Integration of systems biology with organs-on-chips to humanize therapeutic development

Abstract

Mice are not little people"-a refrain becoming louder as the gaps between animal models and human disease become more apparent. At the same time, three emerging approaches are headed toward integration: powerful systems biology analysis of cell-cell and intracellular signaling networks in patient-derived samples; 3D tissue engineered models of human organ systems, often made from stem cells; and micro-fluidic and meso-fluidic devices that enable living systems to be sustained, perturbed and analyzed for weeks in culture. Integration of these rapidly moving fields has the potential to revolutionize development of therapeutics for complex, chronic diseases, including those that have weak genetic bases and substantial contributions from gene-environment interactions. Technical challenges in modeling complex diseases with "organs on chips" approaches include the need for relatively large tissue masses and organ-organ cross talk to capture systemic effects, such that current microfluidic formats often fail to capture the required scale and complexity for interconnected systems. These constraints drive development of new strategies for designing in vitro models, including perfusing organ models, as well as "mesofluidic" pumping and circulation in platforms connecting several organ systems, to achieve the appropriate physiological relevance.

Integrated gut/liver microphysiological systems elucidates inflammatory inter‐tissue crosstalk

“…Overall, our design approach anticipates application of the platform to more complex disease modeling where relatively large complex tissue mass (millions of cells) with high metabolic demands and complex interactions are needed. An example, we have begun pursuing along this avenue is that of addressing resistance to chemotherapeutic drug treatment in breast cancer cells that have metastasized to liver residence (Clark et al, ; Edington et al, ), and numerous others of importance to drug discovery and development can be envisioned.…”

High resolution stereolithography fabrication of perfusable scaffolds to enable long-term meso-scale hepatic culture for disease modeling

“…The results obtained in this study demonstrate that PuSLA printing can be used to fabricate mesoscale scaffolds with microscale 3D fluidic networks, allowing sustained 3D primary liver cultures. One of the driving motivations for this work was the need to create a mesoscale system to bridge the gap between in vitro microsystems operating with limited biological material (∼10 3 -10 4 cells) and in vivo macrosystems with cell numbers orders of magnitude higher (∼10 9 cells), resulting in off-target allometric when considering the amount of medium required for cell culture and in applications such as hosting small liver metastases [15,21].…”

“…Further, while some optical or molecular assays are compatible with 10 3 -10 5 cells, assays ranging from detailed transcriptional analyses to mass spectrometry or phosphoproteomics may require 10 6 -10 8 cells [15,19]. Similarly, disease modeling such as tumor metastases in a host tissue may require substantial cell mass to replicate phenomena adequately [15,20,21]. These observations motivate the need to design physiological systems at mesoscopic scale between micrometric MPS and macrometric animal models, which would help bridge the gap between the two fields and provide more physiologically relevant in vitro models.…”

Integrated experimental-computational analysis of a liver-islet microphysiological system for human-centric diabetes research

“…(insulin resistance and -cell adaptation). This is an advancement from the models that have typically been combined with MPS, which mainly apply PK (Prot et al, 2014;Kimura et al, 2015;Edington et al, 2017; and PKPD (Sung et al, 2010;Lee, Kim, et al, 2017;McAleer et al, 2019;Novak et al, 2020) approaches to describe the pharmacological effect of drugs in the system.…”

“…While several studies have shown the added value of combining computational models with multiorgan MPS for data interpretation, these have mainly focused on pharmacokinetic (PK) (Prot et al, 2014;Kimura et al, 2015;Edington et al, 2017; and in some cases pharmacokinetic/pharmacodynamic (PKPD) strategies (Sung et al, 2010;McAleer et al, 2019;Novak et al, 2020), rather than providing mechanistic understanding of the underlying physiology. Some efforts have been done to integrate MPS with more descriptive models, often referred to as quantitative systems pharmacology (QSP) models (van der Graaf and Benson, 2011;Cirit and Stokes, 2018).…”