Drug screening method and apparatus based on therapeutic index, and electronic device

Abstract

The present invention relates to the technical field of drug screening, in particular to a drug screening method and apparatus based on the therapeutic index, and an electronic device. The present invention combines two key pharmacodynamic evaluation indicators, i.e. survival rate and body weight, with respect to experimental animal models. Body weight data is ingeniously converted into data of the area on a relative body weight curve, which then further undergoes synchronous normalization with survival rate data, and a calculation formula for the therapeutic index is established to be used for drug screening. The drug screening method of the present invention can organically combine survival rate and body weight data to objectively reflect disease progression and prognosis outcomes, thus effectively amplifying the effect differences between different drug treatment groups, more accurately, conveniently and comprehensively screening out drugs having excellent comprehensive effects, greatly reducing the development cost for new drugs, and further providing more accurate data support for clinical and experimental researches.

Description

A drug screening method, apparatus, and electronic device based on a therapeutic index.

[0001] Cross-references

[0002] This application claims priority to Chinese Patent Application No. 2024105506530, filed on May 6, 2024, entitled “A Drug Screening Method, Apparatus and Electronic Device Based on Therapeutic Index”, the entire disclosure of which is incorporated herein by reference. Technical Field

[0003] This invention relates to the field of drug screening technology, and in particular to a drug screening method, apparatus and electronic device based on a therapeutic index. Background Technology

[0004] In the drug development process, many animal disease models require survival rate and body weight as indicators to evaluate drug efficacy. Examples include tumor disease models, cardiovascular disease models, infectious disease models, metabolic disease models, autoimmune disease models, and chronic pain disease models.

[0005] Currently, survival rate is commonly used as an important indicator for evaluating drug efficacy. However, in animal experiments, many factors affect animal survival rate, such as injection method, operator technique, and mouse condition. Relying solely on survival rate to evaluate drug efficacy is not entirely objective. Therefore, using survival rate as a single indicator has limitations and fails to comprehensively reflect the overall effect of drug treatment.

[0006] Changes in the body weight of surviving laboratory animals are one of the objective indicators for evaluating the results of animal experiments. The increase or decrease in the body weight of laboratory animals often reflects information about their health status, nutrient intake, metabolic rate and other aspects, and is therefore of great significance in experimental design and result interpretation.

[0007] Currently, drug development typically considers only survival rate and changes in animal weight, which introduces significant subjective errors. How to integrate survival rate and animal weight change data to conveniently and comprehensively evaluate drug efficacy and improve the reliability and objectivity of drug evaluation results has become a pressing technical challenge in this field. Summary of the Invention

[0008] To address the aforementioned technical challenges, this invention first provides the application of the area under the relative body mass curve in constructing drug screening models;

[0009] The relative body mass refers to the ratio of the experimental animal's body mass to its initial body mass;

[0010] The area on the relative body mass curve refers to the curve plotted with different time points as the x-axis and the relative body mass of the experimental animal as the y-axis, showing the change of relative body mass over time.

[0011] Using the initial relative body mass as a baseline, the area between the curve and the baseline is the area on the relative body mass curve.

[0012] To eliminate differences in initial levels between experimental groups and to intuitively demonstrate the impact of drug treatment on body weight, making inter-group comparisons more intuitive and scientific, this invention introduces the concept of "relative body weight," which is the ratio of the experimental animal's body weight to its initial body weight. By using the experimental animal's initial body weight as a benchmark, the experimental data becomes more accurate and comparable.

[0013] Furthermore, to more rationally and accurately combine body mass and survival rate indicators, this invention proposes the concept of "area on relative body mass curve." This involves plotting a curve showing the change in relative body mass over time with different time points as the x-axis and the relative body mass of the experimental animal as the y-axis. Using the initial relative body mass as the baseline (Y=1), the area between the curve and the baseline is calculated as the area on the relative body mass curve. Prior to this invention, researchers typically used the "area under the curve" to assess changes in body mass.

[0014] When the curve is intact, the smaller the area on the relative body weight curve, the smaller the fluctuation in body weight of the experimental animal after drug treatment, the faster the rate of recovery to the initial body weight, indicating a better therapeutic effect of the drug.

[0015] The curve of relative mass changing over time can be plotted using software commonly used in this field, including but not limited to Graphpad.

[0016] Furthermore, this invention provides a method for constructing a drug screening model, comprising:

[0017] (1) Prepare experimental animal models of diseases and obtain data on the survival rate and body weight of experimental animals after administration of drugs;

[0018] (2) Obtain the area on the relative body mass curve based on the body mass data;

[0019] (3) The area data on the survival rate and relative body weight curves were standardized by the summation normalization method to construct a drug screening model.

[0020] In order to eliminate the influence of different dimensions between different variables and make the data of different variables comparable, this invention uses the summation normalization method to process the area on the survival rate and relative body weight curves before model construction.

[0021] Preferably, when the disease is sepsis, the drug screening model is a therapeutic index model, and its formula is:

[0022] n represents the number of experiments, Si is the survival rate data after standardization using the summation-normalization method, and Ai is the area on the relative body mass curve after standardization using the summation-normalization method.

[0023] Furthermore, the present invention provides a drug screening method, comprising:

[0024] To obtain data on the survival rate and body weight of laboratory animals;

[0025] Body weight data is converted into area on the relative body weight curve (AUC) data, and the survival rate and AUC data are standardized using the summation normalization method. The treatment index is calculated based on the standardized data to assess drug efficacy.

[0026] The formula for calculating the treatment index is as follows:

[0027] n represents the number of experiments, Si is the survival rate data after standardization using the summation-normalization method, and Ai is the area on the relative body mass curve after standardization using the summation-normalization method.

[0028] Considering the high recurrence rate of some diseases, such as sepsis, this invention employs a method of summing up multiple experimental results in the construction of the aforementioned treatment index calculation formula. Specifically, the treatment index is the sum of the survival rate (S) / area on the relative body weight curve (A) after n experiments. By comprehensively considering the values ​​of multiple treatment indices, the long-term therapeutic effect of the drug on the disease can be better reflected, resulting in a more comprehensive and complete evaluation of drug efficacy.

[0029] In this invention, the larger the therapeutic index value, the better the therapeutic effect and the higher the safety of the drug.

[0030] In the specific implementation process, by comparing the T values ​​of each drug treatment group... index The value can accurately determine the therapeutic effect of each drug on the disease and screen out drugs with good overall therapeutic effect.

[0031] Preferably, the drug screening method further includes:

[0032] Animal models of the disease were prepared, and data on the survival rate and body weight of the experimental animals were obtained after drug treatment.

[0033] In this invention, the methods of administration include, but are not limited to: oral administration, intravenous injection, intramuscular injection, subcutaneous injection, rectal irrigation, eye drops, nasal spray, oral spray, local or systemic skin application.

[0034] In this invention, the experimental animals include, but are not limited to, mice, rats, rabbits, cats, dogs, chickens, ducks, geese, cattle, pigs, sheep, horses, donkeys, deer, camels, monkeys, and other experimental animals.

[0035] Preferably, the disease treated by the drug is one for which the efficacy of the drug needs to be evaluated by at least two indicators: survival rate and body weight.

[0036] Preferably, the disease is at least one of tumor, cardiovascular disease, infectious disease, metabolic disease, and autoimmune disease.

[0037] Preferably, the disease is sepsis.

[0038] Preferably, a sepsis experimental animal model is prepared by stimulating experimental animals with lipopolysaccharide, and the survival rate and body weight data of the experimental animals are obtained after drug treatment.

[0039] Preferably, the method for preparing the sepsis experimental animal model includes: taking 8-10 week old mice and preparing the sepsis experimental animal model by intraperitoneal injection of lipopolysaccharide solution.

[0040] More preferably, the mouse is a C57BL / 6 mouse.

[0041] More preferably, the amount of lipopolysaccharide solution used is 15–25 mg / kg.

[0042] In practice, sepsis treatment drugs include, but are not limited to: budesonide, dexamethasone, triamcinolone, prednisone, hydrocortisone and its derivatives, as well as sialic acid-modified nanoemulsions or liposomes.

[0043] More preferably, the immune memory of experimental animals against sepsis was investigated by repeated intraperitoneal injections of lipopolysaccharide solution.

[0044] In practice, the immune memory can be divided into strong immune memory, moderate immune memory, and weak immune memory.

[0045] "Strong immune memory" (or strong immune memory) is a stable and potent acquired immune response, reflecting immune memory established through appropriate treatment. It manifests in long-term efficacy against a disease (or pathogen), excellent prognosis, and even disease cure. "Medium immune memory" (or moderate immune memory) represents a variable type of memory, falling between "weak memory" and "strong memory." "Weak immune memory" (or weak immune memory) represents a harmful type of memory, which may not function effectively in complex environments, or even exhibit unfriendly effects—a pattern of immune system response.

[0046] This approach of classifying immune memory into strong, medium, and weak categories represents a significant breakthrough in researchers' understanding of immune system response mechanisms and the relationship between nanomedicine delivery systems and the immune system. It expands the boundaries of knowledge in the field of immunology and holds promise for playing a key role in designing more effective treatment strategies.

[0047] Furthermore, the present invention provides a drug screening device, comprising:

[0048] The data acquisition module is used to acquire data on the survival rate and body weight of laboratory animals.

[0049] The data processing module is used to convert body weight data into area on the relative body weight curve (AUC) data, and to standardize the survival rate and AUC data using the summation normalization method. The treatment index is then calculated based on the standardized data.

[0050] The formula for calculating the treatment index is as follows:

[0051] n represents the number of experiments, Si is the survival rate data after standardization using the summation normalization method, and Ai is the area on the relative body mass curve after standardization using the summation normalization method.

[0052] The efficacy evaluation module is used to output efficacy evaluation conclusions based on the treatment index.

[0053] Furthermore, the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the drug screening method as described in any of the above embodiments.

[0054] Furthermore, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the drug screening method as described in any of the above embodiments.

[0055] Furthermore, the present invention provides the application of the method for constructing the drug screening model, the drug screening method, the drug screening device, the electronic device, or the computer-readable storage medium described in any of the above embodiments in the preparation of products for drug screening.

[0056] Furthermore, the present invention provides a sialic acid-modified budesonide palmitate nanoemulsion, the raw materials of which include: MCT, DPPC, DPPG-Na, BP and SA-CH; wherein, the molar ratio of SA-CH to phospholipid is 5 mol% to 25 mol%, preferably 10 mol% to 15 mol%, and most preferably 10 mol%.

[0057] Preferably, the phospholipid is DPPC and DPPG-Na.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0059] This invention combines two important evaluation indicators for pharmacodynamic experimental animal models: survival rate and body weight. By cleverly converting body weight data into area on the relative body weight curve (AUC) and further standardizing it in sync with survival rate data, a formula for calculating the therapeutic index is constructed for drug screening. The therapeutic index of this invention can organically combine survival rate and body weight data, objectively reflecting the disease progression and prognosis. By placing the survival rate in the numerator and the AUC in the relative body weight curve in the denominator, it can effectively amplify the differences in efficacy between different drug treatment groups. It can more accurately, conveniently, and comprehensively screen drugs with excellent overall therapeutic effects by considering both safety and long-term efficacy, greatly reducing the development cost of new drugs and providing more accurate data support for clinical and experimental research. Attached Figure Description

[0060] Figure 1 shows the survival curves, relative body weight curves, and treatment index graphs of mice with sepsis treated with SA-modified BP nanoemulsions at different proportions in Example 2.

[0061] Figure 2 shows the survival curves, relative body weight curves, and treatment index graphs of mice in each group after their first infection in Example 3.

[0062] Figure 3 shows the survival curves, relative body weight curves, and overall treatment index of mice after secondary infection in each group in Example 4.

[0063] Figure 4 shows the survival curves, relative body weight curves, and total treatment index of mice in each group after three infections in Example 5.

[0064] Figure 5 shows the survival curves, relative body weight curves, and treatment index graphs of mice treated with SA-modified BP and DP nanoemulsions in Example 6.

[0065] Figure 6 shows the survival curves, relative body weight curves, and treatment index graphs of mice treated with different drug emulsions in Example 7 for sepsis. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this invention, not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0067] Unless otherwise specified, all methods used in the examples were conventional or performed according to techniques or conditions described in the literature in this field, or in accordance with the product instructions. Reagents and instruments used without specified manufacturers were all conventional products that could be purchased from legitimate channels.

[0068] Example 1

[0069] This embodiment prepares budesonide palmitate-related nanoemulsions. The formulations are shown in Table 1.

[0070] Table 1. Emulsion Formulation Composition

[0071] The preparation method is as follows:

[0072] Accurately weigh the prescribed amounts of medium-chain triglycerides (MCT), dipalmitoylphosphatidylcholine (DPPC), dipalmitoylphosphatidylglycerol sodium (DPPG-Na), and budesonide palmitate (BP) according to Table 1. Heat and stir the oil phase (MCT and BP) and the aqueous phase (DPPC, DPPG-Na, and SA-CH (sialic acid cholesterol derivative) dispersed in 3 mL of sterile water for injection to form a homogeneous solution) in water baths at 70℃ and 65℃ respectively. After the oil phase is completely dissolved and the aqueous phase forms a homogeneous solution, slowly add the aqueous phase at the same temperature dropwise to the oil phase. Continue stirring at 65℃ for 30 min to obtain the initial emulsion. Ultrasonically disperse the initial emulsion (power and time: 200W × 2 min + 400W × 6 min, 1 s working, 1 s rest) and then sequentially filter it through 0.80, 0.45, and 0.22 μm aqueous microporous membranes to obtain the sialic acid-modified BP nanoemulsion (drug concentration 2 mg·mL). - 1 Both emulsions have a particle size of 110nm ± 20nm and an encapsulation efficiency of greater than 95%.

[0073] Note: The SA modification ratio in BP-SAE is 10 mol% (molar ratio to phospholipid). In the table, SA represents sialic acid, and SA-CH is a sialic acid-cholesterol derivative (prepared by the method disclosed in the patent application number: 201610533120.7, patent title: "Synthesis of a lipid derivative containing sialic acid group and its application in pharmaceutical preparations").

[0074] Example 2

[0075] This embodiment refers to the preparation method of Example 1 to prepare BP nanoemulsions with different SA modification ratios (5 mol%, 10 mol%, 15 mol%, 20 mol%, 25 mol%), and conducts pharmacodynamic experiments. The steps are as follows:

[0076] Eight to ten-week-old male C57BL / 6 mice were randomly divided into six groups of five mice each: groups containing BP nanoemulsions with SA modification ratios of 5 mol%, 10 mol%, 15 mol%, 20 mol%, and 25 mol% (named 5% SA group, 10% SA group, 15% SA group, 20% SA group, and 25% SA group), and a control group (5% Glu group, i.e., 5% glucose injection group). Mice in each group were intraperitoneally injected with 20 mg / kg of lipopolysaccharide solution to induce the lipopolysaccharide model. Four hours later, each group was administered a single intravenous injection of 4.0 mg / kg of the different formulations via tail vein. Survival rate and body weight were monitored and recorded for 10 days throughout the experiment.

[0077] Body mass data at different time points were converted into relative body mass (the ratio of the experimental animal's body mass to its initial body mass). Using Graphpad software, a curve showing the change in relative body mass over time was plotted with different time points as the x-axis and the relative body mass of the experimental animal as the y-axis. The area under the relative body mass curve (i.e., the area between the curve and the baseline) was calculated using the initial relative body mass as the baseline (Y=1). Survival curves were also plotted.

[0078] Then, the area data on the survival rate and relative body mass curves were standardized using the summation normalization method, so that the data were unified in terms of units of measurement.

[0079] Summation normalization, also known as total sum normalization, divides each data point by the sum of all data points. The advantages of summation normalization include: 1. Eliminating the influence of dimensions: This method eliminates the influence of dimensions, allowing data from different dimensions to be compared and analyzed without considering their units or units. 2. Preserving relative proportions: While normalizing data to the range [0,1] preserves the relative size of the data, summation normalization makes the relative proportions of data points more intuitive because the sum of all data points is 1. 3. Unaffected by extreme values: Compared to some normalization methods, such as min-max normalization, summation normalization is insensitive to extreme values ​​because it normalizes based on the sum of data points, rather than simply considering the maximum and minimum values. 4. Maintaining data distribution characteristics: Summation normalization preserves the original data distribution characteristics because it scales the data simply by dividing by the sum, rather than transforming or shifting the data. 5. Wide applicability: This method is applicable to various types of data, including numerical data and probability distributions, and therefore has wide applications in data analysis, machine learning and other fields.

[0080] The treatment index (T) was calculated based on standardized survival rate data and area under the relative body weight curve. index To evaluate the therapeutic effects of different formulations.

[0081] The formula for calculating the therapeutic index is as follows: n represents the number of experiments (n=1 in this example), Si is the survival rate data after standardization using the summation normalization method, and Ai is the area on the relative body mass curve after standardization using the summation normalization method.

[0082] The results are analyzed as follows:

[0083] Figure 1 shows the survival curves, relative body weight curves, and treatment indices (T0.05) of mice treated with SA-modified BP nanoemulsions at different proportions in Example 2. index )picture.

[0084] Table 2 shows the survival rate and standardized data of mice in each group after infection treatment.

[0085] Table 2. Survival rates and standardized data of mice in each group after infection treatment (n=5)

[0086] As shown in Figure 1 and Table 2, different proportions of SA-modified BP nanoemulsions can prolong the survival rate of septic mice to some extent. However, the survival rate alone cannot clearly compare the therapeutic effects of each group of preparations. For example, the survival rates of the 10% SA group and the 15% SA group were the same (80%), and the survival rates of the 20% SA group and the 25% SA group were the same (40%). In such cases, changes in body weight are needed for further analysis and comparison.

[0087] Table 3 shows the area on the curve and standardized data of relative body weight of mice after infection and treatment in each group.

[0088] Table 3. Area on the curve and standardized data of relative body weight after infection treatment in each group of mice (n=5)

[0089] As shown in Figure 1 and Table 3, except for the 5% Glu group, the relative weight change curves of BP nanoemulsions modified with different proportions of SA are complete. The areas on the curves of each group to the initial weight (Y=1), namely the areas on the relative weight curves of the 5% SA group, 10% SA group, 15% SA group, 20% SA group and 25% SA group, are 1.137±0.040, 0.967±0.025, 1.223±0.028, 1.103±0.036 and 1.244±0.042, respectively. By comparing the areas on the curves, it can be clearly seen that the group with an SA modification ratio of 10 mol% has the smallest weight fluctuation due to sepsis.

[0090] Furthermore, the treatment index was calculated according to the above formula, and the results are shown in Table 4.

[0091] Table 4. T values ​​of mice after infection and treatment in each group index value

[0092] Table 4 shows that different proportions of SA-modified BP nanoemulsion resulted in varying efficacy in treating sepsis. Clearly, T... index The advantages and disadvantages of different groups were clearly distinguished. Among these drugs, the 10 mol% SA-modified BP nanoemulsion showed the best overall effect in treating sepsis. Within the SA modification density range of 5% to 10%, the efficacy gradually improved with increasing modification density, demonstrating a certain SA modification density dependence, suggesting that SA modification is beneficial for targeted therapy of sepsis. However, when the SA modification density increased to above 10% (15% SA, 20% SA, and 25% SA), the anti-septic effect gradually worsened. This may be because excessively high SA modification density leads to binding to a large number of receptors, potentially causing receptor redistribution on the cell membrane to compensate for local losses. This could result in receptor shortages in other areas of the cell membrane, affecting the phagocytic efficiency of the nanoemulsion and thus exacerbating the inflammatory response of sepsis.

[0093] Example 3

[0094] This embodiment uses different drug formulations to conduct pharmacodynamic experiments, and the steps are as follows:

[0095] Male C57BL / 6 mice aged 8–10 weeks were randomly divided into 5 groups of 6 mice each: BP-SAE group (prepared according to the method in Example 1), BP-CE group (prepared according to the method in Example 1), budesonide palmitate solution group (BP-S group), dexamethasone sodium phosphate solution group (DSP-S group), and control group (5% Glu group). Mice in each group were intraperitoneally injected with 20 mg / kg lipopolysaccharide solution to establish the lipopolysaccharide model. Four hours later, they were intravenously injected with 4.0 mg / kg of the BP-related preparation, 3.09 mg / kg of dexamethasone sodium phosphate solution, and an equal volume of 5% Glu solution, for a total of one administration. Throughout the experiment, the survival rate and body weight of the mice were monitored and recorded for 10 days.

[0096] The preparation method for budesonide palmitate solution is as follows: Accurately weigh 20.0 mg BP and dissolve it in 0.5 mL of Tween 80. Then add 0.25 mL of anhydrous ethanol, gently shake to mix, and dilute with physiological saline to a drug concentration of 2.0 mg / mL before use.

[0097] The preparation method of dexamethasone sodium phosphate solution is as follows: accurately weigh 5.0 mg DSP and dissolve it in 1 mL of physiological saline to obtain a concentration of 5 mg / mL.

[0098] The data were processed according to the method in Example 2, and the treatment index was calculated.

[0099] The results are analyzed as follows:

[0100] Figure 2 shows the survival curves, relative body weight curves, and treatment indices (T0.05) of mice in each group during their first infection in Example 3. index )picture.

[0101] Table 5 shows the survival rate and standardized data of mice after initial infection and treatment in each group.

[0102] Table 5. Survival rates and standardized data of mice after initial infection and treatment in each group (n=6)

[0103] As shown in Figure 2 and Table 5, the survival rates of the BP-SAE, BP-CE, BP-S, DSP-S, and 5% Glu groups were 83.30%, 50.00%, 33.30%, 0%, and 0%, respectively. Under the same experimental conditions, the DSP-S group did not improve the survival rate of septic mice, but the BP-S group had a certain effect on prolonging the survival of septic mice. The BP-CE group was able to improve the survival rate of septic mice better, demonstrating the advantages of nanoemulsions as drug delivery systems. The BP-SAE group had the highest survival rate, indicating that SA-targeted nanoformulations have great potential in the treatment of sepsis.

[0104] Table 6 shows the area on the curve and standardized data of relative body weight of mice after the first infection and treatment in each group.

[0105] Table 6. Area on the curve and standardized data of relative body weight after initial infection and treatment in each group of mice (n=6)

[0106] As shown in Figure 2 and Table 6, the relative body weight change curves of the BP-SAE, BP-CE, and BP-S groups are complete. The areas under the curves for each group relative to their initial body weight (Y=1) are 0.890±0.029, 0.943±0.043, and 1.231±0.046, respectively. Comparing the areas under the curves clearly shows that the BP-SAE group experienced the least fluctuation in body weight due to sepsis, indicating the best treatment effect. The BP-CE group followed. The BP-S treatment group showed a slower recovery in body weight compared to the other two groups, with greater fluctuations in body weight due to sepsis, suggesting that the treatment effect of the solution group was not as good as that of the formulation group.

[0107] Further calculations of the treatment index were performed, and the results are shown in Table 7.

[0108] Table 7. T values ​​of mice after initial infection and treatment in each group. index value

[0109] Table 7 shows that the T values ​​for the first treatment of sepsis in different groups were... index The values ​​are: BP-SAE (2.00), BP-CE (1.11), BP-S (0.57), DSP-S (0), and 5% Glu (0). Clearly, T... index The superiority or inferiority of different groups was clearly distinguished. Among these drugs, the SA-modified BP nanoemulsion showed the best overall therapeutic effect, highlighting the importance of nanotechnology in drug delivery.

[0110] Furthermore, the following examples use a treatment index to evaluate drugs for treating secondary sepsis.

[0111] Example 4

[0112] One month after infection as described in Example 3, surviving C57BL / 6 mice from each group were collected after treatment: 5 mice in the BP-SAE group, 3 mice in the BP-CE group, and 2 mice in the BP-S group. These mice were then intraperitoneally injected again with the same dose of lipopolysaccharide solution (20 mg / kg) as during the initial modeling, and no further drug injections were administered to any group. Throughout the experiment, the survival rate and body weight of the mice were monitored and recorded for 10 days. Data were processed according to the method described in Example 2, and the treatment index was calculated.

[0113] The results are analyzed as follows:

[0114] Figure 3 shows the survival curves, relative body weight curves, and total treatment index (T) of mice in each group after secondary infection in Example 4. index )picture.

[0115] Table 8 shows the survival rate and standardized data of mice after secondary infection treatment in each group.

[0116] Table 8. Survival rates and standardized data of mice after secondary infection treatment in each group (n = 2–5)

[0117] As shown in Figure 3 and Table 8, sepsis mice treated with SA-modified BP nanoemulsion recovered and were subsequently challenged with LPS, achieving a 100% survival rate without further medication. In contrast, mice treated with unmodified SA BP nanoemulsion recovered, but the survival rate upon re-challenge was 66.7%. Mice treated with BP solution did not withstand a second LPS challenge and all died. Therefore, the survival rate of sepsis mice with secondary infections after treatment with various BP formulations was: BP-SAE group > BP-CE group > BP-S group. This demonstrates that SA-modified targeted nanoformulations possess excellent long-term efficacy and good safety.

[0118] Table 9 shows the area on the curve and standardized data of relative body weight after secondary infection treatment in each group of mice.

[0119] Table 9. Area on the curve and standardized data of relative body weight after secondary infection treatment in each group of mice (n = 2–5)

[0120] As shown in Figure 3 and Table 9, the relative body weight change curves of the BP-SAE group and the BP-CE group were complete, with areas on the curves of 0.605±0.043 and 1.347±0.118, respectively. This fully demonstrates that the BP-SAE group was less affected by secondary infection and recovered faster. In summary, the data indicate that mice in the BP-SAE treatment group spontaneously and rapidly responded to and cleared the invaders after secondary infection, suggesting that the drug may have a long-term regulatory effect on the immune system, demonstrating the advantage of SA-modified targeted nanoparticles in reducing mortality from sepsis-related secondary infections.

[0121] The survival rate of each group after secondary infection was calculated as the ratio of the area under the relative body weight curve (S2 / A2), as shown in Table 10.

[0122] Table 10 S2 / A2 values ​​of mice after secondary infection treatment in each group

[0123] Table 10 shows that mice in the BP-SAE, BP-CE, and BP-S groups developed varying degrees of immune memory after being challenged a second time with lipopolysaccharide (LPS), which can be categorized as "strong, moderate, and weak immune memory." "Strong immune memory" (or strong immune memory) is a stable and potent acquired immune response, reflecting immune memory established through appropriate treatment. It manifests in long-term efficacy against a disease (or pathogen), excellent prognosis, and even disease cure. The results indicate that septic mice treated with SA-modified BP nanoemulsion exhibited strong immune memory after re-infection with LPS. This is not only reflected in the surprising complete self-healing, but also in the faster recovery rate after secondary infection, further demonstrating that memory cells in the mice can more rapidly and specifically respond to pathogens upon re-encounter, leading to a faster recovery to a healthy state. Furthermore, studies have shown that sepsis patients experience persistent immunosuppression (immune paralysis) for a long period after sepsis, which may lead to increased susceptibility to subsequent infections and increased mortality (this was observed in the solution group of this experiment). The results show that after targeted regulation with SA-modified BP nanoemulsion, the immune system of the mice in this group was not in a state of persistent immunosuppression; instead, the overall immune environment remained healthy and stable. Therefore, upon reinfection, the mice did not die, and their body weight initially decreased and then increased. This indicates that a normal and vigorous immune response can occur in mice, but this response is orderly and steady, without the unresponsive or disordered state of a persistently immunosuppressive immune system.

[0124] "Medium immune memory" (or immune-mediated memory) represents a type of variable memory, falling between "weak memory" and "strong memory." Mice treated with unmodified SA-containing BP nanoemulsion had a 66.7% survival rate after secondary infection, and the surviving mice underwent a relatively long recovery period. The presumed reason is that while BP nanoemulsion treatment could effectively prevent immune dysregulation during cytokine storms, the lack of targeting in BP-CE resulted in incomplete regulation of disease-related immune cell subsets or accidental damage to normal immune cells, potentially leading to a false immune homeostasis (which may actually be an immunosuppressive state). This, in turn, affected the indirect regulation of lymphocytes, resulting in fewer memory lymphocytes produced. Furthermore, immune memory cells may have experienced memory lapses and distortions in the chaotic immune environment during pathogen invasion, i.e., variable memory. Therefore, the response speed is slower, resulting in the phenomenon of "medium immune memory." The specific manifestations of "medium immune memory" will be further elaborated in Example 5.

[0125] "Weak immune memory" (or weak immune memory) represents a type of harmful memory that may not function effectively in complex environments, or even manifest as an unfavorable immune response pattern. The complete death of septic mice treated with BP solution after secondary infection illustrates this weak immune memory. The presumed reason is that while the initial treatment helped the mice survive the early cytokine storm phase of sepsis, the non-targeted BP solution indiscriminately modulates disease-related immune cell subsets, causing damage to healthy immune systems and tissues. Furthermore, the solution is rapidly metabolized in vivo, resulting in limited regulation of lymphocytes. Therefore, the body may not exhibit effective memory function in the complex immune environment of sepsis, and may even mutate or negatively impact prognosis. Immune cells in the solution group, after being damaged by lipopolysaccharide (LPS), may only remember this damage. This memory is negative; upon re-encountering LPS, the immune cells are "frightened" even more quickly and severely, leading to greater damage. Therefore, while the solution group showed a therapeutic effect during the initial infection, the damage caused by subsequent infections was greater.

[0126] The weak immune memory exhibited by the solution group contrasted sharply with the strong or moderate immune memory shown by the nanoparticles, highlighting the importance of nanoparticle development. During initial treatment, nanoparticles, through their targeted action on disease-associated cell populations, particularly disease-associated immune cells and their subsets, regulate immune balance, inhibit the vicious cycle of disease-associated immune cells, and restore the immune system to a healthy homeostasis. When the body is re-exposed to the same or similar pathogens, they can more effectively stimulate the immune system's memory function, resulting in a rapid and powerful response, thereby effectively preventing the occurrence and progression of disease. Although the clinical therapeutic effects of nanoparticles have not yet completely surpassed those of traditional formulations, the differences in the strength, moderateness, and weakness of immune memory highlight the unique value of nanoparticles compared to traditional formulations.

[0127] From a pharmacoeconomic perspective, the development of nanomedicines not only helps reduce healthcare costs but also significantly improves patient productivity, alleviates the disease burden on patients and society, and thus promotes sustainable socioeconomic development. However, for solution-based treatments, due to the problem of weak immune memory, although initial treatment may show some effect, patients may experience a disease flare-up upon subsequent exposure to the same pathogen, leading to sudden and severe disease progression or even death. This illustrates that while cost reductions and improved quality of life can be observed in the short term, in the long run, the continued development of nanomedicines is key to reducing the cost of repeat treatments and preventing disease deterioration, which is also an important factor in promoting sustainable socioeconomic development. The development of nanomedicines will be an important direction for the pharmaceutical industry, laying a solid foundation for building a healthier society.

[0128] This approach of categorizing immune memory into strong, moderate, and weak levels represents a significant breakthrough in our understanding of the immune system's response mechanisms and the relationship between nanomedicine delivery systems and the immune system, expanding the boundaries of knowledge in immunology. This concept holds promise for playing a crucial role in designing more effective treatment strategies, particularly in targeted cancer therapy. It goes beyond simply focusing on the fractional degree of tumor penetration by nanoparticles; it considers the overall immune status of the patient. The role of nanoparticles in cancer treatment extends far beyond simple tumor cell targeting; they can modulate the entire immune system, thereby improving treatment outcomes on a broader scale. Analyzing and classifying immune memory into strong, moderate, and weak levels allows for a deeper understanding of how nanoparticles positively regulate the immune system at a macroscopic level.

[0129] Furthermore, the treatment index was calculated. According to the formula, the treatment index is the sum of the treatment index results from multiple infection experiments. Therefore, the data from secondary infections were combined with the T value of the first treatment for sepsis in Example 3. index The total T value was obtained for each group of mice after secondary infection treatment. indexThe values ​​are shown in Table 11.

[0130] Table 11 T values ​​of mice after secondary infection treatment in each group index value

[0131] The analysis of data from both primary and secondary infections in Table 11 shows that, among these drugs, SA-modified budesonide palmitate nanoemulsion has the best efficacy (T...). index =4.07); followed by unmodified SA budesonide palmitate nanoemulsion (T index =1.74); again, budesonide palmitate solution (T index =0.57); while dexamethasone sodium phosphate solution had the worst effect, T index =0.

[0132] In summary, it can be seen that the treatment index T index This allows for a more accurate reflection of the long-term efficacy and safety of drugs. By utilizing the therapeutic index T... index Drug screening allows for a more scientific and objective evaluation of therapeutic effects, providing clinicians and patients with better treatment options.

[0133] Furthermore, the following examples use a treatment index to evaluate the treatment drugs for tertiary sepsis.

[0134] Example 5

[0135] Two months after the secondary infection in Example 4, surviving C57BL / 6 mice from each group were collected: five in the BP-SAE group and two in the BP-CE group. They were then intraperitoneally injected again with the same dose of lipopolysaccharide solution (20 mg / kg) as in the first modeling. Throughout the experiment, the survival rate and body weight of the mice were monitored and recorded for 10 days. Data were processed according to the method in Example 2, and the treatment index was calculated.

[0136] The results are analyzed as follows:

[0137] Figure 4 shows the survival curves, relative body weight curves, and total treatment index (T) of mice in each group after three infections in Example 5. index )picture.

[0138] Table 12 shows the survival rate and standardized data of mice in each group after three infection treatments.

[0139] Table 12 Survival rates and standardized data of mice in each group after three infection treatments (n = 2–5)

[0140] After three infections, one of the five mice in the BP-SAE group died, resulting in a 10-day survival rate of 80%. In contrast, both mice in the BP-CE group died after three infections. The survival rate of septic mice after three infections was: BP-SAE group > BP-CE group. It should be noted that the strong (moderate) memory developed in the mice after three infections can be defined as "memory-type immune tolerance."

[0141] Table 13 shows the area on the relative body weight curve and standardized data of mice after three infection treatments in each group.

[0142] Table 13. Area on the curve and standardized data of relative body weight after three infection treatments in each group of mice (n = 2–5)

[0143] As shown in Figure 4 and Table 13, only the BP-SAE group had a complete relative body weight change curve, with an area under the curve of 0.800 ± 0.046. Mice in the BP-CE group died during the process of body weight loss.

[0144] The ratio of survival rate to area under the relative body weight curve (S3 / A3) for each group after three infections was calculated, as shown in Table 14.

[0145] Table 14 S3 / A3 values ​​of mice after three infection treatments in each group

[0146] The data in Table 14 further illustrate that the BP-SAE group mice developed strong immune memory, while the BP-CE group mice had significantly weaker immune memory than the BP-SAE group, which can be defined as "intermediate immune memory" (or immune memory in the middle). Specifically, it manifests in three aspects: (1) moderate memory capacity: the immune system's memory capacity for previously encountered pathogens or antigens may not be as strong as in the "strong memory" state, but it is not as lost or unfriendly as in the "weak memory" state; (2) short memory duration: the immune system may retain the memory of previous pathogens for a relatively short period of time, and then gradually forget it, unlike the "strong memory" state which is long-lasting; (3) susceptible to interference: similar to how human memory may be affected by interference or interference, the "intermediate immune memory" of the immune system may also be easily affected by other immune responses, leading to memory instability.

[0147] Furthermore, the treatment index was calculated. According to the formula, the treatment index is the sum of the treatment index results from multiple infection experiments. Therefore, the data from the three infections were combined with the T values ​​after the second treatment for sepsis in Example 4. index The total T value was obtained for each group of mice after three infection treatments. index The values ​​are shown in Table 15.

[0148] Table 15 T values ​​of mice after infection and treatment in each groupindex value

[0149] As can be seen from Table 15, among these pharmaceutical formulations, the SA-modified budesonide palmitate nanoemulsion showed the best efficacy (T...). index =5.25); followed by unmodified SA budesonide palmitate nanoemulsion (T index =1.74); again, budesonide palmitate solution (T index =0.57); dexamethasone sodium phosphate solution had the worst effect. Clearly, using the therapeutic index T... index Multiple summations of this index can further amplify the differences in therapeutic effects between different groups of preparations. Using this index to assess and compare the overall performance of various drugs can help identify the most effective and safest medications for sepsis patients.

[0150] Example 6

[0151] This embodiment uses a therapeutic index to evaluate the efficacy of different drug carriers in treating sepsis.

[0152] Following the formulation process of SA-modified budesonide palmitate emulsion (BP-SAE) in Example 1, SA-modified dexamethasone palmitate emulsion (DP-SAE) was prepared. SA-modified budesonide palmitate emulsion (BP-SAL) and SA-modified dexamethasone palmitate liposomes (DP-SAL) were prepared according to the preparation method of SA-modified dexamethasone palmitate liposomes in patent (application number: 202010515302.8, patent title: Sialic Acid Modified Dexamethasone Palmitate Liposomes and Their Preparation and Application, paragraphs 0057-0074). Related pharmacodynamic studies were conducted according to Example 2 (dose: 4 mg / kg), and the survival rate and body weight of mice were monitored and recorded for 10 days. Data were processed according to the method in Example 2, and the therapeutic index was calculated.

[0153] Figure 5 shows the survival curves, relative body weight curves, and treatment indices (T0.05) of mice treated with SA-modified BP and DP nanoemulsions in Example 6. index )picture.

[0154] Table 16 shows the survival rate and standardized data of mice in each group after infection treatment.

[0155] Table 16 Survival rates and standardized data of mice after infection treatment in each group (n=4)

[0156] As shown in Figure 5 and Table 16, all groups exhibited good treatment effects. The BP-SAE group showed the best treatment effect, with a mouse survival rate of 100%. The BP-SAL and DP-SAE groups had the same survival rate of 75%, requiring further analysis of body weight changes. The DP-SAL group had a relatively low survival rate of 50%.

[0157] The area on the relative body weight curve and the standardized data of mice after infection and treatment in each group are shown in Table 17.

[0158] Table 17. Area on the curve and standardized data of relative body weight after infection and treatment in each group of mice (n=4)

[0159] As can be seen from Figure 5 and Table 17, the relative body weight change curves of the BP-SAE group, BP-SAL group, DP-SAE group and DP-SAL group are complete. By comparing the area on the relative body weight curve, it can be clearly seen that the BP-SAE group has the smallest body weight fluctuation affected by sepsis and the best treatment effect.

[0160] Furthermore, the treatment index T was calculated. index The results are shown in Table 18.

[0161] Table 18. T values ​​of mice after infection and treatment in each group index value

[0162] Based on the data in Table 18, the T values ​​for different groups treating sepsis... index The values ​​were: BP-SAE (1.94), BP-SAL (1.08), DP-SAE (0.96), DP-SAL (0.53), and 5% Glu (0). Among these drug formulations, the SA-modified BP nanoemulsion exhibited the best overall therapeutic effect, demonstrating the importance of SA modification for therapeutic efficacy and highlighting the influence of different drug carriers. The results showed that the effect of SA-modified liposomes was not as good as that of emulsions, possibly due to the influence of the liposome bilayer. Some SA was distributed in the inner aqueous phase during liposome preparation, resulting in the surface modification density not reaching the optimal 10 mol%, thus reducing targeting and preventing effective targeting to disease-related immune cell populations. The structure of the emulsion determined that SA was only distributed on the surface of the emulsion and would not enter the interior of the emulsion, ensuring that the SA surface modification ratio remained stable at the optimal ratio (10 mol%).

[0163] Example 7

[0164] This embodiment uses the therapeutic index to evaluate the efficacy of SA-modified nanoemulsions used in other commonly used treatments for sepsis.

[0165] Following the formulation process of SA-modified budesonide palmitate emulsion (BP-SAE) in Example 1, SA-modified dexamethasone palmitate emulsion (DP-SAE), SA-modified triamcinolone palmitate emulsion (TP-SAE), SA-modified prednisolone palmitate (PP-SAE), and SA-modified hydrocortisone palmitate (HP-SAE) were prepared. Pharmacodynamic studies were conducted according to Example 2 (dose of 4 mg / kg), and the survival rate and body weight of mice were monitored and recorded for 10 days. Data were processed according to the method in Example 2, and the therapeutic index was calculated.

[0166] Note: The dosage of all drugs used in the evaluation was fixed at 4 mg / kg. This is somewhat unreasonable, but the purpose of fixing the dosage is to reduce variables, simplify the analysis of data, and shorten the screening study period.

[0167] Figure 6 shows the survival curves, relative body weight curves, and treatment indices (T0.05) of mice treated with different drug emulsions in Example 7. index )picture.

[0168] Table 19 shows the survival rate and standardized data of mice in each group after infection and treatment.

[0169] Table 19 Survival rates and standardized data of mice after infection treatment in each group (n=4)

[0170] As shown in Figure 6 and Table 19, the BP-SAE group had the best treatment effect, with a mouse survival rate of 100%. The DP-SAE group followed (75%). The TP-SAE and PP-SAE groups had the same survival rate of 25%, requiring further analysis of body weight changes. While the HP-SAE group could prolong the survival time of mice to some extent, it did not improve the survival rate.

[0171] The area under the curve and standardized data of relative body weight after infection and treatment in each group of mice are shown in Table 20.

[0172] Table 20. Area on the curve and standardized data of relative body weight after infection and treatment in each group of mice (n=4)

[0173] As can be seen from Figure 6 and Table 20, the relative body weight change curves of the BP-SAE group, DP-SAE group, TP-SAE group and PP-SAE group are complete. By comparing the area on the relative body weight curve, it can be clearly seen that the BP-SAE group has the smallest body weight fluctuation affected by sepsis and the best treatment effect.

[0174] Furthermore, the treatment index T was calculated. index The results are shown in Table 21.

[0175] Table 21 T values ​​of mice after infection and treatment in each group index value

[0176] Table 21 shows the T values ​​of various drug preparations for treating sepsis. index The values ​​were: BP-SAE (2.81), DP-SAE (1.74), TP-SAE (0.46), PP-SAE (0.32), HP-SAE (0), and 5% Glu (0). These data clearly reveal the differences in the therapeutic effects of nanoemulsions, a commonly used treatment for sepsis, and confirm the T... index The effectiveness of this assessment indicator is highlighted. This result underscores that the use of SA-modified BP nanoemulsions may be a more effective treatment strategy for sepsis, possessing the greatest potential for development. This is significant for the development of more effective sepsis treatments and provides new options for clinical treatment.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Industrial applicability

[0178] This invention provides a drug screening method, apparatus, and electronic device based on a therapeutic index. This invention combines two important evaluation indicators for pharmacodynamic experimental animal models: survival rate and body weight. By cleverly converting body weight data into area on a relative body weight curve, and further standardizing it in sync with survival rate data, a formula for calculating the therapeutic index is constructed for drug screening. This drug screening method organically combines survival rate and body weight data, objectively reflecting disease progression and prognosis, effectively amplifying the differences in efficacy between different drug treatment groups, and more accurately, conveniently, and comprehensively screening for drugs with excellent overall effects. This significantly reduces the development cost of new drugs and provides more accurate data support for clinical and experimental research, demonstrating good economic value and application prospects.

Claims

1. Application of the area under the relative weight curve in constructing drug screening models; The relative body mass refers to the ratio of the experimental animal's body mass to its initial body mass; The area on the relative body mass curve refers to the curve plotted with different time points as the x-axis and the relative body mass of the experimental animal as the y-axis, showing the change of relative body mass over time. Using the initial relative body mass as a baseline, the area between the curve and the baseline is the area on the relative body mass curve.

2. The application according to claim 1, characterized in that, The mathematical expression for the baseline is Y = 1, where Y represents the ordinate.

3. A method for constructing a drug screening model, characterized in that, include: (1) Prepare experimental animal models of diseases and obtain data on the survival rate and body weight of experimental animals after administration of drugs; (2) Obtain the area on the relative body mass curve based on the body mass data, wherein the definition of the area on the relative body mass curve is the same as in claim 1; (3) The area data on the survival rate and relative body weight curves were standardized by the summation normalization method to construct a drug screening model.

4. A drug screening method, characterized in that, include: To obtain data on the survival rate and body weight of laboratory animals; Body weight data is converted into area on the relative body weight curve (AUC) data, and the survival rate and AUC data are standardized using the summation normalization method. The treatment index is calculated based on the standardized data to assess drug efficacy. The formula for calculating the treatment index is as follows: n represents the number of experiments, Si is the survival rate data after standardization using the summation normalization method, and Ai is the area on the relative body mass curve after standardization using the summation normalization method. The definition of the area on the relative body mass curve is the same as that in claim 1.

5. The screening method according to claim 4, characterized in that, The higher the therapeutic index value, the better the therapeutic effect and the higher the safety of the drug.

6. The screening method according to claim 4, characterized in that, The diseases for which the drug treatment is administered are those for which the efficacy of the drug needs to be evaluated through at least two indicators: survival rate and body weight.

7. The screening method according to claim 6, characterized in that, The disease is at least one of the following: tumor, cardiovascular disease, infectious disease, metabolic disease, and autoimmune disease.

8. The screening method according to claim 6, characterized in that, The disease in question is sepsis.

9. The screening method according to claim 8, characterized in that, A sepsis animal model was established by stimulating experimental animals with lipopolysaccharide (LPS). Survival rate and body weight data of the experimental animals were obtained after drug treatment.

10. The screening method according to claim 9, characterized in that, The method for preparing the experimental animal model of sepsis includes: taking 8-10 week old mice and preparing the experimental animal model of sepsis by intraperitoneal injection of lipopolysaccharide solution.

11. The screening method according to claim 10, characterized in that, The immune memory of experimental animals against sepsis was examined by repeatedly injecting lipopolysaccharide solution into the peritoneum.

12. A drug screening device, characterized in that, include: The data acquisition module is used to acquire data on the survival rate and body weight of laboratory animals. The data processing module is used to convert body weight data into area on the relative body weight curve (AUC) data, and to standardize the survival rate and AUC data using the summation normalization method. The treatment index is then calculated based on the standardized data. The formula for calculating the treatment index is as follows: n represents the number of experiments, Si is the survival rate data after standardization using the summation normalization method, and Ai is the area on the relative body mass curve after standardization using the summation normalization method. The definition of the area on the relative mass curve is the same as that in claim 1; The efficacy evaluation module is used to output efficacy evaluation conclusions based on the treatment index.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the drug screening method as described in any one of claims 4 to 11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the drug screening method as described in any one of claims 4 to 11.

15. The application of the method for constructing the drug screening model according to claim 3, the drug screening method according to any one of claims 4 to 11, the drug screening device according to claim 12, the electronic device according to claim 13, or the computer-readable storage medium according to claim 14 in the preparation of products for drug screening.

16. A sialic acid-modified budesonide palmitate nanoemulsion, characterized in that, Its raw materials include: MCT, DPPC, DPPG-Na, BP and SA-CH; wherein, the molar ratio of SA-CH to phospholipid is 5 mol% to 25 mol%, preferably 10 mol% to 15 mol%, and most preferably 10 mol%.

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