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Updated: Jun 29, 2025
A High-content In Vitro Pancreatic Islet β-cell Replication Discovery Platform
Published on: July 16, 2016
High-Throughput Methods for the Discovery of Small Molecule Modulators of Pancreatic Beta-Cell Function and
Sean M McCarty1,2, Martin C Clasby1, Jonathan Z Sexton1,2
1Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA.
Abstract:
The progression of type II diabetes (T2D) is characterized by a complex and highly variable loss of beta-cell mass, resulting in impaired insulin secretion. Many T2D drug discovery efforts aimed at discovering molecules that can protect or restore beta-cell mass and function have been developed using limited beta-cell lines and primary rodent/human pancreatic islets. Various high-throughput screening methods have been used in the context of drug discovery, including luciferase-based reporter assays, glucose-stimulated insulin secretion, and high-content screening. In this context, a cornerstone of small molecule discovery has been the use of immortalized rodent beta-cell lines. Although insightful, this usage has led to a more comprehensive understanding of rodent beta-cell proliferation pathways rather than their human counterparts. Advantages gained in enhanced physiological relevance are offered by three-dimensional (3D) primary islets and pseudoislets in contrast to monolayer cultures, but these approaches have been limited to use in low-throughput experiments. Emerging methods, such as high-throughput 3D islet imaging coupled with machine learning, aim to increase the feasibility of integrating 3D microtissue structures into high-throughput screening. This review explores the current methods used in high-throughput screening for small molecule modulators of beta-cell mass and function, a potentially pivotal strategy for diabetes drug discovery.
Insights
Type II diabetes (T2D) involves beta-cell loss. This review examines high-throughput screening methods for discovering drugs that protect or restore beta-cell mass and function, crucial for diabetes treatment.
Area of Science:
- Endocrinology
- Pharmacology
- Cell Biology
Background:
- Type II diabetes (T2D) is marked by progressive beta-cell dysfunction and loss, impairing insulin secretion.
- Current T2D drug discovery relies heavily on limited beta-cell models, often yielding insights not directly applicable to human physiology.
- Rodent beta-cell lines, while useful, primarily illuminate rodent-specific proliferation pathways, limiting translational relevance.
Purpose of the Study:
- To review current high-throughput screening (HTS) methods for identifying small molecules that modulate beta-cell mass and function.
- To highlight the limitations of traditional screening models and the potential of emerging 3D microtissue approaches.
- To discuss the strategic importance of HTS in advancing diabetes drug discovery.
Main Methods:
- Exploration of established HTS techniques: luciferase reporter assays, glucose-stimulated insulin secretion (GSIS), and high-content screening.
- Evaluation of 3D primary islets and pseudoislets for enhanced physiological relevance compared to 2D monolayer cultures.
- Discussion of novel methods integrating high-throughput 3D islet imaging and machine learning for scalable screening.
Main Results:
- Traditional HTS methods using rodent beta-cell lines have advanced understanding of rodent pathways but lack human relevance.
- 3D primary islet and pseudoislet cultures offer greater physiological fidelity but are typically low-throughput.
- Emerging technologies combining 3D imaging and AI show promise for high-throughput screening of 3D microtissues.
Conclusions:
- There is a critical need for HTS methods that accurately reflect human beta-cell biology for effective T2D drug discovery.
- Advancements in 3D culture and imaging technologies, coupled with machine learning, are paving the way for more physiologically relevant HTS.
- Integrating these novel approaches into drug discovery pipelines is pivotal for developing novel therapeutics for T2D.
