901 results about "Drug effect" patented technology

The invention relates to an optimized method for medicament preparation. A machine learning model of a deep neural network is adopted to perform screening and combinatorial optimization on active ingredients and auxiliary materials of the medicament, and a relation model among the ingredients, the drug effect and the stability is established; a dynamic blending module is adopted to adjust the component proportion and dosage in real time according to different medicament preparation conditions including temperature and pH value; constructing a self-adaptive reaction condition adjusting system, and monitoring reaction conditions including temperature, pressure, pH value and stirring speed in the preparation process in real time; a dynamic mixing system is introduced, and a microfluidic technology is adopted to control metering and mixing of pharmaceutical components; a medicament preparation process is decomposed into a plurality of key steps including primary reaction, purification and concentration, and each step is independently optimized; a real-time quality monitoring system is constructed, and the physical properties, including particle size distribution, solubility and purity, of the medicament are monitored in real time through a sensor and imaging equipment; and optimizing the integration platform in the whole process.

The invention discloses a sewage denitrification dosing method and system based on machine learning and a storage medium, and belongs to the technical field of sewage treatment.The method includes the steps that data are collected and preprocessed, and variable data influencing biochemical pool carbon source dosing behaviors are obtained; and lagging influence of carbon source input on the denitrification amount index is analyzed, and the duration time range of the drug effect is determined. And adopting the trained prediction model, and based on the denitrification amount index and the prediction variable of the future t + X period, obtaining the dosage of the (t + 1) th period. Through a correlation analysis method, the correlation rule of nitrogen conversion in the future X period after the carbon source is added is analyzed, the duration time of the drug effect is determined, the lag effect is accurately quantified, and the problem of mismatching of regulation and control opportunities is avoided. The hysteresis effect is captured and subjected to multi-factor coupling analysis based on the prediction model, the carbon source adding amount and time are optimized, system load fluctuation caused by excessive carbon sources or incomplete nitrogen removal caused by insufficient carbon sources are avoided, and the stability of an original sewage ecological system is gradually improved.

The invention discloses a ginsenoside liposome. The ginsenoside liposome comprises ginsenoside, phospholipid and a surfactant, and the ginsenoside comprises protopanoxadiol or / and protopanaxatriol. The invention also discloses a preparation method of the ginsenoside liposome and application of the ginsenoside liposome in preparation of medicines, cosmetics or skin care products. According to the invention, the final desugared product of ginsenoside with the effect of treating skin toxicity reaction is prepared into the liposome, so that the membrane permeation and absorption capabilities of ginsenoside are greatly improved, the skin toxicity caused by tumor treatment can be quickly and effectively relieved, and the drug effect can be played for a long time; the invention provides a new method for treating skin toxic reaction caused by tumor treatment, and makes up for the requirements which cannot be met by the existing treatment means.

The invention relates to a painless gastrointestinal endoscope self-adaptive drug delivery method and system based on multi-source physiological signal fusion, and belongs to the technical field of medical artificial intelligence and automatic control. An artificial intelligence model is utilized to deeply extract features and quantitatively evaluate the sedation-analgesia level of a patient, a pharmacokinetics-pharmacodynamics model constructed by a big data platform is utilized to dynamically predict the drug effect according to the individual features and real-time state of the patient, and the anesthetic infusion rate is automatically and accurately adjusted through a closed-loop control algorithm, so that the patient can be accurately infused. Personalization and self-adaption of drug delivery are achieved, an independent safety monitoring mechanism is set, and real-time intervention is conducted on risk events such as respiratory depression. The problems that traditional anesthesia depends on artificial experience, single parameter monitoring is not comprehensive and individualized dynamic adjustment is lacked can be effectively solved, and the safety, comfort and medical efficiency of painless gastrointestinal endoscopy are remarkably improved.

The invention relates to the technical field of pharmaceutical knowledge maps, in particular to a pharmaceutical knowledge map construction method and system based on artificial intelligence, and the method comprises the following steps: querying and collecting a molecular structure of a drug and a corresponding target protein sequence through a database, and carrying out the numerical coding of the molecular structure data of the drug, molecular fingerprints and protein structural domain features are extracted, and a drug and protein feature set is formed by combining drug chemical attributes and protein sequence features. According to the invention, through accurate analysis of the molecular structure of the drug and the target protein sequence thereof, the innovative scheme significantly enhances the understanding of the interaction of the drug and the protein, so that researchers can directly extract key features from data and monitor the dynamic change of the drug effect, thereby not only accelerating the development process of the drug, but also improving the development efficiency of the drug. By dynamically tracking the interaction between the side effect of the medicine and the pathological characteristics, the scheme provides powerful data support for personalized medical treatment.

The invention discloses an intelligent anesthesia drug delivery system and a control method thereof, and the method comprises the steps: obtaining operation information, predicting operation time, predicting operation state stability, determining a drug delivery strategy according to an operation time prediction value and an operation state prediction value, and controlling a vein micro pump based on a collaborative sliding mode control algorithm of an intelligent algorithm. And judging whether the anesthesia scheme needs to be adjusted. According to the method, prediction of the operation time and the operation state is achieved, a mode for objectively selecting anesthesia strategies is provided, anesthesia strategy selection errors caused by artificial omission or insufficient level are avoided, a collaborative sliding mode control algorithm based on an intelligent algorithm is used for controlling the multi-channel vein micro pump, and the operation efficiency is improved. Synergism of multiple drugs during injection is guaranteed, and optimal drug effect synergy is achieved.

The invention relates to the technical field of drug interaction prediction, and discloses a drug interaction prediction method based on multilayer attention and elastic message passing, which comprises the following steps: firstly, extracting graph structure information of drug molecules from a 3D structure of the drug molecules, including associated features of atoms and chemical bonds; on the atomic feature level, learning updating and denoising of different atom and chemical bond features in drug molecules are achieved by using an elastic graph neural network and fusing the attention mechanism of Transform and combining a 3D position coding method based on the molecular mass center; on the molecular feature level, the attention mechanism is further utilized, and through supervised learning, comparative learning and structured learning, the potential interaction relationship of different drug molecules is mined, and potential network attacks are detected and defended; and interaction prediction of any two drug molecules i and j is realized. The results of four indexes of ACC, AUC, AP and F1 all reach 98% or above, and the method exceeds the most advanced method at present.

The invention provides a novel strain M2108 of a salt-tolerant bacillus, the preservation number of the salt-tolerant bacillus is CGMCC (China General Microbiological Culture Collection Center) No.28283, and the novel strain M2108 of the salt-tolerant bacillus has relatively good salt tolerance and can grow and proliferate in a high-salt environment; the strain can be rapidly and stably colonized in a plant, and is rapid in propagation speed and strong in multiplication capacity in the plant. The new strain M2108 of the salt-tolerant bacillus provided by the invention has a treatment effect and a high control effect on various plant diseases: the control effect on diseases such as tomato root rot, damping-off and damping-off caused by fusarium oxysporum, pythium aphanidermatum and rhizoctonia solani is high, and the average control effect is 91.2% or above. When being used for preventing and treating plant diseases, the salt-tolerant bacillus M2108 is not easy to generate drug resistance, has good drug effect durability, is safe to human and livestock, and does not cause environmental pollution; the salt-tolerant bacillus M2108 microbial agent and the biocontrol agent provided by the invention are simple in preparation method, low in cost and simple and convenient to use. The salt-tolerant bacillus M2108 has a good application prospect in the prevention and control of plant diseases, and lays a foundation for the development of efficient and broad-spectrum biocontrol preparations.

The invention belongs to the technical field of drug screening, and provides a multi-target drug screening and optimizing method based on machine learning, which comprises the following steps: S1, carrying out feature screening on compound molecular descriptors by utilizing a machine learning algorithm, and determining the molecular descriptor which has the most significant influence on biological activity; s2, constructing a quantitative structure-activity relation model, and predicting the biological activity of the compound; s3, based on a multi-objective optimization algorithm, combining absorption, distribution, metabolism, excretion and toxicity properties of the compound; according to the method, feature screening is carried out on compound molecule descriptors by utilizing a machine learning algorithm, a QSAR model is constructed to predict the biological activity, ADMET property classification prediction is combined, the biological activity, ADMET properties and pharmacokinetic characteristics of drugs are comprehensively considered, and the accuracy and accuracy of drug activity prediction are improved. The method can efficiently and accurately screen and optimize drug candidate compounds with potential drug effects and good pharmacokinetic characteristics, so that the success rate of drug research and development is increased, and the research and development cost and time are reduced.

The invention discloses a movable geotextile pipe bag mud dewatering and curing treatment method, and relates to the technical field of sludge treatment.According to the movable geotextile pipe bag mud dewatering and curing treatment method, the adding amount of a flocculating agent is dynamically adjusted according to mud data monitored in real time, and the situation of agent waste or insufficient drug effect caused by a traditional fixed-proportion agent adding mode is avoided; a fuzzy control algorithm is adopted to dynamically adapt to the component change of the slurry, the cost of excessive use of chemicals is reduced, a chemical adding strategy is automatically adjusted, the slurry treatment effect is more stable, meanwhile, a multi-stage chemical adding mode is adopted, a flocculating agent is evenly distributed in the slurry, the flocculating agent can cover large particles and fine particles, and the treatment efficiency is improved. The problem of non-uniform flocculation caused by a single dosing point is improved, the overall efficiency of slurry dehydration is effectively improved by treating slurry with different particle sizes at different stages, and the stirring strength is dynamically adjusted based on slurry flow and particle size parameters, so that a flocculating agent and particles in the slurry are fully mixed, and the flocculation effect is improved.

The invention relates to the technical field of intelligent anesthesia precise regulation and control, and discloses an anesthetic dosage optimization method based on artificial intelligence. According to the method, a dynamic treatment interval is constructed, and the boundary of the dynamic treatment interval is adaptively adjusted according to the real-time sedation depth and the nociceptive stimulation level. And in the interval, performing pattern recognition on the continuous electroencephalogram signals and the hemodynamic parameters, and marking abnormal events deviating from a standard anesthesia state. And establishing a correlation network of the drug effect chamber concentration and the abnormal events, and generating a virtual drug response curve for predicting the trend of the abnormal events under different doses. Whether dose strategy reconstruction is started or not is determined by comparing the goodness of fit between the prediction curve and the actual physiological trajectory. During reconstruction, contribution weights of historical drug infusion points to abnormal events are backtracked and analyzed, and adjustment coefficients are distributed and integrated into a new infusion sequence. According to the invention, individualization and self-adaptive optimization of anesthesia administration are realized, and the accuracy and safety of anesthesia depth control are improved.

The invention discloses a dependency-free anti-aging sleep-aiding preparation and a preparation method thereof, and relates to the technical field of preparations, the anti-aging sleep-aiding preparation comprises an ellipsoidal shell and an ellipsoidal core wrapped in the ellipsoidal shell, the ellipsoidal core comprises an anti-aging agent layer, a water absorption expansion layer and a sleep-aiding agent layer which are stacked in sequence, the water absorption expansion layer protrudes at the two ends of the ellipsoidal core to form small water diversion columns; small water inlet holes are formed in the two ends of the ellipsoidal shell and are connected with small water diversion columns; a plurality of first release holes and a plurality of second release holes are formed in the circumferential surface of the ellipsoidal shell, the plurality of first release holes lead to the anti-aging agent layer, and the plurality of second release holes lead to the sleep aid layer. Through the special structural design of the ellipsoidal shell and the ellipsoidal core, isolated coexistence of anti-aging and sleep-aiding components and controllable release of the anti-aging and sleep-aiding components are achieved, so that the dual effects of anti-aging and sleep-aiding can be achieved, and it is guaranteed that the drug effect is continuously exerted.

The invention provides an asymmetric drug interaction prediction method based on a diffusion diagram attention network, and relates to the technical field of drug interaction prediction.The method comprises the steps that a directed graph network is constructed by using chemical structure features of drug molecules, and features are extracted from drug applying and receiving perspectives through a two-way diagram attention network; therefore, the asymmetry between the drugs is effectively represented. Furthermore, a diffusion model is introduced to carry out noise injection and de-noising processing on a graph structure, so that the adaptability of the model to sparse data and the robustness of feature extraction are remarkably enhanced. Finally, multi-modal features are fused through a deep neural network, and high-precision prediction of drug interaction is realized. Compared with the prior art, the method has the advantages that the prediction accuracy exceeds that of the prior art, the dependence on labeled data is greatly reduced, the feasibility and generalization ability of the model in practical application are greatly improved, and a new technical path is provided for safety evaluation and precise medical research of drug combination therapy.

The invention discloses a traditional Chinese medicine curative effect intelligent analysis and prediction platform, and relates to the technical field of traditional Chinese medicine analysis. The intelligent management platform is in communication connection with a data preprocessing and standardization module, a symptom description standardization processing module, a network relation analysis module, a network target positioning module, a network target navigation module, a drug effect prediction and evaluation module and a report generation and output module. According to the traditional Chinese medicine curative effect intelligent analysis and prediction platform, by integrating a machine learning technology, the accuracy of traditional Chinese medicine curative effect evaluation is remarkably improved, a large number of traditional Chinese medicine prescriptions, patient syndromes and curative effect data information are collected and analyzed, and the treatment effects of the traditional Chinese medicine prescriptions on different syndromes are evaluated by combining a network target and an established network relationship; and analysis results of the drug target intervention effect and the synergistic effect are provided, so that the action mechanism of the traditional Chinese medicine prescription can be deeply understood, and the traditional Chinese medicine prescription with a potential curative effect can be quickly screened out.

The invention discloses a single-cell drug causal gene discovery method and system based on adversarial transfer learning, and relates to the technical field of drug sensitivity prediction.The method comprises the steps that a source domain data set and a target domain data set are obtained, an adversarial transfer model is constructed, and the adversarial transfer model is trained and optimized according to the source domain data set and the target domain data set; obtaining a single-cell drug sensitivity prediction result; modeling single-cell gene expression data, combining a k-adjacent matching algorithm and a single-cell drug sensitivity prediction result to obtain an anti-fact value, and further calculating a hybrid effect and a difference effect; and calculating the causal effect based on the hybrid effect and the difference effect, and screening out the causal gene of the single-cell drug. On one hand, the key problem of lack of drug sensitivity labeling data in single cell analysis is solved, on the other hand, the causal gene is successfully found, and an important clue is provided for deep understanding of a drug action mechanism.

The invention provides a whole-process targeting polypeptide, a drug compound thereof, a drug delivery system and application of the whole-process targeting polypeptide. The whole-process targeting polypeptide comprises pHA and VAP which are covalently connected through a bridging structure; the VAP is LVAP, a reverse sequence polypeptide of the LVAP, DVAP or SVAP; wherein the amino acid sequence of the LVAP is as shown in SEQ ID NO: 1; the SVAP is a D-configuration polypeptide of the LVAP; the DVAP is a D-configuration polypeptide of the LVAP inverted sequence polypeptide; the bridging structure is amino-monoethylene glycol-carboxylic acid or a derivative thereof. The whole-process targeting polypeptide not only can cross a blood-brain barrier, target tumor neovascularization, cross a blood-tumor barrier, target tumor mimicry vessels, tumor cells and stem cells thereof, but also has better tumor cell affinity, anti-tumor treatment and in-vivo safety effects. Meanwhile, the drug compound or the drug delivery system has a synergistic effect after being combined with a chemotherapeutic drug, and the anti-tumor drug effect can be remarkably improved.

The invention relates to a deep learning method-based pharmacokinetics-pharmacodynamics and reinforcement learning-based propofol administration method and application thereof, a PKPD model is used for simulating the metabolic process of propofol in a human body, and a time dependency relationship and dynamics continuous information are extracted through LSTM and Neural OED; then a nonlinear relation between the propofol drug effect concentration and a clinically observed anesthesia depth index BIS is established through a Kan network, mapping between monitoring information and the anesthesia depth in an operation is rapidly established, a strategy is adjusted in time according to environment changes, and the method is suitable for processing non-standardized complex problems and has good application prospects. And the dosage and the administration scheme of the medicine are individually adjusted, so that the treatment effect is improved.

The invention discloses a safe medication system and a safe medication method for elderly patients, which can monitor whether the elderly take medicine according to medical advice or not and monitor the health state of the elderly. The physiological data of the patient is monitored by the wearable end, so that the health state of the patient can be roughly judged by combining data such as heart rate, electrocardio, respiratory rate and blood pressure, and whether the patient is in danger or not can be found in time; and meanwhile, whether the drug effect of the patient is exerted and whether the patient has drug safety can be known by monitoring the physiological data for a period of time after drug use. According to the invention, the medical advice is uploaded or issued through the medical care terminal, and the medication information in the medical advice is analyzed into the medicine type counting quantity and the medication mode of the medication, so that the medication plan of the patient is planned, and then the patient is prompted to take the medication on time according to the plan. And the medicines are distributed through the intelligent terminal module, and the intelligent terminal module communicates through the system, so that the medicines can be distributed according to the control of the medical care terminal, the management terminal and the system to prevent the patient from eating by mistake, and the medication safety is greatly improved.

The invention discloses a breast adenoma B3 type source cell strain as well as construction and application thereof, the breast adenoma B3 type source cell strain is named as human breast adenoma cell Hthy2301 Homo sapiens and is preserved in China Center for Type Culture Collection on March 14, 2024, and the preservation number is CCTCC NO: C202478. The human thymoma cell line is stable in character, can be passaged in vitro for a long time, and has high proliferation activity. The human thymoma cell line disclosed by the invention can be used as an effective cell model, and a new experimental model can be provided for deeply researching the occurrence, development and transfer mechanisms of thymoma, the drug resistance mechanism, drug screening, drug effect evaluation and the like.

The invention provides a preparation method and application of magnesium L-threonate, and belongs to the technical field of medicines. The preparation method comprises the following steps: dissolving L-ascorbic acid in water, adding magnesium hydroxide and alkaline magnesium carbonate, stirring, dropwise adding hydrogen peroxide, heating, stirring and reacting, filtering a product, purifying and concentrating by temperature-sensitive molecularly imprinted hydrogel while the product is hot, adding an ethanol water solution into a concentrated solution, standing, crystallizing, filtering, washing and drying to obtain the magnesium L-threonate. And cooling the temperature-sensitive molecularly imprinted hydrogel after adsorption to room temperature, washing and repeatedly using the temperature-sensitive molecularly imprinted hydrogel. The magnesium L-threonate is simple in preparation method, high in purity and high in yield, meanwhile, the slow-release magnesium L-threonate is prepared, and the magnesium L-threonate is low in toxicity, good in biocompatibility, large in drug loading capacity, low in economic cost and good in drug effect and has wide application prospects in preparation of anti-depression drugs.

The invention discloses a quality control method of a traditional Chinese medicine preparation based on an IV-catfish orifice-freeing prescription, and relates to the technical field of analysis of traditional Chinese medicine preparations, and the quality control method comprises the following steps: carrying out microscopic identification on traditional Chinese medicine components in the IV-catfish orifice-freeing prescription, and determining a pharmacodynamic material basis. According to the quality control method for the traditional Chinese medicine preparation based on the IVV orifice-freeing prescription, various evaluation means such as a drug effect equivalent evaluation index, a stability test, a quality test and a clinical test are comprehensively applied, the consistency and reliability of the curative effect of the traditional Chinese medicine preparation can be remarkably improved, and the drug effect equivalent evaluation index is analyzed from the two factors of drug effect intensity and action time; the method ensures the equivalence of the medicinal component group and the original traditional Chinese medicine preparation, comprehensively detects the raw material medicines and the preparation, including characters, identification, inspection and content determination items, and ensures that the quality of each batch of samples meets the standard, so that the curative effect of the traditional Chinese medicine preparation is effectively guaranteed, and the efficacy of the traditional Chinese medicine preparation is improved.

The invention provides a dynamic medication dosage optimization method fused with reinforcement learning. The method comprises the following steps: acquiring a first physiological index parameter of a target patient; obtaining a first diagnosis report of the target patient, wherein the first diagnosis report comprises basic information of the target patient and first disease information of the target patient; the first disease information comprises a first disease type and first disease description information; determining a first reinforcement learning algorithm corresponding to the first disease type; determining a first control parameter of the first reinforcement learning algorithm according to the first physiological index parameter and the basic information; and performing operation on the first disease description information through the first reinforcement learning algorithm and the first control parameter to obtain a first medication dosage parameter. Based on the application, the drug effect can be consistent with the physical condition of a patient, and poor drug effect and excessive side effects caused by too strong drug effect are avoided.

The invention discloses a nano-film for relieving bone fracture pain and a preparation method thereof, and relates to the technical field of medical films, the nano-film comprises an inner layer, a middle layer and an outer layer, the three layers are prepared by mixing traditional Chinese medicine extracts and base materials, the nano-film is prepared through an electrostatic spinning technology, the components of all the layers are the same, but the proportions are different, and the inner layer and the middle layer are different. Wherein a polycaprolactone and polyvinyl alcohol blending system is selected as the base material; the inner layer has high drug-loading capacity to quickly relieve symptoms, the middle layer has continuous release, the outer layer has low drug-loading capacity to reduce initial stimulation and increase stability, the use frequency is reduced, the drug effect is prolonged, and adverse reactions are reduced; the functions of protection, slow release and quick release are realized only by adjusting the proportion of PCL / PVA, and the production process is simplified.

The invention discloses a compound traditional Chinese medicine patch for conditioning hyperplasia of mammary glands and a preparation method thereof, and relates to the technical field of traditional Chinese medicine preparations. The compound traditional Chinese medicine patch for conditioning hyperplasia of mammary glands is prepared from an iron-based metal organic framework composite drug carrying system, dopamine hydrochloride, a blank gel matrix, ethyl oleate, menthol, a solubilizer, a wetting agent and water, the iron-based metal organic framework composite drug loading system is composed of traditional Chinese medicine dihydric alcohol plastid, iron-based metal organic framework nanoparticles and cinnamomum camphora essential oil. The traditional Chinese medicine dihydric alcohol plastid and the cinnamomum camphora essential oil are loaded in the iron-based metal organic framework nano particles, so that the transdermal absorption of the medicine is improved, the pH response release property is realized, the dosage of active ingredients permeating into a focus part and the lasting action time are effectively increased, and then a coating layer is formed by polydopamine, so that the anti-inflammatory effect is improved. The dispersibility and compatibility of the drug loading system in vivo are further enhanced, the drug effect can be fully exerted, and the treatment effect on the hyperplasia of mammary glands is remarkably improved.

The invention relates to the technical field of traditional Chinese medicine research, in particular to a discovery method of a cough relieving and phlegm eliminating quality marker of cough relieving granules and the quality marker. According to the application, the cough-relieving and phlegm-eliminating drug effects of the cough-relieving granules are evaluated by virtue of concentrated ammonia water cough inducing and phenol red excretion tests, plasma pharmaceutical chemistry research of the cough-relieving granules is developed by virtue of a UHPLC-Q-Exactive Plus Orbitrap HRMS technology, and 26 prototype blood-entering components of the cough-relieving granules are analyzed and identified; through network pharmacological analysis of components entering blood, 11 potential active components for relieving cough and eliminating phlegm of the cough-relieving granules are screened, relate to 40 common targets such as IL6, TLR4, STAT3 and the like, and mainly participate in signal channels such as PI3K-Akt, HIF-1, EGFR (epidermal growth factor receptor) and the like; the seven prototype blood-entering components are quantitatively analyzed by utilizing pharmacokinetics. The three compounds of azelaic acid, caffeic acid and vanillin are used as the cough relieving and phlegm eliminating quality markers of the cough relieving granules through effectiveness, transitivity and testability. The research result is of great significance in deeply defining the pharmacodynamic material basis of the cough-relieving granules, optimizing the quality standard and promoting the clinical application of the cough-relieving granules.

The invention relates to the technical field of pesticide detection, in particular to a pesticide preparation efficacy detection method and system, which improve the objectivity and accuracy of efficacy detection through data driving and multi-dimensional evaluation in combination with real-time monitoring and automatic analysis, ensure the reliability of results through abnormal physiological index recognition, and improve the accuracy of efficacy detection. The method has the advantages of high efficiency, flexibility and high environmental adaptability, and the problems of high subjectivity, long consumed time, inaccurate result and the like in a traditional method are solved; the method comprises the following steps: collecting real-time growth state data and growth environment data of crops after a set duration of application of a pesticide preparation to be detected, and initial growth state data of the crops before application; inputting the initial growth state data, the real-time growth state data and the growth environment data into a pesticide effect analysis model to obtain a first pesticide effect detection result; and performing real-time biochemical analysis on the crops to obtain a crop physiological index set.

The invention provides a PTK7 targeted nucleic acid aptamer coupling drug and a new application thereof, through research, drugs are respectively coupled at the third end and the fifth end of a targeted PTK7 nucleic acid aptamer, the constructed drug is found to have obvious difference in stability and drug effect, aiming at a PTK7 target spot, the most preferable targeted nucleic acid aptamer and the most preferable drug are found, and the most suitable connexon is selected, so that the PTK7 targeted nucleic acid aptamer coupling drug can be used for preparing the PTK7 targeted nucleic acid aptamer coupling drug and the new application of the PTK7 targeted nucleic acid aptamer coupling drug. Based on a covalent coupling reaction of sulfydryl-maleimide, a PTK7 targeted aptamer coupling drug SM capable of remarkably improving the anti-tumor effect is constructed, and a new direction is provided for screening more efficient anti-tumor drugs.

The invention discloses a novel PARP / CK2 double-target kinase inhibitor small molecule as well as a pharmaceutical composition and application thereof, the small molecule takes benzofuran pyrimidone as a parent drug effect ring and a benzene ring as a connector in drug design, and is coupled with a 1-amino-2-methylisothiourea group, so that the novel PARP / CK2 double-target kinase inhibitor is obtained. The compound has good inhibitory activity on exogenous PARP enzyme, exogenous CK2 alpha enzyme and proliferation activity of various cancer cells, and can be used for preparing antitumor drugs. # imgabs0 #

Compared with the prior art, the traditional Chinese medicine compound oral liquid is mainly used for invigorating qi and blood, regulating yin and yang, nourishing liver and kidney, strengthening spleen and stomach, strengthening muscles and bones and the like, a plurality of traditional Chinese medicine components are compounded and decocted to obtain liquid medicine, and finally specific modified polysaccharide, steviosin, sodium benzoate and ethylparaben are added, so that the traditional Chinese medicine compound oral liquid is prepared. The modified polysaccharide is screened and optimized and is added into the compound oral liquid, and the problems of serious wall hanging and high liquid medicine waste rate in the prior art are solved by reducing the low-temperature storage wall hanging rate and the hydrolysis rate in storage stability on the premise of not influencing the medicine effect and safety.

The invention relates to the field of drug effect simulation, in particular to a drug effect simulation system, which comprises a data input module for receiving drug information and patient information and carrying out structured storage on the information; the data preprocessing module is used for performing cleaning, standardization and feature extraction on the input data; the intelligent model selection module automatically selects the most suitable PK and PD models through a machine learning algorithm in combination with historical data; the personalized parameter adjusting module is used for dynamically adjusting simulation parameters according to the specific data of the patient; the drug effect simulation module is used for simulating the action process of the drug in the virtual environment and adjusting the simulation in real time through the real-time feedback module; the calculation module is used for executing simulation calculation and generating a drug effect prediction result; and the result analysis module is used for carrying out statistical analysis on the simulation result and generating a drug effect prediction curve and a detailed report.