Abstract

Enhancing the degree of functional multiplexing while assuring operational reliability and manufacturability at competitive costs are crucial ingredients for enabling comprehensive sample-to-answer automation, e.g., for use in common, decentralized “Point-of-Care” or “Point-of-Use” scenarios. This paper demonstrates a model-based “digital twin” approach, which efficiently supports the algorithmic design optimization of exemplary centrifugo-pneumatic (CP) dissolvable-film (DF) siphon valves toward larger-scale integration (LSI) of well-established “Lab-on-a-Disc” (LoaD) systems. Obviously, the spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally accessible disc space. At the same time, the retention rate of a rotationally actuated CP-DF siphon valve and, most challengingly, its band width related to unavoidable tolerances of experimental input parameters need to slot into a defined interval of the practically allowed frequency envelope. To accomplish particular design goals, a set of parametrized metrics is defined, which are to be met within their practical boundaries while (numerically) minimizing the band width in the frequency domain. While each LSI scenario needs to be addressed individually on the basis of the digital twin, a suite of qualitative design rules and instructive showcases structures are presented.

Highlights

  • Empowering even untrained operators to autonomously perform decentralized testing of bioliquids outside the specialized laboratory infrastructure, such as hospital labs, general practitioners’ offices, in the field, or even patient self-testing at home, represents the key driver for the development of so-called “Point-of-Care” (PoC) devices

  • The spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally accessible disc space

  • centrifugo-pneumatic dissolvable-film (CP-DF) siphon valve and, most challengingly, its band width related to unavoidable tolerances of experimental input parameters need to slot into a defined interval of the practically allowed frequency envelope

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Summary

Introduction

Empowering even untrained operators to autonomously perform decentralized testing of bioliquids outside the specialized laboratory infrastructure, such as hospital labs, general practitioners’ offices, in the field, or even patient self-testing at home, represents the key driver for the development of so-called “Point-of-Care” (PoC) devices. Based on previous publications on “digital twin” [76] modeling of fluidic performance and operational robustness on LoaD systems [73,78], valve retention frequencies and their band widths were identified as key performance indicators They can directly be calculated, either algebraically of numerically, from the standard deviation of elementary input parameters, such as general (linear) machining and pipetting tolerances [79,80]. These statistical spreads can either be found in manuals or the literature, and are determined by low-complexity test structures; importantly, these basic parameters are broadly independent of the specific layout of a specific LoaD cartridge This method is, essential to predict and optimize the device performance and its operational robustness in silico, prior to the time- and resource-consumption and, the risky and costly development of manufacturing and assembly. Examples for typical tasks in multiplexing and resulting valve geometries are given before compiling general rules guiding the layout and rotational automation of multi-step/multi-reagent bioanalytical assay panels

Pressures
Critical Spin Rate
Example
Operational Robustness
Laboratory Unit Operations
Multiplexing
Parameter Space
Band Width
Refined Geometry
Retention Rate and Field Strength
Concurrent Valving
Radial Space
Spatial Footprint
Definition of Liquid Volumes
Ambient Pressure
Manufacturing-Process Limitations and Costs
3.3.10. Multi-Parameter Optimization
3.3.11. General Design Guidelines
Findings
Summary and Outlook
Full Text
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