Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.


CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

Open Access
Online
ISSN
2364-5504
See all formats and pricing
More options …

Flow optimised design of a novel point-of-care diagnostic device for the detection of disease specific biomarkers

Manuel Dethloff
  • Corresponding author
  • University of Rostock, Fluid Technology and Microfluidics, Justus-von-Liebig Weg 6, 18059 Rostock, Germany
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Marc Dangers / Boris Wilmes / Hermann Seitz
Published Online: 2016-09-30 | DOI: https://doi.org/10.1515/cdbme-2016-0149

Abstract

For the development of a novel, user-friendly and low cost point-of-care diagnostic device for the detection of disease specific biomarkers a flow optimised design of the test system is investigated. For this, computational fluid dynamics and rapid prototyping methods are used. The result is a functional design, which can be used for further experimental investigations.

Keywords: computational fluid dynamics (CFD); line immune-assay (LIA); point-of-care diagnostic (POC)

1 Introduction

Rapid test systems for the diagnosis of current diseases are attracting more and more attention in medical technologies. Particularly in vitro diagnostic devices play an important role in the examination of patient samples (blood, plasma, urine) for different disease specific biomarkers [1], [2].

A novel user-friendly and easy to handle diagnostic product is developed by combining the benefits of existing concepts. The basic element of the device is a line-immunoassay (LIA) with a membrane for the solid phase based on the enzyme-linked-immunosorbent-assay-technology (ELISA). The ELISA system is state-of-the-art and used for biochemical detection of several antibodies and antigens. Another speciality of the device is the transfer of the LIA-membrane into a flow optimised test case, which should move the actual execution of the test from the lab to point-of-care (POC). The resulting test system is characterised by a reduced execution period, a reduction of execution steps and an integrated waste management. A wide range of biomarkers (e.g. the cytomegalovirus) can be implemented in the test system.

In this study, the development of the flow optimised design of the diagnostic product is presented. Computational fluid dynamics (CFD) is used. CFD is a branch of fluid mechanics that uses numerical methods and algorithms to solve and analyse problems that involve fluid flows [3]. CFD studies are very suitable for the implementation of parameter variations. It is possible to change several options or vari-ables during preprocessing, and the simulations themselves can be calculated in parallel on a computing cluster. This saves time and money in comparison to experimental analyses. But although CFD is a powerful tool for the execution of flow calculations, it is necessary to validate the results with experimental analyses. Based on the CFD results, first prototypes are printed using an additive manufacturing process.

2 Material and methods

The path towards the development of a flow optimised design of the diagnostic product is based on an iterative process. First, the constructive implementation is done with the CAD tool Creo 2.0 (PTC, Needham, USA). Subsequently, the CAD design is exported to the CFD tool ANSYS CFX 16.1 (Canonsburg, PA, USA). The basis of most CFD calculations is a spatial discretization [3]. The volume occupied by the fluid is divided into discrete cells. The uniform mesh (approximately 1 million grid points) must have a sufficient resolution to get plausible results. Afterwards, the physical modelling and the boundary conditions are defined, e.g. initial conditions, inlet, outlet, etc. After preprocessing, the simulation is started on a computing cluster and the Navier-Stokes equations, which describe the motion of the viscous two-phase fluid, are solved iteratively in a transient way [4]. Then, a postprocessor is used for the analysis and visualization of the resulting solution. With the help of the visualized results, further modifications are made with respect to the geometry of the diagnostic product. Thus, the iterative process starts again until an analysed partial solution meets the requirements.

With the calculated and optimised design, first prototypes are built with an additive manufacturing process. For this case, a Poly Jet 3D-printing technique is used. (Objet Eden, Stratasys, Eden Praire, MN, USA). With this 3D-printing technique it is possible to produce components quickly and cost-efficiently.

3 Requirements for the POC device

The diagnostic product should be very user-friendly. This is achieved by using a rectangular shaped and easy to handle body. A membrane basin and a waste reservoir for the reagents waste is located within the body. A membrane strip with dried up reagents is positioned within the membrane basin (see Figure 1). The dimensions of the membrane strip are 25 × 3 mm.

First draft of the diagnostic product.
Figure 1

First draft of the diagnostic product.

The test principle involves successive reaction steps, where several solution steps and subsequent wash steps are necessary. After every single step a lateral movement (5°–10°, for mixing) and a subsequent tilting of the body by about 90° follow in order to carry the liquid fluid from the membrane basin into the waste reservoir. In this case, no rest fluid should remain in the membrane basin after tilting, since this would lead to erroneous results if new liquid were added. Another challenge is the ability to switch between large and small volumes during the test execution. The membrane basin must be designed in such a way, that it is big enough for large fluid volumes of about 5 ml (incubation of the patient sample), but also in such a way that small volumes of about 0.5 ml (solution and wash steps) ensure a sufficiently high liquid column over the membrane in order to ensure complete wetting. Furthermore, a mixing of waste and re-agents fluid in the membrane basin must be avoided. After finishing the test execution a total of 9 ml of liquid is delivered. So the waste reservoir must be designed for such a liquid volume. The inflow of the liquids takes place through an opening in the cover of the body. The cover is transparent in order to allow for optical evaluation of the membrane strip. A first draft of the diagnostic product can be seen in Figure 1.

4 Results

Based on the draft in Figure 1 and the dimensions of the membrane strip, the initial shape of the membrane basin is developed. During the iterative development process several shapes of the membrane basin are designed and improved. Some shapes of the membrane basin can be seen in Figure 2.

Different shapes of the membrane basin.
Figure 2

Different shapes of the membrane basin.

Shape 1 in Figure 2 shows a membrane basin geometry in an early stage of development. Substantial disadvantages can be seen. To realize an initial filling of 5 ml, the height of the rectangular-shaped basin is 25 mm. This kind of shape leads to a restricted optical view of the membrane strip as well as an increase of the total height of the body. Furthermore, flow simulations show that it is not possible to empty the basin at an angle of 90°. A rest fluid remains in the basin and leads to erroneous test results (see Figure 3).

CFD simulation of shape 1 (in Figure 2).
Figure 3

CFD simulation of shape 1 (in Figure 2).

As part of the further development, the design of the basin is changed with respect to the shape and size. Shape 2 in Figure 2 shows a wider and flatter form of the basin. The membrane strip is situated in the centred channel, which is designed for a filling volume of about 1 ml. An inclined wall makes the tilting of the fluid easier. The disadvantages of this shape are explained with the help of the CFD simulation presented in Figure 4. A small dead volume remains in the basin near the vertical walls after tilting the basin by 90°.

CFD simulation of shape 2 (in Figure 2).
Figure 4

CFD simulation of shape 2 (in Figure 2).

Further investigations show that the fluid column over the planar areas lateral to the membrane channel has no influence on the membrane. The height of the fluid column is essential for the biochemical processes and therefore for the effectiveness of the membrane. So in a next step, new geometrical solutions are designed, c.f. shapes 3 and 4 in Figure 2. Here, the membrane basins have sloped side walls as well as no vertical walls in the direction of tilting, so no dead volumes can occur.

Another important fact is the size and the arrangement of the waste reservoir in the body. The reservoir should be designed for a total waste of about 10 ml. In the first stage of development, the reservoir is located under the membrane basin at the bottom of the body (see Figure 5 or Figure 3). The membrane basin (shape 4 in Figure 2) is centred on the front face. The simulation study in Figure 5 shows the effect of tilting the basin forwards and then backwards again into the initial position. The membrane basin is filled with 5 ml of water in the initial position (see Figure 5A). In this study only the gravitation vector is changed. Figure 5B demonstrates the maximal tilting position of 90°. The fluid flows out of the basin. In Figure 5C and d the body is tilted backwards and the fluid flows back into the waste reservoir. Due to the inertia the fluid sloshes against the opposite wall (see Figure 5E).

CFD simulation study: Tilting forwards and backwards; waste reservoir under membrane basin.
Figure 5

CFD simulation study: Tilting forwards and backwards; waste reservoir under membrane basin.

If the rotating velocity of the tilting is higher than 1.5 m/s, fluid can splash back into the membrane basin. This particular case leads to incorrect results and has to be avoided. In the further course of development, the geometry of the body is changed so that the waste reservoir is located next to the membrane basin, as can be seen in Figure 6.

CAD model: new arrangement of basin and reservoir.
Figure 6

CAD model: new arrangement of basin and reservoir.

The width of the basin extends up to the side walls of the body. With this modification, the height of the body can be reduced by about 40% up to 25 mm. To ensure that no fluid splashes back into the basin during the tilting phase, the faces of the waste reservoir are equipped with absorbent material. This material absorbs the predominate part of the fluid. Figure 7 shows a 3D-printed prototype of the CAD model presented in Figure 6. It was printed using the Poly Jet technique. A membrane strip is located in the membrane basin (shape 3 in Figure 2). The waste reservoir next to the membrane basin is equipped with fleece material.

3D printed prototype of diagnostic product without cover.
Figure 7

3D printed prototype of diagnostic product without cover.

5 Conclusion

For the development of a new diagnostic product, a flow optimised design was successfully engineered. With the help of CFD, a novel, simple and user-friendly test body was designed which satisfies all requirements. It was demonstrated that for an optimised shape of the membrane basin and a suitable arrangement of the basin and waste reservoir a reliable test implementation is guaranteed. The dimensions of the body are 60 × 26 × 27 mm and thus make it easy to handle. In a next step, a cover with a click closure should be designed and further experimental investigations will be conducted. Once the biochemistry for relevant biomarkers is developed, the diagnostic product can then be tested for marketability.

Author’s Statement

Research funding: This project is funded by the Bundesministerium für Wirtschaft und Energie initiative “ZIM– Zentrales Innovationsprogramm Mittelstand”. Conflict of interest: Authors state no conflict of interest. Material and Methods: Informed consent: Informed consent has been obtained from all individuals included in this study. Ethical approval: The research related to human use complies with all the relevant national regulations, institutional policies and was performed in accordance with the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board or equivalent committee.

References

  • [1]

    Grevers G, Röcken M. Taschenatlas Allergologie – Grundlagen, Diagnostik, Klinik. Stuttgart: Thieme Verlag KG; 2008. Google Scholar

  • [2]

    Drescher P, Dangers M, Rübenhagen R, Seitz H. The effects of various flow velocities on the sensivity of an ELISA in a fluidic allergy diagnostic device. Point of Care: The Journal of Near-Patient Testing and Technology. 2014;2:35–40. Google Scholar

  • [3]

    Ferziger J, Peric M. Computational methods for fluid dynamics. 3rd ed. Berlin: Springer; 2002. Google Scholar

  • [4]

    Oertel jr H, Böhle M, Reviol T. Strömungsmechanik. 6. Auflage. Wiesbaden: Vieweg+Teubner; 2011 Google Scholar

About the article

Published Online: 2016-09-30

Published in Print: 2016-09-01


Citation Information: Current Directions in Biomedical Engineering, Volume 2, Issue 1, Pages 685–688, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2016-0149.

Export Citation

©2016 Manuel Dethloff et al., licensee De Gruyter.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

Comments (0)

Please log in or register to comment.
Log in