亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

A demand-offer critical analysis of current drug development. Phase I drugs versus TCGA sequencing data

电流(流体) 药品 药物开发 医学 计算生物学 药理学 生物 工程类 电气工程
作者
Matteo Repetto,Edoardo Crimini,Carmen Belli,Luca Boscolo Bielo,Liliana Ascione,Funda Meric‐Bernstam,Alexander Drilon,Giuseppe Curigliano
出处
期刊:European Journal of Cancer [Elsevier BV]
卷期号:190: 112958-112958
标识
DOI:10.1016/j.ejca.2023.112958
摘要

Phase I clinical trials have become increasingly critical to regulatory approvals of novel agents. In phase I drug development, a global problem of unknown magnitude is the multiplicity of similar drugs being investigated against the same target, colloquially known as the 'me too' phenomenon.Ranging from December 2020 to December 2022 we annotated phase I clinical trials present on clinicaltrials.gov. Public databases were queried for annotation of investigational agents (IAs). Extensive literature research and data mining were performed to annotate agents not present in public databases. The Cancer Genome Atlas (TCGA) pan-cancer sequencing cohort was used to perform second-level analyses to evaluate tumour types with a higher number of IA matches.A total of 1054 unique drug targets were identified. The most frequent IA classes were: cell products (1223), small-molecule inhibitors (1110), antibodies (733), and vaccines (346). Only a minority (8.9%) of phase I IAs were explored against a target without a competitive agent; 7% of agents shared targets with 2-3 other agents. Unfortunately, the majority (84%) shared targets with at least four other agents. Using data from the TCGA pan-cancer sequencing potentially underserved histologies were identified. Analysis of alteration-IA matches revealed potentially frequent and unexplored alterations in many tumour types.The majority of IAs (86%) shared targets with at least three other agents. We argue that these duplicative efforts could be redirected toward unmet needs instead.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
月半小夜曲完成签到 ,获得积分10
刚刚
3秒前
5秒前
6秒前
7秒前
7秒前
polestar发布了新的文献求助10
8秒前
8秒前
9秒前
风景园林发布了新的文献求助10
10秒前
哈哈哈哈完成签到,获得积分10
10秒前
怡然芷蝶发布了新的文献求助10
11秒前
kun1376发布了新的文献求助10
13秒前
雪雪儿发布了新的文献求助10
14秒前
哈哈哈哈发布了新的文献求助10
15秒前
Criminology34应助Bin_Liu采纳,获得10
16秒前
19秒前
潇洒的嵩完成签到,获得积分10
22秒前
dyjjudy完成签到,获得积分10
24秒前
CipherSage应助白河采纳,获得20
25秒前
雪雪儿完成签到,获得积分10
29秒前
小洪完成签到,获得积分10
31秒前
31秒前
Criminology34应助xiaomo采纳,获得10
32秒前
34秒前
Renaissance完成签到 ,获得积分10
35秒前
英俊的铭应助风景园林采纳,获得10
37秒前
37秒前
爱笑的路灯完成签到,获得积分10
40秒前
40秒前
白河发布了新的文献求助20
40秒前
cdercder应助科研通管家采纳,获得10
42秒前
cdercder应助科研通管家采纳,获得10
42秒前
42秒前
香蕉觅云应助科研通管家采纳,获得10
42秒前
42秒前
cdercder应助科研通管家采纳,获得10
42秒前
共享精神应助科研通管家采纳,获得10
42秒前
cdercder应助科研通管家采纳,获得10
42秒前
44秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
内視鏡的に摘除しえた十二指腸乳頭部腫瘍の2例 660
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Positive Obsession: The Life and Times of Octavia E. Butler 500
Interpolation and Regression Models for the Chemical Engineer: Solving Numerical Problems 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7687668
求助须知:如何正确求助?哪些是违规求助? 9250588
关于积分的说明 19963645
捐赠科研通 7260646
什么是DOI,文献DOI怎么找? 3289878
关于科研通互助平台的介绍 2446781
邀请新用户注册赠送积分活动 2294522