CN113571202A - Prediction method and device for drug resistance of combined drug-resistant bacteria and electronic equipment - Google Patents

Prediction method and device for drug resistance of combined drug-resistant bacteria and electronic equipment Download PDF

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CN113571202A
CN113571202A CN202110790881.1A CN202110790881A CN113571202A CN 113571202 A CN113571202 A CN 113571202A CN 202110790881 A CN202110790881 A CN 202110790881A CN 113571202 A CN113571202 A CN 113571202A
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李耘
赵海晴
刘哲
钱永忠
邱静
梁严内
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Institute of Agricultural Quality Standards and Testing Technology for Agro Products of CAAS
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Abstract

The application provides a prediction method and device for drug resistance of combined drug-resistant bacteria and electronic equipment. The method comprises the following steps: (iii) cumulative probability distribution of exposure EC from the combinationiJudging when the second medicine is takeniWhether the corresponding experiment at concentration satisfies the possibility of bacterial drug resistance mutation; if yes, MIC is determined according to the minimum inhibitory concentrationiThe mutation preventing concentration MPCiThe cumulative probability distribution of exposure ECiAnd said inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationi(ii) a Obtaining Q probability curves PCiArea of curve a under the lineiAnd the second drug is taken yiProbability of occurrence p of concentrationiAccording to the curve under the lineArea aiAnd the occurrence probability piAnd acquiring the total probability of the drug resistance mutation of the bacteria. By implementing simulation and prediction by the technology, the problems of inaccurate possibility and lack of practicability of predicting the drug resistance mutation of the bacteria based on a limited experiment can be solved.

Description

Prediction method and device for drug resistance of combined drug-resistant bacteria and electronic equipment
Technical Field
The application relates to the technical field of biology, in particular to a prediction method and device for drug resistance of drug combination inhibition bacteria and electronic equipment.
Background
Combinations are widely tried for the control of drug resistance, aiming to achieve suppression and killing of the flora at low dosage levels while preventing as much as possible the development of bacterial resistance, in particular multi-resistance. Under the strict control condition of a laboratory, the proportion and the action mode of the drug combination can constantly meet the requirement of an optimal narrow spectrum region in a mutation selection window period, and meanwhile, the optimal resistance control can be realized on the drug resistance of flora in a specific environment.
However, in practical application scenarios, due to the existence of various factors such as different dosage combinations and ratios, the final drug resistance induction and inhibition control are affected to different degrees, and the final drug resistance induction and inhibition control have uncertainty. Moreover, only a few representative drug combinations can be considered in the experiment, and all the combination situations cannot be exhausted, so that the possibility of predicting the drug resistance mutation of the bacteria based on the limited experiment is not accurate enough and lacks practicability.
Disclosure of Invention
The embodiment of the application aims to provide a prediction method and a prediction device for controlling bacterial drug resistance by combined drug administration, and electronic equipment, so as to solve the problems that the prediction of bacterial drug resistance mutation possibility based on limited experiments is not accurate enough and lacks practicability.
The invention is realized by the following steps:
in a first aspect, the embodiments of the present application provide a method for predicting drug resistance of bacteria by combined drug administration, the method comprising: according to the second drug fetch yiThe n drug concentrations corresponding to the combined drug at the concentration and the bacteriostatic effect generated in each experimental scene are obtainedInhibition rate of dosing cumulative probability distribution ICiEach experimental scene is that x is taken from the first medicine respectively1、…、xnThe concentration and the second drug are respectively y1、…、ymIn concentration, the two are combined in pairs to carry out the combined medication scene, and the inhibition rate dose response cumulative probability distribution ICiRepresenting the probability of the corresponding antibacterial effect under the condition that the combined medicine is taken at different medicine concentration, wherein i is 1 to m; taking y according to the second medicineiObtaining the exposure cumulative probability distribution EC of the combined medication by the n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined medication at the concentrationiThe cumulative probability distribution of exposure ECiCharacterizing the probability of residual concentration of the drug at different dosing concentrations of the combination; (iii) cumulative probability distribution of exposure EC from the combinationiJudging when the second medicine is takeniWhether the corresponding experiment at concentration satisfies the possibility of bacterial drug resistance mutation; if yes, taking y according to the second medicineiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is taken yiMutation prevention concentration MPC among said n drug concentrations at concentrationiThe cumulative probability distribution of exposure ECiAnd said inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationiThe minimum inhibitory concentration is the lowest concentration of the first medicament and the second medicament which can inhibit the growth and the reproduction of bacteria, and the mutation prevention concentration is the lowest concentration of the antibacterial medicament required for preventing the selective multiplication of the first-step drug-resistant mutant strain; obtaining Q probability curves PCiArea of curve a under the lineiAnd the second drug is taken yiProbability of occurrence p of concentrationiAccording to the probability curve PCiArea of curve a under the lineiAnd the occurrence probability piObtaining the total probability of the drug-resistant mutation of the bacteria, wherein the total probability of the drug-resistant mutation of the bacteria represents the actual situationThe chance probability of the variation of the bacterial drug resistance is that Q is less than or equal to m.
In the embodiment of the application, the inhibition rate dose response cumulative probability distribution IC is obtained through a combined medication experimentiAnd cumulative probability distribution of exposure ECiAnd then accumulating probability distribution EC by exposureiRemoving experimental data which do not meet the possibility of breakthrough of bacterial drug resistance, and taking y with the rest of the second drugiProbability of occurrence p of concentrationiAnd according to said cumulative probability distribution of exposure ECiThe inhibition rate dose response cumulative probability distribution ICiThe mutation probability YiThe probability of effect XiAnd the occurrence probability piThe total probability of the drug resistance mutation of the bacteria is obtained, namely the influence of the drug combination with different concentrations and different proportions on the drug resistance is conjectured from limited drug combination experimental data under the condition that other experiments are not carried out, so that the prediction of the drug resistance mutation capability of the bacteria induced by the binary drug combination in a real scene is realized. And, according to the exposure cumulative probability distribution EC corresponding to each experimentiJudging when the second medicine is takeniWhether the corresponding experiment meets the possibility of the drug resistance mutation of the bacteria in concentration or not enables the experiment data participating in calculation to be effective experiment data, and therefore the accuracy of the finally obtained total probability of the drug resistance mutation of the bacteria is guaranteed.
With reference to the technical solution provided by the first aspect, in some possible implementations, the taking y according to the second medicamentiObtaining the exposure cumulative probability distribution EC of the combined medication by the n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined medication at the concentrationiThe method comprises the following steps: obtaining x from the first drug according to the exposure cumulative probability distribution of the first drug under a single condition1、…、xnProbability value F corresponding to concentrationjWherein j is 1 to n; obtaining y of the second medicament according to the exposure cumulative probability distribution of the second medicament under a single condition1、…、ymProbability value G corresponding to concentrationiWherein i is 1 to m; taking y according to the second medicineiWhen the concentration is higher than the preset value, the concentration of n medicines corresponding to the combined medicine and the first medicine are respectively x1、…、xnThe corresponding probability value M and the second medicine are respectively y1、…、ymProbability value G corresponding to concentrationiObtaining an exposure cumulative probability distribution EC for the combinationiWherein M ═ { F ═ F1,...,Fj,...,Fn}。
In the embodiment of the application, the exposure cumulative probability distribution of the first medicament in a single case is the exposure cumulative probability distribution obtained by only carrying out experiments on the first medicament, and x is taken as the first medicament in the combined medicament experiment1、…、xnThe concentration value of (A) is substituted into the cumulative probability distribution of exposure, so as to obtain that the first medicine respectively takes x under a single condition1、…、xnProbability value at concentration; similarly, the second drug in the combined drug experiment is respectively taken as y1、…、ymThe concentration value of the second drug is substituted into the exposure cumulative probability distribution of the second drug under a single condition, and the second drug can be respectively taken as y under the single condition1、…、ymProbability value at concentration. Taking the second medicine yiWhen the concentration is in the concentration, the n drug concentrations corresponding to the combined drug are taken as the abscissa, and the y is taken as the second drugiThe probability value at concentration is x respectively taken from the first medicine1、…、xnMultiplying the probability values at the concentration as a vertical coordinate, and fitting the exposure cumulative probability distribution EC of the combined medicinei. Through the method, the exposure cumulative probability distribution EC containing other unexperienced scenes can be constructed from limited experimental datai。
With reference to the technical solution provided by the first aspect, in some possible implementations, the taking y according to the second medicamentiWhen the concentration is higher than the preset value, the concentration of n medicines corresponding to the combined medicine and the first medicine are respectively x1、…、xnThe corresponding probability value M and the second medicine are respectively y1、…、ymPair at the time of concentrationCorresponding probability value GiObtaining an exposure cumulative probability distribution EC for the combinationiThe method comprises the following steps: taking x from the first medicine respectively1、…、xnThe corresponding probability value M at the concentration is respectively equal to the second medicine y1、…、ymProbability value G corresponding to concentrationiMultiplying to obtain the second drug yiProbability of drug combination concentration at concentration; taking the second medicine yiThe probability of the concentration of the combined medicine is used as the ordinate, and the second medicine is taken as yiThe n drug concentrations corresponding to the combined drug at the time of concentration are taken as abscissa, and the exposure cumulative probability distribution EC of the combined drug is obtainedi。
In the embodiment of the application, the first medicine is respectively taken as x1、…、xnThe corresponding probability value M at the concentration is respectively taken out of y with the second medicine1、…、ymProbability value G corresponding to concentrationiMultiplying to obtain y at the second drugiThe probability of the concentration of the combined medication at the concentration is that the occurrence probability corresponding to different concentrations of the first medicament under a single condition is multiplied by the occurrence probability corresponding to different concentrations of the second medicament under a single condition in pairs, so that the probability of the simultaneous occurrence of the first medicament and the second medicament can be obtained; taking the second medicine for yiThe probability of the concentration of the combined medicine is used as the ordinate, and the second medicine is taken as yiThe n drug concentrations corresponding to the combined drug at the concentration are taken as the abscissa, and the exposure cumulative probability distribution of the combined drug can be obtained. By the mode, the exposure cumulative probability distribution corresponding to the combined medication of the first medicine and the second medicine can be effectively obtained, and the accuracy of the exposure cumulative probability distribution can be ensured.
With reference to the technical solution provided by the first aspect, in some possible implementations, the exposure cumulative probability distribution EC according to the combination isiJudging when the second medicine is takeniThe corresponding experiments at concentrations met the possibility of bacterial resistance mutations, including: MIC according to the minimum inhibitory concentrationiObtaining the cumulative probability distribution of exposure ECiCorrespond toMutation probability Y ofi(ii) a Judging the mutation probability YiIf it is less than 1, if the mutation probability YiLess than 1 indicates that y is taken for the second drugiThe corresponding experiments at concentration satisfy the possibility of a resistant mutation in bacteria.
In the examples of the application, the minimum inhibitory concentration MICiCarry-in cumulative probability distribution of exposure ECiCan obtain mutation probability YiY is the lowest concentration of the first drug and the second drug which can inhibit the growth and reproduction of bacteriaiThe probability that the bacteria do not develop resistance to the drug; thus, if the mutation probability Y isiWhen the number is less than 1, it means that the possibility of the mutation of the bacterial drug resistance in the test is 1-YiI.e. when said second drug is taken yiThe corresponding experiments at concentration satisfy the possibility of a resistant mutation in bacteria. Through the method, experimental data which do not meet the possibility of drug resistance mutation of the bacteria can be screened, and only the experimental data which meet the conditions are subjected to subsequent steps, so that the accuracy of subsequent calculation is ensured.
With reference to the technical solution provided by the first aspect, in some possible implementations, the taking y according to the second medicamentiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is taken yiMutation prevention concentration MPC among said n drug concentrations at concentrationiThe cumulative probability distribution of exposure ECiAnd said inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationiThe method comprises the following steps: MIC according to the minimum inhibitory concentrationiObtaining said inhibition rate dose response cumulative probability distribution ICiAnd the cumulative probability distribution of exposure ECiRespectively corresponding effect probability XiAnd mutation probability Yi(ii) a MPC based on said mutation prevention concentrationiObtaining a plurality of points (X ', Y '), wherein Y '<1-Yi、X'>Xi(ii) a Obtaining the probability curve PC according to the plurality of pointsi。
In the examples of the present application, the minimum suppression will beMIC of bacterial concentrationiDose response cumulative probability distribution IC with separate inlining inhibitioniAnd cumulative probability distribution of exposure ECiThe effect probabilities X corresponding to the two can be obtainediAnd mutation probability YiDue to XiThe corresponding concentration above has the risk of drug resistance mutation of bacteria, so the value of the abscissa X' is required to be larger than that of XiAnd due to mutation probability YiSo as not to generate a threshold point for drug-resistant mutation, 1-YiIs a region where resistance mutations can occur. Thus, MPC was based on the mutation prevention concentrationiAfter a plurality of points are obtained, a probability curve PC can be fitted according to the obtained plurality of pointsi. In this way, a second drug y can be obtained1、…、ymProbability curve PC of drug resistance mutation of binary combination at concentrationi。
With reference to the technical solution provided by the first aspect, in some possible implementation manners, the probability curve PC is obtained according to the probability curveiArea of curve a under the lineiAnd the occurrence probability piObtaining the total probability of the drug-resistant mutation of the bacteria, comprising the following steps: according to the area a of the curve under the lineiAnd the occurrence probability piAcquiring a total probability curve; and calculating the area of the curve under the total probability curve, wherein the area of the curve under the total probability curve is the total probability of the drug-resistant mutation of the bacteria.
The probability curve PCiArea of curve a under the lineiAs ordinate, the probability p of occurrenceiAs the abscissa, fitting the abscissa and the ordinate in a one-to-one correspondence manner to obtain a total probability curve; and solving the area of the curve under the total probability curve to obtain the total probability of the bacterial drug resistance mutation. Area of curve a under the factor lineiFor the second drug in yiThe probability of drug-resistant mutation of the corresponding bacterium at concentration, i.e., the area of the curve a under the lineiThe probability of occurrence depends on the second drug being takeniProbability at concentration, so the area of curve a under the lineiAnd the second drug is takeniProbability of occurrence p of concentrationiAnd (3) constructing a total probability curve to obtain the integral probability condition of the drug resistance mutation of the bacteria. And in the way described above, the above-mentioned mode,the accuracy of the calculated total probability of the drug resistance mutation of the bacteria can be ensured.
In combination with the technical solution provided by the first aspect, in some possible implementations, the inhibition rate of the combination is obtained by obtaining a dose response cumulative probability distribution ICiAnd cumulative probability distribution of exposure ECiPreviously, the method further comprises: obtaining the residual concentrations of the first medicament and the second medicament in each experimental scene when the bacteriostasis rate of c% is realized, wherein c is more than or equal to 0 and less than or equal to 100; according to the concentration of the first drug in a single condition at the c% bacteriostasis rate, the concentration of the second drug in a single condition at the c% bacteriostasis rate and the y value of the second drugiAnd obtaining the n drug concentrations corresponding to the combined drug according to the residual concentration of the first drug and the residual concentration of the second drug in concentration.
In the embodiment of the application, after the residual concentrations of the first drug and the second drug in each experimental scene at the c% bacteriostatic rate are obtained, y is taken according to the concentration of the first drug at the single condition at the c% bacteriostatic rate, the concentration of the second drug at the single condition at the c% bacteriostatic rate, and the concentration of the second drug at the single condition at the c% bacteriostatic rateiObtaining n drug concentrations corresponding to the combined medication by the residual concentration of the first drug and the residual concentration of the second drug during concentration obtaining n drug concentrations corresponding to the combined medication of the first drug and the second drug by an effect superposition model, wherein the concentration of the first drug under a single condition, the concentration of the second drug under a single condition and the concentration of the second drug under a single condition are obtained by yiThe residual concentration of the first medicament and the residual concentration of the second medicament in concentration are values under the same bacteriostasis rate.
In combination with the technical solution provided by the first aspect, in some possible implementations, the inhibition rate is obtained as a dose response cumulative probability distribution ICiAnd the cumulative probability distribution of exposure ECiThereafter, the method further comprises: (ii) dose-response cumulative probability distribution IC of said inhibition rateiAnd the cumulative probability distribution of exposure ECiAre presented in the same coordinate system.
In the examples of this application, dose responses were accumulated by suppressing ratesProbability distribution ICiCorresponding inhibition dose response cumulative probability distribution curves and exposure cumulative probability distributions ECiThe corresponding exposure cumulative probability distribution curves are presented in the same coordinate system, so that a user can visually observe the corresponding conditions of different experiments, such as: when the possibility of the drug resistance mutation of bacteria is not met in a certain experiment, a user can directly see out the condition which is not met in the experiment through an exposure accumulation probability distribution curve, the actual exposure level of the experiment is lower than or far lower than the minimum inhibitory concentration, or the experiment directly exceeds the mutation prevention concentration, so that the drug resistance mutation probability does not exist, and the convenience is brought to the user to judge the experiment condition.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, the probability curve PCiArea of curve a under the lineiAre all larger than the preset area value.
In the embodiment of the application, a preset area value is set in advance, and a probability curve PC is obtainediArea of curve a under the lineiThen, the curve area a under the line is determinediAll are compared with a preset area value to eliminate the area a of the curve under the lineiExperimental data less than a predetermined area value. By the mode, experimental data with small influence on the result can be removed, so that the calculation amount of the data is reduced under the condition of ensuring the accuracy of the result.
In a second aspect, embodiments of the present application provide a device for predicting drug resistance of bacteria by combined drug administration, the device comprising: a processing module for taking y according to the second medicineiObtaining the inhibition rate dose response cumulative probability distribution IC of the combined medication by n drug concentrations corresponding to the combined medication and the bacteriostatic effect generated in each experimental sceneiEach experimental scene is that x is taken from the first medicine respectively1、…、xnThe concentration and the second drug are respectively y1、…、ymIn concentration, the two are combined in pairs to carry out the combined medication scene, and the inhibition rate dose response cumulative probability distribution ICiThe probability of the corresponding antibacterial effect generated under the condition that the combined medicine is taken at different medicine concentration is represented, wherein,i is 1 to m; taking y according to the second medicineiObtaining the exposure cumulative probability distribution EC of the combined medication by the n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined medication at the concentrationiThe cumulative probability distribution of exposure ECiCharacterizing the probability of residual concentration of the drug at different dosing concentrations of the combination; a judging module for determining the cumulative probability distribution EC of the drug combinationiJudging when the second medicine is takeniWhether the corresponding experiment at concentration satisfies the possibility of bacterial drug resistance mutation; if yes, taking y according to the second medicineiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is taken yiMutation prevention concentration MPC among said n drug concentrations at concentrationiThe cumulative probability distribution of exposure ECiAnd said inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationiThe minimum inhibitory concentration is the lowest concentration of the first medicament and the second medicament which can inhibit the growth and the reproduction of bacteria, and the mutation prevention concentration is the lowest concentration of the antibacterial medicament required for preventing the selective multiplication of the first-step drug-resistant mutant strain; a prediction module for obtaining Q probability curves PCiArea of curve a under the lineiAnd the second drug is taken yiProbability of occurrence p of concentrationiAccording to the probability curve PCiArea of curve a under the lineiAnd the occurrence probability piAnd acquiring the total probability of the bacterial drug resistance mutation, wherein the total probability of the bacterial drug resistance mutation represents the opportunity probability of bacterial drug resistance mutation under the actual condition, and Q is less than or equal to m.
In a third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory, the processor and the memory connected; the memory is used for storing programs; the processor is configured to invoke a program stored in the memory to perform a method as provided in the above-described first aspect embodiment and/or in combination with some possible implementations of the above-described first aspect embodiment.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, performs the method as set forth in the above first aspect embodiment and/or in combination with some possible implementations of the above first aspect embodiment.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig.1 is a dose design example of a binary combination provided in an embodiment of the present application.
FIG.2 is a graph of resistance profiles for antagonistic, synergistic and additive effects of the binary combinations provided in the examples herein.
FIG.3 is a graph of the resistance profile of a combination showing antagonistic effect provided by the examples of the present application.
Fig.4 is a flowchart illustrating steps of a method for predicting drug resistance of bacteria by drug combination therapy according to an embodiment of the present disclosure.
FIG. 5 shows a second drug fetch y provided in an embodiment of the present application1Inhibition Rate dose response cumulative probability distribution IC at concentration1And cumulative probability distribution of exposure EC1All types of situations arise.
FIG. 6 shows a second drug fetch y provided in an embodiment of the present application1Concentration, probability curve, all types of situations occur.
FIG. 7 shows the cumulative probability distribution of the bacterial suppressor dose response of enrofloxacin and florfenicol in each case provided in the examples of the present application.
FIG. 8 is the MIC and MPC data for the enrofloxacin and florfenicol dual combination drug experiments provided in the examples of the present application.
Fig. 9 is the cumulative probability distribution of the exposure of enrofloxacin and florfenicol in each case in the single case provided in the examples of the present application.
FIG. 10 shows the cumulative probability distribution of exposure and the cumulative probability distribution of bacterial suppressor dose response for the combination of enrofloxacin and florfenicol administered at a concentration of 0.085. mu.g/mL of florfenicol as provided in the examples herein.
FIG. 11 is a probability curve of the combination of enrofloxacin and florfenicol at a concentration of 0.085 μ g/mL for florfenicol provided in the examples of the present application.
FIG. 12 is a probability curve of combined administration of enrofloxacin and florfenicol at concentrations of 0.085. mu.g/mL and 0.17. mu.g/mL, respectively, provided in the examples of the present application.
Fig. 13 is a block diagram of a prediction apparatus for controlling bacterial drug resistance by combining drugs according to an embodiment of the present disclosure.
Fig. 14 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
In view of the fact that the prediction of the possibility of drug-resistant mutation of bacteria based on limited experiments is not accurate enough and lacks in practical utility, the present inventors have conducted research and proposed the following examples to solve the above problems.
First, prior to performing a dual combination drug test using a first drug and a second drug, the test doses of the first drug and the second drug can be designed according to the following method.
Respectively measuring the minimum inhibitory concentration MIC and the mutation prevention concentration MPC of the first medicament and the second medicament acting on target bacteria under a single condition and the cumulative probability distribution of the inhibition rate dose response of the first medicament and the second medicament under the single condition according to a minimum inhibitory concentration MIC standard method, wherein the single condition is the condition that the first medicament and the second medicament are respectively and independently taken; then comparing MIC of the first drugxAnd MIC of the second drugySelecting a drug with relatively high minimum inhibitory concentration MIC, and adjusting the experimental concentration gradient ratio according to the MIC weight of the drug, such as: MIC x10 μ g/mL, MICy0.10. mu.g/mL, i.e., MICxGreater than MICyThe ratio of the first and second drug doses should first be based on MICxTo adjust. Therefore, the dilution ratio span is preferably selected to be 0.10 times, 0.25 times, 0.50 times, 1 time, 1.5 times, more than 0.1 times, 1 time, 5 times, 10 times. Moreover, the medicines with the proportioning concentration preferentially reaching the MPC under a single condition do not need to be designed into higher dosage concentration, so the concentration number set by the first medicine and the second medicine can be different in the experiment.
As shown in FIG.1, the concentration value of the first drug is x1、…、xnThe concentration value of the second drug is y1、…、ymEach grid in fig.1 represents a different combination experiment, wherein it should be noted that the concentration values of the first drug and the second drug in fig.1 are both n, that is, m is equal to n, but in the experiment, the concentration numbers of the first drug and the second drug may be different, that is, n and m may be the same or different, and the application is not limited; the left value of each grid represents the concentration value of the first drug, and the right value represents the concentration value of the second drug, for example, x is taken for the first drug in the grid at the leftmost lower corner in fig.11Concentration and second drug fetch y1Combination test at concentration, where 0.1IC50MIs the concentration value of the first drug, 0.1IC50NIs taken as the concentration value of the second drug, IC50MIs the semi-inhibitory concentration, IC, of the first drug50NIs the half inhibitory concentration of the second drug. The design of the experiment under equal ratios should cover the whole MIC and MPC ranges as much as possible, and should take into account the respective half inhibitory concentrations IC of the different drugs50Wherein the IC of the first drug and the second drug50All according to the inhibition rate dose response cumulative probability distribution under the single condition of the inhibition rate dose response cumulative probability distribution. In addition, because the actual drug residue is likely to be lower than the MIC of the drug, and higher than the MIC in only a few cases, it is designed at a limited concentrationIn combination, more different gradient concentration ratios should be designed in the MIC area as much as possible.
After the experimental doses of the first medicament and the second medicament are designed according to the principle, the two medicaments are combined in a two-in-two manner for experiment. Wherein the medicine is dissolved in dimethyl sulfoxide (DMSO) solvent for use, the final concentration of DMSO is not more than 0.03%, and the bacterial liquid concentration is adjusted to OD 0.1 (about 1 × 10) according to different culture plate addition amount10CFU/mL) and left to incubate at 28 ℃ for 24h, and then automatically measured on OD600 using a microplate reader according to broth microdilution technique to assess the extent of MIC and MPC growth of the bacteria, i.e. the MIC and MPC of the combination can be obtained by experimental analysis at different concentrations of the second drug.
As shown in FIG.2 and FIG.3, since the dual combination can utilize Drug interactions to generate antagonistic, synergistic or additive effects, the Drug resistance profile of the dual combination can be obtained according to experimental analysis, wherein Drug M in FIG.2 and FIG.3 represents the first Drug, Drug N represents the second Drug, and x represents the second Drug1、…、xnRepresenting the first drug by taking different concentration values, y1、…、ymRepresenting different concentration values of the second drug, fig.3 shows the case where m is equal to n. And the small squares in the left diagram in fig.3 are the combination of the concentration values of the first drug and the second drug corresponding to the squares, for example, the squares in the bottom left corner of the diagram correspond to the first drug, M, is taken1Concentration and second drug N1Experiments conducted on concentrations; the circles in the right panel of fig.3 correspond one-to-one to the squares in the left panel, and MSW is the concentration range between MIC and MPC, i.e. the mutation selection window period, within which the danger zone is selectively enriched for drug resistance of the drug-resistant strain, the wider the MSW, the more likely the drug-resistant strain appears. After the atlas for influencing drug resistance of the binary combination drug is obtained through the experimental analysis, a user can visually obtain the relationship of the drug combination in the combination drug.
The specific process and steps of the prediction method for controlling bacterial drug resistance by combined drug administration are described below with reference to fig. 4. It should be noted that the prediction method for controlling bacterial resistance by combination drug provided in the examples of the present application is not limited to the sequence shown in fig.4 and below.
Step S101: according to the second drug fetch yiObtaining the inhibition rate dose response cumulative probability distribution IC of the combined medication by the n drug concentrations corresponding to the combined medication and the bacteriostatic effect generated in each experimental sceneiWherein i is 1 to m.
Optionally, the dose response cumulative probability distribution IC is used to obtain the inhibition rate of the combinationiAnd cumulative probability distribution of exposure ECiPreviously, the method further comprises: obtaining the residual concentrations of the first medicament and the second medicament in each experimental scene when the c% bacteriostasis rate is realized, wherein c is more than or equal to 0 and less than or equal to 100; according to the concentration of the first drug in the single case of c% bacteriostasis rate, the concentration of the second drug in the single case of c% bacteriostasis rate and the y value of the second drugiThe residual concentration of the first drug and the residual concentration of the second drug at the time of concentration are obtained as n drug concentrations corresponding to the combined administration.
It is noted that the value range of c is any value from 0 to 100, that is, after the value of c is set, y is taken according to the concentration of the first drug in a single case at the c% bacteriostatic rate, the concentration of the second drug in a single case at the c% bacteriostatic rate, and the concentration of the second drug in a single case at the c% bacteriostatic rateiThe residual concentration of the first medicament and the residual concentration of the second medicament during concentration can obtain n medicament concentrations corresponding to the combined medicament.
Obtaining n drug concentrations corresponding to the combined drug through an effect superposition model, wherein the formula is as follows:
Figure BDA0003161035360000131
in the formula (1), the first and second groups,
Figure BDA0003161035360000132
in order to realize the concentration of the combined medicament when the bacteriostasis rate is c percent,
Figure BDA0003161035360000133
and
Figure BDA0003161035360000134
when the c% bacteriostasis rate is realized by the combined medicine, the concentrations of the first medicine and the second medicine in the mixture,
Figure BDA0003161035360000135
and
Figure BDA0003161035360000136
is the concentration of the first and second drugs at which c% inhibition was achieved in a single instance, respectively. Wherein c% can be IC10、IC20、IC30、IC40、IC50、IC70、IC60、IC80、IC90And IC100And taking any value from i to m, and taking j from 1 to n. In addition, the first medicine is x1、…、xnConcentration and the second drug are taken as y1、…、ymConcentration, therefore, in the second drug, y is takeniWhen the concentration is determined, n drug concentrations corresponding to the combined drug can be obtained according to the formula (1), for example, when the second drug is y1At the time of concentration, the above formula (1) becomes:
Figure BDA0003161035360000137
taking the second medicine yiTaking n drug concentrations corresponding to the combined drug as abscissa, and taking y as second drug obtained by experimentiThe antibacterial effect generated in each experimental scene in concentration is used as a vertical coordinate, and the inhibition rate dose response cumulative probability distribution IC of the combined drug can be fittedi. Wherein, each experimental scene is that x is taken from the first medicine respectively1、…、xnConcentration and the second drug are taken as y1、…、ymIn concentration, the two are combined in pairs to carry out the combined medication scene, and the inhibition rate dose response cumulative probability distribution ICiThe probability of the corresponding antibacterial effect is represented under the condition that the combined medicines are taken at different medicine concentration. Wherein n and m are positive integers, which may be the same or differentIn contrast, the present application is not limited.
Step S102: according to the second drug fetch yiObtaining the exposure cumulative probability distribution EC of the combined drug by using n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined drug at the concentrationi。
Specifically, x is taken out respectively according to the exposure cumulative probability distribution of the first medicament under the single condition1、…、xnProbability value F corresponding to concentrationjWherein j is 1 to n; obtaining y of the second medicament respectively according to the exposure cumulative probability distribution of the second medicament in a single condition1、…、ymProbability value G corresponding to concentrationiWherein i is 1 to m; according to the second drug fetch yiThe concentration of n drugs corresponding to the combined administration is x1、…、xnThe corresponding probability value M and the second medicine are respectively y1、…、ymProbability value G corresponding to concentrationiObtaining cumulative probability distribution of exposure EC for drug combinationiWherein M ═ { F ═ F1,...,Fj,...,Fn}. The corresponding exposure cumulative probability distribution of the first medicine and the second medicine under a single condition is respectively constructed after the residual concentration levels of the first medicine and the second medicine in an actual scene are monitored; cumulative probability distribution of exposure ECiThe probability of the residual concentration of the drug is characterized under different drug concentrations of the combined drug.
Taking y according to the second drugiThe concentration of n drugs corresponding to the combined administration is x1、…、xnThe corresponding probability value M and the second medicine are respectively y1、…、ymProbability value G corresponding to concentrationiObtaining cumulative probability distribution of exposure EC for drug combinationiThe method specifically comprises the following steps: taking x from the first medicine respectively1、…、xnThe corresponding probability value M at the concentration is respectively taken out of y with the second medicine1、…、ymCorresponding to when the concentration isProbability value G ofiMultiplying to obtain a second drug yiProbability of drug combination concentration at concentration; taking the second medicine yiThe probability of the concentration of the combined drug is used as the ordinate, and the second drug is taken as yiThe n drug concentrations corresponding to the combined drug at the concentration are used as the abscissa, and the exposure cumulative probability distribution EC of the combined drug is obtainedi。
Through the method, the exposure cumulative probability distribution EC containing other unexperienced scenes can be constructed from limited experimental datai。
Step S103: cumulative probability distribution of exposure based on combinationiJudging when the second medicine is takeniThe corresponding experiment at concentration was satisfied with the possibility of bacterial resistance mutations.
Specifically, MIC is determined according to the minimum inhibitory concentrationiObtaining an exposure cumulative probability distribution ECiCorresponding mutation probability Yi(ii) a Judging mutation probability YiIf it is less than 1, if the mutation probability YiLess than 1 indicates that y is taken as the second drugiThe corresponding experiments at concentration satisfy the possibility of a resistant mutation in bacteria.
In the embodiment of the application, the minimum inhibitory concentration is the concentration of the lowest drug which can inhibit the growth and reproduction of bacteria and is used in combination with the first drug and the second drug. MIC of minimum inhibitory concentrationiCarry-in cumulative probability distribution of exposure ECiCan obtain mutation probability YiY is the concentration of the first drug and the second drug which can inhibit the growth and reproduction of bacteria at the minimum inhibitory concentrationiThe probability that the bacteria do not develop resistance to the drug; thus, if the mutation probability Y isiWhen the number is less than 1, it means that the possibility of the mutation of the bacterial drug resistance in the test is 1-YiThat is, when the second drug is takeniThe corresponding experiments at concentration satisfy the possibility of a resistant mutation in bacteria. By the mode, experimental data which do not meet the possibility of drug resistance mutation of bacteria can be removed, and only the experimental data which meet the conditions are subjected to subsequent calculation, so that the accuracy of the subsequent calculation is ensured.
Optionally, the suppression ratioDose response cumulative probability distribution ICiAnd cumulative probability distribution of exposure ECiAre presented in the same coordinate system.
When the second drug is taken y, as shown in FIG. 51Dose response cumulative probability distribution IC of inhibition at concentration1And cumulative probability distribution of exposure EC1It is assumed that 6 relationships in total are possible in the same coordinate system, respectively, diagram (a) to diagram (f) in fig. 5. Wherein the horizontal axis represents drug concentration corresponding to combined drug administration, the vertical axis represents probability, and MIC is y for the second drug1Minimum inhibitory concentration MIC at concentration1MPC for the second drug fetch y1Mutation prevention concentration at concentration MPC1G (x) is the second drug y1Inhibition at concentration dose response cumulative probability distribution IC1And f (x) is the second drug y1Cumulative probability distribution of exposure at concentration, EC1。
Mutation probability Y in 4 cases of FIGS. 5 (a) to (d)1All less than 1, the actual exposure level will be in the MSW range, with the possibility of drug-resistant mutations; mutation probability Y in graph (e) in FIG. 51Equal to 1, the actual exposed water is lower than or far lower than MIC on average, and the probability of drug resistance mutation does not exist, and the relation represents that the conditions are common in good culture environment and natural ecological environment; the situation in graph (f) of fig. 5 is an extreme case directly exceeding the MPC values, i.e. not in the MSW region, there is no probability of drug-resistant mutations, and the drug concentration levels in the system are extremely high, possibly with large or large combined toxic effects on the host. Therefore, in the experiments represented by panels (e) and (f) in fig. 5, there is no possibility of drug-resistant mutation, and it is not necessary to proceed to the next calculation. In addition, when the second drug is taken yiInhibition Rate dose response cumulative probability distribution IC at concentrationiAnd cumulative probability distribution of exposure ECiThe above 6 relationships may also appear in the same coordinate system, so as to avoid repetition, and will not be described herein again.
By accumulating the inhibition rate dose response probability distribution ICiAnd cumulative probability distribution of exposure ECiThe second medicine is presented in the same coordinate system, so that the user can visually see when the second medicine is usedGet yiAt concentration, what the experiment is. And, when the second drug is taken yiIn the case where the experiment at the concentration does not satisfy the possibility of the bacterial drug resistance mutation, the user can intuitively know which of the two cases the experiment does not satisfy the possibility of the bacterial drug resistance mutation.
Step S104: if yes, taking y according to the second medicineiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is takeniMutation prevention concentration MPC in n drug concentrations at concentrationiCumulative probability distribution of exposure ECiAnd inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationi。
Specifically, MIC is determined according to the minimum inhibitory concentrationiObtaining inhibition rate dose response cumulative probability distribution ICiAnd cumulative probability distribution of exposure ECiRespectively corresponding effect probability XiAnd mutation probability Yi(ii) a MPC according to mutation prevention concentrationiObtaining a plurality of points (X ', Y '), wherein Y '<1-Yi、X'>Xi(ii) a Obtaining a probability curve PC from a plurality of pointsi。
In the examples of the application, the minimum inhibitory concentration MICiDose response cumulative probability distribution IC with separate inlining inhibitioniAnd cumulative probability distribution of exposure ECiThe effect probabilities X corresponding to the two can be obtainediAnd mutation probability YiDue to XiThe corresponding concentration above has the risk of drug resistance mutation of bacteria, so the value of the abscissa X' is required to be larger than that of XiAnd due to mutation probability YiSo as not to generate a threshold point for drug-resistant mutation, 1-YiIs a region where resistance mutations can occur. Thus, MPC was based on the mutation prevention concentrationiAfter a plurality of points (X ', Y') are acquired, a probability curve PC can be fitted according to the acquired pointsi。
As shown in FIG. 6, FIG. 6 Fig.1 is the probability curve PC corresponding to the graph (a) in FIG. 51FIG.2 is a probability curve PC corresponding to the graph (b) in FIG. 51FIG.3 is a summary corresponding to the diagram (c) in FIG. 5Rate curve PC1FIG.4 is a probability curve PC corresponding to the graph (d) in FIG. 51(ii) a Probability curves PC corresponding to 4 cases in fig. 5 (a) to (d)1Roughly indicated by FIG. 6, Fig.1-Fig.4, when the second drug is yiProbability curve PC obtained at concentrationiOne of the above 4 curve conditions may also occur to avoid repetition, which is not described herein again.
Step S105: obtaining Q probability curves PCiArea of curve a under the lineiAnd the second drug is takeniProbability of occurrence p of concentrationiAccording to the probability curve PCiArea of curve a under the lineiAnd probability of occurrence piAnd acquiring the total probability of drug resistance mutation of the bacteria, wherein Q is less than or equal to m.
In the embodiment of the application, first, Q probability curves PC are obtainediArea of curve a under the lineiAnd the second drug is takeniProbability of occurrence p of concentrationi. Wherein, Q probability curves PCiIs a probability curve PC corresponding to the experiment judged to satisfy the possibility of the bacterial drug resistance mutation at step S103iSince there may be a possibility that the experiment does not satisfy the mutation of the drug resistance of the bacteria, Q is less than or equal to m; probability of occurrence piRespectively taking y for the second medicament in step S1021、…、ymProbability value G corresponding to concentrationi. Then according to the probability curve PCiArea of curve a under the lineiAnd probability of occurrence piAnd acquiring the total probability of the drug resistance mutation of the bacteria. Wherein, the total probability of the bacterial drug resistance mutation represents the chance probability of bacterial drug resistance mutation under the actual condition.
Specifically, the above is according to the probability curve PCiArea of curve a under the lineiAnd probability of occurrence piObtaining the total probability of the drug-resistant mutation of the bacteria, comprising the following steps: according to the area of the curve a under the lineiAnd probability of occurrence piAcquiring a total probability curve; and calculating the area of the curve under the total probability curve, wherein the area of the curve under the total probability curve is the total probability of the drug-resistant mutation of the bacteria. Wherein, according to the area a of the curve under the lineiAnd probability of occurrence piThe total probability curve is obtained specifically as follows: wire-cutting machineLower curve area aiAs ordinate, the probability p of occurrenceiThe total probability curve is fitted as abscissa.
Therefore, the total probability TP of the bacterial drug resistance mutation is:
Figure BDA0003161035360000181
in equation (3), TPC is a total probability curve.
Optionally, probability curve PCiArea of curve a under the lineiAre all larger than the preset area value. By dividing the area of the curve a under the lineiAnd eliminating the experimental data smaller than the preset area value, thereby reducing the calculation amount of the data under the condition of ensuring the accuracy of the result.
Referring to FIGS. 7 to 12, a method for predicting drug resistance of a combination drug-resistant bacteria will be described below by way of example.
Taking the combined resistance control of enrofloxacin (Enr) and florfenicol (Florfenicol, Flo) to aeromonas hydrophila (A. hydrophyllia) in high-pollution wastewater as an example.
Firstly, the MICs and MPCs of Enr and Flo to Aeromonas hydrophila are respectively measured, and the residual data monitored in a certain assumed area are adopted to carry out fitting according to a basic model of probability distribution, so that the cumulative probability distribution of the bacterial inhibitor dose response of Enr and Flo under a single condition is obtained. As shown in fig. 7, graphs (a) and (b) in fig. 7 are cumulative probability distributions of the bacterial suppressor dose response in the single cases of Enr and Flo, respectively. According to the obtained cumulative probability distribution of bacterial inhibitor dose response of Enr and Flo in a single case, the IC of Enr and Flo can be obtained respectively50. The results are shown in Table 1.
TABLE 1
Figure BDA0003161035360000191
Due to MICEnr<<MICFloThus, the MIC concentration levels of the reference Flo were simultaneously at the respective ICs50Different gradient concentration ratios were set for the reference, where the dilution factor was tested at 0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 4.0, 8.0, 12.0 and 16.0 times. The final experimental dosage design is shown in table 2.
TABLE 2
Figure BDA0003161035360000192
As shown in fig. 8, fig. 8 is data of MIC and MPC of the above experiment. Wherein the concentration of drug Enr is Enr1～Enr14Wherein, Enr1～Enr140.0016. mu.g/mL, 0.0032. mu.g/mL, 0.0064. mu.g/mL, 0.0096. mu.g/mL, 0.0128. mu.g/mL, 0.016. mu.g/mL, 0.064. mu.g/mL, 0.128. mu.g/mL, 0.192. mu.g/mL, 0.256. mu.g/mL, 0.5. mu.g/mL, 0.8. mu.g/mL, 1. mu.g/mL and 1.45. mu.g/mL, respectively; the concentration of the drug Flo is Flo1～Flo10Wherein, Flo1～Flo100.085. mu.g/mL, 0.17. mu.g/mL, 0.34. mu.g/mL, 0.51. mu.g/mL, 0.68. mu.g/mL, 0.85. mu.g/mL, 3.4. mu.g/mL, 6.8. mu.g/mL, 10.2. mu.g/mL, and 13.6. mu.g/mL, respectively.
As shown in fig. 9, according to the basic model of probability distribution, the residual data monitored in a certain assumed area is used for fitting to obtain Enr and the cumulative probability distribution of exposure of Flo in a single case. Among them, the graphs (a) and (b) in fig. 9 are the exposure cumulative probability distributions of Enr and Flo in a single case, respectively.
The cumulative probability distribution of the bacterial inhibitor dose response and the cumulative probability distribution of the exposure in the combined drug scene can be obtained based on the cumulative probability distribution of the exposure of Enr and Flo in a single case. Wherein the drug Flo is taken out of Flo1In concentration, the corresponding n drug concentrations of the combination are obtained by an effect superposition model, and the formula is as follows:
Figure BDA0003161035360000201
in the formula (4), Ccom1,mixTo take out Flo in the medicine Flo1When the concentration is higher, the concentration of the combined medicine is realized when the bacteriostasis rate is c%; cEnr,i,mixAnd CFlo1,mixRespectively taking out Flo from the drug Flo1When the concentration is higher, the concentration of the drug Flo and the drug Enr in the mixture is higher when the drug Flo and the drug Enr are jointly used to realize the c% bacteriostasis rate; cEnr,iAnd CFlo1The concentration of the first medicament and the concentration of the second medicament for realizing the c% bacteriostasis rate under a single condition respectively; i is from 1 to 14.
Similarly, the method can be used to obtain the drug Flo and take the Flo respectively2～Flo10When the concentration is higher, the concentration of the combined medicine is realized when the bacteriostasis rate is c%.
Respectively bringing the concentrations of the medicines Enr into the exposure cumulative probability distribution under the single condition, and acquiring the probability value P corresponding to each concentrationEnr,i(ii) a Then the drug Flo is changed into the Flo1Is brought into its single-case exposure cumulative probability distribution to obtain a probability value PFlo1(ii) a Finally P is addedEnr,iAnd PFlo1Multiplying to obtain the ordinate of the cumulative probability distribution of exposure of the combined medicine, wherein the formula is as follows:
S(Ccomi,mix)＝PEnr,i×PFlo1 (5)
wherein i is 1 to 14.
As shown in FIG. 10, the drug Flo is taken out of the Flo1Taking the concentration of the combination drug at the c% bacteriostasis rate as the abscissa and taking the P as the X-axisEnr,iAnd PFlo1The probability value obtained by multiplication is used as a vertical coordinate to fit the drug Flo in the sampling Flo1Cumulative probability distribution of exposure of combination at concentration, EC1. The drug Flo is taken out of the Flo1The concentration of the drug combination at the c% inhibition rate was obtained as the abscissa, and the drug Flo was Flo1The effect obtained by the experiment corresponding to the concentration is used as the ordinate to fit the Flo taken from the drug Flo1Inhibition Rate dose response cumulative probability distribution IC of combination at concentration1. Wherein S (C) in FIG. 10comi,mix) The medicament Flo is Flo1Cumulative probability distribution of exposure for concentration-corresponding combination1W (comi, mix) is the drug Flo is Flo1Corresponding to the concentrationInhibition rate dose response cumulative probability distribution IC for combination1。
Similarly, the method can be used to obtain the drug Flo and take the Flo respectively2～Flo10At concentration, the cumulative probability distribution of exposure and the cumulative probability distribution of inhibitory rate dose response for the corresponding combination.
As shown in FIG. 11, the cumulative probability distribution EC according to the exposure1And inhibition rate dose response cumulative probability distribution IC1Obtaining the corresponding probability curve PC1. And the probability curve PC is obtained through the Origin software1Area a enclosed by horizontal and vertical axes1Is 0.0035, i.e. the drug Flo is Flo1The concentrations of the combination correspond to those in the case of graph (a) in FIG. 5, but close to those in graph (e) in FIG. 5, mutations in the overall appearance can occur with very low or very low probability.
Similarly, a can be obtained2To a10The numerical value of (c). As shown in FIG. 12, the two curves in FIG. 12 are probability curves PC1And probability curve PC2In FIG. 12, a is visually observed1And a2A remaining of3To a10And a1The positional relationship presented may be as shown in fig. 12.
Suppose a1To a10All are 0.0035, and the total probability of the bacterial drug resistance mutation is calculated by adopting the following formula:
TP＝12.25×0.0035＝0.0429 (6)
wherein 12.25 is the highest concentration of the combination. The total probability TP of the drug resistance mutation of the bacteria is a unitless dimensional parameter which can comprehensively reflect the chance probability of the drug resistance mutation of the actual situation, and the larger the numerical value is, the higher the probability of the drug resistance mutation is.
Referring to fig. 13, based on the same inventive concept, an embodiment of the present invention further provides an apparatus 100 for predicting drug resistance of bacteria by drug combination, where the apparatus 100 includes: a processing module 101, a judging module 102 and a predicting module 103.
A processing module 101 for taking y from the second medicationiN drug concentrations corresponding to the combination of drugs at concentration and generated in each experimental scenarioObtaining inhibition rate dose response cumulative probability distribution IC of drug combination by using antibacterial effectiIn each experimental scenario, x is taken from the first drug1、…、xnConcentration and the second drug are taken as y1、…、ymIn concentration, the two are combined in pairs to carry out the combined medication scene, and the inhibition rate dose response cumulative probability distribution ICiRepresenting the probability of correspondingly generating the bacteriostatic effect under the condition that the combined medicines are used at different medicine concentration, wherein i is 1 to m; according to the second drug fetch yiObtaining the exposure cumulative probability distribution EC of the combined drug by using n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined drug at the concentrationiCumulative probability distribution of exposure ECiThe probability of the residual concentration of the drug is characterized under different drug concentrations of the combined drug.
A judging module 102, configured to calculate an exposure cumulative probability distribution EC according to the drug combinationiJudging when the second medicine is takeniWhether the corresponding experiment at concentration satisfies the possibility of bacterial drug resistance mutation; if yes, taking y according to the second medicineiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is takeniMutation prevention concentration MPC in n drug concentrations at concentrationiCumulative probability distribution of exposure ECiAnd inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationiThe minimum inhibitory concentration is the concentration of the drug combination of the first drug and the second drug which can inhibit the growth and the reproduction of bacteria, and the mutation prevention concentration is the minimum concentration of the antibacterial drug required for preventing the selective multiplication of the drug-resistant mutant strain in the first step.
A prediction module 103 for obtaining Q probability curves PCiArea of curve a under the lineiAnd the second drug is takeniProbability of occurrence p of concentrationiAccording to the probability curve PCiArea of curve a under the lineiAnd probability of occurrence piObtaining the total probability of the drug-resistant mutation of the bacteria, and representing the drug resistance of the bacteria under the actual conditionProbability of chance of mutation, wherein Q is less than or equal to m.
Optionally, the processing module 101 is specifically configured to obtain x values of the first drug respectively according to the cumulative probability distribution of the exposure of the first drug under a single condition1、…、xnProbability value F corresponding to concentrationjWherein j is 1 to n; obtaining y of the second medicament respectively according to the exposure cumulative probability distribution of the second medicament in a single condition1、…、ymProbability value G corresponding to concentrationiWherein i is 1 to m; according to the second drug fetch yiThe concentration of n drugs corresponding to the combined administration is x1、…、xnThe corresponding probability value M and the second medicine are respectively y1、…、ymProbability value G corresponding to concentrationiObtaining cumulative probability distribution of exposure EC for drug combinationiWherein M ═ { F ═ F1,...,Fj,...,Fn}。
Optionally, the processing module 101 is specifically configured to take x from the first medicine respectively1、…、xnThe corresponding probability value M at the concentration is respectively taken out of y with the second medicine1、…、ymProbability value G corresponding to concentrationiMultiplying to obtain a second drug yiProbability of drug combination concentration at concentration; taking the second medicine yiThe probability of the concentration of the combined drug is used as the ordinate, and the second drug is taken as yiThe n drug concentrations corresponding to the combined drug at the concentration are used as the abscissa, and the exposure cumulative probability distribution EC of the combined drug is obtainedi。
Optionally, the determining module 102 is specifically configured to determine the MIC according to the minimum inhibitory concentrationiObtaining an exposure cumulative probability distribution ECiCorresponding mutation probability Yi(ii) a Judging mutation probability YiIf it is less than 1, if the mutation probability YiLess than 1 indicates that y is taken as the second drugiThe corresponding experiments at concentration satisfy the possibility of a resistant mutation in bacteria.
Optionally, the determining module 102 is specifically configured to determine the MIC according to the minimum inhibitory concentrationiObtaining inhibition rate dose response cumulative probability distribution ICiAnd exposure ofCumulative probability distribution ECiRespectively corresponding effect probability XiAnd mutation probability Yi(ii) a MPC according to mutation prevention concentrationiObtaining a plurality of points (X ', Y '), wherein Y '<1-Yi、X'>Xi(ii) a Obtaining a probability curve PC from a plurality of pointsi。
Optionally, the prediction module 103 is specifically configured to determine the area a of the curve under the lineiAnd probability of occurrence piAcquiring a total probability curve; and calculating the area of the curve under the total probability curve, wherein the area of the curve under the total probability curve is the total probability of the drug-resistant mutation of the bacteria.
Optionally, the processing module 101 is further configured to obtain residual concentrations of the first drug and the second drug in each experimental scenario when the c% bacteriostatic rate is achieved, where c is greater than or equal to 0 and less than or equal to 100; according to the concentration of the first drug in the single case of c% bacteriostasis rate, the concentration of the second drug in the single case of c% bacteriostasis rate and the y value of the second drugiThe residual concentration of the first drug and the residual concentration of the second drug at the time of concentration are obtained as n drug concentrations corresponding to the combined administration.
Optionally, the processing module 101 is further configured to accumulate the inhibition rate dose response probability distribution ICiAnd cumulative probability distribution of exposure ECiAre presented in the same coordinate system.
Referring to fig. 14, a schematic block diagram of an electronic device 200 for a method and an apparatus for predicting drug resistance of drug-resistant bacteria is provided. In the embodiment of the present application, the electronic Device 200 may be, but is not limited to, a Personal Computer (PC), a smart phone, a tablet Computer, a Personal Digital Assistant (PDA), a Mobile Internet Device (MID), and the like. Structurally, electronic device 200 may include a processor 210 and a memory 220.
The processor 210 and the memory 220 are electrically connected, directly or indirectly, to enable data transmission or interaction, for example, the components may be electrically connected to each other via one or more communication buses or signal lines. The processor 210 may be an integrated circuit chip having signal processing capabilities. The Processor 210 may also be a general-purpose Processor, for example, a Central Processing Unit (CPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a discrete gate or transistor logic device, or a discrete hardware component, which can implement or execute the methods, steps, and logic blocks disclosed in the embodiments of the present Application. Further, a general purpose processor may be a microprocessor or any conventional processor or the like.
The Memory 220 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), and an electrically Erasable Programmable Read-Only Memory (EEPROM). The memory 220 is used for storing a program, and the processor 210 executes the program after receiving the execution instruction.
It should be noted that, as those skilled in the art can clearly understand, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Based on the same inventive concept, embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, the computer program performs the methods provided in the above embodiments.
The storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a division of one logic function, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above embodiments are merely examples of the present application and are not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims (12)

1. A method for predicting resistance of bacteria to drugs by combined administration, the method comprising:
according to the second drug fetch yiN drug concentrations corresponding to combined drug administration at concentration and yield in each experimental sceneObtaining the inhibition rate dose response cumulative probability distribution IC of the combined medicine by the raw antibacterial effectiEach experimental scene is that x is taken from the first medicine respectively1、…、xnThe concentration and the second drug are respectively y1、…、ymIn concentration, the two are combined in pairs to carry out the combined medication scene, and the inhibition rate dose response cumulative probability distribution ICiRepresenting the probability of the corresponding antibacterial effect under the condition that the combined medicine is taken at different medicine concentration, wherein i is 1 to m;
taking y according to the second medicineiObtaining the exposure cumulative probability distribution EC of the combined medication by the n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined medication at the concentrationiThe cumulative probability distribution of exposure ECiCharacterizing the probability of residual concentration of the drug at different dosing concentrations of the combination;
(iii) cumulative probability distribution of exposure EC from the combinationiJudging when the second medicine is takeniWhether the corresponding experiment at concentration satisfies the possibility of bacterial drug resistance mutation;
if yes, taking y according to the second medicineiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is taken yiMutation prevention concentration MPC among said n drug concentrations at concentrationiThe cumulative probability distribution of exposure ECiAnd said inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationiThe minimum inhibitory concentration is the lowest concentration of the first medicament and the second medicament which can inhibit the growth and the reproduction of bacteria, and the mutation prevention concentration is the lowest concentration of the antibacterial medicament required for preventing the selective multiplication of the first-step drug-resistant mutant strain;
obtaining Q probability curves PCiArea of curve a under the lineiAnd the second drug is taken yiProbability of occurrence p of concentrationiAccording to said probabilityCurve PCiArea of curve a under the lineiAnd the occurrence probability piAnd acquiring the total probability of the bacterial drug resistance mutation, wherein the total probability of the bacterial drug resistance mutation represents the opportunity probability of bacterial drug resistance mutation under the actual condition, and Q is less than or equal to m.
2. The method of claim 1, wherein said taking y from said second medicationiObtaining the exposure cumulative probability distribution EC of the combined medication by the n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined medication at the concentrationiThe method comprises the following steps:
obtaining x from the first drug according to the exposure cumulative probability distribution of the first drug under a single condition1、…、xnProbability value F corresponding to concentrationjWherein j is 1 to n;
obtaining y of the second medicament according to the exposure cumulative probability distribution of the second medicament under a single condition1、…、ymProbability value G corresponding to concentrationiWherein i is 1 to m;
taking y according to the second medicineiWhen the concentration is higher than the preset value, the concentration of n medicines corresponding to the combined medicine and the first medicine are respectively x1、…、xnThe corresponding probability value M and the second medicine are respectively y1、…、ymProbability value G corresponding to concentrationiObtaining an exposure cumulative probability distribution EC for the combinationiWherein M ═ { F ═ F1,...,Fj,...,Fn}。
3. The method of claim 2, wherein said taking y from said second medicationiWhen the concentration is higher than the preset value, the concentration of n medicines corresponding to the combined medicine and the first medicine are respectively x1、…、xnThe corresponding probability value M and the second medicine are respectively y1、…、ymProbability value G corresponding to concentrationiObtaining an exposure cumulative probability distribution EC for the combinationiThe method comprises the following steps:
taking x from the first medicine respectively1、…、xnThe corresponding probability value M at the concentration is respectively equal to the second medicine y1、…、ymProbability value G corresponding to concentrationiMultiplying to obtain the second drug yiProbability of drug combination concentration at concentration;
taking the second medicine yiThe probability of the concentration of the combined medicine is used as the ordinate, and the second medicine is taken as yiThe n drug concentrations corresponding to the combined drug at the time of concentration are taken as abscissa, and the exposure cumulative probability distribution EC of the combined drug is obtainedi。
4. The method of claim 1, wherein the cumulative probability distribution of exposure, EC, based on the combination isiJudging when the second medicine is takeniThe corresponding experiments at concentrations met the possibility of bacterial resistance mutations, including:
MIC according to the minimum inhibitory concentrationiObtaining the cumulative probability distribution of exposure ECiCorresponding mutation probability Yi；
Judging the mutation probability YiIf it is less than 1, if the mutation probability YiLess than 1 indicates that y is taken for the second drugiThe corresponding experiments at concentration satisfy the possibility of a resistant mutation in bacteria.
5. The method of claim 1, wherein said taking y from said second medicationiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is taken yiMutation prevention concentration MPC among said n drug concentrations at concentrationiThe cumulative probability distribution of exposure ECiAnd said inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationiThe method comprises the following steps:
according to said minimumMIC of bacteriostatic concentrationiObtaining said inhibition rate dose response cumulative probability distribution ICiAnd the cumulative probability distribution of exposure ECiRespectively corresponding effect probability XiAnd mutation probability Yi；
MPC based on said mutation prevention concentrationiObtaining a plurality of points (X ', Y '), wherein Y '<1-Yi、X'>Xi；
Obtaining the probability curve PC according to the plurality of pointsi。
6. The method of claim 1, wherein the PC is based on the probability curveiArea of curve a under the lineiAnd the occurrence probability piObtaining the total probability of the drug-resistant mutation of the bacteria, comprising the following steps:
according to the area a of the curve under the lineiAnd the occurrence probability piAcquiring a total probability curve;
and calculating the area of the curve under the total probability curve, wherein the area of the curve under the total probability curve is the total probability of the drug-resistant mutation of the bacteria.
7. The method of claim 1, wherein the inhibition rate of said combination is obtained by obtaining a dose response cumulative probability distribution ICiAnd cumulative probability distribution of exposure ECiPreviously, the method further comprises:
obtaining the residual concentrations of the first medicament and the second medicament in each experimental scene when the bacteriostasis rate of c% is realized, wherein c is more than or equal to 0 and less than or equal to 100;
according to the concentration of the first drug in a single condition at the c% bacteriostasis rate, the concentration of the second drug in a single condition at the c% bacteriostasis rate and the y value of the second drugiAnd obtaining the n drug concentrations corresponding to the combined drug according to the residual concentration of the first drug and the residual concentration of the second drug in concentration.
8. The method of claim 1, wherein dose response is accumulated while obtaining the inhibition rateProbability distribution ICiAnd the cumulative probability distribution of exposure ECiThereafter, the method further comprises:
(ii) dose-response cumulative probability distribution IC of said inhibition rateiAnd the cumulative probability distribution of exposure ECiAre presented in the same coordinate system.
9. The method of claim 1, wherein the probability curve PCiArea of curve a under the lineiAre all larger than the preset area value.
10. A prediction device for controlling bacterial resistance by combination therapy, the device comprising:
a processing module for taking y according to the second medicineiObtaining the inhibition rate dose response cumulative probability distribution IC of the combined medication by n drug concentrations corresponding to the combined medication and the bacteriostatic effect generated in each experimental sceneiEach experimental scene is that x is taken from the first medicine respectively1、…、xnThe concentration and the second drug are respectively y1、…、ymIn concentration, the two are combined in pairs to carry out the combined medication scene, and the inhibition rate dose response cumulative probability distribution ICiRepresenting the probability of the corresponding antibacterial effect under the condition that the combined medicine is taken at different medicine concentration, wherein i is 1 to m; taking y according to the second medicineiObtaining the exposure cumulative probability distribution EC of the combined medication by the n drug concentrations, the exposure cumulative probability distribution of the first drug in a single case and the exposure cumulative probability distribution of the second drug in a single case corresponding to the combined medication at the concentrationiThe cumulative probability distribution of exposure ECiCharacterizing the probability of residual concentration of the drug at different dosing concentrations of the combination;
a judging module for determining the cumulative probability distribution EC of the drug combinationiJudging when the second medicine is takeniWhether the corresponding experiment at concentration satisfies the possibility of bacterial drug resistance mutation; if yes, taking y according to the second medicineiMinimum inhibitory concentration MIC of n drug concentrations at concentrationiThe second drug is taken yiMutation prevention concentration MPC among said n drug concentrations at concentrationiThe cumulative probability distribution of exposure ECiAnd said inhibition rate dose response cumulative probability distribution ICiObtaining the probability curve PC of the drug resistance mutationiThe minimum inhibitory concentration is the lowest concentration of the first medicament and the second medicament which can inhibit the growth and the reproduction of bacteria, and the mutation prevention concentration is the lowest concentration of the antibacterial medicament required for preventing the selective multiplication of the first-step drug-resistant mutant strain;
a prediction module for obtaining Q probability curves PCiArea of curve a under the lineiAnd the second drug is taken yiProbability of occurrence p of concentrationiAccording to the probability curve PCiArea of curve a under the lineiAnd the occurrence probability piAnd acquiring the total probability of the bacterial drug resistance mutation, wherein the total probability of the bacterial drug resistance mutation represents the opportunity probability of bacterial drug resistance mutation under the actual condition, and Q is less than or equal to m.
11. An electronic device, comprising: a processor and a memory, the processor and the memory connected;
the memory is used for storing programs;
the processor is configured to execute a program stored in the memory to perform the method of any of claims 1-9.
12. A computer-readable storage medium, on which a computer program is stored which, when executed by a computer, performs the method of any one of claims 1-9.
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