Multiplexed microfluidic platform for stem-cell derived pancreatic islet β cells

Global Literature Analysis of Organoid and Organ-on-Chip Research

Organoids and cells in organ-on-chip platforms replicate higher-level anatomical, physiological, or pathological states of tissues and organs. These technologies are widely regarded by academia, the pharmacological industry and regulators as key biomedical developments. To map advances in this emerging field, a literature analysis of 16,000 article metadata based on a quality-controlled text-mining algorithm is performed. The analysis covers titles, keywords, and abstracts of categorized academic publications in the literature and preprint databases published after 2010. The algorithm identifies and tracks 149 and 107 organs or organ substructures modeled as organoids and organ-on-chip, respectively, stem cell sources, as well as 130 diseases, and 16 groups of organisms other than human and mouse in which organoid/organ-on-chip technology is applied. The analysis illustrates changing diversity and focus in organoid/organ-on-chip research and captures its geographical distribution. The downloadable dataset provided is a robust framework for researchers to interrogate with their own questions.

AI-Powered Microfluidics: Shaping the Future of Phenotypic Drug Discovery

Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents numerous opportunities for augmenting phenotypic drug screening on microfluidic platforms, leveraging its predictive capabilities, data analysis, efficient data processing, etc. Microfluidics coupled with AI is poised to revolutionize the landscape of phenotypic drug discovery. By integrating advanced microfluidic platforms with AI algorithms, researchers can rapidly screen large libraries of compounds, identify novel drug candidates, and elucidate complex biological pathways with unprecedented speed and efficiency. This review provides an overview of recent advances and challenges in AI-based microfluidics and their applications in drug discovery. We discuss the synergistic combination of microfluidic systems for high-throughput screening and AI-driven analysis for phenotype characterization, drug-target interactions, and predictive modeling. In addition, we highlight the potential of AI-powered microfluidics to achieve an automated drug screening system. Overall, AI-powered microfluidics represents a promising approach to shaping the future of phenotypic drug discovery by enabling rapid, cost-effective, and accurate identification of therapeutically relevant compounds.

Identification of unique cell type responses in pancreatic islets to stress

Diabetes involves the death or dysfunction of pancreatic β-cells. Analysis of bulk sequencing from human samples and studies using in vitro and in vivo models suggest that endoplasmic reticulum and inflammatory signaling play an important role in diabetes progression. To better characterize cell type-specific stress response, we perform multiplexed single-cell RNA sequencing to define the transcriptional signature of primary human islet cells exposed to endoplasmic reticulum and inflammatory stress. Through comprehensive pair-wise analysis of stress responses across pancreatic endocrine and exocrine cell types, we define changes in gene expression for each cell type under different diabetes-associated stressors. We find that β-, α-, and ductal cells have the greatest transcriptional response. We utilize stem cell-derived islets to study islet health through the candidate gene CIB1, which was upregulated under stress in primary human islets. Our findings provide insights into cell type-specific responses to diabetes-associated stress and establish a resource to identify targets for diabetes therapeutics.

Cell identity dynamics and insight into insulin secretagogues when employing stem cell-derived islets for disease modeling

Stem cell-derived islets (SC-islets) are not only an unlimited source for cell-based therapy of type 1 diabetes but have also emerged as an attractive material for modeling diabetes and conducting screening for treatment options. Prior to SC-islets becoming the established standard for disease modeling and drug development, it is essential to understand their response to various nutrient sources in vitro. This study demonstrates an enhanced efficiency of pancreatic endocrine cell differentiation through the incorporation of WNT signaling inhibition following the definitive endoderm stage. We have identified a tri-hormonal cell population within SC-islets, which undergoes reduction concurrent with the emergence of elevated numbers of glucagon-positive cells during extended in vitro culture. Over a 6-week period of in vitro culture, the SC-islets consistently demonstrated robust insulin secretion in response to glucose stimulation. Moreover, they manifested diverse reactivity patterns when exposed to distinct nutrient sources and exhibited deviant glycolytic metabolic characteristics in comparison to human primary islets. Although the SC-islets demonstrated an aberrant glucose metabolism trafficking, the evaluation of a potential antidiabetic drug, pyruvate kinase agonist known as TEPP46, significantly improved in vitro insulin secretion of SC-islets. Overall, this study provided cell identity dynamics investigation of SC-islets during prolonged culturing in vitro, and insights into insulin secretagogues. Associated advantages and limitations were discussed when employing SC-islets for disease modeling.

Emerging approaches for the development of artificial islets

The islet of Langerhans, functioning as a "mini organ", plays a vital role in regulating endocrine activities due to its intricate structure. Dysfunction in these islets is closely associated with the development of diabetes mellitus (DM). To offer valuable insights for DM research and treatment, various approaches have been proposed to create artificial islets or islet organoids with high similarity to natural islets, under the collaborative effort of biologists, clinical physicians, and biomedical engineers. This review investigates the design and fabrication of artificial islets considering both biological and tissue engineering aspects. It begins by examining the natural structures and functions of native islets and proceeds to analyze the protocols for generating islets from stem cells. The review also outlines various techniques used in crafting artificial islets, with a specific focus on hydrogel-based ones. Additionally, it provides a concise overview of the materials and devices employed in the clinical applications of artificial islets. Throughout, the primary goal is to develop artificial islets, thereby bridging the realms of developmental biology, clinical medicine, and tissue engineering.

Twenty years of islet-on-a-chip: microfluidic tools for dissecting islet metabolism and function

Pancreatic islets are metabolically active micron-sized tissues responsible for controlling blood glucose through the secretion of insulin and glucagon. A loss of functional islet mass results in type 1 and 2 diabetes. Islet-on-a-chip devices are powerful microfluidic tools used to trap and study living ex vivo human and murine pancreatic islets and potentially stem cell-derived islet organoids. Devices developed over the past twenty years offer the ability to treat islets with controlled and dynamic microenvironments to mimic in vivo conditions and facilitate diabetes research. In this review, we explore the various islet-on-a-chip devices used to immobilize islets, regulate the microenvironment, and dynamically detect islet metabolism and insulin secretion. We first describe and assess the various methods used to immobilize islets including chambers, dam-walls, and hydrodynamic traps. We subsequently describe the surrounding methods used to create glucose gradients, enhance the reaggregation of dispersed islets, and control the microenvironment of stem cell-derived islet organoids. We focus on the various methods used to measure insulin secretion including capillary electrophoresis, droplet microfluidics, off-chip ELISAs, and on-chip fluorescence anisotropy immunoassays. Additionally, we delve into the various multiparametric readouts (NAD(P)H, Ca2+-activity, and O2-consumption rate) achieved primarily by adopting a microscopy-compatible optical window into the devices. By critical assessment of these advancements, we aim to inspire the development of new devices by the microfluidics community and accelerate the adoption of islet-on-a-chip devices by the wider diabetes research and clinical communities.