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

TLDR
A comprehensive analysis of all 89 innovative targets of first-in-class drugs approved in 2004–17 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 revealed a simple rule for identifying the speedy human targets through clinical trials.
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.

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Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics

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Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents.

TL;DR: In this article, a major update of the Therapeutic Target Database, previously featured in NAR, was introduced, which includes poor binders and non-binders for developing discovery tools, prodrugs for improved therapeutics, co-targets of therapeutic targets for multi-target strategies and off-target investigations, and collective structureactivity and drug-likeness landscapes of enhanced drug feature.
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Consistent gene signature of schizophrenia identified by a novel feature selection strategy from comprehensive sets of transcriptomic data.

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Crystal structure of the Jak3 kinase domain in complex with a staurosporine analog. Commentary

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NOREVA: enhanced normalization and evaluation of time-course and multi-class metabolomic data.

TL;DR: NOREVA 2.0 is distinguished for its capability in identifying well-performing normalization method(s) for time-course and multi-class metabolomics, which makes it an indispensable complement to other available tools.
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