ライフサイエンスコーパス: drug repurposing

1 -approved drug, is a promising candidate for drug repurposing.

2 ch for both novel disease gene discovery and drug repurposing.

3 knowledge base in disease gene discovery and drug repurposing.

4 derstanding of disease etiology and in rapid drug repurposing.

5 is important for computational approaches to drug repurposing.

6 ns, and opportunities for drug discovery and drug repurposing.

7 sms and can be used to improve computational drug repurposing.

8 as novel pathways that could be targeted via drug repurposing.

9 design of small molecules and biologics, and drug repurposing.

10 tion of novel targets for drug discovery and drug repurposing.

11 (SSRI) class represent prime candidates for drug repurposing.

12 rugs, we identified potential candidates for drug repurposing.

13 improve the prioritization of candidates for drug repurposing.

14 tirely different disease, a concept known as drug repurposing.

15 s, phenotype-based diagnosis of disease, and drug repurposing.

16 ms that may guide disease gene discovery and drug repurposing.

17 in cell-based infectivity assays in Covid-19 drug repurposing.

18 nent targets for therapeutic development and drug repurposing.

19 ed in many biomedical applications including drug repurposing.

20 em, among others, are primary candidates for drug repurposing.

21 used for clinically relevant, evidence-based drug repurposing.

22 l for phenotype-based compound screening and drug repurposing.

23 actable for the development of drugs and for drug repurposing.

24 iral therapeutics at pace, including through drug repurposing.

25 practical applications in lead discovery and drug repurposing.

26 e; therefore, we have also found options for drug repurposing.

27 howcasing insights to facilitate data-driven drug repurposing.

28 generation pipeline for prediction models in drug repurposing.

29 and publications, especially in the field of drug repurposing.

30 ides and gene and cell therapies, as well as drug repurposing.

31 for novel drug targets and possibilities of drug repurposing.

32 nt a novel machine learning-based method for drug repurposing.

33 ressed to help realize the full potential of drug repurposing.

34 s on compound MoA and potential insights for drug repurposing.

35 et the need for improved cancer treatment is drug repurposing.

36 then be targeted by specific therapies) and drug repurposing.

37 e drugs, and providing new opportunities for drug repurposing.

38 hree-step approach for knowledge graph-based drug repurposing: (1) constructing a heterogeneous knowl

39 d recommendations that included (1) enabling drug repurposing, (2) identifying a drug therapy, (3) va

40 tivirals as the most promising compounds for drug repurposing, additional compounds that may have val

41 re precise gut microbiome modulation through drug repurposing, aimed at targeting specific dysbiotic

42 Drug repurposing also has some other advantages such as

43 this Review, we present approaches used for drug repurposing (also known as drug repositioning), dis

44 leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonor

45 Drug repurposing analyses revealed enrichment of targets

46 Bioinformatics drug repurposing analyses with the gene expression biosi

47 es and natural compounds upon bioinformatics drug repurposing analyses, such as calcium folinate and

48 ssion signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible n

49 In silico drug-repurposing analyses highlight several drugs with k

50 We perform drug repurposing analysis and identify compounds that mi

51 A network-based drug repurposing analysis further revealed that everolim

52 Drug repurposing analysis identified anticonvulsants, be

53 Further validating these observations, a drug repurposing analysis identified distinct FDA-approv

54 In silico drug repurposing analysis identified statins as potentia

55 signature, which was used for computational drug repurposing analysis.

56 ug nitrofurantoin were envisioned, employing drug repurposing and biology-oriented drug synthesis, to

57 Lastly, we perform computational drug repurposing and confirm that PUMICE + outperforms o

58 rview of the current approach to early-stage drug repurposing and consider the issues contributing to

59 TT treatment from multiple angles, including drug repurposing and de novo discovery efforts, and disc

60 bioinformatics-driven discovery roadmap for drug repurposing and development in overcoming resistanc

61 g to effective target compound screening for drug repurposing and discovery of putative chemical liga

62 directions for stroke research and ideas for drug repurposing and discovery.

63 tools that leverage gene expression data for drug repurposing and discovery.

64 diseases, pointing to many opportunities for drug repurposing and drug discovery.

65 in various areas such as virtual screening, drug repurposing and identification of potential drug si

66 avitomiX, a novel computational pipeline for drug repurposing and identifying ligands and inhibitors

67 phagy, highlighting potential candidates for drug repurposing and novel treatment strategies.

68 studies and highlight the opportunities for drug repurposing and pharmacogenomics for the treatment

69 rall, these results highlight the utility of drug repurposing and preclinical testing of drug combina

70 a: see text] in various applications such as drug repurposing and similarity search, among others.

71 ioritize drugs and preclinical compounds for drug repurposing and suggest indications and adverse eve

72 Drug repurposing and target identification analyses pred

73 s that offer unprecedented opportunities for drug repurposing and the detection of adverse effects.

74 Zinc in DrugBank identified via research on drug repurposing and the Drug Consensus Score (DCS) for

75 ng gene expressions with drugs/compounds for drug repurposing and translational research.

76 e groundwork for potential opportunities for drug repurposing and translational studies.

77 roteins is crucial for novel drug discovery, drug repurposing and uncovering off-target effects.

78 among known drugs plays an essential role in drug repurposing and understanding of their unexpected s

79 fy compounds with known targets, we screened drug-repurposing and natural product libraries.

80 of NRs, but they also provide a resource for drug-repurposing and precision medicine.

81 arising from off-target effects, comment on drug repurposing, and introduce approaches to the comput

82 ogy detection, structure-function inference, drug repurposing, and other downstream biological tasks.

83 method as an effective pre-screening tool in drug repurposing applications.

84 In summary, we developed an integrated drug repurposing approach and identified five repurposed

85 The portraits were used with the drug repurposing approach of signature matching to ident

86 We trained our drug repurposing approach separately on nine cutaneous d

87 This in-silico drug repurposing approach suggested several compounds th

88 findings provide preclinical evidence that a drug repurposing approach to prevent metastatic disease

89 A computational drug repurposing approach was proposed to predict novel

90 A drug repurposing approach was used to predict surrogate

91 By integrating a signature-driven drug repurposing approach with a pairwise pharmacologica

92 Overall, this multiplex drug repurposing approach, developed and utilized herein

93 By applying HDT and a drug repurposing approach, we demonstrate that (R)-DI-87

94 s in order to fuel a multiplex computational drug repurposing approach.

95 ting evidence for using celecoxib toward the drug-repurposing approach by exploring drug targets.

96 ting evidence for using celecoxib toward the drug-repurposing approach by exploring drug targets.

97 Herein, we followed a drug-repurposing approach to find drugs in a Food and Dr

98 By using an "in silico drug repurposing" approach and by validating our predict

99 Following a "drug repurposing" approach, we tested anti-trypanosomal

100 An emerging class of drug repurposing approaches applies deep learning to str

101 omedical researchers to employ network-based drug repurposing approaches for their individual use cas

102 Further cancer drug repurposing approaches reveal that NVP-AUY922 downr

103 However, thus far, the proposed drug repurposing approaches still need to meet expectati

104 causal inference, outperforming the present drug repurposing approaches.

105 The clinical utility of drug-repurposing artificial intelligence (AI) models rem

106 Outputs help to develop hypotheses about drug repurposing as well as potential side effects.

107 s has significant implications for potential drug repurposing, as baseline renal disease must be cons

108 Drug repurposing attempts to determine new indications f

109 s designed to identify potential targets for drug repurposing based on sub-structural similarity to t

110 Drug repurposing bioinformatics analyses identified the

111 ure directions, dealing with such aspects as drug repurposing, biologicals, multispecific drugs, the

112 For these reasons, drug repurposing - both a less expensive and time-effici

113 Predicting new DTIs can leverage drug repurposing by identifying new targets for approved

114 rning approach, termed deepDR, for in silico drug repurposing by integrating 10 networks: one drug-di

115 e machinery, providing a design strategy for drug repurposing by siderophore modification and heavy-m

116 oning Systems network (GPSnet) algorithm for drug repurposing by specifically targeting disease modul

117 Drug repurposing can be cheaper and faster than developi

118 In contrast, drug repurposing can be introduced to clinical practice

119 In contrast, drug repurposing can significantly accelerate translatio

120 ering novel uses for existing drugs, through drug repurposing, can reduce the time, costs, and risk o

121 Our data identify GA as an attractive drug repurposing candidate to treat infections with Gram

122 e studies identify fluoxetine as a potential drug-repurposing candidate for dry AMD.

123 steogenesis may use silibinin as a potential drug-repurposing candidate for modulating alveolar bone

124 ively, this work provides an overview of RSV drug repurposing candidates and establishes lonafarnib a

125 formation from which a rational selection of drug repurposing candidates can be made.

126 year have led to the discovery of nearly 200 drug repurposing candidates for COVID-19.

127 However, prioritizing drug repurposing candidates for downstream studies remai

128 at offer support for systematic discovery of drug repurposing candidates in oncology are lacking, we

129 sessment reveals several clinically-relevant drug repurposing candidates predicted by the in silico a

130 algorithms for identifying drug targets and drug repurposing candidates.

131 , but also to identify novel combinations of drug repurposing candidates.

132 throughput approach to identify and validate drug repurposing candidates.

133 ine tools have emerged to identify potential drug repurposing candidates.

134 shared MOAs to improve the prioritization of drug repurposing candidates.

135 ilepsy, suggesting they will help prioritize drug repurposing candidates.

136 us, we sought to utilise genetics to propose drug-repurposing candidates that could improve respirato

137 Here, we present a computational approach to drug repurposing, CATNIP, that requires only biological

138 racking could provide a scalable approach to drug repurposing commensurate with the number of Mendeli

139 cal guidelines, many more could benefit from drug repurposing, considering compounds at various stage

140 rch and development of new drugs, a focus on drug repurposing could alleviate this problem by reposit

141 Overall, drug repurposing could become increasingly important as

142 Drug repurposing could provide novel treatment options f

143 data in the downstream applications such as drug repurposing, disease modeling and gene function pre

144 Drug repurposing (DR) is a cost-effective, low-risk, and

145 Drug repurposing (DR) may identify treatments for IR; ho

146 tions are essential for developing in silico drug repurposing (DR) methods and understanding underlyi

147 s (KG) have promise in many tasks, including drug repurposing, drug toxicity prediction and target ge

148 y network providing the opportunity to infer drug repurposing due to transitivity, (viii) remove comp

149 models, case reports, and clinical trials of drug repurposing efficacy in allergic disease are review

150 report a new approach, called DREAM-in-CDM (Drug Repurposing Effort Applying Integrated Modeling-in

151 These mechanisms may guide drug discovery or drug repurposing efforts for hypertension by enhancing R

152 e findings of our original study and may aid drug repurposing efforts in discovering the compound's t

153 on, anticipate adverse events, and assist in drug repurposing efforts.

154 a useful tool to advance drug discovery and drug repurposing efforts.

155 implications for exploring opportunities for drug repurposing, enabling more accurate patient stratif

156 Connectivity Map analysis and drug repurposing experiments identified pyroxamide as a

157 on is a relevant but challenging task in the drug repurposing field.

158 s targeting inflammation already exist, thus drug repurposing for AD is a suitable approach.

159 fidence drug target candidates for potential drug repurposing for ARS.

160 -drug-disease network shows the potential of drug repurposing for cross-organ diseases.

161 r disease and related dementia (ADRD) in the Drug Repurposing for Effective Alzheimer Medicines (DREA

162 ising new drug targets have been identified, drug repurposing for kidney diseases offers numerous adv

163 ting progress towards the key goal of cancer drug repurposing for PIK3CA-driven overgrowth is discuss

164 esting that PPS is a promising candidate for drug repurposing for the treatment of alphavirus-induced

165 e role of CIP2A in OvCa and the potential of drug repurposing for therapeutic interventions.

166 Computational approaches for drug repurposing for viral diseases have mainly focused

167 ry, GPSnet offers a network-based, in silico drug repurposing framework for more efficacious therapeu

168 Genomics-based drug repurposing (GBR) offers the potential of savings i

169 ed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment,

170 Transcriptome-based computational drug repurposing has attracted considerable interest by

171 Drug repurposing has been proposed as a strategy to deve

172 This methodological framework for drug repurposing has broad applicability to other diseas

173 , using biological network-based methods for drug repurposing has generated promising results.

174 Computational drug repurposing has the ability to remarkably reduce dr

175 While empirical drug-repurposing has been a routine practice in clinical

176 libraries and discovered a molecule from the Drug Repurposing Hub-halicin-that is structurally diverg

177 e new classification can be used to generate drug repurposing hypotheses, using Alzheimers disease as

178 The task of drug repurposing hypothesis generation is well-posed as

179 used in a variety of applications, including drug repurposing, identification of drug targets, predic

180 Drug repurposing, identifying novel indications for drug

181 xGNN, a graph foundation model for zero-shot drug repurposing, identifying therapeutic candidates eve

182 Drug repurposing-identifying new therapeutic uses for ap

183 n cancer risk and highlight the potential of drug repurposing in CRC and GC.

184 l models, suggesting that there is scope for drug repurposing in humans.

185 disease, among others, however computational drug repurposing in neurodegenerative disease has presen

186 sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzh

187 Our approach could also reveal insights for drug repurposing in other cancers.

188 Our findings suggest that NRTIs are ripe for drug repurposing in P2X7-driven diseases.

189 examine existing approaches to computational drug repurposing, including molecular, clinical, and bio

190 Drug repurposing is a more cost-effective measure.

191 Drug repurposing is a potential alternative to the class

192 Drug repurposing is a promising strategy for expanding t

193 Drug repurposing is a rational strategy to generate new

194 Drug repurposing is a strategy for identifying new clini

195 Drug repurposing is a viable solution for reducing the t

196 e-wide association results in psychiatry for drug repurposing is an ongoing challenge.

197 urces that has been relatively neglected for drug repurposing is animal model phenotype.

198 Moreover, as drug repurposing is becoming an attractive drug discover

199 ability of DT2Vec as an effective method for drug repurposing is discussed through case studies and e

200 Drug repurposing is increasingly becoming an attractive

201 Drug repurposing is potentially the fastest available op

202 Drug repurposing is the application of approved drugs to

203 The basis of several recent methods for drug repurposing is the key principle that an efficaciou

204 Drug repurposing is the use of a given therapeutic agent

205 ious signature-based in silico approaches to drug repurposing, its integration with multiple omics pl

206 -approved drug-disease indication as well as drug-repurposing knowledge that is crucial for applying

207 Overall, this systematic approach to drug repurposing lays the groundwork to streamline futur

208 oughput chemical screen of the comprehensive drug repurposing library ReFRAME, here we report the ide

209 From a high-content imaging screen of the drug repurposing library ReFRAME, we identified that dip

210 the 12,657 compounds of the Scripps ReFRAME drug repurposing library using a recently developed high

211 ndrial ATP synthase disorders, we screened a drug repurposing library, and applied genomic and bioche

212 clinical decision making, medical diagnosis, drug repurposing, literature-based discovery and hypothe

213 Following a drug repurposing methodology, and taking advantage of a

214 drug therapy compared to two bulk-cell-based drug repurposing methods.

215 rformance of Dr Insight over several popular drug-repurposing methods to detect known cancer drugs an

216 span use cases including COVID-19 research, drug repurposing, microbial-environmental interactions,

217 Early drug repurposing occurred in academia and was based on s

218 the clinical and scientific community to try drug repurposing of existing antiviral agents as a quick

219 Drug repurposing of non-cancer drugs represents an attra

220 Drug repurposing offers a promising strategy to accelera

221 enia gravis carry important implications for drug repurposing opportunities and for future studies of

222 ve and renal-protective drugs and identifies drug repurposing opportunities for kidney disease.

223 Our findings suggest unrealized drug repurposing opportunities or adverse effects relate

224 ng cardiovascular disease risk and potential drug repurposing opportunities.

225 ecular diversity of AD and predict promising drug repurposing opportunities.

226 on of adverse effects, and identification of drug repurposing opportunities.

227 targets for therapy development and critical drug repurposing opportunities.

228 evance to atopic inflammation and some offer drug repurposing opportunities.

229 determined 474 causal proteins, providing 37 drug-repurposing opportunities and 26 promising targets

230 cessed our data to identify novel target and drug-repurposing opportunities including anti-inflammato

231 genetic justification for a number of novel drug-repurposing opportunities that could improve lung f

232 l/psychiatric diseases, and identify several drug-repurposing opportunities.

233 individuals who may benefit from particular drug-repurposing opportunities.

234 t genes highly rated across diseases suggest drug repurposing opportunity, while genes in a particula

235 everal tasks in biomedical research, such as drug repurposing or drug-target identification.

236 Drug repurposing (or repositioning) is a cost-effective

237 ntrast to other network-based approaches for drug repurposing, our approach explicitly takes the dire

238 cient predictive models for DRPs, aiding for drug repurposing, personalized medicine, and new drug di

239 lico toolbox for drug target identification, drug repurposing, phenotypic screening, and side effect

240 ications of computational pocket matching in drug repurposing, polypharmacology and side effects.

241 the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic

242 g response prediction applications including drug repurposing, precision oncology, and new drug devel

243 Next, knowledge graph-based drug repurposing predicted six Food and Drug Administrat

244 We applied an in silico "drug repurposing" procedure for identification of nonste

245 interaction (DTI) is a critical step in the drug repurposing process, which can effectively reduce t

246 Drug repurposing provides a potentially efficient soluti

247 Drug repurposing provides a rapid approach to meet the u

248 In conclusion, ASGARD is a promising drug repurposing recommendation tool guided by single-ce

249 Computation-based drug-repurposing/repositioning approaches can greatly sp

250 Drug repurposing requires distinguishing established dru

251 A drug repurposing screen identifies synthetic lethal inte

252 As a proof-of-concept, we performed a drug repurposing screen of an FDA-approved compound libr

253 ther neurological conditions, we performed a drug repurposing screen of approximately 6,000 compounds

254 Our systematic computational drug repurposing screen predicted that selumetinib, a MA

255 In a drug repurposing screen targeting CYP2J2, the human orth

256 Herein, we performed a drug repurposing screen to identify compounds that selec

257 A drug-repurposing screen identified a subset of protease

258 In this study, we performed a novel drug-repurposing screening to identify Food and Drug Adm

259 Drug repurposing screens identified 2C-targeting compoun

260 Two recent drug repurposing screens identified ITZ as a promising a

261 inhibitors compared to those of the original drug repurposing screens.

262 SARS-CoV-2 activity from several large-scale drug repurposing screens.

263 Drug repurposing significantly reduces development costs

264 Drug repurposing signifies an appealing approach to enha

265 d of drug repurposing, the implementation of drug repurposing still faces important financial and reg

266 Drug repurposing strategies for IBD have had limited cli

267 in the context of clinical trials to develop drug repurposing strategies for patients with urgent med

268 ditionally, normalizing these pathways using drug repurposing strategies represents therapeutic oppor

269 ns on COVID-19 susceptibility and help guide drug-repurposing strategies.

270 speed new medicines to chordoma patients, a drug repurposing strategy represents an attractive appro

271 ual screening by applying a robust in silico drug repurposing strategy.

272 By using a "drug repurposing" strategy, histone deacetylase inhibito

273 Multiple drug repurposing studies for COVID-19 are now underway.

274 ific antiviral drugs has instigated multiple drug repurposing studies to redirect previously approved

275 Most drug repurposing studies using real-world data focused o

276 e type of drug interaction, are important in drug repurposing studies.

277 In a previous drug-repurposing study, we reported that salicylic acid

278 ical studies to validate our method's top 10 drug repurposing suggestions, which have exhibited promi

279 atures, suggesting potential region-specific drug repurposing targets for ad.

280 e detail a few examples from Binding MOAD of drug repurposing targets with their respective similarit

281 , highlighting potential new therapeutic and drug repurposing targets.

282 the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in c

283 Identification of drug-repurposing targets with genetic and biological sup

284 he-art machine learning methods on a general drug repurposing task.

285 s, will have high potential in computational drug repurposing tasks.

286 These drug repurposing techniques have been successful in iden

287 proof-of-concept, we utilize the concept of drug repurposing that is enabled by 3D-REMAP to design d

288 ociations, we uncover novel opportunities of drug repurposing that may benefit cancer treatment throu

289 earch is progressing rapidly in the field of drug repurposing, the implementation of drug repurposing

290 s crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance hum

291 lights the value of novel approaches such as drug repurposing to identify effective antimicrobial age

292 s iguratimod as a valuable new candidate for drug repurposing to MIF-relevant diseases, including mul

293 al. leverage single-cell RNA sequencing and drug repurposing to propose a promising combination ther

294 ative splicing connection," data mining, and drug repurposing to protect B-cells in T1D and then some

295 ufficiency prediction and the development of drug repurposing tools.

296 prediction provides valuable information for drug repurposing, understanding of side effects as well

297 ation and validation of genes as targets for drug repurposing using glioblastoma as an exemplar.

298 provides a workflow for pathway analysis and drug repurposing using GWAS results.

299 Focusing on birinapant for its potential in drug repurposing, we uncovered that IAP inhibitor-induce

300 ofiles can be used to generate hypotheses of drug-repurposing, whereas positively correlated profiles