Developing effective drugs for Alzheimer’s disease (AD), the most common cause of dementia, has been difficult because of complicated pathogenesis. Here, we report an efficient, network-based drug-screening platform developed by integrating mathematical modeling and the pathological features of AD with human iPSC-derived cerebral organoids (iCOs), including CRISPR-Cas9-edited isogenic lines. We use 1300 organoids from 11 participants to build a high-content screening (HCS) system and test blood–brain barrier-permeable FDA-approved drugs. Our study provides a strategy for precision medicine through the convergence of mathematical modeling and a miniature pathological brain model using iCOs.

Summary The brain controls various cognitive functions in a robust and efficient way. What is the control architecture of brain networks that enables such robust and optimal control? Is this brain control architecture distinct from that of other complex networks? Here, we developed a framework to delineate a control architecture of a complex network that is compatible with the behavior of the network and applied the framework to structural brain networks and other complex networks. As a result, we revealed that the brain networks have a distributed and overlapping control architecture governed by a small number of control nodes, which may be responsible for the robust and efficient brain functions. Moreover, our artificial network evolution analysis showed that the distributed and overlapping control architecture of the brain network emerges when it evolves toward increasing both robustness and efficiency.

Background: Developing effective drugs for Alzheimer's disease (AD), the most common cause of dementia, has been difficult because of complicated pathogenesis. The difficulty of acquiring human brain samples and the lack of a disease model that adequately recapitulates the pathological hallmarks pose significant challenges in the field.Method: Here, we report an efficient, network-based drug-screening platform developed by integrating mathematical modelling and the pathological features of AD with human iPSC-derived cerebral organoids (iCOs), including CRISPR-Cas9-edited isogenic lines. We use 1,300 organoids from 11 participants to build a high-content screening (HCS) system and test blood-brain barrier-permeable FDA-approved drugs.Result: Our results confirmed that our iCOs had pathological features of AD, and thus could be an appropriate model reflecting characteristics of the actual disease-related human brain lesions. Also, We completed the construction and validation of the molecular regulatory network model for AD. We proposed candidate drugs based on systems analysis of the dynamical network model with detailed regulatory mechanisms.We found that all of the candidate drugs were effective to some degree in reducing Aβ or tau deposition and enhancing or maintaining neuronal cell viability. Conclusion:Our study provides a strategy for precision medicine through the convergence of mathematical modelling and a miniature pathological brain model using iCOs.With further generation of the iCOs or iPSC-derived microglia (iMG) from various types of AD patients, our approach may propose strategies for the precision medicine therapy.