CN111135883A - Ultrahigh-flux platform for screening crystal generation conditions and screening method - Google Patents
Ultrahigh-flux platform for screening crystal generation conditions and screening method Download PDFInfo
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- B01L3/50—Containers for the purpose of retaining a material to be analysed, e.g. test tubes
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- B01L3/5027—Containers for the purpose of retaining a material to be analysed, e.g. test tubes with fluid transport, e.g. in multi-compartment structures by integrated microfluidic structures, i.e. dimensions of channels and chambers are such that surface tension forces are important, e.g. lab-on-a-chip
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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Abstract
The invention discloses an ultrahigh-flux platform for screening crystal generation conditions and a screening method. The platform comprises a microfluidic droplet chip, a microfluidic droplet collection chip and a characterization-analysis system; the microfluidic droplet chip is used for generating a crystallization droplet with ultrahigh flux; the micro-droplet collection chip is used for collecting the crystallization droplets generated by the micro-fluidic droplet chip; and after the micro-droplet collection chip collects the crystallization droplets, the characterization-analysis system characterizes and identifies the morphology of crystals in the crystallization droplets, and analyzes the characterized and identified morphology of the crystals to screen out crystallization conditions corresponding to the optimal crystallization morphology. The ultra-high flux platform provides a good solution for the rapid screening of crystal generation conditions. The screening method for screening the crystal generation conditions is based on the ultrahigh-flux platform, and the screening method can quickly screen excellent and stable crystallization conditions, and is convenient, fast and accurate.
Description
Technical Field
The invention relates to the technical field of microfluidic screening, in particular to an ultrahigh-flux platform for screening crystal generation conditions and a screening method.
Background
Crystals are the subject of intensive research in many fields, such as drug crystals, inorganic crystals, organometallic framework material crystals, organic crystals, etc., and the physical and chemical properties of crystals of different crystal forms are greatly different. However, the crystallization of crystals is often influenced by many parallel combination conditions, such as different ratios of multiple combination solvents (classical single crystal culture solvent combination: dichloromethane/toluene/n-hexane), in addition to temperature, pH, inducing agents, etc.
According to the mathematical permutation and combination method, the number of experiments required for screening the crystal generating conditions may reach ten thousand, even ten thousand or more, which undoubtedly brings great difficulty to the screening of the crystal generating conditions. The conventional screening method has the defects of low flux, high cost, time consumption and the like, and the flux of the conventional screening method cannot meet the screening requirement when the screening component ratio is more (three components or more); moreover, as people have higher and higher requirements on the properties of crystals in different fields (such as medicines, non-organic substances and the like), and the crystal generation conditions are more and more complex, the screening method with high cost, low efficiency and low flux is more difficult to meet the requirements.
Disclosure of Invention
The invention aims to provide an ultrahigh flux platform for screening crystal generation conditions aiming at the defects or shortcomings in the prior art. The ultrahigh-flux platform fully utilizes the advantages of low reagent consumption, high experiment speed, no cross contamination among liquid drops and the like of the micro-device ultrahigh-flux liquid drop generation technology, has a powerful automatic analysis function with the image recognition-artificial intelligence processing technology, and provides a good solution for the rapid screening of crystal generation conditions.
The invention also aims to provide a screening method for screening crystal generation conditions based on the platform. The screening method can quickly screen out excellent and stable crystallization conditions, and is convenient and accurate.
The purpose of the invention is realized by the following technical scheme.
An ultra-high flux platform for screening crystal growth conditions comprises a microfluidic droplet chip, a microfluidic droplet collection chip and a characterization-analysis system;
the microfluidic droplet chip is used for generating a crystallization droplet with ultrahigh flux; the micro-droplet collection chip is used for collecting the crystallization droplets generated by the micro-fluidic droplet chip; and after the micro-droplet collection chip collects the crystallization droplets, the characterization-analysis system characterizes and identifies the morphology of crystals in the crystallization droplets, and analyzes the characterized and identified morphology of the crystals to screen out crystallization conditions corresponding to the optimal crystallization morphology.
Preferably, the micro-droplet collecting chip is a micro-fluidic chip with a groove array; the micro-droplet collecting chip can automatically collect the crystal droplets generated by the micro-fluidic droplet chip and arrange the crystal droplets into a droplet array according to the groove array.
More preferably, the micro-droplet collecting chip is freely movable in a horizontal plane by a movable stage and is arranged at the outlet end of the micro-fluidic droplet chip.
Preferably, the characterization-analysis system comprises a characterization recognition device and an analysis processing terminal; the characterization identification device is connected with the analysis processing terminal; the characterization recognition device is used for characterizing and recognizing the appearance of crystals in the crystal droplets collected by the micro-droplet collection chip, and the analysis processing terminal analyzes and processes the appearance information recognized by the characterization recognition device.
The microfluidic technology has the advantages of small reagent and sample consumption, simple operation, short time consumption, controllable reaction conditions, capability of providing large-scale ultrahigh flux, independent liquid drop reaction unit and the like, and is widely concerned; the characterization recognition device has an image recognition function, the analysis processing terminal is artificial intelligence, the image recognition and the artificial intelligence have strong data rapid processing capacity, automatic analysis experiment results can be achieved in a short time, and the characterization recognition device and the artificial intelligence can be combined to facilitate the establishment of an ultrahigh-flux screening platform.
More preferably, the characterization and identification device comprises one or more of an optical microscope, a Differential Scanning Calorimeter (DSC), an X-Ray diffractometer (XRD), and a thermogravimetric Analyzer (TGA).
More preferably, the analysis processing terminal comprises a central processing unit or a computer; and the analysis processing terminal has python Language processing, SQL Language processing, machine learning and natural Language processing functions.
An ultra-high flux screening method for screening crystal production conditions, which adopts the ultra-high flux platform of any one of the above items to screen, comprises the following steps:
s1, pouring into the microfluidic droplet chip to form a droplet containing a crystallization content, and crystallizing the crystallization content in the microfluidic droplet chip under different crystallization conditions to generate a crystallization droplet;
s2, collecting the crystallization liquid drop by the micro liquid drop collecting chip;
s3, the characterization-analysis system characterizes and analyzes crystals in the crystal droplets collected by the micro-droplet collection chip;
s4, screening out crystallization conditions corresponding to the optimal crystallization form;
s5, repeating S1-S3 under the crystallization condition selected in S4, and carrying out crystal growth kinetic verification.
Preferably, the crystallization conditions include one or more of solvent type, solvent amount, solvent concentration ratio, impurity type, impurity amount, mixing speed, crystallization temperature, crystallization pH, and crystallization time.
Preferably, the micro-fluidic droplet chip generates at least 69 crystallization droplets within 1 min.
Preferably, the crystallization droplets are microdroplets containing crystals, including droplets of physical crystallization or droplets of chemical reaction crystallization.
More preferably, the physically crystallized droplets comprise droplets containing a crystallized drug.
More preferably, the droplets of chemical reaction crystallization comprise droplets containing inorganic chemical reactants.
Still further preferably, the continuous phase of the droplets of physical crystallization and the droplets of chemical reaction crystallization is: liquid droplet paraffin mixed with 2vol% Span80, or dimethicone mixed with 2vol% Span 80.
Because the crystals with different morphologies can influence the physicochemical properties of the crystals in the fields of medicines and inorganic substances, further influence the clinical curative effect of medicines and the density, the dispersibility and the like of the inorganic substances, and simultaneously, the generation conditions of the crystals are complex and various, proper medicine crystals and inorganic substance crystals need to be screened out. Therefore, the ultrahigh-flux screening platform is applied to screening of the generation conditions of the drug crystals and the inorganic crystals, and has important significance for the application of the drug crystals and the inorganic crystals.
The screening method of the invention is not only suitable for screening the drug crystal generating condition and the inorganic chemical reaction crystallization condition, but also suitable for screening other crystal crystallization conditions, and is used for discussing the crystal growth dynamics of other crystals under different crystallization conditions, including inorganic crystals, protein crystals or metal organic framework material crystals.
Compared with the prior art, the invention has the following advantages and beneficial effects:
(1) the ultra-high flux platform fully utilizes the advantages of low reagent consumption, high experiment speed, no cross contamination among liquid drops and the like of the micro-device ultra-high flux liquid drop generation technology, has a powerful function of automatic analysis by the image recognition-artificial intelligence processing technology, provides a good solution for the rapid screening of crystal generation conditions, and can realize the ultra-high flux screening of the crystal generation conditions (more than 10 ten thousand times per day) so as to screen the optimal conditions of crystal generation.
(2) The screening method is based on the ultrahigh-flux platform to screen crystallization conditions, has the advantages of low reagent and sample consumption, low cost, large screening range of crystal generation conditions, capability of providing ultrahigh-flux screening, capability of processing a large number of results in a short time by combining an image recognition-artificial intelligence processing technology, rapider screening, and capability of screening the screened results as verified stable results; moreover, the screening method can be popularized to more different substances capable of generating crystals, and crystal forms meeting requirements can be screened out.
Drawings
FIG. 1 is a general schematic diagram of an ultra-high throughput platform for screening crystal production conditions of the present invention in an exemplary embodiment;
FIG. 2 is a view of a micro droplet collecting chip collecting a crystallization droplet in an embodiment;
FIG. 3 is a schematic diagram of the microfluidic droplet chip of example 1 for generating crystallized droplets;
FIGS. 4a and 4b are views of indomethacin drug crystals of different morphologies produced under different crystal production conditions screened in example 1;
FIG. 5 is an XRD spectrum of the linear crystals of the indomethacin drug screened in example 1;
FIG. 6 is a schematic diagram of a microfluidic droplet chip for generating crystallized droplets in example 2;
FIGS. 7a and 7b are views of inorganic calcium carbonate crystals of different morphologies produced under different crystal-producing conditions screened in example 2.
Detailed Description
The technical solution of the present invention is further described in detail with reference to the following specific examples, but the scope and implementation of the present invention are not limited thereto. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In the specific examples, unless otherwise specified, the technical means used are in accordance with the conventional means employed by those skilled in the art of the present invention.
Referring to fig. 1, the ultra-high throughput platform for screening crystal growth conditions of the present invention comprises a microfluidic droplet chip 1, a microfluidic droplet collection chip 2, and a characterization-analysis system, wherein the characterization-analysis system comprises a characterization recognition device 3 and an analysis processing terminal 4; the characterization recognition device 3 is connected with the analysis processing terminal 4.
When the micro-fluidic droplet chip 1 works, the micro-fluidic droplet chip is used for generating crystallization droplets at ultrahigh flux; the micro-droplet collecting chip 2 is used for collecting the crystal droplets generated by the micro-fluidic droplet chip 1; after the micro-droplet collection chip 2 collects the crystallization droplets, the characterization recognition device 3 in the characterization-analysis system characterizes and recognizes the morphology of the crystals in the crystallization droplets, and the analysis processing terminal 4 therein analyzes the morphology of the characterized and recognized crystals to screen out the crystallization conditions corresponding to the optimal crystallization morphology.
Specifically, the characterization and identification device 3 includes one or more of an optical microscope, a differential scanning calorimeter, an X-ray diffractometer and a thermogravimetric analyzer. The analysis processing terminal comprises a central processing unit or a computer; and the analysis processing terminal 4 has python language processing, SQL language processing, machine learning, and natural language processing functions.
Referring to fig. 2, in the present invention, the micro droplet collecting chip 2 is a micro fluidic chip having a groove array. And the micro-droplet collecting chip 2 is arranged on a movable objective table, the movable objective table can move along XY directions in a horizontal plane under the control of online software, and the micro-droplet collecting chip can be freely moved in the horizontal plane through the movable objective table and is arranged at the outlet end of the micro-droplet chip 1, so that the micro-droplet collecting chip 2 can automatically collect the crystal droplets generated by the micro-droplet chip 1 and is arranged into a droplet array according to the groove array.
The invention relates to an ultrahigh flux screening method for screening crystal generation conditions, which particularly adopts the ultrahigh flux platform for screening and comprises the following steps:
s1, pouring into the microfluidic droplet chip to form a droplet containing a crystallization content, and crystallizing the crystallization content in the microfluidic droplet chip under different crystallization conditions to generate a crystallization droplet; the flux for generating the crystallization liquid drops is at least 69 in 1min, so that ultrahigh flux is realized;
s2, collecting the crystallization liquid drop by the micro liquid drop collecting chip;
s3, the characterization-analysis system characterizes and analyzes crystals in the crystal droplets collected by the micro-droplet collection chip;
s4, screening out crystallization conditions corresponding to the optimal crystallization form;
s5, repeating S1-S3 under the crystallization condition selected in S4, and carrying out crystal growth kinetic verification.
The crystallization conditions comprise more than one of solvent type, solvent quantity, solvent concentration ratio, impurity type, impurity quantity, mixing speed, crystallization temperature, crystallization pH value and crystallization time, and the crystallization conditions for generating crystals with specific shapes are screened by utilizing an ultrahigh-flux screening platform.
Moreover, the crystallization liquid drop is a micro-liquid drop containing crystals, and comprises a physical crystallization liquid drop or a chemical reaction crystallization liquid drop; the physically crystallized droplets comprise droplets containing a crystallized drug; the droplets of chemical reaction crystallization include droplets containing inorganic chemical reactants.
The screening method and the ultra-high throughput screening platform of the present invention are described in detail below with reference to specific examples of screening conditions for crystallization of drug crystals (indomethacin drugs) and screening conditions for crystallization of chemically reacted crystalline crystals (calcium carbonate).
Example 1
The method for screening the crystallization conditions of the drug crystal-indometacin drug crystal comprises the following specific steps:
s1 experiment for generating ultra-high flux liquid drop of micro-fluidic liquid drop
S11, manufacturing a microfluidic droplet generation chip: manufacturing a microfluidic droplet chip according to a co-flow focusing micro-channel structure of the microfluidic droplet chip, wherein a molding method is selected as a manufacturing method of the chip;
preparing a micro-fluidic droplet chip by taking PDMS (polydimethylsiloxane) and an aluminum sheet as materials;
(1) designing a co-flow focusing micro-channel structure generated by liquid drops by utilizing SolidWorks2017 software, carving the channel structure on an aluminum sheet by utilizing a high-resolution high-power laser carving machine, controlling the carving depth of a channel by grasping the carving time, and polishing after carving is finished to reduce the surface roughness of the aluminum sheet so as to obtain a bright and flat surface.
(2) Washing the aluminum sheet mold for 3 times by using washing powder, then sequentially placing the aluminum sheet mold in 200ml of acetone, 200ml of ethanol and 200ml of pure water for respectively carrying out ultrasonic treatment for 20 min to wash off dirt on the surface of the aluminum sheet mold, drying the aluminum sheet mold by using nitrogen, and further drying the aluminum sheet mold in a drying oven at 60 ℃.
(3) PDMS and a crosslinker (SYLGARDTM 184 Silicone Elastomer current Agent) were mixed at a ratio of 10: 1, pouring the mixture on a manufactured aluminum sheet die, placing the die on a vacuum drying oven at 80 ℃ for vacuumizing, and then curing.
(4) Finally, stripping the cured PDMS from the aluminum sheet mold to obtain a PDMS chip with a droplet generation channel; coating liquid PDMS on a prepared glass substrate, then uniformly coating the PDMS on the glass at the rotating speed of 800 rpm by using a spin coater, gently sticking the PDMS chip with the droplet generation channel engraved on the glass, placing the glass in an oven at 80 ℃ for 1 h, and curing to obtain the complete microfluidic droplet chip.
S12, preparation of indomethacin drug-organic solvent saturated solution: taking 6 test tubes of 2 ml, weighing 0.2 g indomethacin medicine respectively, placing the indomethacin medicine in the test tubes, adding 200 mu L ethanol, 200 mu L acetone, 200 mu L diethyl ether and 200 mu L chloroform respectively, carrying out ultrasonic oscillation for 2 min until the medicine is just dissolved until a little precipitate is left, centrifuging at 6000 rpm for 10 min, removing the precipitate, and taking the supernatant for later use.
S13, selecting a continuous phase of liquid drops, namely mixing liquid drop paraffin (purchased from Aladdin company) with volume ratios of 1vol%, 2vol%, 3 vol% and 4 vol% of Span 80; liquid paraffin droplets without surfactant (available from Aladdin).
S14, according to the scheme in fig. 3, with indomethacin drug-ethanol saturated solution as component 1, indomethacin drug-acetone saturated solution as component 2, indomethacin drug-diethyl ether saturated solution as component 3, indomethacin drug-chloroform saturated solution as component 4, pH buffer solution (phosphate buffer) as component 5, and antisolvent water as component 6.
S15, drop experiment with drug solution: the channel port of the microfluidic droplet chip is connected with a silicone tube with the inner diameter of 0.5 mm and is connected with an injection pump, the perfusion speed is adjusted, the total perfusion speed of the oil phase is 900 microliters/minute, and the total perfusion speed of the water phase is 300 microliters/minute, so that at least 69 stable droplets with uniform particle size are generated within 1 min.
By adding or modifying the dispersed phase, and changing the dispersed phase perfusion speed, different drug concentrations (0.01 mg/mL, 0.02 mg/mL, 0.03 mg/mL, 0.04 mg/mL, 0.05 mg/mL, 0.06 mg/mL), different polar solvents (ethanol, acetone, ether, and chloroform), pH buffer adjustment and thus different pH environments (pH =2, 4, 6, 7, 8, 10) were set. And then generating liquid drops corresponding to different crystallization conditions at ultrahigh flux, and collecting the liquid drops into a channel of the micro-droplet collection chip (the collection result is shown in figure 2).
S2 characterization of drug crystals within droplets
S21, optical microscope: collecting the liquid drops in a micro-liquid drop collecting chip, placing the micro-liquid drop collecting chip on an optical microscope objective table, turning on a microscope for illumination, adjusting the focal length, automatically and continuously photographing by utilizing microscope control software, and automatically collecting crystal appearance shape pictures, such as drug linear crystals and cubic crystals in the liquid drops shown in figures 4a and 4b, so as to represent the appearance shapes of the drug crystals in the liquid drops.
S22, XRD: classified as X-ray powder diffraction;
x-ray powder diffraction: and (3) taking 0.8 mg of indometacin linear crystals by using a medicine spoon, putting the indometacin linear crystals into a sample groove of a glass sample holder, lightly pressing the sample groove by using frosted glass to fill the sample groove, slightly wiping off redundant crystal powder to enable the surface of the sample and the surface of the glass holder to be in the same plane, and placing the sample groove and the glass holder in an X-ray powder diffraction test. Referring to fig. 5, the XRD pattern corresponding to the linear indomethacin crystal grown under the condition of 6:4 volume ratio of the drug saturated acetone solution to the anti-solvent has two strong characteristic peaks at positions 2 θ of 12 and 15, which can be used as the identification characteristic peaks of the linear indomethacin crystal.
S3 image recognition-big data analysis processing of drug crystal characterization result
The method comprises the steps of identifying and processing crystal forms of drug crystals by using a computer and crystal morphology pictures obtained by an optical microscope and a scanning electron microscope through python Language and mobilenetv2 network image identification technology, screening data results of experimental data obtained by characterization means such as XRD through a big data technology (Structured Query Language) and an analysis technology (machine learning), and further screening the optimal conditions of the indomethacin linear crystals.
S4 crystal growth kinetics experiment
The crystallization conditions of the linear crystals are screened out by utilizing an ultrahigh flux platform screened by crystal generation conditions and a single-factor or multi-factor control variable method to repeat the crystallization conditions of the drugs: pH =7, ratio of indomethacin acetone solution (1 mg/μ L) to antisolvent water volume 6: 4.
and carrying out crystal growth experiment under the crystallization condition, observing the generation of droplet crystals by using an optical microscope, discussing the crystal change rule in crystal dynamics, and the growth and extension of crystal nucleus to form corresponding crystal morphology, wherein the process is influenced by the precipitation rate of the drug from the solvent.
Example 2
The method comprises the following steps of screening crystallization conditions of inorganic crystal-calcium carbonate crystal:
s1 experiment for generating ultra-high flux liquid drop of micro-fluidic liquid drop
S11, manufacturing a microfluidic droplet generation chip: the production method is the same as S11 of example 1.
S12, preparation of 0.5 mol/L and 0.05mol/L calcium chloride solutions: weighing 5.55 g of calcium chloride powder, placing the calcium chloride powder in a volumetric flask with 100mL, adding water to a constant volume of 100mL, placing the volumetric flask in an ultrasonic cleaner, and performing ultrasonic treatment for 10 min to completely dissolve calcium chloride to prepare a 0.5 mol/L calcium chloride solution. Weighing 0.555 g of calcium chloride powder, placing the calcium chloride powder in a volumetric flask with 100mL, adding water to a constant volume of 100mL, placing the volumetric flask in an ultrasonic cleaner for ultrasonic treatment for 10 min to completely dissolve the calcium chloride, and preparing a calcium chloride solution with the concentration of 0.05 mol/L.
Preparation of S13, 0.5 mol/L and 0.05mol/L sodium carbonate solutions: weighing 5.3 g of calcium chloride powder, placing the calcium chloride powder in a volumetric flask with 100mL, adding water to a constant volume of 100mL, placing the volumetric flask in an ultrasonic cleaner, and performing ultrasonic treatment for 10 min to completely dissolve calcium chloride to prepare a 0.5 mol/L calcium chloride solution. Weighing 0.53 g of calcium chloride powder, placing the calcium chloride powder in a volumetric flask with 100mL, adding water to a constant volume of 100mL, placing the volumetric flask in an ultrasonic cleaner, and performing ultrasonic treatment for 10 min to completely dissolve calcium chloride to prepare a calcium chloride solution with 0.05 mol/L.
S14, selecting a continuous phase of liquid drops, namely mixing liquid drop paraffin (purchased from Aladdin company) with volume ratios of 1vol%, 2vol%, 3 vol% and 4 vol% of Span 80; liquid paraffin droplets without surfactant (available from Aladdin).
S15, according to the graph in FIG. 6, pure water is the component 1 and the concentration of the calcium chloride solution is further adjusted by changing the speed, 0.5 mol/L calcium chloride solution is the component 2, 0.05mol/L calcium chloride solution is the component 3, 0.5 mol/L sodium carbonate solution is the component 4, 0.05mol/L sodium carbonate solution is the component 5, pure water is the component 6 and the concentration of the sodium carbonate solution is further adjusted by changing the speed.
S16, droplet experiment of calcium carbonate crystal generated by chemical reaction: the channel port of the microfluidic droplet chip is connected with a silicone tube with the inner diameter of 0.5 mm and is connected with an injection pump, the perfusion speed is adjusted, the total perfusion speed of the oil phase is 900 microliters/minute, and the total perfusion speed of the water phase is 300 microliters/minute, so that continuous, stable and uniform-particle-size droplets are generated.
By adding or changing the dispersed phase and changing the perfusion speed of the dispersed phase, the conditions of different concentrations (0.5 mg/mL, 0.4 mg/mL, 0.3 mg/mL, 0.25 mg/mL, 0.1 mg/mL, 0.05 mg/mL) of calcium chloride and sodium carbonate affecting the crystallization of the inorganic calcium carbonate crystals are set, so that droplets corresponding to different crystallization conditions are generated at ultrahigh flux and are collected in the channels of the micro-droplet collection chip (the collection result is shown in figure 2).
S2 characterization of inorganic reactant crystals within the droplets
S21, optical microscope: collecting the liquid drops in a micro-drop collecting chip, placing the micro-drop collecting chip on an optical microscope objective table, turning on a microscope for illumination, adjusting the focal length, automatically and continuously photographing by using microscope control software, and automatically collecting the crystal appearance shape pictures, such as inorganic reactant bulk crystals and inorganic reactant spherical crystals in the liquid drops shown in figures 7a and 7b, so as to represent the appearance shape of the drug crystals in the liquid drops.
S22, XRD: classified as X-ray powder diffraction;
x-ray powder diffraction: 0.8 mg of inorganic reactant crystal is taken by a medicine spoon and is placed in a sample groove of a glass sample holder, then, the sample groove is lightly pressed by ground glass to be filled with the inorganic reactant crystal, and then, redundant crystal powder is lightly wiped off, so that the surface of the sample and the surface of the glass holder are in the same plane and are placed in an X-ray powder diffraction test.
S3 image recognition-big data analysis processing of inorganic reactant crystal characterization result
The method comprises the steps of identifying and processing crystal forms of drug crystals by using a computer and crystal morphology pictures obtained by an optical microscope and a scanning electron microscope through python Language and mobilenetv2 network image identification technologies, screening data results of experimental data obtained by characterization means such as XRD through a big data technology (Structured Query Language) and an analysis technology (machine learning) technology, and screening the optimal conditions of the sodium carbonate square crystal crystals.
S4 crystal growth kinetics experiment
By utilizing the ultrahigh-flux crystallization condition screening platform and a single-factor or multi-factor control variable method to repeat the crystallization conditions of the inorganic substance calcium carbonate, the crystallization conditions for screening out the cubic calcium carbonate crystals are as follows: pH =7, the ratio of the volume of 0.05mol/L sodium carbonate solution to 0.25mol/L calcium chloride solution was 5: 2.
And carrying out crystal growth experiment under the crystallization condition, continuously monitoring by using an optical microscope and X-ray powder diffraction, observing the generation of droplet crystals, discussing the change rule of diffraction spectrum in crystal dynamics, and growing and extending crystal nucleus to form corresponding crystal morphology, wherein the process is influenced by the concentration of a reactant of the drug and the chemical reaction rate.
The foregoing embodiments are merely preferred embodiments of the present invention, illustrating and describing the basic principles, principal features and advantages of the invention, but not limiting the scope and detailed description of the invention. It should be understood by those skilled in the art that the above-described embodiments are not intended to limit the present invention in any way, and all changes, modifications, substitutions, combinations, simplifications, etc., which are made by taking the same technical solutions as those of the above-described embodiments as equivalent or equivalent alterations, or which do not depart from the spirit and principle of the present invention, should be construed as equivalents and as equivalents included in the scope of the present invention.
Claims (10)
1. An ultra-high flux platform for screening crystal generation conditions, which is characterized by comprising a microfluidic droplet chip, a micro-droplet collection chip and a characterization-analysis system;
the microfluidic droplet chip is used for generating a crystallization droplet with ultrahigh flux; the micro-droplet collection chip is used for collecting the crystallization droplets generated by the micro-fluidic droplet chip; and after the micro-droplet collection chip collects the crystallization droplets, the characterization-analysis system characterizes and identifies the morphology of crystals in the crystallization droplets, and analyzes the characterized and identified morphology of the crystals to screen out crystallization conditions corresponding to the optimal crystallization morphology.
2. The ultra-high throughput platform for screening crystal growth conditions of claim 1, wherein said micro-droplet collection chip is a microfluidic chip with an array of grooves; the micro-droplet collecting chip can automatically collect the crystal droplets generated by the micro-fluidic droplet chip and arrange the crystal droplets into a droplet array according to the groove array.
3. The ultra-high throughput platform for screening crystal growth conditions of claim 2, wherein said micro-droplet collection chip is freely movable in a horizontal plane by a movable stage disposed at an exit end of said micro-fluidic droplet chip.
4. The ultra-high throughput platform for screening crystal production conditions of claim 1, wherein said characterization-analysis system comprises a characterization recognition device and an analysis processing terminal; the characterization identification device is connected with the analysis processing terminal; the characterization recognition device is used for characterizing and recognizing the appearance of crystals in the crystal droplets collected by the micro-droplet collection chip, and the analysis processing terminal analyzes and processes the appearance information recognized by the characterization recognition device.
5. The ultra-high throughput platform of claim 4, wherein the characterization and identification device comprises one or more of an optical microscope, a differential scanning calorimeter, an X-ray diffractometer, and a thermogravimetric analyzer.
6. The ultra-high throughput platform for screening crystal production conditions of claim 4, wherein said analytical processing terminal comprises a central processing unit or computer; and the analysis processing terminal has python language processing, SQL language processing, machine learning and natural language processing functions.
7. An ultra-high throughput screening method for screening crystal production conditions, wherein the ultra-high throughput platform of any one of claims 1 to 6 is used for screening, comprising the steps of:
s1, pouring into the microfluidic droplet chip to form a droplet containing a crystallization content, and crystallizing the crystallization content in the microfluidic droplet chip under different crystallization conditions to generate a crystallization droplet;
s2, collecting the crystallization liquid drop by the micro liquid drop collecting chip;
s3, the characterization-analysis system characterizes and analyzes crystals in the crystal droplets collected by the micro-droplet collection chip;
s4, screening out crystallization conditions corresponding to the optimal crystallization form;
s5, repeating S1-S3 under the crystallization condition selected in S4, and carrying out crystal growth kinetic verification.
8. The screening method according to claim 7, wherein the crystallization conditions include one or more of a solvent type, a solvent amount, a solvent concentration ratio, an impurity type, an impurity amount, a mixing speed, a crystallization temperature, a crystallization pH value, and a crystallization time.
9. The screening method of claim 7, wherein the microfluidic droplet chip generates the crystallization droplets at a flux of at least 69 within 1 min.
10. The screening method according to claim 7, wherein the crystallization droplets are microdroplets containing crystals, including droplets of physical crystallization or droplets of chemical reaction crystallization; the physically crystallized droplets comprise droplets containing a crystallized drug; the droplets of chemical reaction crystallization include droplets containing inorganic chemical reactants.
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| WO2021135090A1 (en) * | 2019-12-31 | 2021-07-08 | 中山大学 | Ultrahigh-throughput platform and ultrahigh-throughput screening method for screening crystal formation conditions |
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