A method and system for extracting and filtering biopharmaceutical liquid

Abstract

The present invention relates to the field of biopharmaceutical technology, and discloses a method and system for extracting and filtering a medicinal liquid for biopharmaceuticals. The impurity content of the filtered medicinal liquid is evaluated, and the necessity of adjusting the medicinal liquid filtration process is judged by the impurity content evaluation score; if there is a necessity for adjustment, the centrifugal speed of the medicinal liquid filtration process and the impurity content evaluation score are linearly correlated. If a linear correlation exists, the first adjustment amount of the centrifugal speed is calculated; the filtered medicinal liquid is obtained using the adjusted centrifugal speed, and the biological activity is analyzed to obtain a biological activity score to judge whether the biological activity of the medicinal liquid meets the standard. The present invention also provides a dual protection mechanism, which avoids the filtration quality being affected by reverse adjustment by judging the consistency of the adjustment direction. For example, after the centrifugal speed is increased for the first time, the secondary adjustment is automatically terminated if it needs to be reduced to ensure process stability.

Description

Technical Field

[0001] The present invention relates to the technical field of biopharmaceuticals, and in particular to a method and system for extracting and filtering a biopharmaceutical liquid. Background Art

[0002] Biopharmaceuticals refer to a class of products used for prevention, treatment, and diagnosis that are manufactured using organisms, biological tissues, cells, and body fluids, utilizing research results from biology, medicine, and biochemistry, and integrating the principles and methods of physics, chemistry, biochemistry, biotechnology, and pharmacy. Biopharmaceuticals have very high purity requirements and require biological separation and purification technologies to remove harmful substances or impurities without destroying the activity of the target product.

[0003] However, the current analysis and processing of filtered drug liquids in the biopharmaceutical process often focuses on the effectiveness of two aspects: impurity content and biological activity. However, there is a lack of dual protection judgment to establish adjustments between impurity control and activity retention. Adjustment conflicts may occur during the production process. For example, reducing the centrifugation speed to retain activity may lead to excessive impurities. Excessive impurities require increasing the speed, which causes activity to be damaged again, thereby affecting production efficiency. Summary of the Invention

[0004] The object of the present invention is to provide a method and system for extracting and filtering a biopharmaceutical liquid to solve at least one of the above-mentioned problems in the prior art.

[0005] In a first aspect, the present invention provides a method for extracting and filtering a biopharmaceutical liquid, comprising the following steps:

[0006] Evaluate the impurity content of the filtered liquid and determine the necessity of adjusting the liquid filtration process based on the impurity content evaluation score;

[0007] If adjustment is necessary, the centrifugal speed during the drug liquid filtration process and the impurity content assessment score are linearly correlated. If a linear correlation exists, the initial adjustment amount of the centrifugal speed is calculated;

[0008] The filtered drug solution is obtained using the adjusted centrifugal speed, and the biological activity is analyzed to obtain a biological activity score to determine whether the biological activity of the drug solution meets the standard;

[0009] If the biological activity of the drug solution does not meet the standard, the linear correlation between the centrifugal speed and the biological activity score during the drug solution filtration process is determined. If a linear correlation exists, the secondary adjustment amount of the centrifugal speed is calculated;

[0010] Whether to perform a secondary adjustment on the centrifugal speed is determined according to the adjustment directions of the secondary adjustment amount of the centrifugal speed and the primary adjustment amount of the centrifugal speed.

[0011] In a second aspect, the present invention provides a biopharmaceutical liquid extraction and filtration system, the system comprising:

[0012] Adjustment Necessity Analysis Module: Evaluates the impurity content of the filtered liquid and determines the necessity of adjustment of the liquid filtration process based on the impurity content evaluation score;

[0013] First adjustment analysis module: If adjustment is necessary, the centrifugal speed and impurity content assessment score of the liquid filtration process are linearly correlated. If a linear correlation exists, the first adjustment amount of the centrifugal speed is calculated;

[0014] Activity judgment module: Use the adjusted centrifugal speed to obtain the filtered drug solution, analyze the biological activity to obtain a biological activity score, and judge whether the biological activity of the drug solution meets the standard;

[0015] Secondary adjustment analysis module: If the biological activity of the drug solution does not meet the standard, the centrifugal speed during the drug solution filtration process and the biological activity score are linearly correlated. If a linear correlation exists, the secondary adjustment amount of the centrifugal speed is calculated;

[0016] Adjustment direction analysis module: determines whether to perform secondary adjustment on the centrifugal speed according to the adjustment direction of the secondary adjustment amount of the centrifugal speed and the primary adjustment amount of the centrifugal speed.

[0017] Beneficial effects of the present invention:

[0018] This invention utilizes a closed-loop process of "impurity detection - centrifugation parameter adjustment - bioactivity verification" to ensure that drug solutions simultaneously meet both impurity content standards and bioactivity requirements, increasing the efficiency of the biopharmaceutical drug solution filtration process. Furthermore, a linear regression model is established based on historical data, linking centrifugation speed with impurities and activity, enabling precise calculation of adjustment amounts, enabling targeted parameter optimization and reducing trial-and-error costs.

[0019] The present invention also provides a dual protection mechanism, which avoids the impact on filtration quality caused by reverse adjustment by judging the consistency of the adjustment direction. For example, after the centrifugal speed is increased for the first time, if the secondary adjustment needs to be reduced, it will be automatically terminated to ensure process stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 This is a flow chart of a method for extracting and filtering a biopharmaceutical liquid according to the present invention;

[0022] Figure 2 The present invention is a schematic structural diagram of a biopharmaceutical liquid extraction and filtration system. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0024] Example 1: The centrifugal rate directly affects the separation efficiency of impurities in the drug solution and may also damage the protein structure through mechanical stress. Therefore, the centrifugal rate is the link between "impurity control" and "activity retention";

[0025] like Figure 1 As shown, an embodiment of the present invention provides a method for extracting and filtering a biopharmaceutical liquid, which specifically includes steps S1 to S5. These steps are described in detail below:

[0026] S1: Evaluate the impurity content of the filtered liquid and determine the necessity of adjusting the liquid filtration process based on the impurity content evaluation score;

[0027] In this embodiment, a sterile sampling valve is installed at the end of the biopharmaceutical liquid filtration system to sample the filtered liquid. The number of samples can be several, and the samples are marked with the serial number, time and sampling point.

[0028] Processing the sampled sample, wherein the processing process includes: if the sample is turbid, centrifuging to remove particulate impurities, and refrigerating the sample at 2-8°C;

[0029] A preferred embodiment of this step includes: detecting the impurity content of the drug solution by multiple indicators;

[0030] Among them, the types of impurities in the drug solution include: physical impurities, chemical impurities and biological impurities;

[0031] Specifically, physical impurity indicators include: particulate impurities and visible foreign matter; chemical impurity indicators include: protein aggregates, DNA residues and host cell proteins; biological impurity indicators include: endomycin;

[0032] Furthermore, according to the impurity type, multi-index combined detection is adopted, specifically:

[0033] For physical impurity index detection: use light scattering method or microscope counting method to count particles; use light inspection method or machine vision inspection to check for visible foreign matter;

[0034] For the detection of chemical impurities: size exclusion chromatography or dynamic light scattering (DLS) is used to detect protein aggregates; fluorescent quantitative PCR and DNA hybridization are used to detect DNA residues; and enzyme-linked immunosorbent assay is used to detect host cell proteins.

[0035] For the detection of biological impurities: endotoxin detection is carried out using the Limulus amebocyte lysate method and the kinetic turbidity method;

[0036] For the multi-index impurities detected, a fuzzy comprehensive evaluation method is used to obtain multi-level comprehensive quantitative evaluation indicators. The specific process is as follows:

[0037] Determine the evaluation level, specifically: the first-level indicator of the evaluation level is: U = {physical impurities, chemical impurities, biological impurities};

[0038] The secondary indicators of the evaluation level are: physical impurities U1 = {particulate impurities, visible foreign matter}; chemical impurities U2 = {protein aggregates, DNA residues, host cell proteins}; biological impurities U3 = {endotoxins};

[0039] Set a 5-level evaluation system and assign quantitative scores: V = {V1 (excellent, 90-100), V2 (good, 80-90), V3 (qualified, 70-80), V4 (nearly unqualified, 60-70), V5 (unqualified, <60)};

[0040] According to the relationship between the test value and the standard, the membership degree of each indicator to each comment is calculated through the membership function; for each secondary indicator under the first-level indicator, the membership degree is calculated to form a matrix;

[0041] Determine the indicator weights through expert scoring;

[0042] Perform fuzzy synthesis on each first-level indicator, i.e., the weights on the membership vector of each comment;

[0043] The membership matrix of the first-level indicators Combined with the first-level weight W=(0.2, 0.3, 0.5), we get the final comprehensive evaluation vector:

[0044] Select the evaluation level with the highest membership (e.g. B=(0.2, 0.3, 0.4, 0.1, 0) corresponds to passing);

[0045] The weighted average method is used to calculate the comprehensive evaluation score as the impurity content evaluation score;

[0046] If the impurity content assessment score is greater than the score limit, it means that the filtration process is qualified and a signal is generated that no adjustment is necessary;

[0047] If the impurity content assessment score is less than or equal to the score limit, it means that the filtration process is unqualified and a high signal of necessity for adjustment is generated;

[0048] The effectiveness of using multiple indicators to comprehensively evaluate the impurity content of the filtered drug solution is as follows: if a single indicator is used, other types of impurities are easily overlooked. Using fuzzy comprehensive evaluation to quantify risks reduces subjective judgment.

[0049] S2: If a high adjustment necessity signal is generated, a linear correlation is determined between the centrifugal speed and the impurity content assessment score during the liquid filtration process. If a linear correlation exists, the initial adjustment amount for the centrifugal speed is calculated based on the correlation relationship.

[0050] In this step, first, specifically, the process of determining the linear correlation between the centrifugal speed and the impurity content evaluation score during the liquid medicine filtration process is as follows:

[0051] Based on historical data, obtain a centrifugal speed data sequence and a corresponding impurity content assessment score sequence;

[0052] The Pearson correlation coefficient was used to determine whether there was a linear correlation between the centrifugal speed and the impurity content assessment score. The specific process was as follows:

[0053] The calculation formula of Pearson correlation coefficient r is: ;in, and Respectively represent the evaluation scores of the i-th centrifugal speed and impurity content, and represent the mean of centrifugal speed and the mean of impurity content assessment score respectively;

[0054] Based on the calculated Pearson correlation coefficient, combined with the hypothesis test, it is determined whether the linear correlation is significant, specifically:

[0055] The null hypothesis, that is, assuming that there is no linear correlation between the centrifugal speed data sequence and the impurity content assessment score sequence, that is, r = 0, is the starting point of the test;

[0056] The alternative hypothesis is opposite to the null hypothesis, that is, it is assumed that there is a linear correlation between the centrifugal speed data series and the impurity content assessment score series, that is, r≠0. If there is sufficient evidence to reject the null hypothesis, the alternative hypothesis is supported, proving that there is a linear correlation between the data;

[0057] Calculate the test statistic t, the calculation formula is: ; Where n represents the number of data;

[0058] The Pearson correlation coefficient is converted into a statistic that obeys the t distribution with degrees of freedom df=n-2, which is used to measure whether the difference between r and 0 is significant;

[0059] Degrees of freedom represent the number of independent variables when calculating a statistic. In correlation analysis, since two parameters need to be estimated (the slope and intercept of the regression line), 2 is subtracted from the sample size n.

[0060] Calculate the p-value through t-distribution, and find the corresponding probability range based on the t-value and degrees of freedom by looking up the t-distribution critical value table;

[0061] Use statistical tools, such as Excel's T.DIST.2T function or Python's scipy.stats.t.sf function, to input the t value and degrees of freedom and directly output the p value;

[0062] Compare the p-value to the significance level α, where the significance level α is usually set to 0.05;

[0063] If p≤α, it means that under the premise that the null hypothesis is true, the probability of observing the current data (or more extreme data) is extremely low (less than 5%). In this case, the null hypothesis is rejected, that is, there is a linear correlation between centrifugal speed and impurity content assessment score;

[0064] Otherwise, it is determined that there is no linear correlation between the centrifugal speed and the impurity content assessment score; based on the absence of a linear correlation, other parameters are analyzed;

[0065] In this step, the second specific process of calculating the centrifugal speed adjustment amount according to the correlation relationship includes: constructing a linear regression equation based on the centrifugal speed data sequence and the impurity content assessment score sequence, and then calculating the first centrifugal speed adjustment amount through the linear regression equation;

[0066] Furthermore, a preferred embodiment of this step includes:

[0067] With centrifugal speed as the X value and impurity content assessment score as the y value, linear regression is performed on the centrifugal speed data series and the impurity content assessment score series. The linear regression equation is: ;

[0068] Calculate the intercept a and slope b of the regression coefficient in the linear regression equation respectively;

[0069] Specifically, the calculation formula of the slope b is: ; The calculation formula for intercept a is: ;

[0070] Construct a linear regression equation based on intercept a and slope b;

[0071] Setting a target impurity content assessment score, inputting the target impurity content assessment score into a linear regression equation, and outputting a target value for the first adjustment of the centrifugal speed;

[0072] Calculating a first adjustment amount of the centrifugal speed based on the current centrifugal speed and the first adjustment target value of the centrifugal speed;

[0073] The centrifugal speed of the liquid medicine filtration process is adjusted by the first adjustment of the centrifugal speed;

[0074] In this embodiment, the effect of S2 is to analyze the quantitative correlation between centrifugal speed and impurity content through Pearson correlation analysis and linear regression model, thereby improving the adjustment efficiency;

[0075] S3: Continue filtering the drug solution using the adjusted centrifugal speed, analyze the biological activity of the filtered drug solution to obtain a biological activity score, and determine whether the biological activity of the drug solution meets the standard;

[0076] In this step, after the centrifugal speed is adjusted for the first time, the liquid medicine is filtered and then sampled, wherein the sampling point remains the same as the sampling point in S1;

[0077] The specific process of drug solution bioactivity testing includes the testing of two indicators: functional activity and structural integrity;

[0078] First, specifically, the functional activity detection process includes: determining relative activity units using a cell proliferation inhibition assay;

[0079] Select cell lines that are sensitive to the target drug and culture them in appropriate culture medium until the logarithmic growth phase;

[0080] Adjust the cell density (e.g. ells / well), seeded into 96-well plates and cultured for 24 h;

[0081] Dilute the drug solution into gradient concentrations (e.g., 100 ng / mL, 10 ng / mL, 1 ng / mL) and add it to the wells, with 3-6 replicate wells per group.

[0082] Set up negative control (no drug) and positive control (standard drug) at the same time;

[0083] After 48-72 hours of culture, add cell viability dye (such as CCK-8, MTT) and incubate for 2 hours;

[0084] The absorbance is measured using an enzyme-labeled instrument (e.g., at a wavelength of 450 nm) to calculate the cell viability. The calculation formula for the cell viability is: ;

[0085] Dose-response curves were drawn and fitted to obtain the concentration of drug that inhibited 50% cell proliferation ( ), the calculation formula of relative activity unit is: ;

[0086] The second specific structural integrity testing process includes:

[0087] Circular dichroism (CD) spectroscopy is used to detect secondary structure. The process is as follows: dilute the drug solution to 0.1-1 mg / mL and place it in a quartz cuvette; scan the wavelength from 190-260 nm on a CD spectrometer and record the ellipticity (θ); perform baseline correction (subtracting the buffer background); fit the spectrum using software (such as CDPro) and calculate the percentage of each secondary structure.

[0088] The relative activity units and the secondary structure percentage were weighted to obtain the bioactivity score;

[0089] If the biological activity is greater than or equal to the biological activity limit, the biological activity of the filtered liquid meets the standard;

[0090] If the biological activity is less than the biological activity limit, the biological activity of the filtered liquid does not meet the standard;

[0091] S4: If the biological activity of the drug solution does not meet the standard, the centrifugal speed during the drug solution filtration process and the biological activity score are linearly correlated. If a linear correlation exists, the secondary adjustment amount of the centrifugal speed is calculated based on the correlation relationship;

[0092] In this step, the first specific process of determining the linear correlation between the centrifugal speed and the biological activity during the drug liquid filtration process is:

[0093] Based on historical data, a centrifugal speed data sequence and a corresponding biological activity score sequence are obtained;

[0094] The Pearson correlation coefficient was used to determine whether there was a linear correlation between centrifugation speed and bioactivity score. The specific process was as follows:

[0095] The calculation formula of Pearson correlation coefficient r is: ;in, and represent the jth centrifugal speed and bioactivity score, respectively. and represent the mean of centrifugation speed and the mean of bioactivity score, respectively;

[0096] Based on the calculated Pearson correlation coefficient, combined with the hypothesis test, it is determined whether the linear correlation is significant, specifically:

[0097] The null hypothesis, that is, assuming that there is no linear correlation between the centrifugal speed data series and the biological activity score series, that is, r = 0, is the starting point of the test;

[0098] The alternative hypothesis is opposite to the null hypothesis, that is, it is assumed that the centrifugal velocity data series and the biological activity score series are linearly correlated, that is, r≠0. If there is sufficient evidence to reject the null hypothesis, the alternative hypothesis is supported, proving that there is a linear correlation between the data;

[0099] Calculate the test statistic t, the calculation formula is: ; Where n represents the number of data;

[0100] The Pearson correlation coefficient is converted into a statistic that obeys the t distribution with degrees of freedom df=n-2, which is used to measure whether the difference between r and 0 is significant;

[0101] The degrees of freedom represent the number of independent variables when calculating a statistic. In correlation analysis, since two parameters need to be estimated (the slope and intercept of the regression line), 2 is subtracted from the sample size n.

[0102] Calculate the p-value through t-distribution, and find the corresponding probability range based on the t-value and degrees of freedom by looking up the t-distribution critical value table;

[0103] Use statistical tools, such as Excel's T.DIST.2T function or Python's scipy.stats.t.sf function, to input the t value and degrees of freedom and directly output the p value;

[0104] Compare the p-value to the significance level α, where the significance level α is usually set to 0.05;

[0105] If p≤α, it means that under the premise that the null hypothesis is true, the probability of observing the current data (or more extreme data) is extremely low (less than 5%). In this case, the null hypothesis is rejected, that is, there is a linear correlation between centrifugation speed and bioactivity score;

[0106] Otherwise, it is determined that there is no linear correlation between the centrifugal speed and the bioactivity score; based on the absence of a linear correlation, other parameters are analyzed;

[0107] In this step, the second specific process of calculating the centrifugal speed adjustment amount according to the correlation relationship includes: constructing a linear regression equation based on the centrifugal speed data sequence and the biological activity score sequence, and then calculating the centrifugal speed secondary adjustment amount through the linear regression equation;

[0108] Furthermore, a preferred embodiment of this step includes:

[0109] With centrifugal speed as the X value and impurity content assessment score as the y value, linear regression is performed on the centrifugal speed data series and the impurity content assessment score series. The linear regression equation is: ;

[0110] Calculate the intercept c and slope d of the regression coefficient in the linear regression equation respectively;

[0111] Specifically, the calculation formula of the slope d is: ; The calculation formula for intercept c is: ;

[0112] Construct a linear regression equation based on the intercept c and slope d;

[0113] Setting a target bioactivity score, inputting the target bioactivity score into a linear regression equation, and outputting a secondary adjustment target value for the centrifugal speed;

[0114] Based on the initial centrifugal speed and the centrifugal speed secondary adjustment target value, a centrifugal speed secondary adjustment amount is calculated;

[0115] In this embodiment, the effect of S4 is that after the initial centrifugal speed adjustment, the effectiveness is verified by biological activity testing. If the activity does not meet the standard, a secondary adjustment analysis is initiated, forming a closed-loop control of impurity control → activity verification → parameter optimization, so that the drug solution preparation meets both the impurity standard and the biological activity requirement, thereby improving production efficiency.

[0116] S5: determining whether the adjustment direction of the secondary adjustment amount of the centrifugal speed is the same as the adjustment direction of the primary adjustment amount of the centrifugal speed; if so, performing a secondary adjustment on the centrifugal speed;

[0117] In this step, the adjustment directions of the first adjustment amount of the centrifugal speed and the second adjustment amount of the centrifugal speed are identified;

[0118] If the first adjustment amount of the centrifugal speed and the second adjustment amount of the centrifugal speed are both increased or decreased, it means that the adjustment directions of the first adjustment amount of the centrifugal speed and the second adjustment amount of the centrifugal speed are consistent;

[0119] Otherwise, it means that the adjustment directions of the first adjustment amount of the centrifugal speed and the second adjustment amount of the centrifugal speed are inconsistent. If they are inconsistent, adjust other parameters;

[0120] If the adjustment direction of the secondary rotation speed adjustment amount is consistent with that of the primary rotation speed adjustment amount, the rotation speed of the crusher is adjusted again according to the secondary rotation speed adjustment amount;

[0121] In this example, the process of S5 is to determine whether the secondary adjustment of the centrifugal speed will affect the impurity content assessment score after the drug solution is filtered. The reason for this determination is that when the centrifugal speed is initially adjusted, the initial adjustment is intended to bring the impurity content assessment score to the target impurity assessment score (i.e., the critical value of the impurity content standard). If the direction of the secondary adjustment of the centrifugal speed is different from that of the initial adjustment of the centrifugal speed (e.g., the initial adjustment of the centrifugal speed increases while the secondary adjustment of the centrifugal speed decreases), continuing the secondary adjustment of the centrifugal speed will affect the impurity content assessment score, causing it to fail to meet the impurity content standard.

[0122] The technical solution of this embodiment is as follows: after terminal sampling, the three major indicators of physical, chemical, and biological properties are tested, and the impurity content score is calculated in combination with fuzzy comprehensive evaluation to determine whether adjustment is triggered; if adjustment is required, the initial adjustment amount of the centrifugal speed is calculated based on the Pearson correlation analysis and linear regression model of historical data to target and improve the impurity score; after adjustment, the functional activity and structural integrity of the drug solution are tested, and the weighted biological activity score is calculated to verify the effectiveness of the process; if the activity does not meet the standard, the correlation between the centrifugal speed and activity is analyzed again to generate a secondary adjustment amount; and the consistency of the adjustment direction is judged to determine whether to execute the secondary adjustment to avoid the risk of impurity exceeding the standard due to reverse adjustment.

[0123] Therefore, the present invention realizes the adjustment of centrifugal speed through closed-loop control of multi-dimensional impurity detection and biological activity verification, combined with statistical models, to improve the production efficiency of biopharmaceutical liquid filtration; fully covers nine impurity indicators including physical, chemical and biological impurities, reducing the risk of missed detection; based on Pearson correlation and linear regression model, realizes targeted optimization of centrifugal speed and performs the first adjustment; and by judging the consistency of the adjustment direction of the first adjustment and the second adjustment, avoids the fluctuation of impurity content in the liquid filtration caused by the reverse adjustment.

[0124] Example 2: Based on the above example, Figure 2 As shown, an embodiment of the present invention provides a biopharmaceutical liquid extraction and filtration system, specifically comprising:

[0125] Adjustment Necessity Analysis Module: Evaluates the impurity content of the filtered liquid and determines the necessity of adjustment of the liquid filtration process based on the impurity content evaluation score;

[0126] In this embodiment, a sterile sampling valve is installed at the end of the biopharmaceutical liquid filtration system to sample the filtered liquid. The number of samples can be several, and the samples are marked with the serial number, time and sampling point.

[0127] Processing the sampled sample, wherein the processing process includes: if the sample is turbid, centrifuging to remove particulate impurities, and refrigerating the sample at 2-8°C;

[0128] Detect the impurity content of the drug solution through multiple indicators;

[0129] Among them, the types of impurities in the drug solution include: physical impurities, chemical impurities and biological impurities;

[0130] Specifically, physical impurity indicators include: particulate impurities and visible foreign matter; chemical impurity indicators include: protein aggregates, DNA residues and host cell proteins; biological impurity indicators include: endomycin;

[0131] Furthermore, according to the impurity type, multi-index combined detection is adopted.

[0132] For the multi-index impurities detected, a fuzzy comprehensive evaluation method is used to obtain multi-level comprehensive quantitative evaluation indicators, and then the impurity content assessment score is calculated;

[0133] If the impurity content assessment score is greater than the score limit, it means that the filtration process is qualified and a signal is generated that no adjustment is necessary;

[0134] If the impurity content assessment score is less than or equal to the score limit, it means that the filtration process is unqualified and a high signal of necessity for adjustment is generated;

[0135] First Adjustment Analysis Module: If a high adjustment necessity signal is generated, a linear correlation is determined between the centrifugal speed and the impurity content assessment score during the liquid filtration process. If a linear correlation exists, the first adjustment amount for the centrifugal speed is calculated based on the correlation relationship.

[0136] In this embodiment, based on historical data, a centrifugal speed data sequence and a corresponding impurity content assessment score sequence are obtained;

[0137] Pearson's correlation coefficient was used to determine whether there was a linear correlation between centrifugation speed and impurity content assessment score;

[0138] Based on the calculated Pearson correlation coefficient, combined with the hypothesis test, determine whether the linear correlation is significant, calculate the test statistic t; calculate the p value through the t distribution;

[0139] Compare the p-value to the significance level α, where the significance level α is usually set to 0.05;

[0140] If p≤α, it means that there is a linear correlation between centrifugal speed and impurity content assessment score;

[0141] Otherwise, it is determined that there is no linear correlation between the centrifugal speed and the impurity content assessment score; based on the absence of a linear correlation, other parameters are analyzed;

[0142] A linear regression equation is constructed based on the centrifugal speed data series and the impurity content evaluation score series;

[0143] Setting a target impurity content assessment score, inputting the target impurity content assessment score into a linear regression equation, and outputting a target value for the first adjustment of the centrifugal speed;

[0144] Calculating a first adjustment amount of the centrifugal speed based on the current centrifugal speed and the first adjustment target value of the centrifugal speed;

[0145] The centrifugal speed of the liquid medicine filtration process is adjusted by the first adjustment of the centrifugal speed;

[0146] Activity judgment module: Use the adjusted centrifugal speed to continue filtering the drug solution, analyze the biological activity of the filtered drug solution to obtain a biological activity score, and judge whether the biological activity of the drug solution meets the standard;

[0147] In this embodiment, after the centrifugal speed is first adjusted, the liquid medicine is filtered and then sampled;

[0148] The specific process of the bioactivity test of the drug solution includes the detection of two indicators: functional activity and structural integrity, and obtaining the relative activity unit and secondary structure percentage;

[0149] The relative activity units and the secondary structure percentage were weighted to obtain the bioactivity score;

[0150] If the biological activity is greater than or equal to the biological activity limit, the biological activity of the filtered liquid meets the standard;

[0151] If the biological activity is less than the biological activity limit, the biological activity of the filtered liquid does not meet the standard;

[0152] Secondary adjustment analysis module: If the biological activity of the drug solution does not meet the standard, the centrifugal speed during the drug solution filtration process and the biological activity score are linearly correlated. If a linear correlation exists, the secondary adjustment amount of the centrifugal speed is calculated based on the correlation relationship;

[0153] In an embodiment, based on historical data, a centrifugal speed data sequence and a corresponding bioactivity score sequence are obtained;

[0154] The Pearson correlation coefficient was used to determine whether there was a linear correlation between centrifugation speed and bioactivity score.

[0155] Based on the calculated Pearson correlation coefficient, combined with the hypothesis test, determine whether the linear correlation is significant, calculate the test statistic t; calculate the p value through the t distribution;

[0156] Compare the p-value to the significance level α, where the significance level α is usually set to 0.05;

[0157] If p ≤ α, it means that there is a linear correlation between centrifugation speed and bioactivity score;

[0158] Otherwise, it is determined that there is no linear correlation between the centrifugal speed and the bioactivity score; based on the absence of a linear correlation, other parameters are analyzed;

[0159] A linear regression equation is constructed based on the centrifugal speed data sequence and the bioactivity score sequence, and then the quadratic adjustment of the centrifugal speed is calculated by the linear regression equation;

[0160] Setting a target bioactivity score, inputting the target bioactivity score into a linear regression equation, and outputting a secondary adjustment target value for the centrifugal speed;

[0161] Based on the initial centrifugal speed and the centrifugal speed secondary adjustment target value, a centrifugal speed secondary adjustment amount is calculated;

[0162] Adjustment direction analysis module: determines whether the adjustment direction of the secondary adjustment amount of the centrifugal speed is the same as the adjustment direction of the first adjustment amount of the centrifugal speed. If they are the same, the centrifugal speed is adjusted twice;

[0163] In the embodiment, the adjustment direction of the first adjustment amount of the centrifugal speed and the second adjustment amount of the centrifugal speed are identified;

[0164] If the first adjustment amount of the centrifugal speed and the second adjustment amount of the centrifugal speed are both increased or both decreased, the rotation speed of the crusher is readjusted according to the second rotation speed adjustment amount.

[0165] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0166] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for extracting and filtering a biopharmaceutical liquid, characterized in that: The following steps are involved: Evaluate the impurity content of the filtered liquid and determine the necessity of adjusting the liquid filtration process based on the impurity content evaluation score; If adjustment is necessary, the centrifugal speed during the drug liquid filtration process and the impurity content assessment score are linearly correlated. If a linear correlation exists, the initial adjustment amount of the centrifugal speed is calculated; The filtered drug solution is obtained using the adjusted centrifugal speed, and the biological activity is analyzed to obtain a biological activity score to determine whether the biological activity of the drug solution meets the standard; If the biological activity of the drug solution does not meet the standard, the linear correlation between the centrifugal speed and the biological activity score during the drug solution filtration process is determined. If a linear correlation exists, the secondary adjustment amount of the centrifugal speed is calculated; Whether to perform a secondary adjustment on the centrifugal speed is determined according to the adjustment directions of the secondary adjustment amount of the centrifugal speed and the primary adjustment amount of the centrifugal speed.

2. A biopharmaceutical liquid extraction and filtration method according to claim 1, characterized in that: The process of determining the necessity of adjusting the liquid medicine filtration process is as follows: The impurity content of the drug solution is tested through multiple indicators; for the multi-indicator impurities detected, a fuzzy comprehensive evaluation method is used to obtain multi-level impurity content assessment scores; If the impurity content assessment score is less than or equal to the score limit, adjustment is necessary.

3. A biopharmaceutical liquid extraction and filtration method according to claim 2, characterized in that: The multiple indicators include: particulate impurities and visible foreign matter; protein aggregates, DNA residues, host cell proteins and endomycin.

4. A biopharmaceutical liquid extraction and filtration method according to claim 1, characterized in that: The process of determining the linear correlation between the centrifugal speed and the impurity content evaluation score during the liquid filtration process is as follows: Based on historical data, obtain the centrifugal speed data series and the corresponding impurity content assessment score series, and calculate the Pearson correlation coefficient; Based on the calculated Pearson correlation coefficient; Calculate the test statistic t and convert the Pearson correlation coefficient to obey the t distribution; calculate the p value through the t distribution. The p value is the probability of observing the current sample data result under the assumption that the null hypothesis is true; Compare the p-value with the significance level α. If p≤α, it means there is a linear correlation.

5. The method for extracting and filtering a biopharmaceutical liquid according to claim 1, wherein: The process of calculating the first adjustment amount of centrifugal speed is as follows: A linear regression equation is constructed based on the centrifugal speed data sequence and the impurity content evaluation score sequence, the target impurity content evaluation score is input into the linear regression equation, and the output is the first adjustment target value of the centrifugal speed; Based on the current centrifugal speed and the centrifugal speed first adjustment target value, the centrifugal speed first adjustment amount is calculated.

6. A biopharmaceutical liquid extraction and filtration method according to claim 1, characterized in that: The process of judging whether the biological activity of the drug solution meets the standard is as follows: The specific process of drug solution bioactivity testing includes the testing of two indicators: functional activity and structural integrity; The monitoring results based on the detection of the two indicators of functional activity and structural integrity are used to obtain the relative activity units and the secondary structure percentage, and the relative activity units and the secondary structure percentage are weighted to obtain the biological activity score.

7. The method for extracting and filtering a biopharmaceutical liquid according to claim 1, wherein: The process of determining the linear correlation between the centrifugal speed and the biological activity score during the liquid filtration process is as follows: Based on historical data, the centrifugal speed data series and the corresponding bioactivity score series are obtained to calculate the Pearson correlation coefficient; Based on the calculated Pearson correlation coefficient; Calculate the test statistic t, convert the Pearson correlation coefficient to obey the t distribution; calculate the p value through the t distribution; Compare the p-value with the significance level α. If p≤α, it means there is a linear correlation.

8. The method for extracting and filtering a biopharmaceutical liquid according to claim 1, wherein: The process of calculating the secondary adjustment amount of centrifugal speed is as follows: A linear regression equation is constructed based on the centrifugal speed data sequence and the bioactivity score sequence, the target bioactivity score is input into the linear regression equation, and the output is the secondary adjustment target value of the centrifugal speed; The secondary adjustment amount of the centrifugal speed is calculated based on the primary centrifugal speed and the secondary adjustment target value of the centrifugal speed.

9. The method for extracting and filtering a biopharmaceutical liquid according to claim 1, wherein: The process of determining whether to perform secondary adjustment on the centrifugal speed is as follows: Identify the adjustment direction of the first adjustment amount of centrifugal speed and the second adjustment amount of centrifugal speed; If the first adjustment amount of the centrifugal speed and the second adjustment amount of the centrifugal speed are both increased or decreased, the rotation speed of the crusher is readjusted according to the second rotation speed adjustment amount.

10. A biopharmaceutical liquid extraction and filtration system, characterized in that: The system is used to execute the method according to any one of claims 1 to 9, and the system comprises: Adjustment Necessity Analysis Module: Evaluates the impurity content of the filtered liquid and determines the necessity of adjustment of the liquid filtration process based on the impurity content evaluation score; First adjustment analysis module: If specific adjustment is necessary, the centrifugal speed during the drug liquid filtration process and the impurity content assessment score are linearly correlated. If a linear correlation exists, the first adjustment amount of the centrifugal speed is calculated; Activity judgment module: Use the adjusted centrifugal speed to obtain the filtered drug solution, analyze the biological activity to obtain a biological activity score, and judge whether the biological activity of the drug solution meets the standard; Secondary adjustment analysis module: If the biological activity of the drug solution does not meet the standard, the centrifugal speed during the drug solution filtration process and the biological activity score are linearly correlated. If a linear correlation exists, the secondary adjustment amount of the centrifugal speed is calculated; Adjustment direction analysis module: determines whether to perform secondary adjustment on the centrifugal speed according to the adjustment direction of the secondary adjustment amount of the centrifugal speed and the primary adjustment amount of the centrifugal speed.

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