한빛사 논문
Yoojin Seoa,1, Seokyoung Banga,1, Jeongtae Sonb, Dongsup Kimb, Yong Jeongb, Pilnam Kimb, Jihun Yangc, Joon-Ho Eomd, Nakwon Choia,e,f,*, Hong Nam Kima,e,g,h,*
aBrain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
bDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
cNext&Bio Inc., Seoul, 02841, Republic of Korea
dMedical Device Research Division, National Institute of Food and Drug Safety Evaluation, Cheongju, 28159, Republic of Korea
eDivision of Bio-Medical Science & Technology, KIST School, Korea University of Science and Technology (UST), Seoul, 02792, Republic of Korea
fKU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, 02841, Republic of Korea
gSchool of Mechanical Engineering, Yonsei University, Seoul, 03722, Republic of Korea
hYonsei-KIST Convergence Research Institute, Yonsei University, Seoul, 03722, Republic of Korea
1These authors contributed equally to this study.
*Corresponding author
Abstract
In the last few decades, adverse reactions to pharmaceuticals have been evaluated using 2D in vitro models and animal models. However, with increasing computational power, and as the key drivers of cellular behavior have been identified, in silico models have emerged. These models are time-efficient and cost-effective, but the prediction of adverse reactions to unknown drugs using these models requires relevant experimental input. Accordingly, the physiome concept has emerged to bridge experimental datasets with in silico models. The brain physiome describes the systemic interactions of its components, which are organized into a multilevel hierarchy. Because of the limitations in obtaining experimental data corresponding to each physiome component from 2D in vitro models and animal models, 3D in vitro brain models, including brain organoids and brain-on-a-chip, have been developed. In this review, we present the concept of the brain physiome and its hierarchical organization, including cell- and tissue-level organizations. We also summarize recently developed 3D in vitro brain models and link them with the elements of the brain physiome as a guideline for dataset collection. The connection between in vitro 3D brain models and in silico modeling will lead to the establishment of cost-effective and time-efficient in silico models for the prediction of the safety of unknown drugs.
Keywords : Brain physiome, In vitro 3D platform, Brain organoid, Brain-on-a-chip, In silico model
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