Method for designing a partitioning of a microfluidic, in particular biological, sample

Abstract

Method (500) for designing a partitioning of a microfluidic, in particular biological, sample into partitions on a partition surface, in particular for determining a concentration of an analyte in the sample, comprising the steps • Definition (510, 520) of a geometric shape (110, 120) of the partitions (110, 120), a shape of the partition surface (101) and a total volume of the sample • Determination (530, 540) of a minimum partition size of the partitions (110, 120) and a corresponding maximum number of partitions (110, 120) that can be arranged on the partition area (101) with minimum partition size as the first number of partitions. • Determination (560) of a second partition measure of the partitions (110, 120) and a corresponding second number of partitions under the condition that a maximum possible proportion of the total volume can be partitioned on the partition area (101) and that the maximum possible proportion is divided into as many partitions (110, 120) as possible on the partition area (101). • Determination (580) of a first uncertainty of a measurable concentration of the analyte using a partition measure from a first range around the minimum partition measure and determination of a second uncertainty of the measurable concentration using a partition measure from a second range around the second partition measure. • Interpretation (591, 592) of the partitions using a partition measure from the first area or from the second area depending on a comparison (590) of the first uncertainty with the second uncertainty.

Description

State of the art

[0001] Microfluidic analysis systems (so-called lab-on-a-chips, or LoCs) enable automated, reliable, fast, compact, and cost-effective processing of patient samples for medical diagnostics. By combining a variety of operations for the controlled manipulation of fluids, complex molecular diagnostic test sequences can be performed on a single lab-on-a-chip cartridge.

[0002] When implementing a partition-based quantitative assay, particularly a digital polymerase chain reaction (digital PCR), in such a line of chemistry (LoC), one of the operations involves aliquoting the sample into multiple partitions. These partitions can be implemented as chambers or drops, for example. Within each partition, endpoint amplification of the specific DNA target occurs independently. If at least one target was present in the respective partition at the start of the amplification reaction, this results in an increase in fluorescence. Based on the proportion of partitions exhibiting an increase in fluorescence, the target concentration in the analyzed sample can be determined using Poisson statistics.

[0003] During the aliquoting process, various sources of error affect the accuracy of the quantitative analysis. The most dominant are fluctuations in the concentration of the analyzed subvolume (so-called subsampling error) and the statistical inaccuracy inherent in the aliquoting process itself (so-called partitioning error). Both of these mechanisms have already been described in the literature (Dube et al., PLoS ONE 3 (8), e2876 (2008), 10.1371 / journal.pone.0002876; Jacobs et al., BMC Bioinformatics 15, 283 (2014), https: / / doi.org / 10.1186 / 1471-2105-15-283; Bizouarn F. (2014) Introduction to Digital PCR. In: Biassoni R., Raso A. (eds) Quantitative Real-Time PCR Methods in Molecular Biology (Methods and Protocols), vol 1160. Humana Press, New York, NY. https: / / doi.org / 10.1007 / 978-1-4939-0733-5_4; Basu, Amar S. (2017): Digital Assays Part I: Partitioning Statistics and Digital PCR. in SLAS technology 22 (4), pp. 369-386. DOI: 10.1177 / 2472630317705680).The general recommendation is to reduce the partitioning error by using as many partitions as possible, thereby increasing the dynamic measurement range of the analysis system. The subsampling error is generally negligible and, according to the literature, only plays a significant role when the proportion of the analyzed volume is below 30% or 50%, depending on the application (Jacobs et al., BMC Bioinformatics 15, 283 (2014), https: / / doi.org / 10.1186 / 1471-2105-15-283). Furthermore, the advantage of using as many partitions as possible is emphasized. Disclosure of the inventionAdvantages of the invention

[0004] Against this background, the invention relates to a method for designing a partition of a microfluidic sample into partitions on a partition surface. In particular, the invention also relates to a method for partitioning, dividing, or aliquoting such a sample into partitions or subsets of the sample. The method can be used, in particular, for determining the concentration of an analyte in the sample, especially in combination with digital PCR in the case of nucleic acid fragments as analytes.

[0005] Sample partitioning, as described, can thus be understood as the division or aliquoting of a sample into sample parts, or, in a preferred embodiment, the actual placement of the sample in the form of sample parts on the partition surface. The sample can be, in particular, a biological sample, for example, comprising a body fluid such as blood, urine, sputum, or a swab. In addition to the body fluid, the sample can contain other substances, for example, in the form of a mixture of the body fluid with a transport medium such as eNAT™ or UTM™. The analyte, also called the target, can be a molecule in the sample, in particular a nucleic acid segment, for example, a part of the DNA or RNA of a pathogen or a specific body cell, especially a tumor cell.In a particular embodiment, the analyte can also be cells, especially single-celled organisms or animal or human body cells, for example, one or more of so-called circulating tumor cells (CTCs). As already mentioned, the method according to the invention can thus be part of or a prerequisite for a partition-based quantitative detection method for analytes in the sample, for example, using digital PCR. Such a detection method can preferably be carried out with a microfluidic device, in particular a lab-on-a-chip system, in the case of microfluidic samples. The method according to the invention advantageously enables the partitioning of the sample for a statistical estimation of the analyte concentration in the sample with low relative error.

[0006] In a preferred embodiment, the method for designing a partition comprises a partitioning of the sample on the partition surface according to the invention. The partition surface can generally be part of a microfluidic device, preferably part of a microfluidic cartridge. For example, the partition surface can be a surface on a substrate in a chamber of the microfluidic device.

[0007] In a first step of the process, the geometric shape of the partitions, the shape of the partition area, and the total volume of the sample are defined. The partition area can, for example, have a square or rectangular shape and may optionally be surrounded by a boundary wall. The partitions can preferably be in the form of droplets or chambers. In the case of droplets, these are preferably in the form of an emulsion, for example, water-based droplets in an oil emulsion, and the droplets can preferably be stabilized by the addition of surface-active substances, so-called surfactants. In the case of chambers, the chambers can have a round or angular base, preferably a hexagonal base. The chambers are separated from each other by walls, which are preferably designed to be as thin as possible in order to block as little surface area as possible.Preferably, the walls are taken into account in the geometric shape of the chambers.

[0008] In a further step of the procedure, a minimum partition dimension is determined. A minimum partition dimension is understood to be a measure, i.e., a representative and preferably unique value for the size of the partition, in particular for the volume of the partition. Specifically, the partition dimension can be the diameter of the partition in the case of a spherical or teardrop-shaped partition, or the width of the chamber in the case of partitioning into chambers with an angular, for example, square or hexagonal, base.

[0009] For example, the partition size is the distance between two opposite corners, preferably the minimum center-to-center distance of the partitions. The minimum partition size implicitly determines a maximum number of partitions with the minimum partition size that can be arranged on the partition surface. This maximum number is referred to as the initial number of partitions and is a measure of a minimum partitioning error, because the statistical inaccuracy of determining the concentration of the entire partitioned volume of the sample decreases with an increasing number of partitions. A partitioning design with as many partitions as possible and a correspondingly small partition size is referred to as the minimal variant.

[0010] In a further step of the procedure, a second partition measure is determined, resulting in a second number of partitions. This determination is based on the condition that the maximum possible proportion of the total volume can be partitioned within the partition area, and that, under this condition, the maximum possible proportion is distributed across as many partitions as possible within the partition area. This has the advantage that the more of the total volume that can be partitioned, the lower the subsampling error. However, the number of partitions should still be kept as large as possible to achieve the lowest possible partitioning error. This second partition measure is subsequently referred to as the maximum partition measure. maxHowever, this denotes and represents the smallest possible partition size for a maximum partitioned total volume. The number of partitions at the maximum partition size is also referred to below as the second partition count A. min The term "maximum variant" is used to describe a partitioning scheme that partitions as much of the sample's total volume as possible, thereby selecting a larger partition size. This approach is distinct from the minimal variant. This step can also be performed before the previous step.

[0011] In a subsequent step of the procedure, a first uncertainty of the analyte concentration is determined when using a partition measure from a first range around the minimum partition measure, and a second uncertainty of the measurable concentration is determined when using a partition measure from a second range around the second partition measure. The first and second uncertainties are preferably relative uncertainties. These determinations advantageously ascertain whether a design according to the minimum or maximum variant is preferable with regard to minimizing the concentration measurement error. The first range is preferably defined such that it includes the minimum partition measure, preferably as the lower end of the first range, and excludes the second partition measure.The second region is preferably defined such that it includes the second partition measure, preferably as the upper end of the second region, and excludes the minimum partition measure. In a particular embodiment, the first region and the second region can be two mutually non-overlapping regions, i.e., in particular, disjoint regions.

[0012] According to a particular refinement of this step of the procedure, the first uncertainty of a measurable analyte concentration is determined using the first number of partitions with the minimum partition measure, and the second uncertainty of the measurable concentration is determined using the second number of partitions with the second partition measure. Preferably, the first uncertainty and / or the second uncertainty are determined for a value from the maximum theoretical range for a measurement of the analyte concentration. This maximum theoretical range extends from -log(1-1 / A) max ) / V par to -log(1-( A max -1) / A max ) / V par , where A max the first partition number, V parThe capacity / volume of a single partition and log denotes the natural logarithm. To preferably generate two equally sized measurement ranges, the midpoint of this range on a logarithmic scale is chosen as the value, which is (log(1-1 / A)). max ) * log(1-( A max -1) / A max ))^0.5 / V par lies.

[0013] According to a particular embodiment of the method, the partitions are designed using a partition measure from the first range, preferably the minimum partition measure, if measuring the analyte concentration at a predetermined concentration value is not possible when designing the partitions with a partition measure from the second range, particularly the second partition measure. The predetermined concentration value can preferably be a value from the maximum theoretical range described above, and more preferably the midpoint of this range on a logarithmic scale.

[0014] In the next step of the procedure, partitions are defined from either the first or second area, depending on a comparison of the first uncertainty with the second uncertainty. This has the advantage that uncertainties for a subsequent concentration measurement can be taken into account when choosing the partition size and thus the specific form of the partition design. In particular, the minimum or maximum variant can be selected based on these determined uncertainties.

[0015] In a specific embodiment of the method, partitions are defined with a partition measure other than the maximum partition measure if the first uncertainty is smaller than the second uncertainty, and partitions are defined with a partition measure other than the minimum partition measure if the first uncertainty is greater than or equal to the second uncertainty. In this embodiment, the first range thus includes all realizable partition measures except the second / maximum partition measure, and the second range thus includes all realizable partition measures except the minimum partition measure.

[0016] In a further specific embodiment of the method, a partition measure from the first range is used if the first uncertainty is smaller than the second uncertainty, and the partitions are designed using a partition measure from the second range if the first uncertainty is larger than or equal to the second uncertainty. The first range can preferably be a range (optionally modified compared to the previous step of the method) such that it only includes partition measures whose associated, preferably relative, uncertainty of the measurable concentration is smaller than the preferably relative uncertainty of the measurable concentration when selecting the second / maximum partition measure.Similarly, a second range (optionally modified from the previous step) can preferably be chosen such that it only includes partition measures whose associated, preferably relative, uncertainty of the measurable concentration is smaller than the preferably relative uncertainty of the measurable concentration when choosing the minimum partition measure. This has the advantage that a partition measure of the minimum variant is chosen in which the relative uncertainty is always smaller than when choosing the maximum variant, and vice versa.

[0017] In another special embodiment of the procedure, the partitions are interpreted as the first number of partitions with the minimum partition measure if the first uncertainty is smaller than the second uncertainty, or as the second number of partitions with the second / maximum partition measure if the first uncertainty is greater than or equal to the second uncertainty.

[0018] As explained above, the method can be part of an analytical procedure for detecting an analyte in a microfluidic sample. The invention therefore also relates to such an analytical procedure, wherein the sample is divided into partitions according to the invention and wherein at least one partition is examined for the presence of the analyte. The analytical procedure preferably comprises performing a digital PCR on at least some of the partitions.

[0019] The invention further relates to a method for producing a partition of a microfluidic sample. A partition surface is provided, and the sample is partitioned according to the design method of the invention. The manufacturing method preferably includes the production of chambers for partitioning on the partition surface. Brief description of the drawings

[0020] Exemplary embodiments of the invention are shown schematically in the drawings and explained in more detail in the following description. The same reference numerals are used for the elements shown in the various figures that have a similar effect, thus omitting a repeated description of the elements.

[0021] It shows Fig. 1 a flowchart of an embodiment of the inventive method for designing a partitioning, Fig. 2a, Fig. 2b a schematic representation of a partitioning of a sample onto a partition surface in the form of droplets or in the form of chambers filled with sample parts, Fig. 3 diagrams with exemplary calculations of relative uncertainties of different concentrations of an analyte in the sample as a function of a chosen partition measure for the partitions, Fig. 4 a flowchart of an embodiment of the analytical method according to the invention for the detection of an analyte in a microfluidic sample and Fig. 5 a flowchart of an embodiment of the manufacturing process according to the invention for partitioning a microfluidic sample. Embodiments of the invention

[0022] Fig. Figure 1 shows a flowchart 500 of an embodiment of the method 500 according to the invention for designing a partitioning of a microfluidic sample. The partitioning can, as described above, in particular be part of or a prerequisite for a partition-based quantitative detection method for analytes in the sample, wherein such a detection method for microfluidic samples can preferably be carried out with a microfluidic device, in particular a lab-on-a-chip system. For example, the method described below is part of a quantitative detection of nucleic acid fragments of pathogens or tumor cells in a biological sample comprising a body fluid (for example, blood, sputum, or a swab), wherein the quantitative detection is carried out via digital PCR with the partitioning of the sample designed according to the invention.

[0023] In the first step of procedure 500, the volume of the sample and the area available for partitioning, or partition area, are determined. For example, the divisible volume V could be sys = 25 microliters (µL) and the partition area should be square with an edge length of L = 10 millimeters (mm).

[0024] In the second step 520, which can also be performed before the first step 510, it is determined whether the sample should be divided into droplets without partitions or into chambers. Fig. Figure 2a schematically shows an arrangement of droplets 110 with diameter d on a partition surface 101 with a width L, wherein the partition surface 101 can be, for example, square or rectangular and bounded by a wall 102 as shown. The partition surface 101 can, in particular, be arranged in a chamber of a microfluidic cartridge. Fig. Figure 2b schematically shows an alternative embodiment of an arrangement of chambers 120 on the partition surface 101, wherein the sample is to be divided among the chambers 120. The chambers 120 have, for example, a hexagonal base 121 with a width d, a wall height D corresponding to a chamber depth, and a wall thickness w between each pair of chambers, where the wall thickness w is preferably chosen to be as small as possible in order to block as little area of ​​the partition surface 101 as possible with the walls 122 of the chambers 120. A minimum wall thickness and maximum wall height for maximizing the volume of the chambers 120 may also be limited, in particular, by manufacturing requirements. When selecting the chamber-based arrangement 120, the minimum wall thickness w, for example w = 25 micrometers (µm), and the wall height / chamber depth D, for example D = 380 µm, are determined in a substep 521.The partition surface 101 can, in particular, be a surface of a substrate, for example, a substrate made of silicon, plastic, or a combination of both materials. In the case of the configuration with chambers 120, the chambers 120, in particular the walls 122, can also be made of silicon, plastic, or a combination of both materials. A hydrophilic design of the partition surface 101 or the chambers 120 is particularly advantageous in the case of an aqueous sample.

[0025] Then, in a third step, a minimum partition size of 530 is determined. min defined, where a size of this minimum partition measure d min The minimum partition size may be determined by manufacturing limitations, as mentioned above, and the resolution of the detection optics used for partition analysis, depending on the specific case. For example, the minimum partition size d is... min= 10 µm and represents the, preferably corresponds to the diameter d of the droplets 110 in the case of the droplet-based arrangement, or the distance between the centers of two chambers 120, or the distance d between two opposite corners in the case of a hexagonal base 121 of the chambers 120 in the case of the chamber-based arrangement. Starting from this minimum partition dimension d min In a fourth step, 540 calculates how many partitions can be accommodated on the partition area 101, possibly while maintaining the minimum wall thickness w. In the case under consideration, this would be A for a chamber-based approach. max = 101871 partitions in hexagonal arrangement, where this number is subsequently referred to as the first partition number A max is designated. From the dimensions of the partitions, together with the depth D of the chambers, the capacity of a single partition V can be determined. parand after multiplication by the first partition count A max the total comprehensible volume V ana calculate. In this case, this amounts to approximately V ana = 2.51 µL and is therefore only about one tenth of the total divisible volume V sys of 25 µL.

[0026] The first partition number A max also defines the maximum theoretical range for a measurement of the analyte concentration (with cp / µL as the unit for copies per microliter), which ranges from -log(1-1 / A max ) / V par to -log(1-( A max -1) / A max ) / V par This is sufficient, where log denotes the natural logarithm. To preferably generate two equally sized measurement ranges, this maximum measurement range is halved on a logarithmic scale according to a fifth step 550. The resulting midpoint λ is then at (log(1-1 / A)). max ) * log(1-( A max -1) / A max ))^0.5 / V parand corresponds in this example to approximately 431 cp / µL. Alternatively, another concentration value λ from this measuring range can be selected, especially if there are reasons for preferring measurement at lower or higher concentrations.

[0027] A preferred alternative to having as many partitions as possible is to choose the dimensions of the partitions so that as much of the entire volume V as possible is used. sys It is also partitioned. Provided the partition area and the height occupied by the partitions are large enough, it is generally always possible to partition the entire volume V. systo accommodate the data on partition area 101, ideally in a single partition. However, to minimize the partitioning error, when using the maximum possible volume, the volume should be divided into as many partitions as possible. Therefore, according to step 560 of procedure 500, a second partition size d must first be created. max to find which, under the given conditions, is the partitionable and therefore analyzable volume V ana maximized while simultaneously implying as many partitions as possible. This second partition measure is also known as the maximum partition measure d. max However, it denotes and represents the smallest possible partition size for a maximally partitioned total volume. In the example shown, this results in d max to 128.52 µm at a maximum partitionable volume V ana of 24.999 µL, i.e., practically the entire volume V sysof 25 µL. The partitionable volume V is then defined. ana divided into 6132 partitions, this number being referred to below as the second partition number A min The sixth step 560 can also be carried out earlier, in particular before or in parallel with one of the preceding steps, provided that the first step 510 and the second step 520 have been carried out.

[0028] According to a preferably seventh step 570 of the method, the maximum theoretical range for a measurement of the concentration of the analyte when using the second partition number A is min of partitions with maximum partition size d max determined, whereby this area is analogous to above from -log(1-1 / A min ) / V par_2 to -log(1-( A min -1) / A min ) / V par_2 extends and wherein V par_2 the volume of a partition with partition measure d maxThis corresponds to the above-calculated midpoint λ. If the midpoint λ calculated above does not fall within this area, the partitioning is preferably designed according to the first number of partitions A, as per substep 571 of the seventh step 570. max with minimum partition size d min . If the calculated center point λ falls within this area, the procedure 500 according to this embodiment is continued as follows.

[0029] According to an eighth step 580 of procedure 500, a first uncertainty of a measurable concentration of the analyte is determined when using the first partition number A. max of partitions with minimum partition size d min (hereinafter referred to as the minimal variant) and a second uncertainty of the measurable concentration when using the second number of partitions A min of partitions with maximum partition size d max (hereinafter referred to as the maximum variant) calculated.

[0030] The relative uncertainties can preferably be determined using the following approach.

[0031] To calculate the partitioning error, an uncertainty based on the confidence interval of the following probability distribution P(CIH) can be used: P(C|H)=(A−1)!(A−A−1)!⋅SC,HAC where C represents the number of targets in the analyzed sample volume V ana , H represents the number of partitions containing at least one analyte, A represents the available number of partitions, and S represents the Stirling number of the second kind.

[0032] The subsampling error can be calculated as an uncertainty based on the confidence interval of the following probability distribution P(C). tot |C, p) are used: P(Ctot|C,p)=(CtotC)⋅pC+1⋅(1−p)Ctot−C where C represents the number of targets in the analyzable sample volume V ana , C totfor the number of targets in the partitionable volume V sys and p for the proportion of the analyzable volume to the partitionable volume V ana / V sys stands.

[0033] When both errors are combined, the result is: P(Ctot|H,p)=∑C=HCtotP(Ctot|C,p)⋅P(C|H)

[0034] Since an exact calculation of this distribution takes a very long time, it can be approximated by a Gaussian distribution. With a Gaussian distribution, the confidence interval can be calculated directly from the variance s. In the case of a 95% confidence interval, this is μ±1.96⋅s, where µ represents the expected value. The standard deviation s The probability of a Gaussian distribution can be calculated from the probability at the expected value, i.e., the maximum probability: s=12π⋅P(μ)

[0035] This relationship is used in the approximation. The maximum value of P(C) tot |H, p) is set equal to P(µ) and then the standard deviation and from that the confidence interval are calculated, which in turn defines the uncertainty.

[0036] The value at which P(C tot |H, p) is maximally at C^tot=⌊−log(1−HN)⋅Np⌋

[0037] The calculation of P(C tot |H, p) is done via: P(C^tot|H,p)=(N−1)!(N−H−1)!∑C=HC^totSC,HNC⋅(C^totC)⋅pC+1⋅(1−p)C^tot−C

[0038] This calculation is advantageous in terms of time expenditure. This approximation allows for a qualitative comparison, and the quantitative results are within approximately 10% of the true, exact value of the uncertainty.

[0039] Using this approximation, the first relative uncertainty of the measurement result σ at midpoint λ in the present example is approximately 0.0566 or 5.66% when applying the minimum variant. When applying the maximum variant, the second relative uncertainty at midpoint λ is approximately 0.0254 or 2.54%, which is less than half the relative uncertainty.

[0040] According to a ninth step 590 of the procedure 500, the two relative uncertainties are compared, and a partitioning design is determined based on this comparison. Specifically, depending on this comparison, a partitioning can be implemented according to the minimum variant 591 or the maximum variant 592, preferably with the lowest possible relative uncertainty. Several approaches are advantageous for the specific choice of variant and, in particular, for choosing a specific value for the partition, which have been described above. For example, the design that yields the lower uncertainty in the middle of the maximum theoretical measurement range can be chosen.In this example, with a square partition area of ​​10 mm side length, a processed volume of 25 µL, a chamber depth / wall height of 380 µm, a minimum wall thickness of 25 µm, and a minimum partition size of 10 µm, the sample is distributed into 6132 hexagonal partitions with a partition size of 128.52 µm. After filling the chambers 120 with the sample according to this partitioning, in a specific embodiment, the chambers 120 can be overlaid with (transparent) oil before subsequent processing or analysis, for example, as part of a digital PCR.

[0041] Fig. Figure 3 shows, as an example, the relative uncertainties σ calculated according to the approximation described above as a function of the partition measure d for different analyte concentrations in the sample (10, 50, 100 and 500 analytes per microliter respectively) using chambers 120 and the same values ​​for volume, edge length, chamber depth / wall height and wall thickness. As shown in Fig. As can be seen in Figure 3, for these boundary conditions, a design with large partition sizes is associated with generally lower relative errors for all calculated concentrations. However, a design with the smallest possible partition size is particularly disadvantageous at low concentrations. This is because, in these cases, the subsampling error dominates over the partitioning error due to the significantly smaller partitionable volume at very small partition sizes. Under other boundary conditions, however, smaller relative errors may result for designs with small partition sizes compared to designs using the maximum partition size for certain concentrations.

[0042] According to a modification of the embodiment 500 described above, the entire divisible volume V sys increased to 30 µL. The minimum partition size d minThe edge length L of the partition surface 101, the wall height / chamber depth D, and the wall thickness w remain unchanged at 10 µm, 10 mm, 380 µm, and 25 µm, respectively. The midpoint λ of the logarithmic measuring range is approximately 431 cp / µL in this case. The largest fraction of the divisible volume V sys can be achieved with a second / maximum partition size of d max = 294.65 µm can be analyzed. With this partition dimension, the measuring range extends up to a concentration of approximately 338 cp / µL. Therefore, this measuring range does not include the midpoint λ, and thus, preferably according to substep 571 of the seventh step 570, the partitioning would be designed according to the minimum variant.

[0043] Fig. Figure 4 shows a flowchart of an embodiment of the analytical method 600 according to the invention. In a first step 610 of the method 600, a sample can preferably be divided into partitions according to the method according to the invention for the design of a partitioning, for example according to the one described above. Fig. The method described in section 1 500. Subsequently, in a second step 620, at least one partition, preferably all partitions, can be examined for the presence of the analyte, and the concentration of the analyte in the divided sample can be deduced from this. This determination of the concentration is preferably carried out by performing a digital PCR, for which the partitions form the basis.

[0044] Fig. Figure 5 shows a flowchart of an embodiment of the manufacturing process 700 according to the invention. In a first step 710, a partition surface is provided. This can be done, for example, by providing a substrate, wherein a surface of the substrate forms the partition surface. The partition surface or the substrate can be part of a microfluidic cartridge or be arranged or fixed in the cartridge during the manufacturing process 700. In a second step 720 of the process, the partitioning is designed according to the inventive method for designing a partitioning, for example, according to the method described above. Fig. 1 described process 500. The manufacturing process 700 can, in an advantageous embodiment, include the production of chambers for partitioning on the partition surface.

Claims

[1] Method (500) for designing a partitioning of a microfluidic, in particular biological, sample into partitions on a partition surface, in particular for determining a concentration of an analyte in the sample, comprising the steps • Determination (510, 520) of a geometric shape (110, 120) of the partitions (110, 120), a shape of the partition surface (101) and a total volume of the sample • Determining (530, 540) a minimum partition size of the partitions (110, 120) and a corresponding maximum number of partitions (110, 120) that can be arranged on the partition surface (101) with a minimum partition size as the first number of partitions. • Determining (560) a second partition measure of the partitions (110, 120) and a corresponding second number of partitions under the condition that a maximum possible portion of the total volume can be partitioned on the partition surface (101) and the maximum possible portion is divided among as many partitions (110, 120) as possible on the partition surface (101). • Determining (580) a first uncertainty of a measurable concentration of the analyte when using a partition measure from a first range around the minimum partition measure and determining a second uncertainty of the measurable concentration when using a partition measure from a second range around the second partition measure. • Designing (591, 592) the partitions with a partition measure from the first range or from the second range depending on a comparison (590) of the first uncertainty with the second uncertainty. [2] The method (500) of claim 1, wherein a design (591, 592) of the partitions (110, 120) is performed with a partition measure unequal to the maximum partition measure if the first uncertainty is smaller than the second uncertainty, and wherein a design of the partitions (110, 120) is performed with a partition measure unequal to the minimum partition measure if the first uncertainty is greater than or equal to the second uncertainty. [3] Method (500) according to claim 1 or 2, wherein a design of the partitions (110, 120) is carried out with a partition measure from the first range if the first uncertainty is smaller than the second uncertainty, and wherein a design of the partitions (110, 120) is carried out with a partition measure from the second range if the first uncertainty is greater than or equal to the second uncertainty. [4] Method (500) according to one of the preceding claims, wherein a design of the partitions (110, 120) is carried out with a minimum partition measure if the first uncertainty is smaller than the second uncertainty, and wherein a design of the partitions (110, 120) is carried out with a maximum partition measure if the first uncertainty is greater than or equal to the second uncertainty. [5] Method (500) according to one of the preceding claims, wherein a design of the partitions (110, 120) is carried out with a partition measure from the first range, in particular with the minimum partition measure, if a measurement of a concentration of the analyte at a predetermined concentration value is not possible when the partitions (110, 120) are designed with a partition measure from the second range, in particular with the second partition measure. [6] Method (500) according to one of the preceding claims, wherein the first uncertainty is determined using the first partition number of partitions with the minimum partition measure and the second uncertainty is determined using the second partition number of partitions with the second partition measure. [7] Method (500) according to claim 6, wherein the first uncertainty and / or the second uncertainty are determined at a value from the maximum theoretical range for a measurement of the concentration of the analyte, in particular wherein the value corresponds to the logarithmic mean of the maximum theoretical range. [8] Method (500) according to one of the preceding claims, wherein the geometric shape (110, 120) of the partitions (110, 120) takes into account a wall (122) at least partially delimiting the partitions (110, 120) with a predetermined wall thickness and / or wall height. [9] Analysis method (600) for detecting an analyte in a microfluidic sample, wherein the sample is divided into partitions (110, 120) according to one of the preceding claims and wherein at least one partition (110, 120) is examined for the presence of the analyte. [10] The analysis method (600) of claim 9, wherein the analysis method (600) comprises performing a digital PCR on at least some of the partitions (110, 120). [11] A method (700) for producing a partition of a microfluidic sample, wherein a partition surface is provided and wherein the partitioning of the sample is carried out according to a design according to any one of claims 1 to 8.

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