Robotic search for optimal cell culture in regenerative medicine

Elife. 2022 Jun 28:11:e77007. doi: 10.7554/eLife.77007.

Abstract

Induced differentiation is one of the most experience- and skill-dependent experimental processes in regenerative medicine, and establishing optimal conditions often takes years. We developed a robotic AI system with a batch Bayesian optimization algorithm that autonomously induces the differentiation of induced pluripotent stem cell-derived retinal pigment epithelial (iPSC-RPE) cells. From 200 million possible parameter combinations, the system performed cell culture in 143 different conditions in 111 days, resulting in 88% better iPSC-RPE production than that obtained by the pre-optimized culture in terms of the pigmentation scores. Our work demonstrates that the use of autonomous robotic AI systems drastically accelerates systematic and unbiased exploration of experimental search space, suggesting immense use in medicine and research.

Keywords: LabDroid; bayesian optimization; computational biology; human; iPS cell; laboratory automation; regenerative medicine; retinal pigment epithelium; stem cells; systems biology.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Cell Culture Techniques / methods
  • Cell Differentiation
  • Induced Pluripotent Stem Cells*
  • Regenerative Medicine
  • Retinal Pigment Epithelium
  • Robotic Surgical Procedures*

Grants and funding

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.