{"title":"基于云应用和协作空间的开放式创新平台:溶解度预测模型开发的案例研究","authors":"Tsuyoshi Esaki, Keiko Kumazawa, Kazutoshi Takahashi, Reiko Watanabe, Tomohide Masuda, Hirofumi Watanabe, Yugo Shimizu, A. Okada, Seisuke Takimoto, Tomohiro Shimada, Kazuyoshi Ikeda","doi":"10.1273/cbij.20.5","DOIUrl":null,"url":null,"abstract":"In recent years, with the emergence of new technologies employing information science, open innovation and collaborative drug discovery research, utilizing biological and chemical experimental data, have been actively conducted. The Young Researcher Association of Chem-Bio Informatics Society (“CBI Wakate”) has constructed an online discussion space using Slack and provided a cloud-based collaborative platform in which researchers have freely discussed specific issues and aimed at raising the level of cross-sectoral communication regarding technology and knowledge. On this platform, we created three channels—dataset, model evaluation and scripts—where participants with different backgrounds co-developed a solution for solubility prediction. In the dataset channel, we exchanged our knowledge and Chem-Bio Informatics Journal, Vol.20, pp.5–18 (2020) 6 methodology for calculations using the chemical descriptors for the original dataset and also discussed methods to improve the dataset for pharmaceutical purposes. We have also developed a protocol for evaluating the applicability of solubility prediction models for drug discovery by using the ChEMBL database and for sharing the dataset among users on the cloud. In the model evaluation channel, we discussed the necessary conditions for the prediction model to be used in daily drug discovery research. We examined the effect of these discussions on script development and suggested future improvements. This study provides an example of a new cloud-based open collaboration that can be useful for various projects in the early stage of drug discovery.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"12 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Open Innovation Platform using Cloud-based Applications and Collaborative Space: A Case Study of Solubility Prediction Model Development\",\"authors\":\"Tsuyoshi Esaki, Keiko Kumazawa, Kazutoshi Takahashi, Reiko Watanabe, Tomohide Masuda, Hirofumi Watanabe, Yugo Shimizu, A. Okada, Seisuke Takimoto, Tomohiro Shimada, Kazuyoshi Ikeda\",\"doi\":\"10.1273/cbij.20.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, with the emergence of new technologies employing information science, open innovation and collaborative drug discovery research, utilizing biological and chemical experimental data, have been actively conducted. The Young Researcher Association of Chem-Bio Informatics Society (“CBI Wakate”) has constructed an online discussion space using Slack and provided a cloud-based collaborative platform in which researchers have freely discussed specific issues and aimed at raising the level of cross-sectoral communication regarding technology and knowledge. On this platform, we created three channels—dataset, model evaluation and scripts—where participants with different backgrounds co-developed a solution for solubility prediction. In the dataset channel, we exchanged our knowledge and Chem-Bio Informatics Journal, Vol.20, pp.5–18 (2020) 6 methodology for calculations using the chemical descriptors for the original dataset and also discussed methods to improve the dataset for pharmaceutical purposes. We have also developed a protocol for evaluating the applicability of solubility prediction models for drug discovery by using the ChEMBL database and for sharing the dataset among users on the cloud. In the model evaluation channel, we discussed the necessary conditions for the prediction model to be used in daily drug discovery research. We examined the effect of these discussions on script development and suggested future improvements. This study provides an example of a new cloud-based open collaboration that can be useful for various projects in the early stage of drug discovery.\",\"PeriodicalId\":40659,\"journal\":{\"name\":\"Chem-Bio Informatics Journal\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2020-04-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chem-Bio Informatics Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1273/cbij.20.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chem-Bio Informatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1273/cbij.20.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Open Innovation Platform using Cloud-based Applications and Collaborative Space: A Case Study of Solubility Prediction Model Development
In recent years, with the emergence of new technologies employing information science, open innovation and collaborative drug discovery research, utilizing biological and chemical experimental data, have been actively conducted. The Young Researcher Association of Chem-Bio Informatics Society (“CBI Wakate”) has constructed an online discussion space using Slack and provided a cloud-based collaborative platform in which researchers have freely discussed specific issues and aimed at raising the level of cross-sectoral communication regarding technology and knowledge. On this platform, we created three channels—dataset, model evaluation and scripts—where participants with different backgrounds co-developed a solution for solubility prediction. In the dataset channel, we exchanged our knowledge and Chem-Bio Informatics Journal, Vol.20, pp.5–18 (2020) 6 methodology for calculations using the chemical descriptors for the original dataset and also discussed methods to improve the dataset for pharmaceutical purposes. We have also developed a protocol for evaluating the applicability of solubility prediction models for drug discovery by using the ChEMBL database and for sharing the dataset among users on the cloud. In the model evaluation channel, we discussed the necessary conditions for the prediction model to be used in daily drug discovery research. We examined the effect of these discussions on script development and suggested future improvements. This study provides an example of a new cloud-based open collaboration that can be useful for various projects in the early stage of drug discovery.