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.

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.

Microfluidics is an emerging technology that is expected to revolutionize biochemical experiments and reduce the need for unwieldy laboratory equipment. Motivated by that, the design automation community has spent considerable efforts and proposed numerous methods on automating the design process for corresponding microfluidic devices. For many of them, however, it often remains unclear whether the (automatically) generated design indeed works as intended and/or satisfies its purpose. Simulations, e.g., based on Computational Fluid Dynam-ics (CFD) can help here as they allow for studying the behavior of microfluidic devices without the need for actual fabrication. However, the setup and configuration of CFD simulations is time-consuming and requires extensive expertise-some of the reasons why it is hardly utilized in the design automation community yet. In this work, we propose a workflow that improves upon this state of the art by automating intermediate steps and highlighting the parameters that are relevant to the specific use case. We demonstrate the feasibility of the proposed workflow for fluid mixing in channel-based microfluidics.

Channel-based microfluidic devices, often in the form of so-called Lab-on-a-Chip (LoC), have a broad range of applications in domains such as biology, chemistry, medicine, etc. Many of these applications rely on merging of droplets, e.g., in order to trigger some kind of reaction inside the droplets. However, the design process of LoCs is, in general, still in its infancy and mostly relies on simplifications, assumptions, as well as the expertise of the designer-making this process rather error-prone and frequently resulting in a “trial-and-error” approach. Simulation tools can help in this regard. While Computational Fluid Dynamics (CFD) tools can simulate the merging of droplets, their complex setup and computational efforts limit their applicability to rather small components and do not allow simulations of larger microfluidic devices. Instead, considerations on the so-called one-dimensional model (1D model) offer a more abstract and, hence, computationally much faster simulation. However, currently there are no simulators based on the 1D model available that support the merging of droplets-severely restricting the applicability of such simulators. In this work, we address this problem by proposing a concept for droplet merging based on the 1D-model and implementing these ideas on top of an already existing 1D-simulator. The resulting simulator (which is made publicly available as part of the Munich Microfluidics Toolkit (MMFT)) eventually allows for the efficient simulation of channel-based microfluidic devices where droplet merging is an essential part.

Microfluidics is a technology that enables moving analytic processes from expensive and bulky laboratory equipment to small-scale devices. Microfluidic devices, usually in the form of labs-on-a-chips (LoCs), have found many great applications in medicine, biology, and chemistry. In particular, LoCs that utilize channels to transport fluids or droplets between different components on the chip are a promising technology. However, the design process of such channel-based LoCs is in need of further automation efforts since the underlying design steps are still rather complex and conducted mainly by hand. An important task in microfluidic design automation is the so-called channel routing, where components on LoCs are connected by microfluidic channels. Methods that aim to automate this routing task must factor in the specific demands of microfluidic devices. Common requirements for microfluidic routing layouts are to prevent sharp channel bends and to realize a particular length of channels. Unfortunately, most of the available routing algorithms address these requirements only partly and insufficiently. In this work, we propose a router that is able to overcome these shortcomings and allows automatic channel routing with a minimal bending radius as well as a desired length. In order to make the router accessible to users with little to no design automation expertise, the solution is implemented as an online tool with a user-friendly and intuitive interface. The resulting tool can be accessed athttps://www.cda.cit.tum.de/research/microfluidics/channel_router/.

Microfluidic devices, often in the form of Lab-on-a-Chip (LoCs), are successfully utilized in many domains such as medicine, chemistry, biology, etc. However, neither the fabrication process nor the respectively used materials are perfect and, thus, defects are frequently induced into the actual physical realization of the device. This is especially critical for sensitive devices such as droplet-based microfluidic networks that are able to route droplets inside channels along different paths by only exploiting passive hydrodynamic effects. However, these passive hydrodynamic effects are very sensitive and already slight changes of parameters (e.g., in the channel width) can alter the behavior, even in such a way that the intended functionality of the network breaks. Hence, it is important that microfluidic networks become robust against such defects in order to prevent erroneous behavior. But considering such defects during the design process is a non-trivial task and, therefore, designers mostly neglected such considerations thus far. To overcome this problem, we propose a robustness improvement process that allows to optimize an initial design in such a way that it becomes more robust against defects (while still retaining the original behavior of the initial design). To this end, we first utilize a metric to compare the robustness of different designs and, afterwards, discuss methods that aim to improve the robustness. The metric and methods are demonstrated by an example and also tested on several networks to show the validity of the robustness improvement process.

Microfluidics is an emerging field that allows to minimize, integrate, and automate processes that are usually conducted with unwieldy laboratory equipment inside a single device; resulting in so-called “Labs-on-a-Chip” (LoCs). The design process of channel-based LoCs is still mainly conducted manually thus far - resulting in time-consuming tasks and error-prone designs. This also holds for the routing process, where multiple components inside an LoC should be connected according to a specification. In this work, we present a routing tool which considers the particular requirements of microfluidic applications and automates the routing process. In order to make the tool more accessible (even to users with little to no EDA-expertise), it is incorporated into a user-friendly and intuitive online interface.

Microfluidics is a prospective field which provides technological advances to the life sciences. However, the design process for microfluidic devices is still in its infancy and frequently results in a "trial-and-error" scheme. In order to overcome this problem, simulation methods provide a powerful solution---allowing for deriving a design, validating its functionality, or exploring alternatives without the need of an actual fabricated and costly prototype. To this end, several physical models are available such as Computational Fluid Dynamics (CFD) or the 1-dimensional analysis model. However, while CFD-simulations have high accuracy, they also have high costs with respect to setup and simulation time. On the other hand, the 1D-analysis model is very efficient but lacks in accuracy when it comes to certain phenomena. In this work, we present ideas to combine these two models and, thus, to provide an accurate and efficient simulation approach for microfluidic networks. A case study confirms the general suitability of the proposed approach.