KR101909447B1 - System and Method for Quantitatively Estimating Delivering Efficiency of Cells and/or Drugs in Microvessels and Tissue - Google Patents

Abstract

According to embodiments of the present disclosure, the distribution (or behavior) of cells and / or drugs in microvascular flow can be predicted using simulation tools based on a plasma skimming model of blood and results obtained from simple in vitro experiments A microvascular endothelial cell and / or a drug delivery efficiency quantification system and method which can be effectively utilized in the design of drugs and the like are described.

Description

Technical Field [0001] The present invention relates to a system and a method for quantitating cell and / or drug delivery efficiency in microvessels and peripheral tissues,

The present disclosure relates to systems and methods that can quantify the delivery efficiency of cells and / or drugs in microvessels and surrounding tissues. More specifically, the disclosure is directed to a simple in vitro (microfluidic) channel-based, in- vitro vitro) assays, and relates to microvascular and simulations to predict the mass transfer from the surrounding tissues tool (e.g., a computational model or a system and method for quantifying the body transfer efficiency by combining the software).

Blood is the most important biological fluid, specifically a multiphase biological fluid (deformable red blood cells are suspended in the plasma), and a variety of basic functions to maintain homeostasis, including the transfer of nutrients and oxygen to tissues and organs To adjust pH and body temperature). Because blood contains a lot of information about the function of the human body, perfect blood analysis has been recognized as the main medical diagnostic test. In a broad sense, plasma and cells are each a major component of about 60% and about 40% of blood, respectively. Of the approximately 5 billion cells per milliliter of blood, red blood cells account for more than 93% of total cellular components.

On the other hand, a drug carrier (or carrier) containing a chemotherapeutic agent is ingested into the above-mentioned macrocirculatory system of blood for effective diagnosis and treatment of various diseases. In order to accurately reach the target site in the blood vessel, methods of adjusting the size and shape of the nano-sized drug carrier, controlling the electrical signal, and introducing the antibody have been proposed. Also, in order to accurately deliver the drug carrier to the diseased site, a method of using microvascular differences between the normal site and the diseased site is considered.

However, microchannel and animal experiments for measuring the efficiency of conventional drug carrier delivery have two limitations. Firstly, only very limited and qualitative measurements are possible, and second, there is a technical difficulty in presenting a clear basis for whether an optimized drug carrier in an animal experiment is applicable in clinical practice.

In this regard, Korean Patent Laid-Open Publication No. 2015-0000450 discloses a method of providing a three-dimensional shape data of a subject's blood vessel region by subjecting a subject to a boundary condition relating to blood flow, dividing the lumen of the subject blood vessel region by a mesh, Discloses a blood flow analysis system that derives a state amount of blood flow by calculation. In addition, Korean Patent No. 1530352 proposes a computational fluid dynamics modeling and analysis method based on material properties that analyze perfusion based on the material properties of blood vessel walls and plaques.

As an alternative method for predicting the distribution characteristics of the drug carrier, it can be exemplified to secure a mathematical and computational model capable of evaluating the target efficiency of the drug carrier in the microvessels. In some computational models, attempts have been made to simulate interaction between cells and drug carriers. Despite the possibility of blood flow simulation using a microvascular drug carrier, the technique of directly simulating the whole microvascular endothelial cells and / or drug carrier has not been reported up to now due to difficulties due to excessive experimentation.

On the other hand, the use of a mathematical model to simplify blood flow in the microvessels is being studied. For example, Korean Patent No. 949460 discloses a fluorescence probe based on a mathematical model capable of accurately measuring the biofluidity of each region in a wide range from a lowered perfusion below a normal perfusion to a normal perfusion using an in vivo dynamics of a fluorescent probe Discloses a method for extracting pharmacokinetic vascular characteristics. However, there is a limit to precisely predict the behavior of a drug carrier from nano size to micro size through the microvessels to the target site by the above method.

In general, microvascular blood flow (flow) can be calculated by Poiseuille 's law using in - vivo viscosity, and flow separation at individual branch points is governed by the law of conservation of mass Lt; / RTI > By using this mathematical model, drug carriers in tumor microvessels can be simulated at the microvascular-network level (typically having diameters in the range of about 100 to 3 mu m).

Also, in order to further refine the mathematical and computational models studied above, the plasma skimming phenomenon of blood flow in the bifurcation channel region must be considered. In microvascular migration, red blood cells (RBCs) are concentrated in the vascular core while cell-free layer (CFL) is present near the vessel wall. As a result, blood and drug carrier passing through the branch tube are changed in concentration by the branch tube, and methods for predicting the change are required.

In this regard, red blood cells are one of the blood cells that constitute blood, hemoglobin-containing cells with a diameter of about 7 ㎛, and have no nucleus. There are about 5 million to about 5 million red blood cells in the peripheral blood of 1 하며, and they carry oxygen to the peripheral nerve by binding oxygen. To achieve this function, red blood cells must pass through a network of complex microvessels spread over all tissues and organs. In order to characterize such microvessels, U.S. Patent No. 8,828,226 suggests a technique for simulating the diffusion characteristics of red blood cells using a microvascular device, but it is difficult to accurately predict the drug delivery behavior through this.

As such, due to the two regions described above (i.e., the vascular core region and the CFL region), the hematocrit level changes in subsequent daughter vessels. At this time, the subsequent branching process changes the overall distribution of micro-blood vessel red blood cells and blood flow characteristics. In addition, the distribution of drug carriers in microvessels is highly related to plasma skimming of blood flow. Therefore, there is a need for a model that can effectively predict plasma skimming of blood and / or drug carriers in order to be applied to the design of drugs that can be delivered to specific target (or disease) sites in the future.

In the present disclosure, in order to precisely predict the cell body and the drug delivery process, the measurement is not possible, the micro-fluidic (microfluidic) A simple extracorporeal channel-based (in vitro) tests, and to quantify the microvascular and improved microvascular over the prior art by combining the simulation or software that can predict the mass transfer from the surrounding tissue and the surrounding tissue cells and / or drug delivery efficiency of the system and Method.

In particular, the present disclosure provides guidelines for effective drug design through in vitro experiments and predictive models of highly accurate microvascular endothelial cells and / or drug carrier delivery.

According to a first aspect of the present disclosure,

a) passing a blood mixture comprising blood and a drug carrier into a microfluidic channel of a microfluidic device that replicates any of the vascular segments of the vasculature;

b) analyzing flow behavior of the blood mixture passing through the microfluidic channel in step a) to obtain intravascular flow information to be simulated; And

c) predicting the concentration distribution of cells and / or drug carriers in the microvessels and surrounding tissues using the mass transfer simulation tool of the microvessels and the intravascular flow information;

A method for quantifying the delivery efficiency of cells and / or drugs in microvessels and surrounding tissues is provided.

In an exemplary embodiment, the intravascular flow information may include a flow rate, a hematocrit, and a concentration of a drug carrier.

According to an exemplary embodiment, the drug carrier may be particles having nanosize.

According to an exemplary embodiment, the blood mixture further comprises a fluorescent substance or a fluorescent probe, said step b) being carried out by an image process based on the fluorescence properties of the blood mixture passing through the microfluidic channel, And calculating a distribution-shape parameter (alpha) on the cross-sectional area concentration distribution of the cells and / or the drug carrier.

According to an exemplary embodiment, in the step c), a generalized plasma skimming model for a cell and a drug carrier represented by the following equations (20) to (23), wherein the calculated distribution- (?) and the microvascular mass transfer simulation tool can be used to predict the distribution of cells and / or drugs in specific microvessels and surrounding tissues:

은 농도 변화 계수이고, α는 미세혈관 내 C의 단면적 분포에 대한 형상 파라미터이고, M은 드리프트 파라미터(drift parameter)이고, A는 각각의 혈관의 단면적이고, 아래 첨자 0, 1 및 2는 각각 모 혈관(parent vessel) 및 2개의 분지된 혈관(daughter vessels)을 지시하며, 그리고 i는 1 및 2의 정수이다.Where C is the concentration of the cell or drug carrier, Q is the flow rate,

Is the concentration variation coefficient, α is the shape parameter for the cross-sectional area distribution of C microvascular, M is the drift parameter (drift parameter), and, A is and cross-section of each vessel, the subscripts 0, 1, and 2 are each parent A parent vessel and two daughter vessels, and i is an integer of 1 and 2.

In an exemplary embodiment, the distribution-shape parameter (alpha) is such that when alpha is 0, all drug carriers remain in the red blood cell core region, whereas when alpha is 1, all drug carriers are in the cell- CFL) region.

According to an exemplary embodiment, the optional vessel segment may be a segment selected or derived from a root vessel.

According to a second aspect of the present disclosure, there is provided a system for quantifying intravascular microcellular cells and / or drug delivery efficiency,

a) a microfluidic device having (i) a microfluidic channel that replicates any of the vascular segments of the vascular system, and (ii) In which the detection device is derived ( in in vitro analysis device; And

b) a microvascular mass transfer simulation tool;

/ RTI >

There is provided a system for predicting concentration distributions of cells and / or drug carriers in microvessels and surrounding tissues using the intravascular flow information and a mass transfer simulation tool of microvessels.

According to an exemplary embodiment, the intravascular flow information may include a flow rate, a hematocrit, and a concentration of a drug carrier.

According to an exemplary embodiment, the ex vivo analyzing apparatus can further calculate a distribution-shape parameter (?) Concerning the cross-sectional area concentration distribution of the cells and / or the drug carrier in the microfluidic channel.

According to an exemplary embodiment, the system is based on a generalized plasma skimming model for a cell and a drug carrier as represented by the following equations (20) - (23), wherein the calculated distribution-shape parameters The above micro-intravascular mass transfer simulation tool can be used to predict the distribution of cells and / or drugs within specific microvessels and surrounding tissues:

은 농도 변화 계수이고, α는 미세혈관 내 C의 단면적 분포에 대한 형상 파라미터이고, M은 드리프트 파라미터(drift parameter)이고, A는 각각의 혈관의 단면적이고, 아래 첨자 0, 1 및 2는 각각 모 혈관(parent vessel) 및 2개의 분지된 혈관(daughter vessels)을 지시하며, 그리고 i는 1 및 2의 정수이다.Where C is the concentration of the cell or drug carrier, Q is the flow rate,

Is the concentration variation coefficient, α is the shape parameter for the cross-sectional area distribution of C microvascular, M is the drift parameter (drift parameter), and, A is and cross-section of each vessel, the subscripts 0, 1, and 2 are each parent A parent vessel and two daughter vessels, and i is an integer of 1 and 2.

The systems and methods for quantifying the intravascular cells and / or drug delivery efficiencies provided in accordance with embodiments of the present disclosure may be used as a mathematical or simulation tool (or computerized model) of blood flow in the vascular system and to simulate simple vascular segments combining the flow information obtained from the experiment result by the in vitro analysis device with a microfluidic channel that can be substantially vivo (in the implementation is difficult as by vivo assay without quantifying the distribution or flow characteristics of cells and / or drugs in the microvessels. In particular, it can provide effective guidelines for designing customized drugs according to individual diseases, and thus it is expected to be widely used in the future.

곡선이고;
도 12c는 2개의 분지된 미세혈관에서의 약물 담체의 농도를 산출하기 위한

곡선이고;
도 13a는 α=0.8인 경우에 있어서, 모 혈관(parent vessel)로부터 2개의 혈관(daughter vessels)이 분지되는 단일 분지 부위에서의 적혈구 세포(RBCs) 및 약물 담체의 재분포(redistributions)에 대한 개략적 선도를 나타내는 도면이고;
도 13b는 2개의 분지된 미세혈관에서의 적혈구 용적율을 산출하기 위한

곡선이고;
도 13c는 2개의 분지된 미세혈관에서의 약물 담체의 농도를 산출하기 위한

곡선이고;
도 14a는 단일 분지 모델에 있어서 분지 부위에서 약물 담체의 재분포에 대한 형상 파라미터(α)의 영향을 나타내는 그래프이고;
도 14b는 단일 분지 모델에 있어서 α=0.2인 경우에 분지 부위에서 약물 담체의 재분포에 대한 드리프트 파라미터(M)의 영향을 나타내는 그래프이고;
도 15는 예시적인 미세혈관 내 전달(transport) 모델에 있어서, 혈관 직경에 따른 적혈구 용적율의 분포 및 혈액 유속을 나타내는 그래프이고;
도 16은 생체 외 실험을 통하여 측정된 형상 파라미터(α) 값을 혈액 흐름 시뮬레이션 툴에 적용하여 도출된 미세혈관 및 주변조직 내에서의 세포 및/또는 약물 담체의 전달 효율의 측정 결과를 나타내는 도면이고;
도 17a 내지 도 17c 각각은 3개의 α 값(α=0.2, α=0.5 및 α=0.8)에 대하여 수학식 5 내지 8에 의하여 산출된 미세혈관 내 약물 담체의 분포를 나타내는 그래프이고;
도 18은 미세혈관계에 있어서 α 값의 변화에 따른 약물 담체의 농도 변화를 나타내는 그래프(루트 혈관 내 약물 담체의 초기 농도는 거대순환계(macrocirculation)에서의 초기 농도와 동일한 것으로 가정함)이고; 그리고
도 19a 내지 도 19c 각각은 3개의 α 값(α=0.2, α=0.5 및 α=0.8)에 대하여 미세혈관계 내 혈관 직경 및 적혈구 용적율과 함께 약물 담체의 농도(체적 분율)를 나타내는 그래프이다. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a flow chart illustrating a series of procedures for predicting the distribution of cells and / or drug carriers in microvessels and surrounding tissues according to one embodiment of the present disclosure;
Figure 2a is a graphical representation of the effect of the intravascular flow information and microvascular mass transfer simulation tool derived from an in-vitro fluorescence detection device on a blood mixture comprising blood and a drug carrier according to an exemplary embodiment of the present disclosure FIG. 3 is a flow chart showing a series of procedures for predicting the distribution of cells and / or drug carriers in microvessels and surrounding tissues; FIG.
FIG. 2B is a view schematically showing the configuration of the fluorescence detection type in-vitro analyzing apparatus and the direction of the flow of blood mixture in the in-vitro analyzing apparatus according to an exemplary embodiment of the present disclosure; FIG.
FIGS. 3A and 3B are views showing an exemplary shape of a microfluidic channel provided in the in vitro analyzing apparatus shown in FIG. 2, respectively;
4 is a diagram illustrating, in an exemplary embodiment, a flow of a blood mixture through a microfluidic channel based on a fluorescence detection scheme in an ex vivo analyzer;
Figure 5 is a flow chart for predicting the concentration of cells and / or drug carrier in the i- th branch area using a microvessel mass transfer simulation tool in accordance with an illustrative embodiment of the present disclosure;
6 is a view showing a position and an angle of the blood vessel at the i- th minute from the entire coordinates;
Figure 7 is a diagram showing the geometric characteristics of microvessels generated by the exemplary algorithm at the first to tenth branch levels;
8 is a diagram showing a one-dimensional blood flow model at the i- th branch point;
9 is a view schematically illustrating a plasma skimming phenomenon of red blood cells at a branching site in the vascular system;
FIG. 10 is a graph illustrating the relationship between intracellular red blood cell (RBCs) and drug (s) in a generalized plasma skimming model according to the alpha value (indicating the relative distribution characteristics between red blood cells (RBCs) and drug carriers) Sectional profile of the carrier; Fig.
11A is a photograph showing a configuration of an apparatus for measuring a shape parameter (?) Using a microfluidic channel according to an embodiment of the present disclosure; And
11B shows a distribution of the fluorescence signal measured by a device having a microfluidic channel according to an embodiment of the present disclosure;
Figure 12a is a schematic representation of red blood cells (RBCs) and redistributions of drug carriers at a single branch site where daughter vessels are branched from the parent vessel in the case of alpha = 0.2. 1 is a diagram showing a schematic diagram;
FIG. 12B is a graph for calculating the hematocrit ratio in two branched microvessels

A curve;
FIG. 12C is a graph showing the concentration of the drug carrier in two branched microvessels

A curve;
13A is a schematic diagram of red blood cells (RBCs) and redistributions of drug carriers at a single branch site where daughter vessels are branched from parent vessels at a = 0.8. Fig.
13B is a graph showing the relationship between the hematocrit

A curve;
13C is a graph showing the concentration of drug carrier in two branched microvessels

A curve;
14A is a graph showing the effect of the shape parameter? On the redistribution of the drug carrier at the branch site in a single branching model;
14B is a graph showing the influence of the drift parameter ( M ) on the redistribution of the drug carrier at the branch site when? = 0.2 in a single branching model;
15 is a graph showing the distribution of hematocrit and the blood flow rate according to the blood vessel diameter, in an exemplary microvascular transport model;
FIG. 16 is a graph showing the measurement results of the delivery efficiency of cells and / or drug carriers in the microvessels and surrounding tissues derived by applying the shape parameter (?) Values measured through in vitro experiments to the blood flow simulation tool ;
17A to 17C are graphs showing the distribution of drug carriers in the microvascular system calculated by Equations 5 to 8 for three alpha values (alpha = 0.2, alpha = 0.5 and alpha = 0.8);
18 is a graph showing the change in the concentration of the drug carrier according to the change of the alpha value in the microvessel system (assuming that the initial concentration of the drug carrier in the root vessel is equal to the initial concentration in the macrocirculation); And
19A to 19C are graphs showing the concentration (volume fraction) of the drug carrier together with the blood vessel diameter and the hematocrit in the microvessel system for three alpha values (alpha = 0.2, alpha = 0.5 and alpha = 0.8).

The present invention can be all accomplished by the following description. The following description should be understood to describe preferred embodiments of the present invention, but the present invention is not necessarily limited thereto.

The accompanying drawings may be exaggeratedly expressed relative to the actual layer thickness (or height) or the ratio with respect to other layers in order to facilitate understanding, and the meaning thereof may be appropriately understood according to the concrete purpose of the related description to be described later .

The terms used in this specification can be defined as follows.

&Quot; Nano-size " or " nanoscale " may typically be defined as at least 1 nm, specifically in the range of 1 to 100 nm.

&Quot; Plasma skimming " refers generally to the phenomenon that red blood cells are naturally separated from the plasma (plasma) at the branching portion of the blood vessel in the vascular tree and the blood is divided into a relatively concentrated flow and a relatively diluted flow do.

&Quot; Hematocrit " can be understood as a volume ratio of erythrocytes in the whole blood, unless otherwise stated.

&Quot; Drug carrier " may mean any structure or means capable of loading the drug and transporting it to a particular organ, organ, tissue, etc., and may typically be nanoparticles or microparticles.

The " nanosized drug carrier " may typically be a material having a particle size in the range of about 1 to 100 nm, more typically about 10 to 50 nm.

&Quot; Fluorescence " may mean a type of luminescence generated by electromagnetic excitation for a short time. That is, fluorescence means a phenomenon that occurs when a specific substance absorbs light energy at a short wavelength and then emits light energy at a longer wavelength. Illustratively, the length of time between absorption and release is typically relatively short, e.g., about 10 ^-9 to 10 ^-8 seconds.

&Quot; Fluorescent probe " can be understood to mean any material (including dyes, molecules, compounds, etc.) that provides characteristic fluorescence in the ultraviolet-visible-near-infrared region. For example, it may refer to a probe complex-bonded with a fluorophore.

A. Overview of systems and methods for quantifying intravascular microcellular cells and / or drug delivery efficiencies

Figure 1 illustrates a series of procedures for predicting the distribution of cells and / or drug carriers in microvessels and surrounding tissues according to one embodiment of the present disclosure.

As shown above, the prediction system can be applied to an animal, specifically, a cell and / or a drug in a specific region in the human body, particularly a drug in a specific region of the human body by applying the intravascular flow information derived through the in- (Or concentration distribution) of the sample. That is, according to the present disclosure, vascular system (microvasculature) in vitro by the microfluidic device to simulate a simulation tool, and a simple blood vessel segment for the blood flow (in vitro) in vivo (in using the data obtained from the experimental results difficult to practically implement the or drug (or drug carrier) distribution or flow characteristics in the microvessels without the need for vivo experiments.

In this regard, the in vitro analyzer device comprises a microfluidic device having (i) a microfluidic channel that replicates any of the vascular segments of the vasculature, and (ii) a microfluidic device Device. At this time, the flow information may include the flow rate of the blood mixture, the hematocrit and the concentration of the drug carrier.

In the above-described flowchart, step 10 may contain blood and a drug carrier to produce a blood mixture to be introduced or injected into the microfluidic channel. In this regard, blood contains largely Red Blood Cells (RBC) and plasma (plasma).

In addition, the blood mixture may contain additional components depending on the manner in which the intravascular flow information is derived, and may contain fluorescent substances or fluorescent probes when using fluorescence detection as exemplified below. According to exemplary embodiments, such a fluorescent substance or fluorescent probe may exist in a form that is covalently or non-covalently bonded to or immobilized with a drug carrier rather than having a physically distinct single form.

In step 20, the blood mixture is injected into a microfluidic device having a microfluidic channel that simulates any of the vascular segments of the vasculature and flows. At this time, as a blood vessel segment to be simulated, an arbitrary blood vessel region can be selected without being limited to a specific part of a macro blood vessel and a micro blood vessel inside a living body. However, considering the ease of derivation or measurement of intravascular flow information, it may be advantageous to target vessels with relatively large diameter and low degree of bifurcation, such as root vessels. The width or diameter of the microfluidic channel may range, for example, from about 1 to about 100 micrometers, specifically from about 20 to about 80 micrometers, and more specifically from about 40 to about 60 micrometers, do.

According to exemplary embodiments, an exemplary blood mixture may contain about 70 to 99.99% by volume of blood, as the amount of the drug carrier in the blood mixture may be too high or too low to cause a difficulty in accurately analyzing the movement of the drug carrier. (Specifically about 80 to 99.95% by volume, more specifically about 90 to 99.9% by volume) and about 0.01 to 30% by volume (specifically about 0.05 to 20% by volume, more specifically about 0.1 to 10% .

On the other hand, the drug carrier may be a biocompatible drug carrier known in the art. According to an exemplary embodiment, such a drug carrier may have nanosize, for example a nanoparticle form having a diameter of about 50 nm or less, more specifically about 30 nm or less, more specifically about 10 nm or less .

According to an exemplary embodiment, silica-based nanoparticles, specifically, mesoporous silica nanoparticles, silica-based nanoparticles having a core-shell structure, iron oxide-based nanoparticles, gold nanoparticles, Group II -V group nanoparticles (specifically, CdTe, CdSe, etc.), and combinations thereof. In addition, in the case of organic carriers, carbon nanoparticles (e.g., carbon nanotubes, fullerene, and graphene), polymer nanoparticles (e.g., chitosan, polyethyleneimine (PEI), poly (L- (PLL), PEG? Oly (amino acid), PEG? Olyester, PEG? Ipid and Polysaccharides) and combinations thereof.

According to an exemplary embodiment, the drug carrier is typically spherical, but may exhibit various three-dimensional shapes, including without limitation. In addition, the surface of the drug carrier may be selectively hydrophilized or hydrophobically imparted to the surface of the drug carrier.

According to an exemplary embodiment, the drug carrier may exhibit electrical properties such as a cation or anion.

In addition, the drug carrier may exhibit stiffness or deformability, and in some cases cells such as erythrocytes and leukocytes may be modified, and artificial cells and / or ions using a lipid-bilayer may be used. You can also use channels.

As described above, flow information including flow rate, hematocrit, and drug carrier concentration can be measured as the blood mixture is injected into the microfluidic device and allowed to pass through the microfluidic channel. Such flow information can be used as information to be initially applied (processed) for processing by a vessel delivery simulation tool as described later.

In addition, the red blood cells (RBC), the plasma (plasma) and the drug carrier in the blood mixture exhibit, for example, a specific distribution pattern in the cross section of the microfluidic channel, specifically in the longitudinal cross section, The shape-parameter? Of the distribution-shape parameter? The shape parameter alpha is used to determine the concentration distribution of the drug carrier in one region (more specifically, the middle region) of the microfluidic channel while the blood mixture passes (flows) through the microfluidic channel simulating the vascular segment , Which can also be included in the flow information to be obtained through an in vitro analysis experiment.

Thereafter, at step 40, the flow information derived from the above-described in-vitro analyzing apparatus is applied (or substituted) to the vascular transportation simulation tool. At step 50, distribution of cells and / or drug carriers Specifically the concentration).

FIG. 2A is a flow chart illustrating a method of simulating mass transfer of microvessels and intravascular flow information derived from an in vitro analyzer of a fluorescence detection system according to an exemplary embodiment of the present disclosure, A series of processes for predicting the distribution of carriers is shown.

In this figure, step 100, step 110, step 140 and step 150 are as described in connection with Fig. However, in order to derive the intravascular flow information in step 30 of FIG. 1, the step of detecting the fluorescence characteristic due to the fluorescent substance or the fluorescent probe combined with the drug carrier of the blood mixture using the fluorescence microscope (step 120) is performed (Step 130), if the fluorescence material or the probe is used as one of the intravascular flow information together with or based thereon, the shape parameter alpha can be easily obtained through image processing.

According to an exemplary embodiment, a fluorescent substance or fluorescent probe may be present in a labeled form on the surface of the drug carrier. Examples of such fluorescent substances or fluorescent probes include umbelliferone, fluorescein, fluorescein isothiocyanate (FITC), rhodamine, TAMRA, Fluorescein, Alexa floor system (including fluorescein) including dichlorotriazinylamine fluorescein, dansyl chloride, quantum dots, phycoerythrin, and fluorecein amidite (FAM) alexa fluorine, and fluorescent materials such as cyanine including Cy3, Cy5, Cy5.5, Cy7, and indocyanine green, and one or more of them may be used. However, the present invention is not limited to the above-exemplified fluorescent substance or probe. In this regard, the fluorescent material is excited by light of a specific wavelength, and then emits light of another wavelength to emit surplus energy. Thus, a fluorescent material such as FITC emits light of a wavelength of 550 nm.

Such a fluorescent substance or probe may be present in the form of a covalent or non-covalent bond or fixed (coated) form with the drug carrier on the surface of the drug carrier, for example, through coating, doping, Can be immobilized on the drug carrier. Therefore, the distribution characteristics of the drug carrier can be confirmed and analyzed through the detection and analysis of fluorescence during in vitro experiments.

On the other hand, various fluorescence detection devices such as a confocal laser microscope, a fluorescence real microscope and the like can be used for detecting fluorescence originating from the above-mentioned fluorescent substance or fluorescence probe, and specifically, an optical imaging device, more specifically, Fluorescence microscopy can be used. The fluorescence microscope basically uses a filter and a dichroic beam splitter. The fluorescence excitation light is passed through the same objective lens for collecting the fluorescence signal for imaging, The excitation light is separated from the fluorescence by using a beam splitter which transmits or reflects light according to the wavelength. At this time, a shorter wavelength excitation light is reflected, while a longer wavelength emission light is transmitted through the splitter, and the transmitted emission light is detected. Accordingly, the fluorescence in one region of the microfluidic channel through which the blood mixture passes can be detected to confirm the distribution of the drug carrier on a cross-sectional basis, from which the shape parameter? Can be determined.

Fig. 2b schematically shows an exemplary configuration of the fluorescence detection type in-vitro analyzing apparatus and a direction of the flow of the blood mixture in the ex-vivo analyzing apparatus.

In the illustrated embodiment, an ex vivo analyzer 200 is shown with a microfluidic channel that simulates any vessel segment. A blood mixture (containing blood, a drug carrier and a fluorophore (probe) 201) is injected through the syringe pump 202 into the microfluidic channel 206 of the microfluidic device 204, And communicates with the injection port 205 of the microfluidic channel 206 via the passage 203.

The injection pressure of the syringe pump 202 is such that the flow rate of the blood mixture within the microfluidic channel 206 is maintained between about 0.1 and 10 mm / s, specifically between about 0.5 and 5 mm / s, 2 mm / s. The blood mixture 201 introduced into and flowing into the microfluidic channel 206 is discharged through the discharge port 207 and collected in the sample collection tube 208. At this time, a fluorescent microscope 209 is positioned on one region of the microfluidic channel 206 to detect the fluorescence characteristic of the blood mixture passing through the microfluidic channel 206.

In this regard. The microfluidic channel 206 may be advantageous for simulating blood vessels that are easy to test, for example, a root vessel having a large diameter in the vascular system may be simulated. And can be produced through a method known in the art.

In an exemplary embodiment, each of the inlet 205 and outlet 207 of the blood mixture 201 is formed using methods known in the art such as, for example, mechanical perforation, laser perforation, chemical etching, plasma etching, . In some cases, a substrate in which an injection port and a discharge port are integrally formed (for example, injection molded) when manufacturing a substrate for device fabrication may be used.

In certain embodiments, a microfluidic device 204 with microfluidic channels 206 may be fabricated through methods known in the art (e.g., photolithography, soft lithography, imprint lithography, etc.).

For example, a photoresist layer (for example, an epoxy-based negative electrode such as SU-8) may be formed on a substrate for a mold (specifically, glass, transparent plastic, silicon wafer or the like) by a polymer coating method such as spin coating, Photoresist) is formed, followed by a selective removal process (patterning process). Then, for example, a liquid polymer (for example, a forming material for producing PDMS) is poured into a mold using a patterned photoresist layer / substrate for a mold substrate as a template, Is removed, cooled, and then separated to form a patterned polymer layer, which can be used for device fabrication. Separately, a lower substrate corresponding to the upper substrate is manufactured by the same manufacturing method as that of the upper substrate, and two substrates (upper substrate and lower substrate) are bonded (bonded) to form fine channels A fluid device can be manufactured. In order to join (join) the upper substrate and the lower substrate, a heat fusion method in which the upper substrate and the lower substrate are fused by heat, a fusion method using ultrasonic waves, a corona discharge or a plasma bonding method may be used have.

It is preferable that the microfluidic device having a microfluidic channel (particularly, a microfluidic channel) is manufactured to have a material characteristic as close as possible to a blood vessel characteristic, for example, oxygen permeable and not toxic to cells, It may be advantageous to select from materials that can precisely tune the dimensions. Illustratively, it is possible to use polyesters (specifically polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polyimide (PI), polystyrene (PS), polycarbonate (PM), polyvinyl chloride (PVC), cyclic olefin copolymer (COC), liquid crystal polymer (LCP), polyamide (PA), polyimide (PI) (PES), polyoxymethylene (POM), polyetheretherketone (PEEK), polyethersulfone (PES), polytetrafluoroethylene (PTFE), acrylic resins, Polydimethylsiloxane (PDMS), combinations thereof, and the like can be considered. However, considering the ease of microchannel fabrication, it may be advantageous to use polydimethylsiloxane (PDMS), but not always limited thereto.

In addition, since the surface of PDMS exhibits hydrophobicity, it may be desirable to functionalize or surface modify the surface thereof with various protein coatings and linker molecules. Examples of the substance used for functionalization or surface modification include polyethylene glycol (PEG), phosphate-buffered saline (PBS-EDTA) and ethylenediaminetetraacetic acid.

3A and 3B show an exemplary shape of a microfluidic channel provided in the in vitro analyzing apparatus shown in FIG. 2, respectively.

Referring to FIG. 3A, the microfluidic channel 206a has a rectangular cross section, wherein the flow rate of the flow information can be measured based on the center plane of the microfluidic channel. However, since this cross section is different from the shape of the actual blood vessel, the actual blood vessel has a circular cross section, so that the flow characteristics in the microfluidic channel of the rectangular cross section may have a limitation in simulating actual blood vessels. For example, the shear stress acting on the red blood cells changes, affecting the build-up of pressure in the channel, which may be different from the flow profile of the cell in the circular cross-section.

In view of the above, it may be desirable to form the microfluidic channel 206b having a circular or round cross-section as shown in FIG. 3B.

According to an exemplary embodiment, a microfluidic channel having a circular or round cross-section is formed by casting a polymeric molding material (e.g., PDMS) around a mold such as a glass capillary, a stainless steel rod and a nylon thread . According to an alternative embodiment, it is possible to use a method in which a polymer material (for example, a PDMS) channel having a rectangular cross section is first formed and then deformed to have a circular cross section. For example, it is possible to make a circular shape through a sol-gel reaction of silica or through a polymerization reaction of a low molecular weight silicone oligomer. According to another embodiment, a microfluidic channel having a rectangular cross section is first prepared, and then a solution in which a silicone oligomer is dissolved in an organic solvent (for example, hexane) and a gas (for example, nitrogen gas) And then the oligomer is polymerized around the gas flow, and then the solvent is removed. In the case of such a microfluidic channel having a circular cross section, the flow characteristics such as the flow velocity can be measured based on the center plane of the microfluidic channel.

Figure 4 illustrates, in an exemplary embodiment, the flow of a blood mixture through a microfluidic channel based on a fluorescence detection scheme in an in vitro analyzer.

As shown, red blood cells (RBC) mainly flow in the core region of the microfluidic channel, and plasma (plasma) is mainly present in the vicinity of the channel wall, that is, in the cell-free layer (CFL) do. At this time, the drug carrier bound to the fluorescent substance or fluorescent probe is distributed not only in the core region but also in the cell-lean region, and different fluorescence intensities are detected by fluorescence microscope according to the distribution characteristics thereof. Therefore, the shape parameter (?) Indicating the relative distribution characteristics between the red blood cells (RBCs) and the drug carrier can be determined in consideration of the fluorescence distribution in the cross section of the region of the microfluidic channel observed by the fluorescence microscope.

In addition, flow information such as flow rate, hematocrit, and drug carrier concentration can be measured through an in vitro analyzer, and each of these flow information can be measured by analyzing image information measured by a glare microscope. For example, a fluorescence microscope is used to obtain an image file that is continuously photographed during the exposure time, and the flow rate is determined by measuring the length of the locus based on the intensity or intensity value of the fluorescently- To derive the value. At this time, the volume ratio of red blood cells is determined by counting the number of stained red blood cells on a continuous photographed image and analyzing based on the ratio of stained red blood cells and red blood cells of blood.

In the case of the parameter (α) measured through the microfluidic channel in vitro, the intensity difference between the channel center and the channel wall surface is checked from the light intensity through the fluorescence microscope similar to the analysis of the red blood cell. Specifically, when the light intensity before being injected into the microfluidic channel is set to 1, the light intensity is measured for each section (from the channel wall surface to the channel center) in the microfluidic channel, and the relative value is determined. Confirm the change in the concentration of the drug carrier between CFLs.

Thus, the flow information including the shape parameter (alpha) value can be obtained through a relatively simple in vitro experiment.

B. Microvascular Mass Transfer Simulation Tool

(1) the geometric shape of microvessels modelling

According to an illustrative embodiment, a microvascular mass transfer simulation tool can include most of the hemodynamic control from blood viscosity to plasma skimming effects into the geometric properties of three-dimensional microvessels, and a simple and cost- It is advantageous to be able to provide. Typically, the microvessel system is formed by a chain branching phenomenon from a particular point, wherein the branching angles are randomly selected within the azimuth and declination limits from the reference coordinate system. The geometric characteristics of the microvessels are then set by storing node information and vessel diameters of all vascular segments so that the blood flow in each vessel segment in the resulting microvessel system is determined using a Poisson flow analysis solution Can be calculated. In addition, the geometric characteristics of the microvessels and the model parameters for the hemodynamics can be described by a mathematical expression / empirical expression

Figure 5 is a flow chart for predicting the concentration of cells and / or drug carrier in the i- th branch area using a microvessel mass transfer simulation tool in accordance with an exemplary embodiment of the present disclosure. Hereinafter, the algorithm shown in FIG. 5 will be described. However, the present disclosure is not limited to this, and other microvessel mass transfer simulation tools may be used as long as the behavior of the cells and / or the drug carrier can be predicted by combining the flow information derived from the above- Should be understood as being available.

According to an exemplary embodiment, a mathematical algorithm is introduced to implement various microvessel geometries. The information about the geometric shape of the microvessels is the node position (x) and the vessel diameter ( d ) in each branch. The position in an individual branch may be determined by the vessel length l and the branch angles [ theta] and [ phi ]. In addition, changes in diameter and angle are included in the geometric model of microvessels to reflect the non-uniformity of the geometric characteristics of the microvessels.

- Branching rule ( bifurcation law )

In the microvessels, the i- th maternal blood vessel (x _i ) is branched into daughter vessel segments (x _2i and x _{2i +1} ), assuming that all parent vessel segments are all branched. Thus, the total number of vascular segments in double, that is, "i 2" Can be displayed. Under the above assumption, the diameter of the blood vessel can be expressed by the following equation (1).

Where y is the bifurcation exponent.

As γ increases, the total volume of microvascular features increases, and flow resistance decreases during blood transport through the capillary network. Therefore, it may be required to provide a high? Value in order to minimize the wall shear stress in the microvessels as described later.

According to Murray's law, the energy dispersion in the vascular system and the shear stress of the wall are minimized when γ = 3. This is because Murray, CD, 1926. The physiological principle of minimum work: I. The vascular system and the cost of blood volume. Proceedings of the National 295 Academy of Sciences of the United States of America 12, 207). Which is incorporated herein by reference. In this regard, the range of wall shear stress may range, for example, from about 50 to 150 dyne / cm ² .

Further, in order to obtain the asymmetric diameter between the branch vessel segments, d _2i and d _{2i +1} are determined by the following equation (2).

Here, N means a normal distribution with mean 1 and standard deviation sigma _d .

- blood vessels In diameter  Length ratio for

The branch vessel segments extend to the next branch point, and the length of the vessel segment is random due to branching uncertainty. In the illustrated algorithm, the length of the vascular segment can be determined using the length ratio ([beta]) to the diameter. The relationship between the length and the diameter can be expressed by the following equation (3).

Where beta is the length ratio to diameter.

The blood viscosity and the hematocrit ratio are independent of? Because the blood vessel length is not included in the equation concerning in-vivo viscosity law (for example, Equations 9 to 11 described later). However, the flow velocity and wall shear stress are highly related to the β value. For example, as the β value increases, the wall shear stress increases in the microvessels and the average flow velocity through the microvessels decreases. However, in the following, β = 25 can be assumed unless otherwise specified.

- Branch angle ( bifurcation angle )

및

를 갖는다. 그 다음, 위치(x _i )는 x _{i /2} , β, θ _i 및 φ _i 으로부터 산출된다.For a three-dimensional microvessel, the i- th position may be defined as l _i , θ _i, and φ _i . 6, the azimuth angle (θ _i) refers to the horizontal angle which is measured from the x- axis, and polarization angle (φ _i) is the number of which is measured at right angles from the z- axis. Azimuth angle (θ _i) and a polarization angle (φ _i) is determined by randomly select a change in the angle (△ θ and φ △), each of the upper and lower limit

And

. Then, the position (x _i ) is calculated from x _{i / 2} , β, θ _i and φ _i .

- Mathematical Algorithm for the geometric shape of microvessels

Using all of the above-described parameters and parameters, a mathematical algorithm for generating the entire microvessels can be summarized as follows.

end. Step 1

The initial vessel parameters (x ₀ , _{θ 1, φ 1, Δ θ} min, Δ θ _max, Δ φ _min, φ _max selects Δ, and d _1).

I. Step 2

{[Delta ] [theta] _i } and { [ Delta ] [ phi] _i } are randomly generated within the ranges of the following equations 4 and 5:

Where n is the total number of vessel segments.

For i = 1, the initial change in azimuth, by not branched is not formed (Δ θ ₁₎ and the initial change in the polarization angle (Δ φ ₁₎ is set to zero.

All. Step 3

To be from the formula 6 and 7 calculated θ _i and _{φ i (i = 2, ···} , n) for each basin:

는 x보다 크지 않은 가장 큰 정수를 의미한다.here,

Means the largest integer not greater than x.

la. Step 4

The position (x _i ) is determined according to the following equation (8).

In this regard, Fig. 7 is a diagram showing the geometric features of microvessels generated by the exemplary algorithm at the first to tenth branch levels. In the figure, the first, fourth, seventh and is shown the geometry of the microvasculature in the basin level 10, β = 25, γ = 3 , σ d = 0.05, Δ θ min = 0, A _{Δ θ max = π / 3,} Δ φ min = 0 and Δ φ _max = π / 3. This mathematical algorithm can determine all positions at once.

(2) microvascular blood flow

Simulation of blood flow through capillaries in complex geometric shapes of microvessels is still a difficult task in fluid mechanics, assuming that the blood flow in the individual vessel segments follows a one-dimensional model of the Poisson flow. The sum of the flow velocities in each branch is also defined as zero in the law of conservation of mass. The blood viscosity and hematocrit ratio can be expressed empirically, and the hematocrit ratio in the microvessel system can be optimized by using the drift parameters (drift parameters are described separately below).

- Blood viscosity

Blood viscosity corresponds to a non-linear parameter for quantifying blood flow in individual vessel segments. In this regard, in vitro studies and in vivo viscosity models have been presented as a function of tube diameter and hematocrit volume (Pries, AR, Secomb, TW, Gaehtgens, P., 1996. Biophysical aspects of blood flow in the 32, 654-667), which is incorporated herein by reference. Typically, in vivo viscosities are known to be higher than in vitro viscosities, and it is known that blood in the geometric shape of vascular vessels in vivo undergoes a higher resistance to in vitro tube channels. In the simulation according to this embodiment, an in-vivo viscosity model is applied to the blood flow simulation. As such, the viscosity equation for an in vivo model can be expressed by the following equations (9) to (11).

Where μ _p is the plasma viscosity, H _D is the emission hemocytometer volume, and d is the vessel diameter (μm). For the numerical experiments, μ _p is given by Yang et al. (Yang, J., Wang, Y., 2013. Design of vascular networks: A mathematical model approach. Int. J. Numer. Meth. Biomed. Engng. ), can be assumed to 9 · 10 ^-6 mmHg · s as set forth in 515-529), this document is herewith included by reference in the present description.

- flow rate

The flow rate (Q _i ) of blood in each vessel segment can be calculated by the Poisson flow model and the in vivo viscosity according to the following equation (12).

Here, Δ P _i refers to the pressure difference between both ends of the blood vessel segment.

In this regard, Figure 8 shows a one-dimensional blood flow model at the i- th branch point. As shown in the figure, three vessel segments ( V _i , V _2i , and V _{2i +1} ) are connected at the i- th branch point, and the mass flow rate can be determined by the following equation have.

As described later, the inflow and outflow pressures of the phosphorus-microcavity can be set to 60 mmHg and 10 mmHg, respectively.

- Wall shear stress ( wall shear stress ; WSS )

The wall shear stress [tau] can be defined by the following equation (14).

Where v is the blood flow velocity, y is the distance from the outer wall of the blood vessel, and [mu] is the blood viscosity. Using the aforementioned equations (12) and (14) and Q = v · A (where A is the cross-sectional area of the blood vessel segment), the wall shear stress (WSS) of the i- th blood vessel segment can be expressed by the following equation .

- red blood cells Floor area ratio

Hematocrit can be defined in two ways as in the tube (tube) hematocrit (H _t) and emission (discharge) hematocrit (H _D). In this regard, H _t is the volume fraction of red blood cells in the blood vessel segment, and H _D is the volume fraction of red blood cells in the whole blood being discharged. The relationship between H _t and H _D is described in Pries et al. (Pries, AR, Secomb, TW, Gaehtgens, P., Gross, JF, 1990. Blood flow in microvascular networks, 4), 826-834, which is incorporated herein by reference.

Here, d is the tube diameter (占 퐉).

Unless otherwise stated herein, all erythrocyte volume ratios mean mean H _D.

- plasma Skimming

FIG. 9 is a view schematically illustrating a plasma skimming phenomenon of erythrocytes at a branching site in the vascular system.

In maternal blood vessels, blood flow is determined by blood viscosity, hematocrit, and pressure drop. After branching from the parent vessel, the blood flow characteristics in the subsequent branch vessel change due to the decrease in vessel diameter, resulting in application of the plasma skimming phenomenon. At this time, the flow rate in the daughter vessel can be relatively easily calculated by the law of conservation of mass using the diameter of the branch vessel. In addition, in the blood vessels, red blood cells are enriched in the red blood cell core region of the microvessel, in which a cell-free layer (CFL) of a certain thickness is formed.

Then, thinner branch vessels contain fewer red blood cells and more plasma, while thicker branch vessels contain more red blood cells and less plasma. Referring to FIG. 9, a thicker blood vessel has a higher erythrocyte volume ratio than a mother blood vessel, and a thinner blood vessel has a lower erythrocyte volume ratio.

As described above, according to the plasma skimming phenomenon, the hematocrit level is changed in the branch vein due to the vascular core in which the red blood cells are concentrated in the microvascular migration and the cell-lean layer near the blood vessel wall, Changes the distribution of total red blood cells and blood flow characteristics in the blood vessels.

In this regard, the distribution of red blood cells in the vascular system and blood flow characteristics according to erythrocyte plasma skimming as parent blood vessels are branched can be expressed by the following equations (17) to (19).

는 플라즈마 스키밍에 의한 적혈구 용적율 변화 계수(coefficient)이고, Q _i 는 i번째 혈관 세그먼트에서의 유속이며, A _i 는 i번째 혈관 세그먼트의 혈관의 단면적을 의미한다.Here, H _i is the hematocrit of the i- th blood vessel segment,

Is the hematocrit variation coefficient (coefficient) due to plasma skimming, and the flow rate in Q _i is the i-th vessel segments, A _i refers to the i-th cross-sectional area of the blood vessel of the blood vessel segment.

The above equations are described in detail in Gould, IG, Linniger, AA, 2015. Hematocrit distribution and tissue oxygenation in large microcirculatory networks, Microcirculation 22 (1), 1-18, It is included as a reference of contents.

In an exemplary embodiment, when the parent blood vessel is divided into two blood vessels, Equations 17 to 19 can be re-expressed as Equations 17 'to 19' below.

Here, subscripts 0, 1 and 2 denote parent vessels and two daughter vessels, respectively, and Δ H denotes a change in the hematocrit by the basin.

In this model, the blood flow must meet the conservation law at the branch site, specifically the flow-in and flow-out must be the same to meet the mass balance. In the mass conservation equation, the preserved value is volumetric flow, while the hematocrit ratio is not preserved. The flow and hematocrit in the maternal blood vessel and the outflow in the final branch vessel are known values, and the hematocrit to the branch vessel can be determined using these values. Unlike mass conservation, hematocrit levels are not the same in each of the branch vessels (because the hematocrit is based on the ratio of the red blood cell volume to the total blood volume in the vessel).

)로 기재할 수 있다. 따라서, 적혈구 상(phase)의 체적 유속 보존 방정식은 혈관 분지에 관한 한, 수학식 19'에 기재된 바와 같이, 플라즈마 스키밍에 의한 적혈구 용적율 변화 계수 및 조정된 적혈구 용적율 값으로 대체하여 기재할 수 있다.As described above, since the branch vessel having a small radius accommodates more plasma than the red blood cells, the volume flow fraction of the erythrocyte phase in the branch vessel can be expressed by the volume fraction H ( H ₀ ) minus the depletion term. However, when a reduction term is included, a high degree of freedom is introduced since its value varies with individual branch vessels. In order to lower the degree of freedom, the fraction of the branched red blood cell phase is calculated from the adjusted hematocrit ratio ( H ^* ) as shown in Equation 17 'and the hematocrit ratio change coefficient

). Therefore, the volume flow rate conservation equation of the erythrocyte phase can be described by replacing the hematocrit ratio change coefficient and the adjusted hematocrit ratio by plasma skimming with respect to the blood vessel branch as described in Equation 19 '.

는 모 혈관의 단면적(A ₀ )과 2개의 분지된 혈관의 단면적(A ₁ 및 A ₂ )의 비(ratio) 및 드리프트 파라미터(M)에 의하여 표시될 수 있다. On the other hand, as shown in Equation (18 '), the hematocrit ratio change coefficient

Can be represented by the ratio of the cross-sectional area ( A ₀ ) of the parent blood vessel to the cross-sectional areas ( A ₁ and A ₂ ) of the two branched blood vessels and the drift parameter ( M ).

)는 모 혈관 및 분지 혈관의 면적 사이의 비율에 의존하는데, 이는 분지 혈관 내 플라즈마의 량이 혈관의 사이즈에 따라 변화하기 때문이다(더 작은 혈관 사이즈에서는 더 많은 량의 플라즈마가 존재함).As described above, the hematocrit ratio change coefficient

) Depends on the ratio between the area of the parent vessel and the branch vessel because the amount of plasma in the branch vessel varies with the size of the vessel (there is a larger amount of plasma in the smaller vessel size).

)는 1에 접근하게 되고, 이는 플라즈마 스키밍이 덜 일어남을 의미한다. 드리프트 파라미터(M)가 무한대로 클 경우에는 모든 혈관 가지(branch)에서 동일한 농도를 갖게 된다.In addition, the drift parameter ( M ) is also an important consideration in the calculation process because it represents the force between the vessel wall and the red blood cell. When the M value exceeds 1, plasma and red blood cells are less separated and tend to exist in larger blood vessels with good mixing. As such, the drift parameter ( M ) is inversely proportional to the effect of skimming on the hematocrit. That is, as the drift parameter ( M ) increases, the hematocrit

) Approaches 1, which means less plasma skimming occurs. If the drift parameter ( M ) is infinitely large, it will have the same concentration in all vascular branches.

As described above, based on the drift parameter M , the plasma skimming can be increased or decreased, and in the case of an in vivo microvascular network, the drift parameter M can be, for example, about 5.25. The drift parameter ( M ) value is described in detail in Gould et al., Supra.

)는 모 혈관으로부터 분리되는 2개의 분지 혈관의 사이즈 차이를 설명할 수 있다. Since the consumption of oxygen in tissue is a function of the adjusted emission hematocrit ( H ^* ), it is necessary to determine the H ^* value. At this time, the hematocrit ratio change coefficient by plasma skimming

) Can explain the difference in size of two branch vessels separated from the parent blood vessel.

)와 H ^* 의 곱에 의하여 적혈구 용적율 값을 나타낼 수 있다. 개별 혈관 내 체적 유속이 정해지고 플라즈마 스키밍에 의한 적혈구 용적율 변화 계수(

)가 산출된 것으로 가정할 때(즉, 체적 유속(Q), 모 혈관에서의 적혈구 용적율 값(H ₀ ) 및 플라즈마 스키밍에 의한 적혈구 용적율 변화 계수(

)는 이미 알려지거나 정해져 있는 경우), 수학식 19'에서 유일하게 특정되지 않은 값은 배출 적혈구 용적율이다. 따라서, 수학식 3은 조정된 적혈구 용적율을 구하기 위하여 하기 수학식 19''와 같이 재배열될 수 있고, 조정된 적혈구 용적율 값(H ^* )은 분지 혈관의 적혈구 용적율 값을 산출하는데 사용될 수 있다.As shown in Equation (19), each blood vessel has a hematocrit ratio change coefficient

) And H ^* can be used to represent the hematocrit ratio. The volumetric flow rate in individual vessels was determined and the change coefficient of hematocrit ratio by plasma skimming

) (I.e., the volume flow rate ( Q ), the hematocrit ratio ( H ₀ ) value in the mother blood vessel, and the hematocrit ratio change coefficient

) Is already known or defined), a value not uniquely specified in Equation 19 'is the emission hematocrit. Accordingly, Equation 3 can be rearranged as shown in Equation 19 " to determine the adjusted hematocrit, and the adjusted hematocrit value H ^* can be used to calculate the hematocrit value of the branch vessel.

로 나타낼 수 있다. Thus, the hematocrit ratio value for each of the branch vessels is

.

) 또는 단면적 비의 합은 1이 된다. 이러한 단일 분지 모델을 이용하여 배출 적혈구 용적율 및 후속적으로 개별 분지 혈관의 적혈구 용적율이 전이(transition) 과정(큰 혈관으로부터 작은 혈관으로 또는 작은 혈관으로부터 큰 혈관으로 전이) 중 각각의 단계에서 결정될 수 있다. In a single branch model, the individual branch intravascular volume flow can be assumed to be different from each other, but its sum is equal to the volume flow of the parent vessel. In a more realistic case, its volume flow also changes as the diameter (or cross-sectional area) of the branch vessel changes. Also, the hematocrit ratio change coefficient

) Or the sum of the cross sectional area ratios is 1. Using this single branching model, the emission hematocrit and subsequently the hematocrit of individual branch vessels can be determined at each stage of the transition process (from large to small vessels or from small to large vessels) .

는 동일하므로 2개의 분지 혈관의 적혈구 용적율 값은 모 혈관의 적혈구 용적율 값과 같을 것이다. 그러나, 대부분의 경우에 있어서 2개의 분지 혈관은 상이한 직경을 갖고 있다. 만약 2개의 분지 혈관의 직경에 큰 차이가 있다면, 보다 두꺼운 분지 혈관이 높은

값을 갖는 반면, 보다 얇은 분지 혈관은 낮은

값을 갖게 된다. 다만,

의 절대 값은 물리적 의미를 갖는 것은 아니며, 2개의 분지 혈관의

값 사이의 상대적 차이가 분지 혈관의 적혈구 용적율에 영향을 미치는 것임을 주목할 필요가 있다. In Equations (17 ') - (19'), if two branch vessels have the same blood vessel diameter, it is possible to determine the hematocrit

The hematocrit ratio of the two branch vessels will be equal to the hematocrit ratio of the parent blood vessel. However, in most cases, the two branch vessels have different diameters. If there is a large difference in the diameter of the two branch vessels, the thicker branch veins are higher

While the thinner branch vessels are low

Value. but,

Is not a physical value, and the absolute value of two branchial vessels

It should be noted that the relative difference between the values has an effect on the hematocrit of the branch vessels.

- Computational algorithm for blood flow at microvascular level

In Fig. 5, the algorithm from generation of microvessels to simulation (simulation) of blood transfer has been described above. That is, the blood flow in the microvessels can be calculated by Equations (9) to (13), and the blood flow value is again calculated in consideration of the plasma skimming effect. In this regard, the circulation loop can be repeated until the hematocrit ratio converges to an acceptable level of ε = 10 ^-6 or less.

According to exemplary embodiments, several cases can be envisaged under various morphological and rheological conditions to test the performance of the phosphorylsilicone microvessel system. Exemplary parameters in the root vessel may be d ₁ = 60 μm, x ₀ = (0, 0, 0), θ ₁ = 0, and φ ₁ = π. At this time, the unit of length is 탆. In addition, it may be determined by using the case of the blood vessel branches from a route segment blood _{vessel, θ 2 = π / 2,} θ 3 = -π / 2, φ 2 = 7π / 8 , and φ ₃ = 7π / 8. In this regard, the microvessel model described above has a limitation of the branch angle ([Delta ] [theta] _min , Θ _max Δ, Δ φ _min, φ _max, and Δ), so randomly produce a fine blood vessel structure in the shape of the microvessels can vary for each attempt.

C. Cells and / or Drugs On the carrier  Generalized for plasma Skimming  Introduction of models

Hereinafter, a method of predicting the concentration of cells and / or a drug carrier in a specific position (i.e., the i- th blood vessel segment) by applying flow information of a blood mixture measured from an in vitro analyzer to a blood vessel delivery simulation tool Will be described in detail. It should be understood, however, that the vessel delivery simulation tool used in FIG. 5 is illustrative and that when flow information derived by the in vitro analyzer can be applied to a generalized plasma skimming model described below, other vessel delivery simulation tools It should be understood that it can be utilized.

The change in hematocrit as a result of the plasma skimming described above corresponds to a special case of mass transport at the branching site. Even if the drug carrier or any cell exhibits different distribution characteristics from the red blood cells, it is necessary to examine whether it can be mathematically modeled using the plasma skimming phenomenon of blood.

On the contrary, in one embodiment of the present disclosure, a method for a generalized plasma skimming model is presented by reflecting the shape parameters as shown in the following equations (20) to (23).

은 농도 변화 계수이고, α는 미세혈관 내 C의 단면적 분포에 대한 형상 파라미터이고, M은 드리프트 파라미터(drift parameter)이고, A는 각각의 혈관의 단면적이고, 아래 첨자 0, 1 및 2는 각각 모 혈관(parent vessel) 및 2개의 분지 혈관(daughter vessels)을 지시하며, 그리고 i는 1 및 2의 정수이다.Where C is the concentration of the cell or drug carrier, Q is the flow rate,

Is the concentration variation coefficient, α is the shape parameter for the cross-sectional area distribution of C microvascular, M is the drift parameter (drift parameter), and, A is and cross-section of each vessel, the subscripts 0, 1, and 2 are each parent A parent vessel and two daughter vessels, and i is an integer of 1 and 2.

In this regard, in a generalized plasma skimming model presented in accordance with the present disclosure, cross-sectional distributions of RBCs (RBCs) and drug carriers according to shape parameters (α) can be illustrated as in FIG.

Referring to the figure, when the shape parameter (alpha) is 0, since all the drug carriers exist in the core region of the red blood cells, the same model as the plasma skimming for the blood (red blood cells) described above can be applied . On the other hand, when the shape parameter (?) Is 1, all the drug carriers exist in the cell-lean layer (CFL) region, and all drug carriers are present in the CFL region. Therefore, Distributed.

In most cases, the shape parameter (α) has a value between 0 and 1. The closer to 0, the more likely it is in the core region of red blood cells, and the closer to 1 the tendency to exist in the cell-lean layer region. Also, the larger the particle is likely to be in the cell-lean layer region, while the smaller the particle is in the core region, the particle size can be proportional to the shape parameter ([alpha]).

Considering the above points, the shape parameter (?) Indicates the degree of relative distribution between the red blood cells and the drug carrier, and as the shape parameter (?) Increases, the distribution of the drug carrier shifts toward the cell- And serves as an indicator for quantifying the transfer efficiency within the capillary bed. For the sake of simplicity of the predictive model, it can be assumed that the drug carrier is uniformly distributed in each of the erythrocyte cell core region and the cell lean layer region, and the shape parameter? Represents the relative level of the drug carrier.

D. Simulation of mass transfer of microvessels Tools and  Generalized plasma Skimming  Combination of models coupling )

The generalized plasma skimming model according to equations (20) to (23) described above can be easily applied at branching, but it is not an easy task to predict the distribution of cells and / or drug carriers in the entire microvessels. Considering the individual erythrocyte and drug carrier in a microvascular network with thousands of vascular segments, it takes a long time to obtain the simulation result, and performing the in vivo experiment also has a limitation in specifying the accurate distribution characteristic do.

및 C ^* _i 를 산출함으로써 C ^* _i , 즉 i번째 혈관 세그먼트에서의 약물 담체의 농도를 결정할 수 있다.Advantages of the present disclosure include flow information, particularly shape parameters (α) values, obtained through experiments using the mass transfer simulation tool of the vascular system and the in vitro analyzer as described above, using the generalized plasma skimming Model, it is possible to effectively solve the above-described technical difficulties. That is, as shown in FIG. 5, an optimized hematocrit ratio distribution is obtained from a microvessel mass transfer simulation tool, and an experimentally derived shape parameter (?) Value is substituted into a generalized plasma skimming model

And C ^* _i to determine the concentration of the drug carrier in C ^* _i , i- th vessel segment.

Hereinafter, preferred embodiments of the present invention will be described in order to facilitate understanding of the present invention. However, the present invention is not limited thereto.

Example

(1) Production of blood mixture and derivation of flow information from in vitro analysis experiments

The preparation of the blood mixture is roughly composed of three steps. Specifically, blood is collected from a mouse, the mixture blood is prepared by staining red blood cells to measure the flow rate of the blood, and And mixing the drug carrier and the blood to prepare a blood mixture.

In order to collect blood from rats, rats of 8 to 10 weeks of age were used, and anesthetics were mixed with zolethyl and rumpun. The anesthetics were used to anesthetize the abdominal cavity of rats. After anesthetized rats were opened, the diaphragm was removed and blood was collected from the ventricles of the heart of the rats. 4 to 7 IU of heparin was added to the collected blood to prevent aggregation of the blood in the subsequent experiment.

When measuring the flow rate of blood, it is necessary to collect blood and stain only red blood cells. To this end, the process of collecting blood from the rats is preceded. Therefore, only the red blood cells were separated from the whole blood by using a centrifuge. At this time, the centrifuge was stopped in a break-free mode after maintaining the temperature of the centrifuge at 18 to 20 DEG C and 1400 rpm for 10 minutes.

The collected blood was separated into plasma and red blood cells, and then plasma was removed. Red blood cells were washed again with PBS-EDTA (3 times volume ratio) with phosphate buffered saline (ethylenediaminetetraacetic acid). This procedure was repeated three times to obtain purified erythrocyte cells. To attach the fluorescent material DiI (D282, molecular probe, lipophilic tracer, 100mg, Ex. 549nm, Em. 565nm) to red blood cells, 10ml of PBS (Phosphate buffered saline) Lt; / RTI >

Thereafter, a washing procedure was carried out to obtain fluorescently adhered red blood cells. The centrifuge was stopped in a brake-free mode after being maintained at a centrifuge temperature of 18 to 20 ° C and for 4 minutes at 1400 rpm, PBS was used. A total of 2 repetitions were performed to obtain purified fluorescently adhered red blood cells.

PBS was diluted in the same volume ratio as the red blood cells to which the fluorescence was attached, thereby maintaining the same hematocrit as the whole blood. Fluorescent blood and whole blood were diluted at a volume ratio of 1: 100 to prepare mixture blood, which was flowed into the microfluidic channel to measure the flow rate.

In this experiment, particles attached with Cy 5.5 to 10 nm nanoparticles as a drug carrier were diluted with PBS at a concentration of 1 mg / ml in a volume ratio of 1: 100.

The microfluidic channels were fabricated such that the vertical cross section of the channel was circular. In this embodiment, a single channel having a circular cross-sectional area of 100 μm was fabricated. SUS (stainless) wire having a diameter of 100 μm was used for this purpose. A jig capable of supporting the SUS wire was prepared, and a PDMS dilution solution in which the wire was fixed and the PDMS and the curing agent were diluted with a volume ratio of 10: 1 was applied to the jig. Thereafter, the jig and the SUS wire were separated from the cured PDMS after curing at 80 DEG C for 120 minutes. An inlet and an outlet for connecting the tubing for blood injection are formed at both ends of the PDMS mold manufactured in this manner, and a slide glass is attached to the lower end of the PDMS mold by an air plasma to form a vertical A microfluidic channel with a circular cross section was fabricated.

In the case of the shape parameter (alpha) value, as shown in FIGS. 11A and 11B, blood was flown through the microfluidic channel after the fluorescence microscope was installed. Fluorescence signals were measured in real- The relative size of the signal was calculated and predicted.

(2) cells and / or drugs Carrier  Analysis of distribution characteristics

As illustrated in FIG. 5, flow information from the above-described in vitro analyzer was applied to a mass transfer simulation tool of a blood vessel to evaluate cell and / or drug carrier distribution characteristics.

In this regard, FIG. 12A shows a schematic diagram of the redistribution of red blood cells and drug carrier at a single branch site where two blood vessels are branched from the parent blood vessel in the case of? = 0.2. According to the figure, the diameters of the parent blood vessel and the two branch blood vessels are 40 mu m, 33 mu m, and 30.38 mu m, respectively. The flow rates of the three microvessels are 0.01 mm ³ / s, 0.007 mm ³ / s, and 0.003 mm ³ / s, respectively. In maternal blood vessels, the hematocrit ( H ₀ ) and the drug carrier concentration ( C ₀ ) correspond to 45% and 1% of the total blood volume. In microinvasive transmission, the plasma skimming phenomenon increases the concentration of red blood cells in the larger branch vessels, while it decreases in smaller vessels. The change in hematocrit in the two branch vessels was calculated by the following equations (17 ') - (19'). As described above, the drift parameter ( M ) was fixed at 5.25.

곡선이다(α=0). 주어진 조건 하에서, 적혈구 용적율은 도 11b에 나타낸 곡선에 기초하여 변화한다. 보다 큰 분지 혈관 내 적혈구 용적율은 45.56%로 증가하는 반면, 보다 작은 분지 혈관 내 적혈구 용적율은 44.15%로 감소한다. 단일 분지에 있어서, 2개의 분지 혈관 내에서의 약물 담체의 농도 변화는 수학식 20 내지 23에 의하여 예측되었다. 도 10과 관련하여 설명한 바와 같이, α=0.2에서 약물 담체는 적혈구 세포 코어 영역에 농축되어 있다. 따라서, 약물 담체의 농도 변화는 혈액의 적혈구 용적율과 동일한 경향을 나타내는 것으로 판단된다.FIG. 12B is a graph for calculating the hematocrit ratio in two branched microvessels

(A = 0). Under given conditions, the hematocrit ratio changes based on the curve shown in FIG. 11B. The greater basal vascular erythrocyte volume rises to 45.56%, while the smaller basal vascular hematocrit decreases to 44.15%. In a single branch, the change in the concentration of the drug carrier in two branch vessels was predicted by equations (20) to (23). As described in connection with FIG. 10, at alpha = 0.2, the drug carrier is concentrated in the red blood cell core region. Therefore, it is judged that the concentration change of the drug carrier shows the same tendency as the hematocrit ratio of the blood.

곡선이다(α=0.2). 도 12a를 참고하면, 보다 큰 분지 혈관의 농도(C ₁ )는 1.01%로 증가한 반면, 보다 작은 혈관의 농도(C ₂ )는 0.98%로 감소하였다. 이처럼, 농도 변화는 예상되는 바와 같이 적혈구 용적율 변화의 경향을 따른다. FIG. 12C is a graph showing the concentration of the drug carrier in two branched microvessels

Curve (α = 0.2). Referring to FIG. 12A, the larger branch vessel concentration ( C ₁ ) increased to 1.01%, while the smaller vessel concentration ( C ₂ ) decreased to 0.98%. Thus, the concentration change follows the trend of the change in the hematocrit as expected.

Considering the results according to Figs. 12A to 12C as a whole, the drug carrier is present in the red blood cell core region of the mother blood vessel at the low shape parameter (alpha) value, and the red blood cell and the drug carrier after branching are present in two branch veins Redistribution.

On the other hand, FIG. 13A shows a schematic diagram of redistribution of red blood cells and drug carrier at a single branch site where two blood vessels are branched from the parent blood vessel when? = 0.8. When α = 0.8, the initial concentration of the drug carrier is low in the red blood cell core region, while it is high in the cell-lean layer region. This means that the drug carrier easily migrates from the red blood cell core region to the cell-lean layer region. Then, due to the plasma skimming phenomenon at the branch site, the drug carrier accumulates in smaller branch vessels. As a result, the concentration of the drug carrier in the larger branch vessel decreases while it increases in the smaller branch vessels.

곡선이고(α=0), 도 13c는 2개의 분지된 미세혈관에서의 약물 담체의 농도를 산출하기 위한

곡선이다(α=0.8).13B is a graph showing the relationship between the hematocrit

(A = 0), and Fig. 13C is a graph showing the concentration of the drug carrier in two branched microvessels

Curve (α = 0.8).

는 직경 변화(A _i /A ₀ )에 비례한다. 이와 달리, 더 큰 분지 혈관 내에서 약물 담체의 농도 변화는 직경 변화(A _i /A ₀ )에 반비례한다. 더 큰 분지 혈관 내에서의 약물 담체의 농도(C ₁ )는 C ₀ =0.1%인 것과 비교하면 0.93%로 감소한다. 또한, 보다 작은 분지 혈관 내에서 약물 담체의 농도(C ₂ )는 1.14%로 증가한다.As shown in the figure,

Is proportional to the diameter change ( A _i / A ₀ ). Conversely, the change in the concentration of the drug carrier in the larger branch vessel is inversely proportional to the change in diameter ( A _i / A ₀ ). The concentration ( C ₁ ) of the drug carrier in the larger branch vein is reduced to 0.93% as compared to C ₀ = 0.1%. Also, the concentration of drug carrier ( C ₂ ) in the smaller branch vessel increases to 1.14%.

13A to 13C, it can be seen that the drug carrier has a tendency to remain in the cell-lean layer region of the parent blood vessel at a high shape parameter value, and after branching, the red blood cell and the drug carrier are separated into two branch blood vessels It can be seen that it is redistributed within.

(3) The shape parameters (?) And Drift  parameter( M )

With respect to the single branching model, the effect of the shape parameter (?) On the redistribution of the drug carrier at the branch site is shown in Fig. 14a. In the graph, tests were performed on three shape parameter values (0.2, 0.5, and 0.8).

As shown, the concentration change at? = 0.5 for two branch vessels is zero, which means that the drug carrier is uniformly distributed in the microvessels. In the case of α = 0.2, the concentration of the drug carrier increased by 2% in the larger branch vessel but decreased by 5% in the smaller branch vessel. On the other hand, when α = 0.8, the drug carrier concentration decreased by 7% in the larger branch vessels but increased by 14% in the smaller branch vessels.

14B is a graph showing the influence of the drift parameter ( M ) on the redistribution of the drug carrier at the branch site when? = 0.2 in the single branch model. In the graph, a test was performed on three drift parameter ( M ) values (3, 5.25 and 8).

When the drift parameter ( M ) is low, the concentration of the drug carrier in the branch vessel is large. On the other hand, when the M value is high, the red blood cell and the plasma are well mixed. That is, in the case of M = 3 or low M , it can be seen that the separated erythrocyte core region and the cell-lean layer region changed the distribution of the drug carrier. On the other hand, when M = 8, well-mixed blood stabilizes the distribution of the drug carrier.

(4) Intravascular drug Carrier plasma Skimming  effect

As described above, a generalized plasma skimming model for red blood cells and drug carriers is applied to predict its distribution within a microvascular network (not a single branch). For example, from a root vessel of approximately 60 [mu] m diameter, the vascular segment is branched 10 times until [beta] is 25 and the diameter is reduced to 10 [mu] m or less. As a boundary condition, a pressure drop of 50 mmHg occurred between the inflow root vessel and the exit capillary end. In order to calculate the hematocrit ratio distribution, the drift parameter ( M ) was fixed at 5.25. The initial hematocrit in the root vessel was 0.45,

 FIG. 15 is a graph showing the distribution of hematocrit and the blood flow rate according to the diameter of blood vessels by applying a modeling tool (model) for mass transfer of the micro blood vessels illustrated in FIG.

According to the figure, unlike the initial erythrocyte volume rate in the root vessels, the hematocrit was significantly changed due to plasma skimming. The hematocrit ratio ranged from 0.35 to 0.5 at the capillary end. In addition, the hematocrit and the in vivo ( in Based on the vivo viscosity law, the blood flow is calculated and plotted along the diameter, and the volumetric flow rate is proportional to the vessel diameter.

For blood transfer in microvessels, the distribution of the drug carrier can be predicted by equations (20) to (23). The initial volume fraction of the drug carrier was 0.01 and the three shape parameter values (0.2, 0.5, and 0.8, respectively) were combined with a mass transfer simulation tool (computational model) of microvessels as shown in Fig. 16, And the delivery efficiency of cells and / or drug carriers in the surrounding tissues. According to this figure, when the shape parameter (alpha) value is low (alpha = 0.2), the drug carrier is mainly located in the red blood cell core region of the blood vessel, so that the distribution of the drug carrier observed outside the blood vessel low. On the other hand, when the shape parameter (alpha) value is high (alpha = 0.8), the majority of the drug carrier is distributed in the cell-lean layer region, resulting in a relatively high distribution of drug carriers observed outside the blood vessel .

17A to 17C show the distribution of the drug carriers in the microvascular system calculated by the equations (20) to (23) for three shape parameter values (alpha = 0.2, alpha = 0.5 and alpha = 0.8) Graph.

As shown, when the shape parameter (alpha) value is small or more and the drug carrier is distributed in the red blood cell core region, the drug carrier is distributed in the capillary system with small deviation. On the other hand, when the shape parameter (?) Value is large, or when more drug carriers are present in the cell-lean layer region, the drug carriers have accumulated in the capillary system with large deviations (specifically 0.007 to 0.017). From the above simulation results, it is expected that a large amount of drug carrier accumulated in the cell-lean layer region of the root vessel of a large size can rapidly move to the capillary end through the plasma skimming phenomenon of blood. In order to quantitatively evaluate the average accumulation degree of the drug carrier in the capillary system, the average volume fraction can be defined by the following equation (24).

는 약물 담체의 평균 체적 분율이고, n _cap 은 직경이 10 ㎛ 미만인 미세혈관의 총 개수이다. 체적 분율의 상대적 편차는

로서, 여기서 C ₀ 는 약물 담체의 초기 체적 분율이다. 상기 예에서 C ₀ 는 0.01이다. here,

Is the average volume fraction of the drug carrier, and n _cap is the total number of microvessels having a diameter of less than 10 [mu] m. The relative deviation of the volume fraction

, Where C ₀ is the initial volume fraction of the drug carrier. In the above example, C ₀ is 0.01.

18 is a graph showing the change in the concentration of the drug carrier according to the change of the shape parameter (?) Value in the microvessel system. At this time, it is assumed that the shape parameter (alpha) value varies from 0.2 to 0.8, and that the initial concentration of the drug carrier in the root vessel is equal to the initial concentration in the macrocirculation system. According to the graph, it can be seen that as the shape parameter (α) value increases, the average accumulation rate of the drug carrier in the capillary system increases linearly to 10% of the initial volume fraction.

Each of Figures 19A-19C shows the concentration of the drug carrier with the vessel diameter and hematocrit in the microvessel system for three shape parameter values (alpha = 0.2, alpha = 0.5 and alpha = 0.8).

As shown in the graph, the redistribution characteristics of the drug carrier in the microvascular network with respect to the hematocrit and the diameter are shown. At this time, the volume fraction of the drug carrier hardly changed at? = 0.2. However, as shown in Fig. 19C, when α = 0.8, the hematocrit was high, and the volume fraction of the drug carrier in the small diameter blood vessels increased to a significant level. Thus, it can be seen that the concentration of the drug carrier in the microvessels varies significantly due to the plasma skimming phenomenon of the blood.

First, in the case of a single branch, the redistribution of red blood cells and drug carriers was calculated from two shape parameter values. Specifically, when the value of the parameter (alpha) is 0.2, the drug carrier is concentrated in the red blood cell core region, while when the value of the parameter (alpha) is 0.8, it is concentrated in the cell-lean layer region. Next, a generalized plasma skimming model is applied to predict the drug carrier concentration in microvessels. In addition, redistribution of the drug carrier is related to the hematocrit and the cross-sectional distribution thereof in the entire microvessels.

Thus, given the specific parameters of the microvascular environment for the target site (specifically, the target disease site), this simulation, specifically by selecting the cross-sectional distribution of the drug carrier referred to as the shape parameter alpha, Can be applied as a kind of guideline in the design of. This guide function will be described in more detail as follows.

Although it is confirmed through experiments that the drug delivery efficiency is closely related to the microvascular environment, it is difficult to design a drug carrier targeting a specific microenvironment. In contrast, in the present disclosure, a predictive tool capable of evaluating the delivery efficiency of a drug carrier can be implemented by combining a microvascular mass transfer simulation tool with a generalized plasma skimming model.

In the above-described simulation test, the shape parameter? Can serve as an index for predicting whether the drug carrier accumulates rapidly in the capillary blood vessel system. Referring to the result plotted in FIG. 18, it can be confirmed that the concentration of the drug carrier is decreased as compared with that of the macrocyclic system when the value of the parameter (alpha) is less than 0.3 (i.e., when the drug carrier is transported through the microvascular or capillary blood vessels It is not easy to do). On the other hand, as the value of the parameter (alpha) increases from 0.3, the drug carrier can easily move through the microvascular or capillary blood vessels in the vascular system. Therefore, it is possible to provide a guideline for increasing the accumulation amount in the capillary system by the shape parameter? Of the drug carrier. In the above example, the value of the shape parameter (alpha) to be the index is 0.3.

It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (22)

A method for quantifying the delivery efficiency of cells and / or drugs in microvessels and surrounding tissues,
a) passing a blood mixture comprising blood and a drug carrier into a microfluidic channel of a microfluidic device that replicates any of the vascular segments of the vasculature;
b) analyzing the flow behavior of the blood mixture passing through the microfluidic channel in step a) through an in vitro analyzer equipped with a detection device to obtain intravascular flow information to be simulated, wherein Intravascular flow information includes flow rate, hematocrit and concentration of drug carrier; And
c) simulating a mass transfer of a microvessel; and estimating the concentration distribution of cells and / or drug carriers in the microvessels and surrounding tissues using the intravascular flow information obtained from the ex vivo analyzing apparatus;
Lt; / RTI >
Wherein said step b) comprises the step of calculating a distribution-shape parameter (alpha) about the cross-sectional area concentration distribution of the cells and / or drug carrier in said microfluidic channel, and
The step c) is based on a generalized plasma skimming model for cells and drug carriers represented by the following equations (20) to (23), wherein the calculated distribution-shape parameter (?) And the material The method comprising predicting the distribution of cells and / or drugs within a particular microvessel and surrounding tissue using a delivery simulation tool:

Where C is the concentration of the cell or drug carrier, Q is the flow rate,

Is the concentration variation coefficient, α is the shape parameter for the cross-sectional area distribution of C microvascular, M is the drift parameter (drift parameter), and, A is and cross-section of each vessel, the subscripts 0, 1, and 2 are each parent A parent vessel and two daughter vessels, and i is an integer of 1 and 2. delete delete delete 2. The method of claim 1, wherein the optional vessel segment is a segment selected or derived from a root vessel. 2. The method of claim 1, wherein the blood mixture comprises 70 to 99.99 vol% of blood and 0.01 to 30 vol% of the drug carrier. The method of claim 1, wherein the blood mixture further comprises a fluorescent material or a fluorescent probe, and wherein step b) is performed by an imaging process based on the fluorescence properties of the blood mixture passing through the microfluidic channel, And / or a shape parameter (alpha) relating to a cross-sectional area concentration distribution of the drug carrier. The method of claim 1, wherein the drug carrier is micro-sized particles at the nano. The method of claim 8, wherein the drug carrier has a size of less than or equal to 10 μm. 8. The method of claim 7, wherein the fluorescent substance or fluorescent probe is present in a form covalently or non-covalently bonded or immobilized on the surface of the drug carrier. The drug delivery system according to claim 1,
Silica-based nanoparticles having a core-shell structure, Group II-VI nanoparticles, and combinations thereof, as the inorganic carrier; or
Wherein the organic carrier is selected from carbon-based nanoparticles, polymer-based nanoparticles, and combinations thereof. The method of claim 1, wherein the width or diameter of the microfluidic channel is in the range of 1 to 100 [mu] m. The microfluidic channel according to claim 1, wherein the microfluidic channel is made of a material selected from the group consisting of polyester, polyethylene (PE), polypropylene (PP), polyimide (PI), polystyrene (PS), polycarbonate (PC), polyurethane, (PM), polyvinyl chloride (PVC), cyclic olefin copolymer (COC), liquid crystal polymer (LCP), polyamide (PA), polyimide Polyetheretherketone (PEEK), polyether sulfone (PES), polytetrafluoroethylene (PTFE), acryl-based resins, polydimethylsiloxane (PDMS) ≪ / RTI > and combinations thereof. 14. The method of claim 13, wherein the microfluidic channel has a circular or rectangular cross-section. 15. The method of claim 14, wherein the microfluidic channel has a circular or rectangular cross-section by cascading PDMS around a glass capillary, a stainless steel rod, or a nylon thread mold. The method of claim 7, wherein the fluorescent substance or fluorescent probe is selected from the group consisting of umbelliferone, fluorescein, fluorescein isothiocyanate (FITC), rhodamine, TAMRA ), Dichlorotriazinylamine fluorescein, dansyl chloride, quantum dots, phycoerythrin, fluorescein, alexa fluor and cyanine Cyanine, and combinations thereof. ≪ RTI ID = 0.0 > 11. < / RTI > 17. The method according to claim 16, wherein the fluorescence originating from the fluorescent substance or the fluorescent probe is detected by a fluorescence microscope. The method according to claim 1, wherein the microvessel mass transfer simulation tool is based on distribution of blood cells in blood vessels and blood flow characteristics according to plasma skimming represented by the following equations (17 'to 19'):

Where H ₀ , H ₁ and H ₂ are the hematocrit respectively in the mother blood vessel and the two branched blood vessels,

Q ₀ , Q ₁ and Q ₂ are flow velocities in the parent vessel and two branch vessels, respectively, and A ₀ , A ₁ and A ₂ are the blood flow velocities of the mother blood vessels and two It refers to the cross-sectional area in a branched vessel. a) a microfluidic device having (i) a microfluidic channel that replicates any of the vascular segments of the vascular system, and (ii) More equipped with a detection device for deriving in vivo (in vitro) analysis device, wherein the vascular flow information includes a concentration of the flow velocity (flow rate), hematocrit (hematocrit) and a drug carrier (drug carrier), also the body Wherein the external analyzing device calculates a shape parameter (?) Concerning a cross-sectional area concentration distribution of the cells and / or the drug carrier in the microfluidic channel; And
b) a microvascular mass transfer simulation tool;
/ RTI >
(A) and a mass transfer simulation tool for the microvessels based on a generalized plasma skimming model for a cell and a drug carrier represented by the following equations (20) to (23) A system for predicting the distribution of cells and / or drugs in specific microvessels and surrounding tissues:

Where C is the concentration of the cell or drug carrier, Q is the flow rate,

Is the concentration variation coefficient, α is the shape parameter for the cross-sectional area distribution of C microvascular, M is the drift parameter (drift parameter), and, A is and cross-section of each vessel, the subscripts 0, 1, and 2 are each parent A parent vessel and two daughter vessels, and i is an integer of 1 and 2. delete delete delete

Images