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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.

In recent years, as gene therapy technology has rapidly developed, there has been growing concern that it could be misused by athletes as a means of doping. However, current testing methods for gene doping have a range of limitations and require further improvement. Furthermore, significant progress has been made in the fields of blood storage, next-generation sequencing (NGS), and LabDroid (experimental robots). Against this background, this study was implemented to develop a test method for gene doping using dried blood spot (DBS), NGS, and the LabDroid ”Maholo”. As a first step, recombinant adeno-associated virus containing the human erythropoietin gene (hEPO) was injected into mice to establish a gene doping model. Subsequently, DBS was created using whole blood. Maholo was used to extract DNA from the DBS and to create DNA libraries for NGS. NGS in combination with bioinformatic analysis clearly identified DNA fragments that provided definitive evidence of gene doping in the mouse model, which were absent in the control mouse. To the best of our knowledge, this is the first attempt to use a biological model of hEPO gene doping in conjunction with Maholo, NGS, and DBS. This method should facilitate the further development of gene doping tests.

An automated platform for cell culture combines robotics and artificial intelligence to optimize cell culture protocols and reliably produce specific cell types that could be used for regenerative medicine treatments.