably, in step (1), the calculated Kp value and the PEAR model optimization parameters are used to build a PBPK model of the inhaled formulation in rats and beagle dogs. The PEAR model optimization parameters include logP, Particle Size, and Rbp. The Vss and CL obtained by the model are compared with the measured data to determine the predictive stability of the model, and the Kp value of the inhaled formulation in each tissue is further determined. The Kp value is calculated as follows: , Drug concentration in tissues; : The concentration of the drug in the plasma.

[0024] Preferably, in step (2), referring to the results of the construction and validation of rat and beagle PBPK models, the same Kp calculation method, the same Kp values ​​and proportions for each tissue are used in the PBPK modeling process of healthy humans. The clearance rate in humans is calculated using the results of single-species allometric amplification of the total systemic clearance rate in rats and beagle dogs, as shown in the following formula: , Drug clearance rate in the human body; Drug clearance rate in animals.

[0025] Preferably, in step (3), patients with chronic obstructive pulmonary disease (COPD) are used as research subjects, and their lung interstitial absorption rate is set to be three times that of healthy people. This is used to modify the PBPK model of healthy people, thereby constructing an inhaled formulation PBPK model that reflects the pathological characteristics of COPD.

[0026] Preferably, in step (4), the validated inhaled formulation is used in a PBPK model in COPD patients to simulate the cumulative amount of drug absorbed by various parts of the lung tissue after COPD patients have been given the drug for 7 consecutive days. Based on the effective exposure of the drug at the target site in vitro and the distribution of the drug in the lung tissue, the effective dose of the drug in COPD patients is predicted.

[0027] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium. When executed, the program includes the steps of the methods of the above embodiments. The storage medium can be ROM / RAM, magnetic disk, optical disk, memory card, etc. Therefore, corresponding to the method of the present invention, the present invention also includes a PBPK modeling device for cross-species and cross-disease administration of inhaled formulations. This device is typically represented in the form of functional modules corresponding to the steps of the method. The device includes: The first modeling module is configured to construct an animal-level physiological pharmacokinetic (PBPK) model: based on oral and nasal inhalation administration data of rats and dogs, the absorption kinetics of the drug in the animal lungs are fitted and validated by optimizing alveolar interstitial permeability, systemic absorption rate constant, and tissue-plasma partition coefficient Kp using the GastroPlus software platform. The second modeling module is configured to construct a PBPK model of a healthy human: based on the animal pharmacokinetic parameters obtained from the first modeling module, the allometric scaling method is used to perform interspecies extrapolation to build a PBPK model for the first human oral inhalation administration, and to obtain the absorption rate and clearance rate of the drug in each compartment of the lungs of a healthy human. The third modeling module is configured to construct a PBPK model of the disease state: obtain the differences in pulmonary pharmacokinetic characteristic parameters under pathological conditions; optimize the permeability and clearance rate of alveolar interstitium based on the PBPK model of healthy individuals, and fit the pharmacokinetic characteristics of the inhaled formulation in the patient's body according to the PBPK model of healthy individuals, so as to build a PBPK model of the inhaled formulation for the patient. The application and prediction module is configured based on the inhaled formulation PBPK model of the third modeling module to predict the systemic and pulmonary exposure of the inhaled formulation in the patient at different dosages; at the same time, based on the physicochemical properties of the drug, it calculates the deposition ratio and deposition rate in the lungs.

[0028] The present invention will now be described in more detail with reference to the accompanying drawings and embodiments.

[0029] This method uses the commercially available physiological-based pharmacokinetic (PBPK) simulation software GastroPlus® (version 9.9, Simulations Plus, Inc., USA) to build all pharmacokinetic (PK) models and predict blood concentration-time (CT) curves, as well as input the corresponding modeling parameters and output the prediction results.

[0030] I. The methods and operating steps are as follows:

[0031] 1.1 Preparation of modeling parameters and calculation of Kp

[0032] We collected and organized various physicochemical and biopharmaceutical properties of inhaled drug formulations, including molecular weight (Mw), oil-water partition coefficient (logP), acid-base dissociation constant (pKa), solubility, particle density, particle size, permeability, whole blood / plasma drug concentration ratio (Rbp), and plasma protein fractional solubility (Fup). We collected or calculated the systemic clearance (CL) of the compound at the animal level (including but not limited to rats and beagle dogs) through preclinical pharmacokinetic experiments, and calculated the tissue-plasma partition coefficient (Kp). The Lukacova method was used to calculate the tissue-plasma partition coefficient.

[0033] 1.2 Construction of Animal-Level PBPK Model

[0034] Using the calculated Kp value and the PEAR model to optimize modeling parameters (including but not limited to logP, Particle Size, Rbp, etc.), a PBPK model of the inhaled formulation in rats and beagle dogs was constructed. The Vss and CL values ​​obtained from this model were compared with experimental data to determine the predictive stability of the model, and the Kp values ​​of the inhaled formulation in various tissues were further determined. The formula for calculating the Kp value is as follows: .

[0035] 1.3 Construction of PBPK Model for Inhaled Formulation in Healthy Individuals

[0036] Referring to the results of the rat and beagle dog PBPK model construction and validation, the same Kp calculation method, tissue Kp values, and proportions were used in the healthy human PBPK modeling process. The clearance rate in humans was calculated using the single-species allometric amplification results of the total systemic clearance rate in rats and beagle dogs, as shown in the following formula: .

[0037] Since existing data could not determine which species was more relevant to humans, two allometric amplification CL (Clean Physico-Physical Reduction) models of inhaled formulations were constructed separately. Based on the constructed healthy human PBPK models and data from inhaled administration to healthy subjects, the permeability, systemic absorption rate, and clearance rate of the inhaled formulations in various parts of the human lungs were optimized and obtained.

[0038] 1.4 Construction of PBPK Model for Inhaled Medications in COPD Patients

[0039] Considering the differences in lung tissue physiology between COPD patients and healthy subjects, drug permeability and clearance in their lungs may vary. Therefore, based on a healthy subject model, the permeability and clearance of the alveolar interstitium were optimized, and the pharmacokinetic characteristics of the inhaled formulation in COPD patients were fitted using this PBPK model to construct a PBPK model for inhaled formulations in COPD patients.

[0040] 1.5 Predicting Dosage Using a PBPK Model for Inhaled Medications in COPD Patients

[0041] Using a validated PBPK model in COPD patients, the cumulative amount of drug absorbed by various sites in lung tissue after 7 consecutive days of drug administration was simulated. Based on the effective exposure of the drug at the target site in vitro and its distribution in lung tissue, the effective dose of the drug in COPD patients was predicted. This provides an accurate method for dose determination and efficacy dose analysis in innovative drug development.

[0042] II. Method Implementation Examples:

[0043] This method is validated using rryz001, a Class Ia innovative drug developed with the assistance of our unit.

[0044] 2.1 Modeling parameters and Kp value calculation

[0045] Table 1. Relevant modeling parameters of the rryz001PBPK model

[0046] The formula for the Lukacova method model is:

[0047] 2.2 Construction of Animal-Level PBPK Model

[0048] The clearance threshold (CL) for the rat PBPK model was determined directly using the non-compartmental analysis results of intravenously administered PK data, which was 0.546 L / h, and this clearance rate was set for the liver. For the beagle PBPK model, the CL was determined by referencing the non-compartmental analysis results of intravenously administered PK data and the fitting of the actual PK curve, ultimately setting the CL to 27.965 L / h, with a liver CL of 16.46 L / h and a kidney CL of 11.506 L / h.

[0049] Based on the characteristics of the measured PK curves (rapid distribution of inhaled formulations and large distribution volume), the Kp values ​​of rat and beagle muscle tissues were increased by 100 times based on the Kp calculated by Lukacova's Kp algorithm (the final Kp of rat muscle tissue was 899, and the Kp of beagle muscle tissue was 751), while the Kp values ​​of skin tissue and remaining tissues were reduced by 100 times (the final Kp of rat and beagle skin and remaining tissues were 0.08 and 0.18, respectively, while the Kp values ​​of other tissues remained unchanged).

[0050] Using experimentally measured pharmacokinetic (PK) data of intravenous administration of 1 mg / kg rryz001 to rats and beagle dogs as a reference, and combining physicochemical and biopharmaceutical parameters, PBPK models of intravenous administration of rryz001 to rats and beagle dogs were established using GastroPlus software. The simulation results are shown in […]. Figure 3 The simulated PK curves closely match the measured data points, with minimal differences in AUC. Therefore, the established intravenous PBPK models in rats and beagle dogs can accurately characterize the distribution and clearance of rryz001 in rats and beagle dogs, and this model can be further used to establish inhalation-based drug delivery models.

[0051] A rat inhalation-based PBPK model was established based on an intravenous PBPK model. Considering the C-values ​​between different inhaled formulation doses... max The nonlinearity of AUC was considered when optimizing the permeability of the alveolar interstitium and the systemic absorption rate in rats. Three dosage groups were taken into account. The final model simulation results are shown in [link to simulation results]. Figure 4 .

[0052] The simulation results of the currently established rat inhaled PBPK model show that the model can basically accurately fit the measured PK data points, and the predicted PK parameters, such as C... max AUC 0-t and AUC 0-inf All were within 3 times. Considering the large variation in the measured data, the model was not further optimized. It is currently believed that the established model can basically accurately reflect the absorption process in the lungs of rats after inhalation administration.

[0053] Based on the intravenous PBPK model in beagle dogs, an inhaled PBPK model was established. During model optimization, high-dose inhaled PK data (2.039 mg / kg) were primarily used to optimize alveolar interstitial permeability and systemic absorption rate. The final model simulation results are shown below. Figure 5 .

[0054] The simulation results of the currently established PBPK model for inhaled administration in beagle dogs show that the model can basically accurately fit the measured PK data points, and the predicted PK parameters are as follows: Cmax AUC 0-t and AUC 0-inf All were within 3 times (even within 1.5 times). Therefore, the current model can accurately reflect the absorption process in the lungs of beagle dogs after inhalation.

[0055] 2.3 Construction of PBPK Model for Healthy Individuals

[0056] Based on the first human PBPK model of healthy subjects obtained by preclinical species extrapolation and inhalation administration, combined with the material balance data after inhalation of 1200 μg, the proportion of lung absorption was calculated to be 43% (the deposition rate of 43% was defined, mainly based on 8% residue in the device, 36% in mouthwash, and 13% in feces). The deposition rate of each lung compartment was calculated by software. The lung tissue parameters of the model are shown in Table 2.

[0057] Table 2. Model parameters of lung tissue compartments in the PBPK model administered by inhalation in healthy subjects.

[0058] Based on the optimized permeability, systemic absorption rate, and clearance rate of various lung sites in healthy subjects, the optimal drug solubility in lung tissue was determined to be 0.029 mg / mL. Based on these results, the PBPK model was used to predict the PK data for inhaled administration of 800 μg, 1200 μg, and 1600 μg in healthy subjects, and the results were compared with the model-predicted pharmacokinetic curves. (See attached figures). Figure 6 .

[0059] As shown in the figure, the PBPK model for inhalation administration in healthy subjects, established based on the permeability, systemic absorption rate, and clearance rate of different lung regions, exhibits a good fit between the predicted results and the measured data. The simulated C max All are within twice the measured values.

[0060] 2.4 Construction of PBPK model for COPD patients

[0061] Considering the changes in the physiological structure of lung tissue between COPD patients and healthy subjects, the permeability and clearance rate of their lungs may also change. Therefore, the PBPK model for COPD patients with inhaled drug delivery was developed by optimizing the permeability and clearance rate of the alveolar interstitium based on the healthy subject model. The lung tissue parameters of the model are shown in Table 3.

[0062] Table 3. Model parameters of lung tissue compartments in COPD patients undergoing inhaled PBPK administration.

[0063] The table shows that the alveolar interstitial permeability of the COPD patient model was 3 times that of healthy subjects, and the metabolic clearance rate was 1 / 3, which is consistent with the results of the literature.

[0064] The model optimization primarily referenced pharmacokinetic (PK) data from COPD patients administering 200 μg and 400 μg of inhaled medication. The optimized PBPK model for COPD patients administering inhaled medication was then validated using measured PK data from 600 μg and 800 μg inhalations. The validation results are shown below. Figure 7 .

[0065] from Figure 7 The study observed that the prediction results of the established COPD patient inhalation drug delivery PBPK model showed a good fit with the measured data points, and the simulated C max All values ​​were within twice the measured values. The simulation results show the total AUC over seven consecutive days of administration. Based on the fit between the simulated and measured data points, the model almost accurately simulated the plasma drug concentration at each time point, indicating high model accuracy.

[0066] This invention integrates the effects of drug physicochemical properties, physiological parameters, and pathophysiological changes on drug absorption based on a stepwise extrapolation strategy from "animal-healthy human-patient". This method can not only guide the clinical trial dosage design of inhaled formulations in the early stages of new drug development, but also be used to elucidate their pulmonary pharmacokinetic characteristics and dose-response relationships, exhibiting high predictive accuracy and wide applicability.

[0067] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A PBPK modeling method for cross-species and cross-disease administration of inhaled formulations, characterized in that: It includes the following steps: (1) Constructing a physiological pharmacokinetic (PBPK) model at the animal level: Based on oral and nasal inhalation administration data of rats and dogs, the absorption kinetics of drugs in animal lungs were fitted and verified by optimizing alveolar interstitial permeability, systemic absorption rate constant and tissue plasma partition coefficient Kp using the GastroPlus software platform. (2) Constructing a PBPK model of healthy human: Based on the animal pharmacokinetic parameters obtained in step (1), the allometric scaling method was used to extrapolate between species to construct a PBPK model for the first human oral inhalation administration, and the absorption rate and clearance rate of the drug in each compartment of the lung of healthy human were obtained. (3) Construct a PBPK model for disease states: obtain the differences in pulmonary pharmacokinetic characteristic parameters under pathological states; optimize the permeability and clearance rate of alveolar interstitium based on the PBPK model of healthy individuals, and fit the pharmacokinetic characteristics of inhaled formulations in patients based on the PBPK model of healthy individuals, so as to build a PBPK model of inhaled formulations for patients. (4) Model application and prediction: Based on the PBPK model of the inhaled preparation in step (3), the systemic and pulmonary exposure of the inhaled preparation in the patient under different dosages is predicted; at the same time, based on the physicochemical properties of the drug, the deposition ratio and deposition rate in the lungs are calculated.

2. The PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to claim 1, characterized in that: Before step (1), the following steps are also included: collecting and organizing the physicochemical and biopharmaceutical properties of the inhaled drug, including molecular weight Mw, oil-water partition coefficient logP, acid-base dissociation constant pKa, solubility, particle density, particle size, permeability, whole blood / plasma drug concentration ratio Rbp, and plasma protein free fraction solubility Fup; collecting or calculating the systemic clearance rate CL of the compound at the animal level through preclinical pharmacokinetic experiments, and calculating the tissue plasma partition coefficient Kp.

3. The PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to claim 2, characterized in that: Kp is calculated using the Lukacova method: ， : Extracellular water volume fraction in tissues; : Intracellular water volume fraction; : Volume fraction of neutral lipids in tissues; : Volume fraction of neutral phospholipids in tissues; The proportion of the drug in the neutral form in intracellular water (pH 7); The proportion of the drug in the water of tissue cells in its cationic form; The proportion of drugs without positive charge in plasma; : The proportion of positively charged drugs in plasma; K: Solvent / water partition coefficient; Ka: Binding constant between basic drugs and acidic phospholipids; Concentration of acidic phospholipids in tissues; The ratio of albumin concentration in tissues to albumin concentration in plasma; The proportion of unbound drugs in plasma.

4. The PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to claim 3, characterized in that: In step (1), the calculated Kp value and the PEAR model optimization parameters are used to build a PBPK model of the inhaled formulation in rats and beagle dogs. The PEAR model optimization parameters include logP, Particle Size, and Rbp. The Vss and CL obtained by the model are compared with the measured data to determine the predictive stability of the model, and the Kp value of the inhaled formulation in each tissue is further determined. The Kp value calculation formula is as follows: ， Drug concentration in tissues; : The concentration of the drug in the plasma.

5. The PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to claim 4, characterized in that: In step (2), referring to the results of the construction and validation of rat and beagle PBPK models, the same Kp calculation method, the same Kp values ​​and proportions of each tissue were used in the PBPK modeling process of healthy humans; the clearance rate of human subjects used the results of single-species allometric amplification of the total systemic clearance rate of rats and beagle dogs, respectively, as shown in the following formula: ， Drug clearance rate in the human body; Drug clearance rate in animals.

6. The PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to claim 5, characterized in that: In step (3), patients with chronic obstructive pulmonary disease (COPD) are used as research subjects. Their lung interstitial absorption rate is set to be three times that of healthy people. This is used to modify the PBPK model of healthy people, thereby constructing an inhaled formulation PBPK model that reflects the pathological characteristics of COPD.

7. The PBPK modeling method for cross-species and cross-disease administration of inhaled formulations according to claim 6, characterized in that: In step (4), the validated inhaled formulation is used in a PBPK model in COPD patients to simulate the cumulative amount of drug absorbed by various parts of the lung tissue after COPD patients have been given the drug for 7 consecutive days. Based on the effective exposure of the drug at the target site in vitro and the distribution of the drug in the lung tissue, the effective dose of the drug in COPD patients is predicted.

8. A PBPK modeling device for cross-species and cross-disease administration of inhaled formulations, characterized in that: It includes: The first modeling module is configured to construct an animal-level physiological pharmacokinetic (PBPK) model: based on oral and nasal inhalation administration data of rats and dogs, the absorption kinetics of the drug in the animal lungs are fitted and validated by optimizing alveolar interstitial permeability, systemic absorption rate constant, and tissue-plasma partition coefficient Kp using the GastroPlus software platform. The second modeling module is configured to construct a PBPK model of a healthy human: based on the animal pharmacokinetic parameters obtained from the first modeling module, the allometric scaling method is used to perform interspecies extrapolation to build a PBPK model for the first human oral inhalation administration, and to obtain the absorption rate and clearance rate of the drug in each compartment of the lungs of a healthy human. The third modeling module is configured to construct a PBPK model of the disease state: obtain the differences in pulmonary pharmacokinetic characteristic parameters under pathological conditions; optimize the permeability and clearance rate of alveolar interstitium based on the PBPK model of healthy individuals, and fit the pharmacokinetic characteristics of the inhaled formulation in the patient's body according to the PBPK model of healthy individuals, so as to build a PBPK model of the inhaled formulation for the patient. The application and prediction module is configured based on the inhaled formulation PBPK model of the third modeling module to predict the systemic and pulmonary exposure of the inhaled formulation in the patient at different dosages; at the same time, based on the physicochemical properties of the drug, it calculates the deposition ratio and deposition rate in the lungs.

9. The PBPK modeling device for cross-species and cross-disease administration of inhaled formulations according to claim 8, characterized in that: The device also includes a computational module configured to collect and organize physicochemical and biopharmaceutical properties of inhaled formulations, including molecular weight Mw, oil-water partition coefficient logP, acid-base dissociation constant pKa, solubility, particle density, particle size, permeability, whole blood / plasma drug concentration ratio Rbp, and plasma protein free fraction solubility Fup; collect or calculate the systemic clearance CL of the compound at the animal level through preclinical pharmacokinetic experiments; and calculate the tissue-plasma partition coefficient Kp.

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