Establishment of a Robust Platform for Induced Pluripotent Stem Cell Research Using Maholo LabDroid

Author:

Sasamata Miho1,Shimojo Daisuke1,Fuse Hiromitsu2,Nishi Yohei2,Sakurai Hidetoshi2,Nakahata Tatsutoshi2,Yamagishi Yukiko12,Sasaki-Iwaoka Haruna1

Affiliation:

1. Drug Discovery Research, Astellas Pharma Inc., Tsukuba-shi, Ibaraki, Japan

2. Center for iPS Cell Research and Application (CiRA), Kyoto University, Sakyo-ku, Kyoto, Japan

Abstract

Induced pluripotent stem cells (iPSCs) are attractive for use in early drug discovery because they can differentiate into any cell type. Maintenance cultures and differentiation processes for iPSCs, however, require a high level of technical expertise. To overcome this problem, technological developments such as enhanced automation are necessary to replace manual operation. In addition, a robot system with the flexibility and expandability to carry out maintenance culture and each of the required differentiation processes would also be important. In this study, we established a platform to enable the multiple processes required for iPSC experiments using the Maholo LabDroid, which is a humanoid robotic system with excellent reproducibility and flexibility. The accuracy and robustness of Maholo LabDroid enabled us to cultivate undifferentiated iPSCs for 63 days while maintaining their ability to differentiate into the three embryonic germ layers. Maholo LabDroid maintained and harvested iPSCs in six-well plates, then seeded them into 96-well plates, induced differentiation, and implemented immunocytochemistry. As a result, Maholo LabDroid was confirmed to be able to perform the processes required for myogenic differentiation of iPSCs isolated from a patient with muscular disease and achieved a high differentiation rate with a coefficient of variation (CV) <10% in the first trial. Furthermore, the expandability and flexibility of Maholo LabDroid allowed us to experiment with multiple cell lines simultaneously.

Funder

Japan Agency for Medical Research and Development

Publisher

Elsevier BV

Subject

Medical Laboratory Technology,Computer Science Applications

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