Particle measurement apparatus

Abstract

To reduce detection sensitivity fluctuations caused by individual characteristics (difference between apparatuses) in a particle measurement apparatus that measures the size of particles in a liquid sample by irradiating the particles with light.SOLUTION: A particle measurement apparatus of the invention measures size of particles in a liquid sample by irradiating the particles with light, and corrects the size of the particles using a correction function that uses as an input value an irradiation position of a light spot in at least one of the X, Y and Z directions.SELECTED DRAWING: Figure 10B

Description

[Technical Field]

[0001] The present invention relates to a technique for measuring particles in a solvent using light. [Background technology]

[0002] In recent years, pharmaceutical development has been shifting from small molecule drugs to biopharmaceuticals. Because biopharmaceuticals are polymers, they are prone to aggregation, which can lead to toxicity. For example, the U.S. Food and Drug Administration and other organizations are seeking to strengthen regulations on aggregate concentration control. Therefore, there is a need for a technology that can quantitatively measure the size distribution of aggregates at a desired concentration in the submicron range of 0.1 to 1 μm. Protein aggregates float in a solvent and their position changes over time due to Brownian motion. This article describes a technology for measuring the size and concentration of protein aggregates and standard particles such as polystyrene beads. These test objects are collectively referred to as "particles."

[0003] Patent Document 1 describes a technology for detecting particles using optical measurement. The document discloses an optical measurement method for focusing light to generate a light spot and measuring a test object approximately three times the size of the light spot, the method comprising: a signal acquisition step for detecting reflected light from the test object by irradiating the test object with the light while moving at least the focal position of the light in the optical axis direction; a step for acquiring correspondence data describing the correspondence between the intensity of the reflected light and the size of the test object; and a size calculation step for obtaining the size of the test object by referencing the correspondence data using the intensity of the reflected light (claim 1). The technology described in the document achieves high-resolution measurement without preprocessing by causing the reflected light to interfere with a reference light to enhance the signal.

[0004] Patent Document 2 discloses a technology that eliminates the need for phase adjustment of a reference light by mirror scanning in time domain OCT (Optical Coherence Tomography) by physically scanning an objective lens and receiving the interference between signal light and interference light with four detectors with different phase conditions. Furthermore, based on the technology of Patent Document 1, a technology for speeding up scanning of a light spot is disclosed so as not to be affected by the movement of particles undergoing Brownian motion in a liquid.

[0005] Patent Document 3 discloses a technology for measuring biological tomographic images using a semiconductor laser as a light source, in which the coherence length is controlled within a predetermined range by superimposing a high frequency on the driving current, thereby reducing the influence of noise contained in the acquired tomographic image.

[0006] Patent Document 4 discloses a technique for correcting positional deviation of the irradiated light in accordance with the light receiving positions of a pair of photodetectors positioned at positions shifted from the optical axis of the irradiated light, in relation to an apparatus that measures the three-dimensional shape of an electronic component by irradiating the electronic component with irradiated light scanned in mutually orthogonal main and sub-scanning directions and receiving light reflected from the electronic component.

[0007] Patent Document 5 discloses a technology for non-contact measurement of the height or shape of an object by irradiating the object with laser light, focusing the light reflected from the surface of the object onto an array of position detection elements, and measuring the signal output from the position detection elements according to the position of the reflected light using the principle of triangulation.

[0008] Patent Document 6 discloses a technology relating to a detection device that includes a control unit that irradiates a target with laser light through a projection window, detects reflected light from the target, and generates measurement information, and corrects a signal value based on either the detection time or the detection intensity of the reflected light from the projection window. [Prior art documents] [Patent documents]

[0009] [Patent Document 1] Patent No. 06559555 [Patent Document 2] WO2020 / 144754 publication [Patent Document 3] Japanese Patent Application Laid-Open No. 2015-49204 [Patent Document 4] Japanese Patent Application Laid-Open No. 2008-267853 [Patent Document 5] Japanese Patent Application Laid-Open No. 2000-292127 [Patent Document 6] Japanese Patent Application Publication No. 2019-045224 Summary of the Invention [Problem to be solved by the invention]

[0010] As described above, the technologies described in Patent Documents 1 and 2 can determine particle size from the measured maximum detection signal Amax by acquiring correspondence data between particle size and the maximum detection signal obtained at the focal position in advance. Furthermore, particle concentration can be determined from the number of detected particles. However, when performance management is performed by suppressing differences between multiple devices of the same product model, variations in the energy of the light spot and the intensity of interference with the reference light occur when the light spot is scanned three-dimensionally within the measurement target, due to characteristics unique to each device, such as the emission angle and coherence length of the semiconductor laser light source, and the mounting position of the objective lens. Therefore, it is difficult to maintain a constant detection signal magnitude, i.e., to suppress variations in detection sensitivity.

[0011] Patent Documents 4 to 6 disclose a method for correcting the position of a detection signal by geometrical optics such as triangulation based on the position of reflected light, rather than the intensity of the reflected light, for a measurement target that is significantly larger than the wavelength of the light source. Therefore, it is difficult to suppress fluctuations in detection sensitivity due to wave optics responses from microparticles that are equal to or smaller than the wavelength of the light source, which is the subject of the present invention.

[0012] The present invention has been made in view of the above-mentioned problems, and aims to suppress fluctuations in detection sensitivity caused by individual characteristics (instrumental differences) of a particle measuring device that measures the size of particles in a liquid sample by irradiating the particles with light. [Means for solving the problem]

[0013] The particle measuring device according to the present invention measures the size of particles in a liquid sample by irradiating the particles with light, and corrects the size of the particles using a correction function that uses as an input value the irradiation position of the light spot in at least one of the X, Y, and Z directions. [Effects of the Invention]

[0014] According to the present invention, in a particle measuring device that measures the size of particles in a liquid sample by irradiating the particles with light, it is possible to suppress fluctuations in detection sensitivity caused by individual characteristics (instrumental differences) of the device. Problems, configurations, and effects other than those described here will become clear from the description of the following embodiments. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a schematic diagram showing the relationship between defocus and detection signals in Patent Documents 1 and 2. FIG. [Figure 2] 1 shows the results of a simulation of the present invention, showing the relationship between particle size and maximum detection signal, using the interference detection optical system described in Patent Documents 1 and 2. [Figure 3] An example of measurement data is shown below. [Figure 4A] This is an example of the experimental results quantifying the fluctuation in detection sensitivity. [Figure 4B] This is an example of the experimental results quantifying the fluctuation in detection sensitivity. [Figure 5] 2 is a schematic diagram showing the relationship between a semiconductor laser serving as a light source and the intensity distribution of emitted light. FIG. [Figure 6A] FIG. 10 is a schematic diagram showing a laser beam when a light spot is formed in the center in the X or Y direction. [Figure 6B] 10A and 10B are schematic diagrams showing laser light when a light spot is formed at an end in the X or Y direction. [Figure 7] 10A and 10B are schematic diagrams showing fluctuations in detection sensitivity that occur when a light spot is scanned in the Z direction. [Figure 8] 10 is a flowchart illustrating a procedure for calibrating individual characteristics for each device. [Figure 9] 10 is a flowchart showing an operation when the device is operated in an operational environment. [Figure 10A] This is the result of the correction model using the first-order polynomial shown in Equation 1. [Figure 10B] This is the result of the correction model using the second-order polynomial shown in Equation 2. [Figure 10C] This is the result of the correction model using the third-order polynomial shown in Equation 3. [Figure 10D] This is the result of the correction model using the fourth-order polynomial shown in Equation 4. [Figure 10E] This is the result of the correction model using the three-dimensional Gaussian distribution formula shown in Equation 5. [Figure 10F] This is the result of the correction model using the Gaussian distribution formula with three-dimensional offset shown in Equation 6. [Figure 11] 1 is a size frequency distribution of raw data before the application of the detection sensitivity correction function of the present invention. [Figure 12A] This is the result of the correction model using the first-order polynomial shown in Equation 1. [Figure 12B] This is the result of the correction model using the second-order polynomial shown in Equation 2. [Figure 12C] This is the result of the correction model using the third-order polynomial shown in Equation 3. [Figure 12D] This is the result of the correction model using the fourth-order polynomial shown in Equation 4. [Figure 12E] This is the result of the correction model using the three-dimensional Gaussian distribution formula shown in Equation 5. [Figure 12F] This is the result of the correction model using the Gaussian distribution formula with three-dimensional offset shown in Equation 6. [Figure 13]11 is a summary of the results of comparing RMS values ​​of standard particle sizes, which shows the effect of the detection sensitivity correction method of the present invention. [Figure 14A] This is the result of the correction model using the second-order polynomial shown in Equation 7. [Figure 14B] This is the result of a correction model that combines the second-order polynomial shown in Equation 8 with a Gaussian distribution. [Figure 15A] This is the result of the correction model using the second-order polynomial shown in Equation 7. [Figure 15B] This is the result of a correction model that combines the second-order polynomial shown in Equation 8 with a Gaussian distribution. [Figure 16] 11 is a summary of the results of comparing RMS values ​​of standard particle sizes, which shows the effect of the detection sensitivity correction method of the present invention. [Figure 17] 10 is a diagram illustrating an example of the configuration of a particle measuring device according to a fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0016] <Background of the invention> The measurement targets of this invention are submicron to micron-order particles that float in a solvent and undergo Brownian motion, such as protein aggregates in biopharmaceuticals. The objective here is to precisely measure the size and concentration of the target by utilizing the wave-optical response of laser light.

[0017] In the following description of the present invention, the optical axis direction is taken as the Z axis, and the X and Y axes are taken in a plane perpendicular to the Z axis, and the explanation will proceed assuming that the positions of the light spot in the X, Y, and Z axis directions are x, y, and z, respectively.

[0018] FIG. 1 is a schematic diagram showing the relationship between defocus and detection signal in Patent Documents 1 and 2. If the optical axis direction of the objective lens is z, the light spot diameter at the z position of the particle being measured is determined by the wavelength of the light source, the numerical aperture of the objective lens, and the amount of defocus. The amount of reflected light from the particle is approximated and the detection signal increases or decreases depending on the ratio of the light spot diameter to the particle's area. The left side of FIG. 1 is a schematic diagram showing a state in which the particle being measured is defocused from the focal position of the objective lens. In this case, the particle size is relatively small compared to the light spot diameter, and the amount of reflected light received through the objective lens and the detection signal converted from that reflected light into an electrical signal are relatively small. On the other hand, the right side of FIG. 1 is a schematic diagram showing a state in which the particle being measured is at the focal position of the objective lens. In this case, the particle size is maximized compared to the light spot diameter, and the amount of reflected light received through the objective lens and the detection signal are maximized. Figure 17 of Patent Document 1 discloses that when the size (diameter) of the target particle is approximately three times or less the minimum light spot diameter at the focus, the particle size and the maximum detection signal obtained at the focus position are uniquely determined, and that by acquiring this correspondence data in advance, it is possible to determine the particle size from the measured maximum detection signal.

[0019] Figure 2 shows the results of a simulation of the present invention, showing the relationship between particle size and maximum detection signal, using the interference detection optical system described in Patent Documents 1 and 2. The simulation was performed using a method combining Mie scattering and Fraunhofer diffraction. The light source wavelength was 785 nm, the objective lens numerical aperture was 0.45, the particle refractive index was 1.40 based on experimental results for protein aggregates, and the solvent refractive index was 1.333, corresponding to pure water. As shown in the figure, if the particle size is d, in the region d<0.1 μm, the maximum detection signal is proportional to the cube of d, corresponding to Rayleigh scattering, while in the region d>0.3 μm, the maximum detection signal is proportional to the first power of d, corresponding to Mie scattering. The linearity of the particle size and maximum detection signal in the region d>0.3 μm is consistent with Figure 17 of Patent Document 1.

[0020] To avoid misunderstandings about particle size dependence, we will provide a more detailed explanation. It is generally known that the energy intensity of scattered light in Rayleigh scattering is proportional to the sixth power of the particle size d. The magnitude of the electrical signal obtained by photoelectrically converting reflected light with a photodetector is also proportional to the sixth power of d. The optical systems described in Patent Documents 1 and 2, as well as the present invention, utilize homodyne interference, which amplifies the interference between reflected light and a reference light. In this case, the electric field amplitude, rather than the energy of the reflected light, is converted into an electrical signal, so the maximum detected signal is proportional to the cube of d. Using such an optical system results in a more gradual change in the magnitude of the detected signal with particle size compared to methods that photoelectrically convert the energy of reflected light, thereby advantageously widening the dynamic range of measurable particle sizes. When using a semiconductor laser as the light source, the technology described in Patent Document 3 allows for the reduction of laser noise, primarily caused by feedback light, by superimposing a high frequency on the drive current.

[0021] While the widely known Rayleigh scattering detects light energy and is proportional to the sixth power of d, this method converts the electric field amplitude of the reflected light into a detection signal through interference amplification, so it is proportional to the third power of d. This means that the change in the magnitude of the detection signal is small relative to the size range of the object being measured, making it superior in terms of dynamic range compared to conventional methods.

[0022] A specific measurement method will be explained based on the above principle. With the optical axis direction set to Z, the detection signal obtained by scanning the inside of the measurement object three-dimensionally with a light spot focused by an objective lens is called three-dimensional image data. Three-dimensional image data is generated by using an AD converter or other device to save the control signal or position monitor signal for the light spot scanning in the X, Y, and Z directions, and the detection signal as time-series data, and then processing the data.

[0023] Figure 3 shows an example of measurement data. The upper left of Figure 3 is a visualization of 3D image data. Here, the scanning range of the light spot is 300 μm, 300 μm, and 50 μm in the X, Y, and Z directions, respectively. The upper right of Figure 3 shows an enlarged view of data for a single separated particle, and the maximum value Amax of the detection signal obtained when the light spot position and particle position are aligned is the index for evaluating the size of that particle. The bottom of Figure 3 shows the results of overlaying the relationship between the amount of defocus and the magnitude of the detection signal for multiple measured particles. As can be seen from the figure, the detection signal Amax when the defocus amount is zero (at focus) is an index for evaluating the particle size.

[0024] To facilitate understanding of the present invention, actual measurement results relating to fluctuations in detection sensitivity during scanning of a light spot caused by the individual characteristics of two devices will be shown here.

[0025] Figures 4A and 4B show an example of experimental results quantifying the variation in detection sensitivity. Here, the detection signal was acquired by focusing the light spot on the bottom glass of the sample container. Figure 4A shows a two-dimensional image in which the detection signal from one device was converted into brightness information. As can be seen, the change in the detection signal when the light spot is scanned in the X direction is dominant, reaching a maximum at the center and a minimum at the right edge. Because the reflectivity of the bottom glass of the sample container is constant, the variation in the detection signal, i.e., the variation in the detection sensitivity of this device, was approximately 15%. Figure 4B shows a two-dimensional image in which the detection signal from another device was converted into brightness information. As can be seen, the change in the detection signal when the light spot is scanned in the X direction is dominant, reaching a maximum at the right edge and a minimum at the left edge. The variation in the detection signal, i.e., the variation in the detection sensitivity of this device, was approximately 43%.

[0026] To avoid any misunderstanding, we will provide a further explanation of the detection sensitivity fluctuations shown here. The measurement target is a microparticle suspended in a sample container. If the standard measurement position for the 3D image data is approximately 500 μm away from the bottom glass of the sample container, the optical system of the device is aberration-corrected so that spherical aberration is minimized at this point. Therefore, when measuring the bottom glass of the sample container, spherical aberration of approximately 2λ occurs. Therefore, the detection sensitivity fluctuations shown in Figure 4 are larger than the detection sensitivity fluctuations that actually occur when measuring the target microparticles, such as protein aggregates. The objective of the present invention is to suppress the detection sensitivity fluctuations that occur when measuring target microparticles, such as protein aggregates, that undergo Brownian motion in a solvent.

[0027] Next, the main cause of fluctuations in detection sensitivity caused by scanning with a light spot will be described.

[0028] Figure 5 is a schematic diagram showing the relationship between the semiconductor laser as a light source and the intensity distribution of the emitted light. The cavity of the semiconductor laser is larger in the horizontal direction (etching direction) than in the vertical direction (lamination direction), and the intensity distribution of the emitted laser light is affected by diffraction and has a half-maximum full-width θ ⊥ (≒16 degrees), θ / / The parallel beam converted by the collimating lens has a corresponding two-dimensional Gaussian distribution of intensity.

[0029] 6A is a schematic diagram showing a laser beam when a light spot is formed in the center in the X or Y direction. As can be seen in the figure, the parallel beam is not deflected by the scanning mirror, and the light in the center of the parallel beam is collected by the objective lens.

[0030] Figure 6B is a schematic diagram showing a laser beam when a light spot is formed at the end in the X or Y direction. As can be seen in the figure, the parallel beam is deflected by the scanning mirror, and the light at the periphery of the parallel beam is focused by the objective lens. At this time, the light intensity focused at the light spot is lower than that at the center.

[0031] Due to these factors, the intensity of the light focused on the light spot fluctuates as the light spot is scanned in the X or Y direction. / / Since the direction is aligned with the X direction, the fluctuation in detection sensitivity in the X direction is greater than that in the Y direction, as shown in FIGS. 4A and 4B.

[0032] Figure 7 is a schematic diagram showing the fluctuations in detection sensitivity that occur when a light spot is scanned in the Z direction. It is widely known that the magnitude of the detection signal obtained by interference between the signal light reflected from the measurement target and the reference light exhibits Gaussian distribution characteristics depending on the optical path length difference between the two. Here, the coherence length is defined as the optical path length difference (FWHM value) at which the detection signal is half its maximum value. As can be seen in the figure, the coherence length is approximately 200 μm. If the movement of the light spot in the Z direction when acquiring 3D image data is 50 μm, then the sensitivity of the detection signal will fluctuate depending on the position z in the Z direction. This sensitivity fluctuation will vary for each device and each output power depending on the semiconductor laser element, output power, and high-frequency superposition conditions.

[0033] In the following description of the present invention, a Cartesian coordinate system is used in which the optical axis direction is the Z axis and the X and Y axes are in a plane perpendicular to the Z axis, and the positions of the light spot in the X, Y, and Z axes are designated as x, y, and z, respectively. Furthermore, to facilitate understanding of the detection sensitivity correction function, unless otherwise specified, the values ​​of x, y, and z are expressed as positions normalized to ±1 within the measurement scanning range. Furthermore, for simplicity of explanation, the maximum detection signal Amax obtained when the particle is at the focal position of the objective lens is simply referred to as the detection signal. Furthermore, in each embodiment, unless otherwise specified, the correction results of the present invention for the device with the larger detection sensitivity fluctuation shown in Figure 4B are shown. In the present invention, the individual characteristics of the device are stored as model formula coefficients in a storage device or the like during calibration. Therefore, it goes without saying that the device differences appearing in the measurement results can be suppressed by correcting the detection sensitivity not only for the device with the smaller detection sensitivity fluctuation shown in Figure 4A, but also for any device that satisfies certain performance standards.

[0034] <Embodiment 1: Method for measuring and correcting sensitivity fluctuations during particle measurement> The measurement targets of this invention are submicron to micron-order microparticles suspended in a solvent and undergoing Brownian motion, such as protein aggregates in biopharmaceuticals. Because the position, size, and concentration of the microparticles being measured are unknown, it is not possible to quantify the variations in detection sensitivity that differ between instruments using biopharmaceutical samples. Furthermore, as mentioned above, measurement data for the glass bottom of a sample container involves large spherical aberration, so it can only be used as a guide for variations in detection sensitivity.

[0035] In this study, we measured the detection sensitivity fluctuation using a commercially available polystyrene standard particle suspension with a uniform particle size and controllable concentration, and then demonstrated a method for determining the coefficients of the detection sensitivity correction function described below. While any polystyrene standard particle can be selected as long as it is in the submicron range, we selected polystyrene particles with an average size of 0.551 μm, whose size had been accurately calibrated in advance through observation with a scanning electron microscope. This was diluted to a particle concentration of approximately 10 M particles / mL and sealed in a sample container to serve as the reference sample. Because the positions of the polystyrene particles contained in the reference sample change randomly due to Brownian motion, acquiring a sufficient number of 3D image data sets enables the acquisition of detection signals with nearly uniform standard deviations in the X, Y, and Z directions. Approximately 12,600 calibration particle data sets (x, y, z, Amax) were prepared here.

[0036] FIG. 8 is a flowchart illustrating the procedure for calibrating the individual characteristics of each device. In step S801, a reference sample containing the standard particles described above is prepared. In step S802, standard measurement conditions are set for the particle measurement device to be calibrated. In step S803, 3D image data is acquired according to the method described above, and calibration particle data is obtained from the standard particles contained in the reference sample. In step S804, each coefficient of the detection sensitivity correction function is determined based on the model formula described below so that the RMS value of the detection signal is minimized. In step S805, the type of model formula and the numerical values ​​of each coefficient are saved in a storage device. As a result, the individual characteristics of the device can be acquired and saved as coefficients of the determined model formula.

[0037] Figure 9 is a flowchart showing the operation when the device is operated in an operational environment. In step S901, the type of model formula and each coefficient are read from storage. In step S902, the sample is measured. In step S903, sensitivity correction is performed on the position and detection signal (x, y, z, Amax) of each particle using the model formula and each coefficient, thereby obtaining Amax' from Amax. In step S904, the size and concentration of the target particle contained in the sample are calculated and displayed from Amax'.

[0038] As a result, it is possible to correct the detection sensitivity for the individual characteristics of the device, which were determined during calibration (often at the time of shipment), in the operational environment, and obtain measurement data in which differences between multiple devices are suppressed.

[0039] <Second embodiment: Method for correcting detection sensitivity for three-dimensional position of light spot> In the second embodiment of the present invention, a specific example of the correction model formula explained in the first embodiment will be described. The correction model formula (detection sensitivity correction function) is expressed as η(x, y, z).

[0040] The following equation is a correction model using a first-order polynomial: C xyz0 , C x1 , C y1 , Cz1 is a coefficient indicating the amount of correction of the detection sensitivity for the characteristics of each device.

[0041]

number

[0042] The following equation is a correction model using a second-order polynomial: C xyz0 , C x1 , C x2 , C y1 , C y2 , C z1 , C z2 is a coefficient indicating the amount of correction of the detection sensitivity for the characteristics of each device.

[0043]

number

[0044] The following equation is a correction model using a third-order polynomial: C xyz0 , C x1 , C x2 , C x3 , C y1 , C y2 , C y3 , C z1 , C z2 , C z3 is a coefficient indicating the amount of correction of the detection sensitivity for the characteristics of each device.

[0045]

number

[0046] The following equation is a correction model using a fourth-order polynomial: C xyz0 , C x1 , C x2 , C x3 , C x4 , C y1 , C y2 , C y3 , C y4 , C z1 , C z2 , C z3 , Cz4 is a coefficient indicating the amount of correction of the detection sensitivity for the characteristics of each device.

[0047]

number

[0048] Although correction model equations based on first to fourth degree polynomials have been exemplified above, it should be noted that in the present invention, fifth degree or higher polynomials can also be used as correction models for detection sensitivity.

[0049] The following equation is a correction model based on a three-dimensional Gaussian distribution: C xyz0 , μ x , μ y , μ z , σ x , σ y , σ z is a coefficient indicating the amount of correction of the detection sensitivity for the characteristics of each device.

[0050]

number

[0051] The following equation is a correction model based on a Gaussian distribution with a three-dimensional offset: x , a y , a z , b x , b y , b z , μ x , μ y , μ z , σ x , σ y , σ z is a coefficient that indicates the amount of correction of the detection sensitivity for the characteristics of each device. The difference from Equation 5 is the DC value a x , a y , a z and the sensitivity correction amount b that follows a Gaussian distribution x , b y , b z The introduction of this technology has improved the range of adaptability to the characteristics of individual devices.

[0052]

number

[0053] In addition to the Gaussian distribution shown here, the present invention can utilize various special functions according to the characteristics of the device, such as the error function, which is its integral form, the Poisson distribution derived from the binomial distribution, and the chi-squared distribution, which is the square of a random variable that follows the Gaussian distribution.

[0054] The results of sensitivity calibration performed on each model formula according to the method shown in FIG. 8 are explained below.

[0055] Figure 10A shows the results of the correction model using the first-order polynomial shown in Equation 1. The upper part of the figure shows the raw data results before applying the detection sensitivity correction function of the present invention, and the lower part shows the results after applying the detection sensitivity correction function of the present invention. In each figure, the horizontal axis represents the normalized light spot position, and the vertical axis represents the measured particle size. Each plot point in the figure represents the experimental result corresponding to each of the calibration particle data mentioned above. As can be seen from the figure, the raw data results show changes dependent on the spot positions x, y, and z. As mentioned above, this is due to the detection sensitivity fluctuations that depend on the individual characteristics of each device. On the other hand, when the detection sensitivity correction function of the present invention is applied, it can be seen that the variation in the vertical axis of each plot point (variation in measurement size) is improved. In particular, with regard to the dependency in the X-axis direction, it can be seen that applying the detection sensitivity correction function of the present invention improves the characteristics to become symmetrical, with the center of the light spot scanning range (x = 0) being the extreme value.

[0056] Figure 10B shows the results of the correction model using the quadratic polynomial shown in Equation 2. As with Figure 10A, it shows the results of the raw data and the results of applying the detection sensitivity correction function of the present invention. As can be seen from the figure, application of the detection sensitivity correction function of the present invention suppresses the spot position dependence in the X, Y, and Z directions to the point that it is no longer visible. The variation along the vertical axis of the figure represents the SNR of the instrument and the size variation of the standard particles themselves. The reason why the effect of the present invention is so pronounced using the quadratic polynomial is that, as explained above, the cause of variation in detection sensitivity is due to a Gaussian distribution in all directions, and the change near the center of the Gaussian distribution can be approximated by a quadratic equation.

[0057] Figure 10C shows the results of a correction model using the third-order polynomial shown in Equation 3. As can be seen from the figure, by applying the detection sensitivity correction function of the present invention, the spot position dependence in the X, Y, and Z directions is suppressed to the point where it is not visible. As shown in the definition, this correction model includes a second-order polynomial, so it is natural that the suppression performance is better than that shown in Figure 10B.

[0058] Figure 10D shows the results of a correction model using the fourth-order polynomial shown in Equation 4. As can be seen from the figure, by applying the detection sensitivity correction function of the present invention, the spot position dependence in the X, Y, and Z directions is suppressed to the point where it is not visible. As shown in the definition, this correction model includes a second-order polynomial, so it is only natural that the suppression performance is better than that shown in Figure 10B.

[0059] Figure 10E shows the results of a correction model using the three-dimensional Gaussian distribution formula shown in Equation 5. As can be seen from the figure, application of the detection sensitivity correction function of the present invention has improved the spot position dependency in the X, Y, and Z directions compared to the raw data. However, as in Figure 10A, visible sensitivity fluctuations in the X direction remain, leaving room for improvement.

[0060] Fig. 10F shows the results of a correction model using the Gaussian distribution equation with a three-dimensional offset shown in Equation 6. As mentioned above, this correction model improves the application range of Equation 5. As a result, it can be seen that by applying the detection sensitivity correction function of the present invention, the spot position dependency in the X, Y, and Z directions is suppressed to the point where it is not visible.

[0061] To intuitively and quantitatively compare the above results, the frequency distribution of the measured standard particle sizes is shown below.

[0062] Figure 11 shows the size frequency distribution of the raw data before the application of the detection sensitivity correction function of the present invention. As can be seen in the figure, the distribution is asymmetrical with respect to the peak. The tail of the distribution on the larger size side (right side) reflects the characteristics of the device on the +X direction side (the side with higher detection sensitivity) shown above. If the size of the standard particles is measured precisely, the size frequency distribution should be symmetrical with respect to the peak. The RMS value, which represents the variation in the measured size of the standard particles, was 4.60%.

[0063] Figure 12A shows the results of the correction model using the first-order polynomial shown in Equation 1. As can be seen from the figure, the symmetry of the peak of the size frequency distribution has improved compared to the raw data in Figure 11. This is as explained in the explanation of Figure 10A. The RMS value of the measured size of the standard particles was 3.66%.

[0064] Figure 12B shows the results of the correction model using the quadratic polynomial shown in Equation 2. As can be seen from the figure, application of the detection sensitivity correction function of the present invention improves the symmetry of the size frequency distribution peak and narrows the spread of the distribution. The RMS value of the measured size of the standard particles was 2.74%.

[0065] Figure 12C shows the results of the correction model using the third-order polynomial shown in Equation 3. As can be seen from the figure, application of the detection sensitivity correction function of the present invention improves the symmetry of the size frequency distribution with respect to the peak, and also narrows the spread of the distribution. The RMS value of the measured size of the standard particle was 2.74%. Since this correction model includes a second-order polynomial, as defined, it is natural that the suppression performance is better than that of Figure 12B.

[0066] Figure 12D shows the results of the correction model using the fourth-order polynomial shown in Equation 4. As can be seen from the figure, application of the detection sensitivity correction function of the present invention improves the symmetry of the size frequency distribution with respect to the peak, and also narrows the spread of the distribution. The RMS value of the measured size of the standard particle was 2.73%. Since this correction model includes a second-order polynomial, as defined, it is natural that the suppression performance is better than that of Figure 12B.

[0067] Figure 12E shows the results of the correction model using the three-dimensional Gaussian distribution formula shown in Equation 5. As can be seen from the figure, application of the detection sensitivity correction function of the present invention improves the symmetry of the size frequency distribution peak and narrows the spread of the distribution. The RMS value of the measured size of the standard particles was 3.25%.

[0068] Figure 12F shows the results of a correction model using the three-dimensional offset Gaussian distribution equation shown in Equation 6. As can be seen from the figure, application of the detection sensitivity correction function of the present invention improves the symmetry of the size frequency distribution with respect to the peak, and also narrows the spread of the distribution. The RMS value of the measured size of the standard particle was 2.75%. As mentioned above, this correction model improves the applicability range of Equation 5, so it is not surprising that the RMS value is smaller than that shown in Figure 12E.

[0069] Figure 13 summarizes the results of comparing the RMS values ​​of standard particle sizes, demonstrating the effectiveness of the detection sensitivity correction method of the present invention. In the figure, the horizontal axis represents the correction model equation shown above, and the vertical axis represents the RMS value of the measured standard particle size. As can be seen, the RMS values ​​of standard particle sizes are smaller for all correction model equations when the present invention is applied compared to raw data when the present invention is not applied, quantitatively demonstrating the effectiveness of the detection sensitivity correction method of the present invention. Furthermore, the RMS values ​​of standard particle sizes obtained by applying the quadratic polynomial, cubic polynomial, quartic polynomial, and Gaussian distribution equation with a three-dimensional offset are nearly identical and minimal, indicating that these model equations are suitable for the characteristics of the device shown here. The fewer the number of coefficients included in a model equation, the easier and more stable the calibration can be performed and the more robust it is when operated in an operational environment. Therefore, for example, the quadratic polynomial equation in Equation 2 can be said to be suitable as a sensitivity correction model equation.

[0070] We will now explain the selection of an appropriate model equation based on the design of the instrument and the characteristics of its components. It goes without saying that, as long as sufficient detection sensitivity correction can be achieved, a simpler model equation with fewer coefficients will be more robust. For instruments designed to minimize variations in detection sensitivity between individual instruments through the selection of components, a first-order polynomial (Equation 1) or a Gaussian distribution (Equation 5) are suitable as simple model equations. When measuring particles with different physical properties (refractive indexes), such as protein aggregates and inorganic nanoparticles or silicone oil spheres, instruments capable of simultaneously measuring these particles irradiate the particles with laser light of multiple wavelengths simultaneously to utilize the wavelength dependence of their physical properties. In such cases, it is preferable to select a higher-order polynomial, such as a third-order polynomial (Equation 3) or a fourth-order polynomial (Equation 4), as the sensitivity correction model equation. For instruments designed to shorten measurement time by expanding the light spot scanning range in the Z direction, it is preferable to select a Gaussian distribution equation with a three-dimensional offset (Equation 6), which allows for more precise detection sensitivity correction than a polynomial, given changes in the optical path length difference in the Z direction.

[0071] In an apparatus designed so that some sensitivity fluctuations in the X, Y, and Z directions are sufficiently small, it is easy and preferable to selectively correct the detection sensitivity in at least one axial direction by modifying the model formula disclosed in the present invention by eliminating one or two coefficients for the particle positions x, y, and z.

[0072] As described above, according to the present invention, by following the method shown in FIGS. 8 and 9, an appropriate model formula can be selected from a variety of model formulas including the above-mentioned model formula, characteristics that differ for each device can be saved as coefficients, and the detection signal can be corrected in the customer's environment based on these coefficients, thereby improving the variation in measurement results and suppressing differences between multiple devices.

[0073] <Embodiment 2: Summary> The particle measuring device according to the second embodiment can suppress fluctuations in detection sensitivity due to the individual characteristics of the particle measuring device by correcting the magnitude of the detection signal using a detection sensitivity correction function including a polynomial or Gaussian distribution, with the light spot position in each of the X, Y, and Z directions as a variable.

[0074] <Third embodiment: Method for correcting sensitivity fluctuations when the refractive index of measurement target particles varies> The measurement targets handled by this invention are submicron to micron-order microparticles suspended in a solvent and undergoing Brownian motion, such as protein aggregates in biopharmaceuticals. As mentioned above, this invention can also measure commercially available polystyrene bead particles in addition to protein aggregates. Furthermore, it is also possible to measure Au particles, Ag particles, TiOx particles, silicone oil spheres, and other particles. Because these generally have a higher refractive index than protein aggregates, even for particles of the same size, the amount of reflected light and the magnitude of the detection signal increase depending on the measurement target. Calibration data for the detection signal and particle size corresponding to the type of particle to be measured can be stored in the device in advance. To avoid saturation of the detection signal, the semiconductor laser output power can be reduced. As mentioned above, the fluctuations in detection sensitivity in the X and Y directions depending on the scanning position of the light spot are primarily determined by the emission intensity distribution based on diffraction phenomena dependent on the shape of the semiconductor laser cavity. Therefore, even if the semiconductor laser output power is reduced, the change is negligibly small. On the other hand, the main cause of the fluctuation in detection sensitivity in the Z direction according to the scanning position of the light spot is a change in the coherence length, so it is necessary to select an appropriate correction amount according to the emission power of the semiconductor laser.

[0075] Here, we present a model formula suitable for dealing with multiple semiconductor laser emission power conditions depending on the factors that cause fluctuations in detection sensitivity. In the following, the emission power of the semiconductor laser is represented as p, and the detection sensitivity correction function is represented as η(x, y, z, p).

[0076] The following equation is a correction model using a second-order polynomial: C xyz0 , C x1 , C x2 , C y1 , C y2 , C z0 (p), C z1 (p), C z2 (p) is a coefficient that indicates the amount of correction for the detection sensitivity for the individual characteristics of the device. By making each coefficient in the Z direction dependent on p, it is possible to appropriately suppress fluctuation factors in the detection sensitivity related to changes in the emission power of the semiconductor laser.

[0077]

number

[0078] The following equation is a correction model that combines correction in the X and Y directions using a quadratic polynomial and a Gaussian distribution in the Z direction. C xyz0 , C x1 , C x2 , C y1 , C y2 , μ z (p), σ z (p) is a coefficient that indicates the amount of correction for the detection sensitivity for the individual characteristics of the device. Similarly, by making each coefficient in the Z direction dependent on p, it is possible to appropriately suppress fluctuations in the detection sensitivity caused by changes in the emission power of the semiconductor laser.

[0079]

number

[0080] For each model formula, sensitivity calibration was performed according to the method shown in Figure 8. The difference from the previously described method is that calibration was performed under two different emission power conditions: an emission power p-p0 suitable for measuring protein aggregates, and an emission power p-p1 (p1 = 0.42p0) suitable for measuring polystyrene bead particles.

[0081] FIG. 14A shows the results of a correction model using the quadratic polynomial shown in Equation 7. The raw data has been omitted. The upper part of the figure shows the results of applying the detection sensitivity correction function of the present invention when the light emission power p = p0. The lower part of the figure shows the results of applying the detection sensitivity correction function of the present invention when the light emission power p = p1. It can be seen that by applying the detection sensitivity correction function of the present invention, the spot position dependence in the X, Y, and Z directions is suppressed to the point where it is not visible under any of the light emission power conditions.

[0082] 14B shows the results of a correction model that combines the quadratic polynomial shown in Equation 8 with a Gaussian distribution. The upper part of the figure shows the results of applying the present invention when the light emission power p=p0, and the lower part shows the results of applying the present invention when the light emission power p=p1. It can be seen that, with the present invention, the spot position dependence in the X, Y, and Z directions is suppressed to the point where it is not visible under any light emission power conditions.

[0083] 15A shows the results of the correction model using the quadratic polynomial shown in Equation 7. The upper part of the figure shows the results of the raw data before applying the detection sensitivity correction function of the present invention, and the lower part shows the results after applying the detection sensitivity correction function of the present invention. When the emission power p=p0, it can be seen that the symmetry of the size frequency distribution of the standard particles with respect to the peak improved before and after applying the present invention, and the RMS value of the measured size improved from 4.60% to 2.73%. When the emission power p=p1, it can also be seen that the symmetry of the size frequency distribution of the standard particles with respect to the peak improved before and after applying the present invention, and the RMS value of the measured size improved from 4.98% to 2.82%. Figure 15B shows the results of a correction model that combines the quadratic polynomial shown in Equation 8 with a Gaussian distribution. The upper part of the figure shows the results of the raw data before applying the detection sensitivity correction function of the present invention, and the lower part shows the results after applying the detection sensitivity correction function of the present invention. At all emission powers, the symmetry of the standard particle size frequency distribution peak is improved similarly before and after applying the present invention. When the emission power p = p0, the RMS value of the measured size of the standard particle improves from 4.60% to 2.74% before and after applying the present invention. When the emission power p = p1, the RMS value of the measured size of the standard particle improves from 4.98% to 2.83% before and after applying the present invention.

[0084] Figure 16 summarizes the results of a comparison of the RMS values ​​of standard particle sizes, demonstrating the effect of the detection sensitivity correction method of the present invention. In the figure, the horizontal axis represents the correction model formula shown above, and the vertical axis represents the RMS value of the measured standard particle size, with the cases of emission power p=p0 and p=p1 shown side by side. As can be seen from the figure, the RMS value of the standard particle size is reduced to the same extent by applying the present invention compared to the raw data to which the present invention is not applied, quantitatively demonstrating the effect of the detection sensitivity correction method of the present invention.

[0085] As described above, according to the present invention, by following the method shown in FIGS. 8 and 9, an appropriate model formula can be selected from a variety of model formulas including the above-mentioned model formula, characteristics that differ for each device can be saved as coefficients, and the detection signal can be corrected in the operating environment based on these coefficients, thereby improving the variation in measurement results and suppressing differences between multiple devices.

[0086] In the above, the cases of light emission power p = p0 and p = p1 were shown as suitable output powers for protein aggregates and polystyrene bead particles, but it is easy to add other suitable light emission powers for metal nanoparticles, silicone oil spheres, etc. Also, σ in Equation 8 z Instead of (p), the FWHM value of the coherence length measured separately, w z It is also easy to use (p). In that case, as is well known, you can convert it as follows. Therefore, σ z (p) and w z Since (p) can be treated as physically equivalent, the mathematical expressions obtained by converting them into each other can also be treated as equivalent.

[0087]

number

[0088] Furthermore, in an apparatus designed so that the sensitivity fluctuation in either the X or Y direction is sufficiently small, it is easy and preferable to implement the present invention by modifying the model formula disclosed in the present invention by eliminating the coefficient of either the particle position x or y.

[0089] As described above, according to the present invention, by following the method shown in Figures 8 and 9, an appropriate selection is made from a variety of model formulas including the model formula described above, and the characteristics that differ for each device for multiple light emission power conditions suitable for the measurement object are saved as coefficients of the model formula, and the detection signal is corrected in the customer's environment based on these, thereby improving the variation in measurement results and suppressing differences between multiple devices.

[0090] <Fourth embodiment: particle measurement device> 17 is a diagram showing an example of the configuration of a particle measuring device according to embodiment 4 of the present invention. Laser light emitted from light source 100, whose light emission state is controlled by laser driver 101 that controls high-frequency superposition and output power, is converted into parallel light by collimating lens 102, and after the polarization direction is adjusted by λ / 2 plate 103, whose optical axis is set at approximately 22.5 degrees with respect to the horizontal direction, the light is split into signal light and reference light by polarizing beam splitter 104.

[0091] The reference light is converted to a circularly polarized state by the λ / 4 plate 105, then reflected by the reference light mirror 106. The λ / 4 plate 105 causes the reference light to have a polarization state rotated 90 degrees from the outward path, and the signal light is then reflected by the polarizing beam splitter 104. The signal light is deflected in its traveling direction by the XY-direction composite deflection element 107 (scanning mechanism), then converted to a circularly polarized state by the action of the built-in λ / 4 plate, and is focused within the sample 204 held in the sample container 200 by the objective lens 108. The drive mechanism 109 (scanning mechanism), which moves the sample in the Z-axis direction, has the function of scanning the focal position of the signal light along the Z-axis (optical axis direction). The signal light components reflected from individual particles contained in the sample 204 are deflected in the same direction as the outward path by the XY-direction composite deflection element 107, and are also converted to a polarization state rotated 90 degrees from the outward path by the action of the built-in λ / 4 plate, and are transmitted through the polarizing beam splitter 104. Here, sample container 200 holds sample 204 in a well and guides signal light into the sample through transparent window 202. Reference numeral 203 denotes a resin member that forms the well of the sample container. Base plate 201 contacts transparent window 202 and mechanically holds sample container 200 while stabilizing the temperature of the sample.

[0092] The signal light and the reference light are combined by the polarizing beam splitter 104, guided to the detection optical system 112, and split into transmitted light and reflected light by the half beam splitter 113 via the pinhole 111.

[0093] The reflected light passes through a λ / 4 plate 114, whose optical axis is set at approximately 45 degrees to the horizontal, and is then focused by a focusing lens 115 and split into two by a polarizing beam splitter 116. The two beams are then photoelectrically converted by photodetectors 150 and 151, and differentially amplified by a current differential amplifier 152 to become a detection signal 123.

[0094] The transmitted light passes through a λ / 2 plate 118, whose optical axis is set at approximately 22.5 degrees with respect to the horizontal direction, and is then focused by a focusing lens 119 and split into two by a polarizing beam splitter 120. The two beams are then photoelectrically converted by photodetectors 153 and 154, and differentially amplified by a current differential amplifier 155 to become a detection signal 122.

[0095] The detection optical system 112 shown here constitutes a homodyne phase diversity method, and the real part component 122 and imaginary part component 123 of the detection signal are electrical signals corresponding to the real part and imaginary part of the electric field amplitude of the signal light reflected from individual particles contained in the sample 204. The detection signal is calculated in the signal processing unit 124 as a numerical value obtained by calculating the sum of the squares of these and then calculating the square root.

[0096] The signal processing unit 124 synthesizes the time-series data of the acquired detection signals to form three-dimensional image data in the X, Y, and Z directions within the sample, and also separates and tracks the data of individual particles contained therein to calculate the maximum detection signal obtained for each particle under the focusing conditions. The signal processing unit 124 has the function of improving the variation in measurement results and suppressing differences between multiple devices by performing calibration of the detection sensitivity fluctuations shown in Figures 8 and 9 and correction for the customer's environment. Finally, the signal processing unit 124 organizes the measurement results corrected using the methods described in embodiments 1 to 3 of the present invention into graphs, numerical tables, etc., and presents the results to the user on the display unit 125.

[0097] The signal processing unit 124 in the figure is implemented by an embedded microcomputer built into the device, or by a computer placed outside the device that enables the exchange of necessary signals via an interface board, etc. If there are time or power constraints on the processing items of the signal processing unit 124, a dedicated processing circuit implemented by an FPGA or the like may be used as an auxiliary computing unit.

[0098] The memory unit 126 can store, for example, a correction model formula for each individual particle measuring device. The signal processing unit 124 can use the correction model formula stored in the memory unit 126 to correct for differences in the detection sensitivity fluctuations by the method described in the above embodiments.

[0099] <Modifications of the present invention> The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0100] In the above embodiment, the coefficient (C z0 (p), C z1 (p), C z2 (p), μ z (p), σ z (p)) may be a mathematical function expressed as a formula, a data table listing values ​​corresponding to p, or any other form that defines the functional relationship between p and these coefficients.

[0101] In the above embodiments, the signal processing unit 124 can be built into the particle measuring device, or the particle measuring device may acquire only data describing the results of measuring a sample, and the signal processing unit 124 may be arranged outside the particle measuring device to receive that data. In either case, the configuration of the particle measuring device according to the present invention is the same as that described in the above embodiments. [Explanation of symbols]

[0102] 100: Light source 101: Laser driver with high frequency superposition function 108: Objective lens 109: Sample container drive mechanism 112: Detection optical system 124: Signal processing unit 200: Sample container 201: Base plate 202: Transparent window 203: Resin member forming a well

Claims

1. 1. A particle measurement device for measuring particles in a liquid sample, comprising: a light source that emits light; a branching unit that branches the light from the light source into signal light and reference light; a scanning mechanism that scans an irradiation position of the optical spot of the signal light; an irradiation unit that condenses the signal light using an objective lens and irradiates the sample with the collected light; a detection unit for detecting an interference signal obtained by causing the reflected light from the particle to interfere with the reference light; a processing unit that measures the size of the particle using the interference signal; Equipped with the scanning mechanism is configured to scan the irradiation position in a first direction and a second direction that are perpendicular to each other in a plane perpendicular to an optical axis of the light, and to scan the irradiation position in a third direction that is parallel to the optical axis, The processing unit corrects the size of the particle using a correction function that has as an input value at least one of the irradiation position in the first direction, the irradiation position in the second direction, and the irradiation position in the third direction. A particle measuring device characterized by:

2. The correction function is configured by a polynomial having at least one of the irradiation position in the first direction, the irradiation position in the second direction, and the irradiation position in the third direction as a term.

2. The particle measuring device according to claim 1.

3. The correction function is a first or higher order term of the irradiation position in the first direction; a first or higher order term of the irradiation position in the second direction; a first or higher order term of the irradiation position in the third direction; It is constructed by linearly adding 3. The particle measuring device according to claim 2.

4. The correction function is configured to correct the size of the particle using the inverse of a normal distribution of at least one of the irradiation position in the first direction, the irradiation position in the second direction, and the irradiation position in the third direction.

2. The particle measuring device according to claim 1.

5. The correction function is a mean and a standard deviation of the irradiation position in the first direction on the normal distribution; a mean and a standard deviation of the irradiation position in the second direction on the normal distribution; a mean and a standard deviation of the irradiation position in the third direction on the normal distribution; It is made up of 5. The particle measuring device according to claim 4.

6. The correction function further includes a DC value that offsets the normal distribution and a sensitivity correction amount that multiplies the normal distribution by a constant.

5. The particle measuring device according to claim 4.

7. The correction function includes the power of the light or the coherence length of the light as an input value.

2. The particle measuring device according to claim 1.

8. the correction function is configured by first or higher order terms of the irradiation position in the third direction, The first or higher order terms of the irradiation position in the third direction have coefficients that are functions that use the power or the coherence length as input values.

8. The particle measuring device according to claim 7.

9. The correction function is a first or higher order term of the irradiation position in the first direction; a first or higher order term of the irradiation position in the second direction; a Gaussian distribution equation that corrects the particle size in the third direction by the inverse of a normal distribution of the irradiation position in the third direction; It is composed of the Gaussian distribution formula includes a mean and a standard deviation on the normal distribution, the average is formed by a function that uses the power or the coherence length as an input value, The standard deviation is formed by a function that uses the power or the coherence length as an input value.

8. The particle measuring device according to claim 7.

10. the particle measuring device further includes a storage unit that stores data describing the correction function; The processing unit corrects the size of the particles using the correction function read from the data.

2. The particle measuring device according to claim 1.

Images