Microfluidics is a rapidly growing field that aims to simplify complex analytical procedures by moving them to small-scale devices. A particularly interesting application of microfluidics are so-called Organs-on-Chips, i.e., microfluidic devices that mimic the structure and function of human organs and, therefore, allow studying the effects of drugs and diseases. Recent recognition of the need for standardization in this domain has led to the generation and uptake of new ISO standards—providing the basis of modular and reusable microfluidic building blocks that allow for various organ-on-chip setups. However, designing these building blocks, especially so-called routing blocks that interconnect pumps, cell cultures, and other modules is a cumbersome, repetitive task that is still conducted manually. In this work, we propose a design and routing method that significantly simplifies the design of such routing blocks by fully automating the process of interconnecting components of a microfluidic chip. The evaluation of physical, fabricated routing blocks that were designed using the proposed method showcases its feasibility in real-world applications and its potential to reduce design effort and time significantly. In order to make the work accessible to the microfluidic community, we provide implementations of the resulting methods in the form of a user-friendly, interactive online tool, provided as part of the Munich Microfluidic Toolkit (MMFT).

Microfluidic devices have become essential in biochemical and medical research, enabling high-throughput experimentation on compact and cost-effective platforms. However, the design and realization of microfluidic devices is a manual, tedious, and error-prone task. Additionally, multiple iterations for prototyping are often needed until a physical realization works as intended. Accordingly, methods for the automatic design and simulation of microfluidic devices are key—something that is standard in the design of conventional circuits and systems. In this work, we present the Munich Microfluidics Toolkit (MMFT), an open-source toolkit that provides corresponding tools for automating the design and simulation of microfluidic systems. For selected design tasks—such as the generation of meanders, gradient generators, organs-on-chip layouts, as well as ISO-compliant routing and validation—we showcase corresponding tools and provide an overview of simulators for microfluidics. MMFT helps researchers and engineers to design microfluidic devices in an automatic fashion (often with the click of a button) and to validate them through simulation across different abstraction levels. All tools are publicly available at https://www.cda.cit.tum.de/research/microfluidics/mmft/.

Multiorgans-on-chips (multi-OoCs) represent human or other animal physiology on a chip—providing testing platforms for the pharmaceutical, cosmetic, and chemical industries. They are composed of miniaturized organ tissues (so-called organ modules) that are connected via a microfluidic channel network and, by this, represent organ functionalities and their interactions on-chip. The design of these multi-OoC geometries, however, requires a sophisticated orchestration of numerous aspects, such as the size of organ modules, the required shear stress on membranes and subsequently the flow rate, the dimensions and geometry of channels, pump pressures, etc. Mastering all this constitutes a nontrivial design task for which, unfortunately, no automatic support exists yet. In this work, we propose a design automation solution for multi-OoC geometries. To this end, we review the respective design steps and derive a corresponding formal design specification from them. Based on that, we then propose an automatic design tool, which generates a design of the desired device and exports it in a fashion that is ready for subsequent simulation or fabrication. The open-source tool and a step-by-step tutorial are available athttps://github.com/cda-tum/mmft-ooc-designer. Evaluations (inspired by real-world use cases and confirmed by computational fluid dynamic simulations as well as a fabrication process) demonstrate the applicability and validity of the proposed approach.

The design of microfluidic devices, i.e., Lab-on-Chips (LoCs) or Micro Total Analysis Systems ($\mu $TASs), is a tedious and cumbersome process with many time-consuming and costly fabrication cycles. Many of these devices contain dissolved species (i.e., solutes) that are required to appear in the system at specific predefined concentrations. The use of simulations can aid the design process of microfluidic devices. However, methods from Computational Fluid Dynamics (CFDs), which are commonly used, are computationally costly and require a lot of time to finish. In this work, we present a simulator for species concentrations in channel-based microfluidic devices that operates on a higher level of abstraction and is multiple orders of magnitude faster than CFD simulation methods. The simulator has been implemented in C++ and is benchmarked against CFD simulations as well as against measured results from experiments on a fabricated device. The results are analyzed and the applicability of the simulator for the simulation of microfluidic devices is assessed.

Organs-on-Chips (OoCs) are testing platforms for the phar-maceutical, cosmetic, and chemical industries. They are composed of miniaturized organ tissues (so-called organ modules) that are connected via a microfluidic channel network and, by this, emulate human or other animal physiology on a miniaturized chip. The design of those chips, however, requires a sophisticated orchestration of numerous aspects, such as the size of organ modules, the required shear stress on membranes, the dimensions and geometry of channels, pump pressures, etc. Mastering all this constitutes a non-trivial design task for which, unfortunately, no automatic support exists yet. In this work, we propose a first design automation solution for OoCs. To this end, we review the respective design steps and formalize a corresponding design specification from it. Based on that, we then propose an automatic method which generates a design of the desired device. Evaluations (inspired by real-world use cases and confirmed by CFD simulations) demonstrate the applicability and validity of the proposed approach.