DRESIS: the first comprehensive landscape of drug resistance information

Author:

Sun Xiuna12,Zhang Yintao1,Li Hanyang1,Zhou Ying3,Shi Shuiyang1,Chen Zhen1,He Xin14,Zhang Hanyu1ORCID,Li Fengcheng1,Yin Jiayi1,Mou Minjie1ORCID,Wang Yunzhu1,Qiu Yunqing3,Zhu Feng12ORCID

Affiliation:

1. College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University , Hangzhou 310058, China

2. Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba–Zhejiang University Joint Research Center of Future Digital Healthcare , Hangzhou 330110, China

3. The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University , Hangzhou 310058, China

4. Zhejiang University–University of Edinburgh Institute, Zhejiang University , Haining 314499, China

Abstract

Abstract Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named ‘DRESIS’ was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/

Funder

Natural Science Foundation of Zhejiang Province

National Natural Science Foundation of China

National High-Level Talents Special Support Plan of China

Fundamental Research Fund of Central University

Key R&D Program of Zhejiang Province

Chinese ‘Double Top-Class’ Universities

Westlake Laboratory

Alibaba-Zhejiang University

Alibaba Cloud

Information Tech Center of Zhejiang University

Publisher

Oxford University Press (OUP)

Subject

Genetics

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