2020
DOI: 10.3390/molecules25051150
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Unprecedented Potential for Neural Drug Discovery Based on Self-Organizing hiPSC Platforms

Abstract: Human induced pluripotent stem cells (hiPSCs) have transformed conventional drug discovery pathways in recent years. In particular, recent advances in hiPSC biology, including organoid technologies, have highlighted a new potential for neural drug discovery with clear advantages over the use of primary tissues. This is important considering the financial and social burden of neurological health care worldwide, directly impacting the life expectancy of many populations. Patient-derived iPSCs-neurons are invalua… Show more

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Cited by 9 publications
(7 citation statements)
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References 65 publications
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“…hiPSCs are especially relevant to neural tissue engineering since brain cells from patients are rarely available for research. hiPSC-derived neural tissues could become a powerful diagnostic and prognostic tool for drug screening [60][61][62]. Additionally, bioinks can efficiently mimic the extracellular matrix found in brain tissue.…”
Section: Introductionmentioning
confidence: 99%
“…hiPSCs are especially relevant to neural tissue engineering since brain cells from patients are rarely available for research. hiPSC-derived neural tissues could become a powerful diagnostic and prognostic tool for drug screening [60][61][62]. Additionally, bioinks can efficiently mimic the extracellular matrix found in brain tissue.…”
Section: Introductionmentioning
confidence: 99%
“…Region-specific neural organoids can be created by the differentiation of hiPSC [ 40 ]. These organoids can recapitulate distinct brain regions that arise during human brain development, as it has been shown in cortical plate [ 41 ], forebrain [ 42 ], midbrain [ 43 ], and hypothalamic organoids [ 44 ].…”
Section: Brain Organoids To Investigate Brain Disordersmentioning
confidence: 99%
“…For example, similar systems have already been employed clinically in the estimation of survival prognosis in patients diagnosed with eye melanoma (Damato et al, 2008), thyroid cancer (Mourad et al, 2020), glioblastoma multiforme (Hao et al, 2018), among other diseases (Kourou et al, 2015;Zhu et al, 2020). Indeed, AI-based technologies can be wisely applied to compile, digest and interpret "hidden knowledge" in large datasets and make the data usable to researchers in the ALS field and beyond (Ko et al, 2014;Kusumoto and Yuasa, 2019;Cota-Coronado et al, 2020;Zhou and Manser, 2020).…”
Section: Challenges and Future Perspectivesmentioning
confidence: 99%