人胚胎干细胞分化的心肌细胞心脏毒性评价模型构建
Management and Research on Scientific & Technological Achievements（2016）
Abstract
药物引发的心脏毒性是导致新药开发终止的主要因素，也是药物撤市的主要原因。在因安全问题撤市的药物中，心脏毒性占据45%。药物引起的心脏毒性主要表现在对心脏电生理功能的影响以及对生理功能和组织结构的影响，前者主要引起心肌除极化、复极化的异常，后者通过作用于心肌组织引起心脏毒性。因此，在药物研发早期阶段对其心脏毒性进行评估具有重要意义。近年来，有关人胚胎干细胞诱导分化的心肌细胞（hESC-CM）的研究越来越多，其可能成为一种有效的新型模型，用于评价药物的心脏毒性。为了验证hESC-CM用于药物安全性评价的可行性，国家药物安全评价监测中心主任汪巨峰研究员团队在北京市课题的支持下建立了药物心脏毒性评价模型，并应用此模型评价化合物的心脏毒性。
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined