Efficient chromatography system and method for blood product separation

Abstract

The invention belongs to the field of blood product separation, and discloses a high-efficiency chromatography system and method for blood product separation, and the system comprises an intelligent chromatography column module, an automatic sample injection and accurate flow rate control module, a chromatography filler and column design module, a real-time detection and data analysis module, and an intelligent automatic control and management module. By designing an efficient micro-nano filler chromatographic column and matching with a pulsed electric field auxiliary technology and intelligent automatic control, efficient and high-purity separation and purification of target blood product components are realized. The intelligent regulation and control module used in the invention can dynamically regulate chromatography conditions in real time, and the problems of unstable flow velocity and column pressure in the traditional method are thoroughly solved. And meanwhile, a multi-point real-time detection and feedback technology is adopted, so that the separation process is more accurate, transparent and controllable.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the technical field of blood product separation, and in particular relates to a high-efficiency chromatography system and method for separating blood products. Background Art

[0002] Traditional gravity chromatography technology uses filler particles to separate blood products. Due to the influence of gravity, the separation speed is slow, the separation efficiency is low, the sample processing volume is small, the production cycle is long, and it is difficult to accurately control, which cannot meet the requirements of industrial-scale production.

[0003] Although conventional HPLC technology has high separation efficiency, due to the large particle size of the column packing, unstable column pressure, and easy clogging of the separation material, the column efficiency drops rapidly during operation, and the column needs to be replaced frequently, making it difficult to achieve stable continuous operation on an industrial scale, and the maintenance cost is high.

[0004] In view of the above analysis, the technical problems that need to be solved urgently in the existing technology are:

[0005] In the separation process of blood products, due to low separation efficiency, frequent material blockage and complex operation, it is unable to meet the needs of high-throughput, industrial-scale production and high-quality, high-purity separation of blood products. There is an urgent need to develop an efficient, stable and industrially suitable blood product separation system. Summary of the Invention

[0006] In view of the problems existing in the prior art, the present invention provides a high-efficiency chromatography system and method for separating blood products.

[0007] The present invention is achieved by a high-efficiency chromatography system for separating blood products, characterized in that the high-efficiency chromatography system for separating blood products specifically comprises:

[0008] Intelligent chromatography column module, the chromatography column is filled with highly stable nano-porous filler, adopts a special column head structure, and is equipped with a pressure sensor to monitor and automatically adjust the mobile phase pressure in real time;

[0009] Automatic injection and precise flow rate control module, which uses a fully automatic injection system to accurately control the injection volume of blood samples and achieves precise flow rate control through an intelligent peristaltic pump;

[0010] The chromatography packing and column design module develops new ultrafine particle stationary phase packings with a particle size of 1 to 3 μm, using innovative micro-nano porous structures to increase separation surface area and adsorption sites;

[0011] The real-time detection and data analysis module uses ultraviolet spectrometry, fluorescence detectors, and highly sensitive conductivity detectors to monitor the absorption spectra and concentration changes of each component during the chromatography process in real time. It uses a built-in AI analysis algorithm to dynamically analyze the detection data and provide feedback to adjust the separation parameters.

[0012] The intelligent automatic control and management module, based on a deep reinforcement learning algorithm, analyzes feedback data in real time and autonomously adjusts injection volume, mobile phase flow rate, pressure, and column temperature.

[0013] Furthermore, the intelligent chromatography column module has a chromatography column filled with nano-scale porous fillers with a particle size of 1-3 μm.

[0014] Furthermore, the automatic injection and precise flow rate control module can achieve an injection volume accuracy of blood samples of ±0.1 μL and a flow rate control accuracy of ±0.01 mL / min.

[0015] Another object of the present invention is to provide a high-efficiency chromatography method for separating blood products, the method specifically comprising:

[0016] S1: Sample pretreatment: The blood product to be separated is centrifuged to initially separate and remove solid particles, and then accurately injected into the chromatography system through the automatic sampling system and enters the chromatography column;

[0017] S2: Optimize chromatographic separation. Through the intelligent automatic control module, the mobile phase flow rate, column pressure and column temperature are precisely adjusted to maintain the stable and efficient operation of the chromatography column. Micro-nano porous fillers are used for efficient adsorption and desorption to quickly and efficiently separate target proteins or other target components in blood products.

[0018] S3: Real-time detection and analysis. When the separated sample flows out of the chromatography column, the real-time detection module immediately performs ultraviolet spectrum scanning or conductivity detection on the chromatography effluent, monitors the elution curve of the target component in real time, and feeds back to the control system, automatically adjusting the separation parameters based on the feedback data.

[0019] S4: Automatic collection and storage of target components. The automatic collection system is intelligently controlled based on real-time detection data to accurately collect different components in sections to obtain high-purity target blood products. These components are automatically stored in dedicated containers, and the separation process data for each batch is recorded and stored to achieve full traceability.

[0020] S5: System adaptive optimization. After each run, the system automatically performs in-depth analysis and training on the separation data, and the optimization algorithm automatically updates the various separation parameters to the optimal level.

[0021] Furthermore, the injection volume range of the S1 system is set to 10-500 μL, with a control accuracy of ±0.1 μL.

[0022] Furthermore, the S2 has a mobile phase flow rate range of 0.2 to 2 mL / min, with an accuracy of ±0.01 mL / min; a column pressure range of 1000-3000 psi; and a column temperature range of 4-25°C.

[0023] Furthermore, the S3 real-time detection module continuously monitors the components of the chromatography fluid through ultraviolet spectroscopy (UV, detection wavelength 220-280nm), a fluorescence detector (excitation wavelength 280nm, emission wavelength 350nm) and a high-sensitivity conductivity detector; the data acquired by the sensor is transmitted to the central controller in real time after analog-to-digital conversion, providing real-time feedback information of the separation process; the central controller has a built-in deep reinforcement learning algorithm model, which automatically predicts the elution behavior and trend of each component based on the real-time acquired detection data and the historical separation database, and analyzes and evaluates the current separation conditions, calculates the optimal control strategy according to the target setting (such as purity > 95%, activity loss < 5%), and continuously optimizes parameters such as flow rate, column temperature, pressure and injection volume.

[0024] Furthermore, in S4, the optimization control strategy calculated by the central controller is converted into a digital signal and output to the pressure valve, peristaltic pump, and column temperature control unit in real time through the digital-to-analog conversion module; the system automatically adjusts the mobile phase flow rate, system pressure, and column temperature (control temperature range 25-35°C, error ±0.5°C) according to the optimization instructions to achieve automatic closed-loop feedback control.

[0025] Furthermore, in S5, the results of the chromatographic separation process completed by automatic control are compared with the target values in real time to verify whether the purity and activity indicators meet the predetermined standards; when the target is achieved, the system records the optimal process parameters into the historical database to provide data support for subsequent separation; if the indicators do not reach the preset targets, the system automatically starts the iterative optimization program and continues to optimize the parameters until the target values are reached, thereby realizing an efficient, stable and intelligent blood product separation process.

[0026] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0027] This invention utilizes a novel micro-nano porous structured filler with a precisely controlled particle size between 1 and 5 microns, significantly lower than the 10-micron particle size used in existing technologies. This significantly improves separation efficiency, achieving target component purity exceeding 95%. Furthermore, the combination of intelligent adaptive control technology and an automatic pressure adjustment mechanism improves column pressure stability by over 50%, fundamentally resolving the efficiency degradation issues associated with traditional high-performance liquid chromatography (HPLC) due to blockage and pressure fluctuations, ensuring the stability and controllability of the separation process.

[0028] This invention introduces an AI-powered reinforcement learning optimization module to fully automatically and precisely control parameters such as injection volume, flow rate, and temperature in the chromatography process. Compared to traditional methods that rely on manual operation, this system significantly reduces human error and improves operational accuracy. Through intelligent optimization and control, the separation cycle is shortened from 3 hours to less than 1.5 hours, more than doubling separation efficiency while reducing production costs and enhancing its value for industrial applications.

[0029] During the separation and purification of blood products, the present invention enables precise control of chromatographic conditions to maximize the biological activity of plasma proteins, coagulation factors, and immunoglobulins, ensuring stable product quality. In particular, during the separation of coagulation factor VIII and immunoglobulins, the recovery rate and activity preservation of active ingredients are significantly improved, thereby resolving the protein denaturation and activity loss issues associated with separation and purification in existing technologies, further enhancing the safety and clinical effectiveness of blood products.

[0030] This invention combines a high-efficiency micro-nanoscale packed chromatography column with pulsed electric field-assisted technology to achieve efficient, high-purity separation and purification. An intelligent control module dynamically adjusts chromatographic conditions in real time, ensuring that flow rate and column pressure remain optimal. Furthermore, the use of multi-point real-time detection and feedback mechanisms makes the separation process more precise, transparent, and controllable, further enhancing process stability and repeatability.

[0031] The implementation of this technical solution is expected to significantly improve production efficiency in the blood products industry while reducing production costs. The automated, intelligent separation process reduces manual intervention, lowers operating costs, and mitigates product quality fluctuations caused by human factors. Furthermore, the increased purity of the target component will ensure more stable results in downstream applications, significantly enhancing the product's market competitiveness and expected to generate significant commercial returns.

[0032] Currently, chromatographic separation technologies that combine intelligent automatic control with micro-nanofillers have not been widely adopted internationally. Existing chromatographic fillers have large particle sizes, low separation efficiency, and a low degree of automation, relying on manual adjustment of process parameters. This invention, by introducing AI reinforcement learning and intelligent control technology, achieves efficient separation and purification of blood products, filling a technological gap in this field and providing a new technical solution for the blood products industry both domestically and internationally.

[0033] Existing HPLC chromatography processes are susceptible to problems such as packing clogging, pressure fluctuations, and unstable operation, resulting in unstable purity or loss of activity of the target component. This invention fundamentally addresses the core issues of traditional separation processes by precisely controlling packing particle size, optimizing chromatography conditions, and introducing an intelligent control module, thereby improving production efficiency and product quality.

[0034] The technical solution of this invention not only improves the production efficiency and quality of a single product, but also promotes the development of the entire blood products industry towards intelligent and automated processes. The system's strong standardization and repeatability can be extended to different types of blood product separations, providing a model for technological upgrades in the industry.

[0035] Because blood products require extremely high purity and stability in clinical applications, the high-purity, high-recovery blood products provided by this invention offer a competitive advantage in the market. The intelligent production process ensures stable product quality, increasing the company's recognition in the high-end pharmaceutical market and laying the technical foundation for entry into the international market.

[0036] In addition to the separation and purification of blood products, the present invention's micro-nanoscale filler chromatography technology, pulsed electric field-assisted technology, and intelligent control module can also be applied to the purification process of antibody drugs, recombinant proteins, and other high-value-added biological products, further expanding the scope of technology application and promoting the development of the biopharmaceutical industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a module diagram of a high-efficiency chromatography system for separating blood products provided by an embodiment of the present invention;

[0038] Figure 2 This is a flow chart of a high-efficiency chromatography method for separating blood products provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0040] like Figure 1 As shown, an embodiment of the present invention provides a high-efficiency chromatography system for separating blood products, the method specifically comprising:

[0041] Intelligent chromatography column module, the chromatography column is filled with highly stable nano-porous filler, adopts a special column head structure, and is equipped with a pressure sensor to monitor and automatically adjust the mobile phase pressure in real time to ensure stable flow rate and separation effect;

[0042] Automatic injection and precise flow rate control module, which uses a fully automatic injection system to accurately control the injection volume of blood samples and achieves precise flow rate control through an intelligent peristaltic pump;

[0043] The chromatography packing and column design module develops new ultrafine particle stationary phase packings with a particle size of 1 to 3 μm. This innovative micro-nano porous structure increases the separation surface area and adsorption sites, significantly improving separation purity and efficiency while reducing clogging risks and pressure fluctuations.

[0044] The real-time detection and data analysis module uses ultraviolet (UV) spectroscopy, fluorescence detectors, and highly sensitive conductivity detectors to monitor the absorption spectrum and concentration changes of each component during the chromatography process in real time. It uses a built-in AI analysis algorithm to dynamically analyze detection data and provide feedback to adjust separation parameters to ensure stable and efficient separation results.

[0045] The intelligent automatic control and management module, based on a deep reinforcement learning algorithm, analyzes feedback data in real time, autonomously adjusts injection volume, mobile phase flow rate, pressure, and column temperature to maintain optimal chromatographic conditions, and automatically optimizes the separation process without frequent manual intervention.

[0046] The intelligent chromatography column module is filled with nano-scale porous fillers with a particle size of 1-3 μm.

[0047] The automatic injection and precise flow rate control module can achieve an injection volume accuracy of ±0.1μL for blood samples and a flow rate control accuracy of ±0.01mL / min, ensuring the consistency and stability of high-efficiency chromatographic separation effects.

[0048] The intelligent automatic control and management module receives signal data collected by various sensors in the system in real time, including mobile phase pressure, flow rate, column temperature, sample concentration and elution time. The data is processed by the analog-to-digital (A / D) conversion module and transmitted to the central controller. The central controller has a built-in deep reinforcement learning model, which combines historical chromatography data, real-time feedback data and preset targets for analysis and calculation, and determines the current optimal operating parameters such as injection volume (102mL / min) and pressure (1000-3000psi) through the optimization algorithm. The optimized control signal is fed back to the pressure valve, temperature control unit and flow pump through the digital-to-analog (D / A) module to automatically adjust the chromatography conditions to ensure that the separation results achieve the technical goals of high purity (>95%) and high activity (activity loss <5%).

[0049] The intelligent automatic control and management module in the embodiment of the present invention monitors the key operating parameters of the chromatography process in real time through a variety of sensing devices such as high-precision pressure sensors, flow meters, temperature sensors, spectral detection modules (UV / fluorescence), conductivity detectors, etc. The analog signals collected by each sensor (such as mobile phase pressure, flow rate, column temperature, sample concentration, elution time) are quantized and processed by the analog-to-digital (A / D) conversion module and converted into high-precision digital signals. The A / D conversion adopts a Δ-Σ type ADC to ensure the high resolution (≥24bit) and low noise characteristics of signal sampling, thereby improving the accuracy and stability of the signal. At the same time, in order to avoid the error accumulation of high-speed sampling signals, the system uses digital filtering algorithms (such as Kalman filtering and low-pass filtering) to perform real-time noise reduction and outlier removal on the original signal to ensure data quality.

[0050] The digital signals after A / D conversion are transmitted to the central controller (embedded processing unit or FPGA+DSP architecture), which has built-in time series data cache and efficient data analysis modules to ensure that the sampling data of different sensors can be processed synchronously. Ultraviolet spectrum (UV) and fluorescence signals are extracted using Fourier transform (FFT) and wavelet transform to identify concentration changes of target proteins and impurity components; the mobile phase pressure signal is analyzed based on short-time Fourier transform (STFT) and time series regression model to analyze pressure change trends and predict possible blockage or packing compaction problems; flow rate and temperature data are predicted using sliding mean filtering and autoregressive integrated moving average (ARIMA) model for trend prediction to ensure stable control of flow rate and temperature.

[0051] The central controller has a built-in deep reinforcement learning (DRL) model, which combines historical chromatography data, real-time sensor feedback and target separation conditions, and autonomously adjusts chromatography parameters through policy gradient optimization (Policy Gradient) and adaptive dynamic programming (ADP) methods. The model input variables include the current injection volume, flow rate, pressure, column temperature, elution time, etc., and the current optimal chromatography conditions are calculated through iterative optimization of the value function. The reinforcement learning network uses convolutional neural network (CNN) + long short-term memory network (LSTM) to perform time series modeling on multidimensional data to achieve optimal control decisions. The optimized parameters, such as the optimal injection flow rate (102mL / min) and pressure (1000-3000psi), are output to the flow pump, pressure valve and temperature control system via control instructions to achieve fully automatic adaptive adjustment of the chromatography process.

[0052] After the chromatography control parameters are optimized by deep reinforcement learning model calculation, the system converts the control signal into an analog signal to control the precise operation of the actuator. The D / A conversion module uses a high-precision DAC (16-32bit) to convert the digital signal into an analog voltage / current signal to drive the flow pump, pressure regulating valve and temperature control unit. The driving signal of the flow pump adopts a PWM (pulse width modulation) control strategy to achieve a flow rate regulation accuracy of ±0.01mL / min; the adjustment signal of the pressure valve adopts a PID (proportional-integral-differential) closed-loop control algorithm to keep the pressure stable within the set range; the temperature control unit is based on fuzzy adaptive control (Fuzzy Adaptive Control) to adjust the column temperature in real time to reduce the impact of temperature fluctuations on the separation effect. The entire system forms a closed-loop feedback control, and through periodic data sampling, signal processing, optimization calculation and parameter adjustment, it ensures that the chromatography process is carried out in the best operating state.

[0053] like Figure 2 As shown, an embodiment of the present invention provides a high-efficiency chromatography method for separating blood products, which specifically includes:

[0054] S1: Sample pretreatment: The blood product to be separated is centrifuged to initially separate and remove solid particles, and then accurately injected into the chromatography system through the automatic sampling system and enters the chromatography column;

[0055] S2: Optimize chromatographic separation. Through the intelligent automatic control module, the mobile phase flow rate, column pressure and column temperature are precisely adjusted to maintain the stable and efficient operation of the chromatography column. Micro-nano porous fillers are used for efficient adsorption and desorption to quickly and efficiently separate target proteins or other target components in blood products.

[0056] S3: Real-time detection and analysis. When the separated sample flows out of the chromatography column, the real-time detection module immediately performs ultraviolet spectrum scanning or conductivity detection on the chromatography effluent, monitors the elution curve of the target component in real time, and feeds back to the control system, automatically adjusting the separation parameters based on the feedback data.

[0057] S4: Automatic collection and storage of target components. Intelligently control the automatic collection system based on real-time detection data, accurately collect different components in segments, obtain high-purity target blood products, and automatically store them in dedicated containers. The separation process data of each batch is recorded and saved to achieve full traceability.

[0058] S5: System adaptive optimization. After each run, the system automatically performs in-depth analysis and training on the separation data. The optimization algorithm automatically updates various separation parameters to the optimal level to ensure higher stability and separation efficiency in the next run.

[0059] The S1 accurately injects the sample into the chromatography column through a high-precision injection valve according to the injection volume set by the system (range is 10-500 μL, control accuracy is ±0.1 μL), avoiding the influence of human error and volume fluctuation on the separation effect.

[0060] In S2, after the sample enters the intelligent chromatography column, a highly stable nanoporous filler (particle size 1-3 μm) is used to ensure stable sample distribution and efficient separation within the column. A real-time pressure sensor monitors the pressure within the column, and an intelligent automatic control module precisely adjusts the mobile phase flow rate (0.2-2 mL / min, accuracy ±0.01 mL / min), column pressure (1000-3000 psi), and column temperature (4-25°C).

[0061] The S3, real-time detection module continuously monitors the components of the chromatography fluid through ultraviolet spectroscopy (UV, detection wavelength 220-280nm), fluorescence detector (excitation wavelength 280nm, emission wavelength 350nm) and high-sensitive conductivity detector. The data acquired by the sensor is transmitted to the central controller in real time after analog-to-digital conversion, providing real-time feedback information of the separation process. The central controller has a built-in deep reinforcement learning algorithm model, which automatically predicts the elution behavior and trend of each component based on the real-time detection data and historical separation database, and analyzes and evaluates the current separation conditions. It calculates the optimal control strategy according to the target setting (such as purity > 95%, activity loss < 5%), and continuously optimizes parameters such as flow rate, column temperature, pressure and injection volume.

[0062] In step S4, the central controller converts the optimized control strategy calculated into a digital signal, which is then output in real time to the pressure valve, peristaltic pump, and column temperature control unit via a digital-to-analog conversion module. Based on the optimized signal, the system automatically adjusts the mobile phase flow rate, system pressure, and column temperature (within a control range of 25-35°C, with an error of ±0.5°C), achieving automatic closed-loop feedback control.

[0063] In S5, the results of the automated chromatographic separation process are compared in real time with target values to verify whether purity and activity indicators meet predetermined standards. When the targets are achieved, the system records the optimal process parameters into a historical database, providing data support for subsequent separations. If the indicators do not reach the preset targets, the system automatically initiates an iterative optimization process to continue optimizing the parameters until the target values are reached, achieving an efficient, stable, and intelligent blood product separation process.

[0064] At the moment the separated sample flows out of the chromatography column, the real-time detection module performs online continuous spectral detection and conductivity measurement on the effluent, obtaining real-time information on the concentration changes of the target components. Ultraviolet spectral scanning uses a dual-wavelength UV detector (such as 280nm and 260nm) to calculate the light absorption ratio to identify the presence of blood proteins, nucleic acids, or other impurities. Conductivity detection uses a highly sensitive conductivity electrode (such as the four-electrode method) to monitor the changes in ion concentration of different elution buffers, thereby inferring the elution status of proteins or other solutes.

[0065] All test signals are quantified using a high-speed A / D converter (24-bit delta-sigma ADC) and processed by a digital signal processing (DSP) module for noise filtering, baseline correction, and background subtraction, ensuring data stability and high resolution. The processed data is cached in a time series data storage module for subsequent analysis.

[0066] The detected UV absorption and conductivity curves are modeled in real time using data fitting algorithms (e.g., multivariate regression and principal component analysis (PCA)) to construct the target component's elution kinetics. The central control system accurately determines the start and end elution times of the target component based on baseline drift compensation models and peak identification algorithms (e.g., second-order derivative method and Savitzky-Golay smoothing). It also dynamically calculates key parameters such as peak area, peak symmetry, and tailing factor to assess the stability of the separation process.

[0067] At the same time, the detection data is analyzed in real time through an adaptive control algorithm (Model Predictive Control, MPC), and combined with a deep reinforcement learning model (Deep Reinforcement Learning, DRL), the flow rate, gradient elution program, pressure regulation and eluent concentration of the chromatography column are automatically adjusted to optimize the separation effect and ensure that the recovery rate and purity of the target component meet the set standards.

[0068] Once the real-time detection system identifies the optimal elution time window for the target component, the automated collection system receives instructions from the central control system and performs segmented collection based on multi-dimensional parameters such as elution peak position, integrated absorbance value, and conductivity threshold. The sample outflow channel is connected to different collection units via a multi-port valve, and precise flow distribution is achieved by an automated separation and distribution system driven by a high-precision stepper motor.

[0069] The collection system uses a dynamic fraction collection algorithm (DFCA) to adjust the collection mode based on real-time concentration changes, including time-slice mode, peak-tracking mode, and hybrid adaptive mode to maximize the recovery rate of target blood products and reduce cross-contamination. After collection, samples are automatically transferred to a dedicated low-temperature storage module (4°C or -20°C) and sealed for storage.

[0070] Throughout the chromatographic separation process, all key parameters (such as flow rate, pressure, elution time, target component concentration, conductivity curve, and collection segment information) are recorded in real time and stored in a central database, creating a traceable batch production record. The data management system utilizes blockchain data logging technology to achieve tamper-proof, full-process traceability.

[0071] Data is stored in standardized time-series formats (such as HDF5 or Parquet), and historical data analysis is performed through machine learning modeling to optimize chromatographic separation parameters for future batches. Furthermore, the system integrates a remote monitoring and data visualization platform, allowing operators to view the separation process in real time via a SCADA (Supervisory Control and Data Acquisition) interface or cloud server, and export detailed experimental reports to ensure traceability and reproducibility of quality control.

[0072] Compared to traditional technologies, this invention offers significant advantages in terms of component purity, product quality stability, and activity retention in blood products. In particular, in applications involving the separation of key proteins such as immunoglobulins and coagulation factor VIII, this system improves product purity and bioactivity retention by over 20% and 30%, respectively. This significantly improves the safety and efficacy of blood products, significantly reduces production costs and operating cycles, and promotes technological advancement and industrial expansion in the blood products industry, with significant social and economic benefits.

[0073] 1. Specific application fields and related products of the present invention

[0074] This invention is primarily used for the separation and purification of blood products, particularly for the fine separation of key plasma proteins such as coagulation factor VIII, immunoglobulins, and albumin. This technology can be used to improve the purity and activity of these blood products, enhancing their safety and effectiveness in clinical treatment.

[0075] Furthermore, the high-efficiency micro- and nano-scale filler chromatography system of this invention can also be applied to the purification of high-value-added biological products such as antibody drugs, recombinant proteins, and vaccines. In particular, in the purification of monoclonal antibodies and recombinant protein drugs, intelligent automated control technology can ensure process stability, improve product consistency, and meet the strict quality standards of the pharmaceutical industry.

[0076] At the same time, this technology is also suitable for process development, laboratory research and large-scale production in the biopharmaceutical industry, which will help to improve the overall level of bioseparation technology and provide efficient technical support for future precision medicine, cell therapy and protein drug research and development.

[0077] II. Relevant evidence of the technical effects obtained by the embodiments of the present invention

[0078] Experimental data from this invention show that compared with traditional chromatography separation technology, this system has significantly improved target protein purity, recovery rate, separation efficiency, and operational stability. The following are the main experimental results and related technical effects:

[0079] 1. Improve the purity of target components

[0080] The technology of the present invention is used to separate plasma proteins, and the purity of target components (such as coagulation factor VIII or immunoglobulins) is increased to more than 98%. Compared with the traditional filler chromatography process (about 90%-92%), it effectively reduces impurity protein contamination and improves product quality.

[0081] 2. Increase recovery rate

[0082] Experimental results show that the target protein recovery rate of the present invention reaches 85%-90%, which is significantly better than the 70%-80% of traditional technology. This improvement greatly reduces the loss of active ingredients and improves production efficiency and economic benefits.

[0083] 3. Shorten separation time and improve production efficiency

[0084] By optimizing parameters such as injection volume, flow rate, and temperature through AI reinforcement learning, the system of the present invention can shorten a single separation cycle to less than 1.5 hours. Compared with the traditional method (3 hours), the separation efficiency is more than doubled.

[0085] 4. Improve system stability and reduce operating costs

[0086] In long-term experiments, the system's column pressure stability improved by over 50%, significantly reducing the risk of downtime due to blockage and pressure fluctuations. Furthermore, intelligent automated control reduced manual intervention by 80%, significantly reducing manual operation costs and operational errors.

[0087] Table: Comparative experimental data of the present invention and traditional technology

[0088]

[0089] The experimental data of the present invention fully demonstrates its technical advantages in improving the separation purity of blood products, increasing the recovery rate, optimizing production efficiency and stability, etc., and has significant industrial application value. The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited to this. Any modifications, equivalent substitutions and improvements made by any person skilled in the art within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered by the scope of protection of the present invention.

Claims

1. A high-efficiency chromatography system for separation of blood products, characterized in that: The method specifically includes: Intelligent chromatography column module, the chromatography column is filled with highly stable nano-porous filler, adopts a special column head structure, and is equipped with a pressure sensor to monitor and automatically adjust the mobile phase pressure in real time; Automatic injection and precise flow rate control module, which uses a fully automatic injection system to accurately control the injection volume of blood samples and an intelligent peristaltic pump to achieve precise flow rate control; The chromatography packing and column design module develops new ultrafine particle stationary phase packings with a particle size of 1 to 3 μm, using innovative micro-nano porous structures to increase separation surface area and adsorption sites; The real-time detection and data analysis module uses ultraviolet spectrometry, fluorescence detectors, and highly sensitive conductivity detectors to monitor the absorption spectra and concentration changes of each component during the chromatography process in real time. It uses a built-in AI analysis algorithm to dynamically analyze the detection data and provide feedback to adjust the separation parameters. The intelligent automatic control and management module, based on a deep reinforcement learning algorithm, analyzes feedback data in real time and autonomously adjusts injection volume, mobile phase flow rate, pressure, and column temperature.

2. The high performance chromatography system for separation of blood products according to claim 1, characterized in that: The intelligent chromatography column module is filled with nano-scale porous fillers with a particle size of 1-3 μm.

3. The high performance chromatography system for separation of blood products according to claim 1, characterized in that: The automatic injection and precise flow rate control module can achieve an injection volume accuracy of blood samples of ±0.1 μL and a flow rate control accuracy of ±0.01 mL / min.

4. A high-performance chromatography method for separating blood products, characterized in that: The method specifically includes: S1: Sample pretreatment: The blood product to be separated is centrifuged to initially separate and remove solid particles, and then accurately injected into the chromatography system through the automatic sampling system and enters the chromatography column; S2: Optimize chromatographic separation. Through the intelligent automatic control module, the mobile phase flow rate, column pressure and column temperature are precisely adjusted to maintain the stable and efficient operation of the chromatography column. Micro-nano porous fillers are used for efficient adsorption and desorption to quickly and efficiently separate target proteins or other target components in blood products. S3: Real-time detection and analysis. When the separated sample flows out of the chromatography column, the real-time detection module immediately performs ultraviolet spectrum scanning or conductivity detection on the chromatography effluent, monitors the elution curve of the target component in real time, and feeds back to the control system, automatically adjusting the separation parameters based on the feedback data. S4: Automatic collection and storage of target components. The automatic collection system is intelligently controlled based on real-time detection data to accurately collect different components in sections to obtain high-purity target blood products. These components are automatically stored in dedicated containers, and the separation process data for each batch is recorded and stored to achieve full traceability. S5: System adaptive optimization. After each run, the system automatically performs in-depth analysis and training on the separation data, and the optimization algorithm automatically updates the various separation parameters to the optimal level.

5. The high performance chromatography method for separation of blood products according to claim 4, characterized in that: For S1, the injection volume range set by the system is 10-500 μL, and the control accuracy is ±0.1 μL.

6. The high performance chromatography method for separation of blood products according to claim 4, characterized in that: The S2 has a mobile phase flow rate range of 0.2 to 2 mL / min, with an accuracy of ±0.01 mL / min; a column pressure range of 1000-3000 psi; and a column temperature range of 4-25°C.

7. The high performance chromatography method for separating blood products according to claim 4, wherein: The S3 real-time detection module continuously monitors the components of the chromatography fluid through ultraviolet spectroscopy, fluorescence detectors and high-sensitivity conductivity detectors; the data obtained by the sensors are transmitted to the central controller in real time after analog-to-digital conversion, providing real-time feedback information on the separation process; the central controller has a built-in deep reinforcement learning algorithm model, which automatically predicts the elution behavior and trend of each component based on the real-time detection data and historical separation database, analyzes and evaluates the current separation conditions, calculates the optimal control strategy according to the target setting, and continuously optimizes parameters such as flow rate, column temperature, pressure and injection volume.

8. The high performance chromatography method for separating blood products according to claim 4, wherein: In S4, the optimization control strategy calculated by the central controller is converted into a digital signal, which is output to the pressure valve, peristaltic pump, and column temperature control unit in real time through the digital-to-analog conversion module; the system automatically adjusts the mobile phase flow rate, system pressure, and column temperature according to the optimization instructions to achieve automatic closed-loop feedback control.

9. The high performance chromatography method for separating blood products according to claim 4, wherein: S5, the chromatographic separation process completed by automatic control, its results are compared with the target values in real time to verify whether the purity and activity indicators meet the predetermined standards; when the target is achieved, the system records the optimal process parameters into the historical database to provide data support for subsequent separation; If the indicator does not reach the preset target, the system automatically starts the iterative optimization program and continues to optimize the parameters until the target value is reached, realizing an efficient, stable and intelligent blood product separation process.

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