Clinical trials, progression-speed differentiating features and swiftness rule of the innovative targets of first-in-class drugs

Author:

Li Ying Hong12,Li Xiao Xu12,Hong Jia Jun1,Wang Yun Xia1,Fu Jian Bo1,Yang Hong2,Yu Chun Yan2,Li Feng Cheng1,Hu Jie3,Xue Wei Wei2,Jiang Yu Yang4,Chen Yu Zong5,Zhu Feng12

Affiliation:

1. Lab of Innovative Drug Research and Bioinformatics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China

2. Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China

3. School of International Studies, Zhejiang University, Hangzhou, China

4. State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Biology, The Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong, China

5. Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Singapore, Singapore

Abstract

Abstract Drugs produce their therapeutic effects by modulating specific targets, and there are 89 innovative targets of first-in-class drugs approved in 2004–17, each with information about drug clinical trial dated back to 1984. Analysis of the clinical trial timelines of these targets may reveal the trial-speed differentiating features for facilitating target assessment. Here we present a comprehensive analysis of all these 89 targets, following the earlier studies for prospective prediction of clinical success of the targets of clinical trial drugs. Our analysis confirmed the literature-reported common druggability characteristics for clinical success of these innovative targets, exposed trial-speed differentiating features associated to the on-target and off-target collateral effects in humans and further revealed a simple rule for identifying the speedy human targets through clinical trials (from the earliest phase I to the 1st drug approval within 8 years). This simple rule correctly identified 75.0% of the 28 speedy human targets and only unexpectedly misclassified 13.2% of 53 non-speedy human targets. Certain extraordinary circumstances were also discovered to likely contribute to the misclassification of some human targets by this simple rule. Investigation and knowledge of trial-speed differentiating features enable prioritized drug discovery and development.

Funder

Fundamental Research Funds for the Central Universities

Innovation Project on Industrial Generic Key Technologies of Chongqing

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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