Bioengineering & Translational Medicine (Jan 2023)

A high‐throughput biomimetic bone‐on‐a‐chip platform with artificial intelligence‐assisted image analysis for osteoporosis drug testing

  • Kyurim Paek,
  • Seulha Kim,
  • Sungho Tak,
  • Min Kyeong Kim,
  • Jubin Park,
  • Seok Chung,
  • Tai Hyun Park,
  • Jeong Ah Kim

DOI
https://doi.org/10.1002/btm2.10313
Journal volume & issue
Vol. 8, no. 1
pp. n/a – n/a

Abstract

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Abstract Although numerous organ‐on‐a‐chips have been developed, bone‐on‐a‐chip platforms have rarely been reported because of the high complexity of the bone microenvironment. With an increase in the elderly population, a high‐risk group for bone‐related diseases such as osteoporosis, it is essential to develop a precise bone‐mimicking model for efficient drug screening and accurate evaluation in preclinical studies. Here, we developed a high‐throughput biomimetic bone‐on‐a‐chip platform combined with an artificial intelligence (AI)‐based image analysis system. To recapitulate the key aspects of natural bone microenvironment, mouse osteocytes (IDG‐SW3) and osteoblasts (MC3T3‐E1) were cocultured within the osteoblast‐derived decellularized extracellular matrix (OB‐dECM) built in a well plate‐based three‐dimensional gel unit. This platform spatiotemporally and configurationally mimics the characteristics of the structural bone unit, known as the osteon. Combinations of native and bioactive ingredients obtained from the OB‐dECM and coculture of two types of bone cells synergistically enhanced osteogenic functions such as osteocyte differentiation and osteoblast maturation. This platform provides a uniform and transparent imaging window that facilitates the observation of cell–cell interactions and features high‐throughput bone units in a well plate that is compatible with a high‐content screening system, enabling fast and easy drug tests. The drug efficacy of anti‐SOST antibody, which is a newly developed osteoporosis drug for bone formation, was tested via β‐catenin translocation analysis, and the performance of the platform was evaluated using AI‐based deep learning analysis. This platform could be a cutting‐edge translational tool for bone‐related diseases and an efficient alternative to bone models for the development of promising drugs.

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