ライフサイエンスコーパス: drug interaction

1 ry outcome was lack of a clinically relevant drug interaction.

2 pore corroborated cationic permeability and drug interaction.

3 uble stranded deoxyribonucleic acid (ds-DNA)/drug interaction.

4 tly with cangrelor without any apparent drug-drug interaction.

5 to decision-making methods for clinical drug-drug interactions.

6 is proposed for label-free study of cell and drug interactions.

7 enal failure, as well as posttransplant drug-drug interactions.

8 veled the complexity underlying host-microbe-drug interactions.

9 alence classes and, in one case, synergistic drug interactions.

10 trator or victim of clinically relevant drug-drug interactions.

11 -O nearest neighbor contacts present in drug-drug interactions.

12 s that may impact aquatic organisms via drug-drug interactions.

13 both molecular biomarkers and potential drug-drug interactions.

14 were predicted to potentially cause clinical drug interactions.

15 ndergo metabolism and cause detrimental drug-drug interactions.

16 risk for a host of clinically relevant drug-drug interactions.

17 potential hematologic toxic effects and drug-drug interactions.

18 s by modulating the strength of receptor and drug interactions.

19 in HIV-infected persons is the potential for drug interactions.

20 one-induced hepatotoxicity and clinical drug-drug interactions.

21 dications were used, with no documented drug-drug interactions.

22 d not reveal any clinically significant drug-drug interactions.

23 ues at different percentiles and assess drug-drug interactions.

24 drug metabolism and bioavailability and drug-drug interactions.

25 f clinical pharmacokinetics and site of drug-drug interactions.

26 (SCT) is hindered by adverse events and drug-drug interactions.

27 tolerated drugs with less potential for drug-drug interactions.

28 g response and prediction of unexpected drug-drug interactions.

29 al efficacy, poor tolerability, and numerous drug interactions.

30 mmune modulation and resource modulation, to drug interactions.

31 lar-level investigations into sodium channel-drug interactions.

32 ways, as well as possible NTCP-related viral-drug interactions.

33 se toxic effect profiles, comorbidities, and drug interactions.

34 to predict in vivo pharmacokinetics and drug-drug interactions.

35 ical bioavailability, MDR, and possible food-drug interactions.

36 aximize drug cytotoxicity and/or synergistic drug interactions.

37 ative stress, hepatic steatosis, and adverse drug interactions.

38 serve a previously unrecognized site of drug-drug interactions.

39 pping resistance mechanisms or for favorable drug interactions.

40 d urine (14.4%), with low potential for drug-drug interactions.

41 ith the most dramatic cases leading to fatal drug interactions.

42 ce is also predictive for different types of drug interactions.

43 ith IDA did not show evidence of significant drug-interactions.

44 tions, they can plausibly modify the protein-drug interactions, affecting selectivity and drug-bindin

45 Owing to patient intolerance or drug interactions, alternative agents to rifampin are ne

46 e ALPS through application to a complex gene-drug interaction analysis in the Predictors of Breast Ca

47 Drug interaction analysis, which reports the extent to w

48 pound 3 has a much lower propensity for drug-drug interactions and a reduced estimated human half-lif

49 y, there is great potential for serious drug-drug interactions and adverse drug reactions.

50 The potential for drug-drug interactions and altered pharmacokinetics and pharm

51 nt of the cART can avoid risk of significant drug interactions and development of cART-resistant HIV.

52 ic insights from nonfitness measures of gene-drug interactions and extend the use of mutation accumul

53 DTG has few drug interactions and is taken without regard to meals.

54 ity signals, and had low probability of drug-drug interactions and moderate in vitro metabolic rates.

55 , toxicity profile in non-malignant tissues, drug interactions and off-target effects) as well as an

56 at this risk is partly mediated through drug-drug interactions and only evident in at-risk population

57 basis of the number of resistant cells where drug interactions and pharmacokinetic curves can be esti

58 basis for the CYP3A induction class of drug-drug interactions and provided a high-throughput means f

59 : 01-12/2018 by linkage of the Liverpool HIV drug interactions and SHCS databases.

60 gests that CoQ10 is relatively safe with few drug interactions and side effects.

61 in drug development owing to potential drug-drug interactions and the variability of 3A4 and 3A5 exp

62 independence have been developed to evaluate drug interactions and their combination efficacy based o

63 t quantitative knowledge of pharmacokinetic, drug interaction, and evolutionary processes is essentia

64 the lack of many clinically significant drug-drug interactions, and acceptable adverse event profile

65 Adverse reactions to oral azoles, drug interactions, and azole resistance in Aspergillus s

66 hemoresistance in cancer, understanding drug-drug interactions, and developing efficient and specific

67 Off-target effects, drug-drug interactions, and emerging toxicities should be car

68 ms in terms of metabolism-mediated toxicity, drug interactions, and low bioactivation.

69 constant review of the pharmacology, dosing, drug interactions, and monitoring techniques may reduce

70 cts among individuals with HIV co-infection, drug interactions, and other sources of heterogeneity, a

71 o incorporate clinical characteristics, drug-drug interactions, and patient preference in decision ma

72 sk reduction benefits, adverse effects, drug-drug interactions, and patient preferences.

73 prognosis, excessive toxicities, concomitant drug interactions, and poor efficacy.

74 Omadacycline has minimal known drug-drug interactions, and should be administered in a fasti

75 of Micromedex defined two precautionary drug-drug interactions, and two medications whose use may be

76 tween tumor subtype, oncogenic drivers, gene-drug interactions, and varying niche requirements for tu

77 se optimization, risk of adverse effects and drug interactions, and verification of target engagement

78 lications, particularly atrial fibrillation; drug interactions; and infections.

79 ow toxicity profiles and propensity for drug-drug interactions are a goal for future ARV regimens.

80 Several gene-drug interactions are identified, where the copy number

81 inhibition is lost when residues involved in drug interactions are mutated.

82 Drug interactions are often analyzed in terms of isobolo

83 for bacterial or most viral infections, and drug interactions are particularly problematic.

84 Gene-gene or gene-drug interactions are typically quantified using fitness

85 nt side effects, including increased risk of drug interactions, are described, and the possibility of

86 We focused on warfarin-drug interactions as the prototype.

87 e studies, usually due to concerns over drug-drug interactions associated with antiretroviral therapy

88 Because drug-drug interactions at these transporters may induce adver

89 nts and genotoxic drugs, we quantify 76 gene-drug interactions based on both mutation rate and fitnes

90 to follow dosing, contraindications and drug-drug interactions based on product insert materials.

91 nt outcome with the two antidepressants (CRP-drug interaction: beta=3.27, 95% CI=1.65, 4.89).

92 These findings highlight a possible drug-drug interaction between caffeine and cisplatin for otot

93 this study due to a clearly illustrated drug-drug interaction between FA and RIF, which lowered FA le

94 wed by 325 mg aspirin revealed a potent drug-drug interaction between ibuprofen and aspirin and betwe

95 Drug interaction between inhibitors of monoamine oxidase

96 inetic testing did not show evidence of drug-drug interaction between irinotecan and alisertib.

97 It was hypothesized a potential drug-drug interaction between morphine and antiplatelet agent

98 Evidence suggests that there may be drug interactions between antiepileptic drugs and hormon

99 Therefore, potential drug interactions between antiretroviral drugs and HCV d

100 The risk of drug-drug interactions between antiretroviral therapy and ara

101 ticipated, overlap of toxic effects and drug-drug interactions between chemotherapy and ART may alter

102 is study sought to examine the possible drug-drug interactions between clopidogrel and morphine.

103 Drug-drug interactions between commonly coprescribed medicati

104 dies were performed to investigate potential drug interactions between faldaprevir and the commonly u

105 ires careful consideration of potential drug-drug interactions between HCV direct-acting antiviral ag

106 Our objective was to identify drug interactions between ledipasvir (LDV) and sofosbuvi

107 Drug-drug interactions between orally administered antiretrov

108 n be used to optimize the management of drug-drug interactions between PPIs and erlotinib.

109 There were no significant drug-drug interactions between the study arms.

110 A matrix of gene and drug interactions built on NCI-60 data identified that I

111 involved in one-half of pharmacokinetic drug-drug interactions, but details of the exact mechanisms o

112 These drug-drug interactions can increase the risk of toxicity or d

113 enetic polymorphisms, disease conditions, or drug interactions can lead to changes in enterohepatic r

114 apidly identify synergistic and antagonistic drug interactions can potentially alter the patient outc

115 method is interpretable in that it generates drug interaction candidates that are traceable to pharma

116 to predict novel DDIs based on similarity of drug interaction candidates to drugs involved in establi

117 perpetrator or victim of clinically relevant drug interactions-coformulated with the NRTI combination

118 Knowledge about drug-drug interactions commonly arises from preclinical trial

119 ucing cytochrome P450 inhibition driven drug-drug interaction concerns to deliver the desired balance

120 Protein-Drug Interaction Database (PDID) addresses incompletenes

121 ically translatable model to assess the drug-drug interaction (DDI) cardiac risk of current and futur

122 Drug-drug interaction (DDI) is an important topic for public

123 Drug-drug interaction (DDI) is becoming a serious clinical sa

124 A drug-drug interaction (DDI) is defined as a drug effect modif

125 g-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein inter

126 ug transporter biomarkers to facilitate drug-drug interaction (DDI) risk assessment in early phase I

127 4 and PXR is critical in toxicology and drug-drug interaction (DDI) studies.

128 ugs, the ability to discern and predict drug-drug interactions (DDI) has become crucial to guarantee

129 While knowledge of potential drug-drug interactions (DDI) is necessary to prevent ADR, the

130 perties and potency; however, potential drug-drug interactions (DDI) were predicted based on CYP 2D6

131 ife longer than 40 h and likely to have drug-drug-interactions (DDI), as 2 is a victim of CYP3A4 inhi

132 Drug-drug interactions (DDIs) are a major cause of adverse dr

133 psychiatric adverse effects of DAAs and drug-drug interactions (DDIs) between DAAs and psychiatric me

134 this study was to simulate and predict drug-drug interactions (DDIs) between these LA antiretroviral

135 ical methods for prediction of putative drug-drug interactions (DDIs) can guide in vitro testing and

136 Drug-drug interactions (DDIs) can lead to serious and potenti

137 nt of TB therapy and a common source of drug-drug interactions (DDIs) due to induction of drug metabo

138 ng antivirals (DAAs), the management of drug-drug interactions (DDIs) has become an important challen

139 Drug-drug interactions (DDIs) involving antiretrovirals (ARVs

140 Drug-drug interactions (DDIs) involving the DOACs represent a

141 drugs, owing to the potential to cause drug-drug interactions (DDIs) leading to changes in pharmacok

142 Drug-drug interactions (DDIs) may cause serious side-effects

143 Drug-drug interactions (DDIs) that involve antiretrovirals (A

144 ples for the use of hBCRP mice to study drug-drug interactions (DDIs).

145 ively evaluate their potential to cause drug-drug interactions (DDIs).

146 potential source of clinically relevant drug-drug interactions (DDIs).

147 and corresponding AEs caused solely by drug-drug interactions (DDIs).

148 eir insufficient potency, side effects, drug-drug interactions, developing drug-resistance, and narro

149 r the automated and arrayed analysis of cell-drug interaction down to the single cell level.

150 sment of the pharmacologic landscape of drug-drug interactions downstream of mutated EGFR revealed sy

151 al timing of antiretroviral initiation, drug-drug interactions, drug tolerability, and the prevention

152 th HIV because of an increased potential for drug interactions due to competing cytochrome P450 metab

153 dicted to have a low risk for potential drug-drug interactions due to its cytochrome P450 3A4 profile

154 PPARalpha, suggesting the potential for drug-drug interactions due to upregulation of CYP2C8 by PPAR

155 y employed for prediction of PK profiles and drug interactions during drug development and in case of

156 terpretation of the clinical significance of drug interactions during targeted temperature management

157 tions have emerged on the potential for drug-drug interactions during the transition from cangrelor t

158 and clopidogrel showed marked clinical drug-drug interactions (e.g., with cerivastatin and repaglini

159 ns (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies

160 onal strategy to explore pharmacokinetic and drug interaction effects in evolutionary models of cance

161 Group x Drug interaction effects were found in the amygdala (sma

162 rect pharmacokinetics, pharmacodynamics, and drug interaction effects.

163 clearly inadequate in modeling dynamic gene-drug interactions, especially for applications such as l

164 tides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min p

165 Consistent with these findings, drug interaction experiments indicated that inhibition o

166 tein-protein interaction prediction and drug-drug interaction extraction), collectively using over 25

167 We present drug interaction fingerprint analysis as a cheap, sensit

168 tive pharmaceutical ingredients by comparing drug interaction fingerprint similarity metrics such as

169 Therefore, drug interaction fingerprinting may be harnessed to diff

170 lified checkerboard assay to generate unique drug interaction fingerprints of antimicrobial drugs.

171 udied, 29 could be identified based on their drug interaction fingerprints.

172 ented in a searchable web-portal called gene-drug Interaction for survival in cancer (GDISC).

173 summarize the available data regarding drug-drug interactions for direct-acting antiviral agents, th

174 atical model was fit to the data to identify drug interactions for effect.

175 We developed a method to analyze drug interactions for the application of identifying act

176 ing evidence networks built with protein and drug interactions from the STITCH and STRING interaction

177 ategy of extracting lapatinib intermolecular drug interactions from the total PDF x-ray pattern was s

178 eed to avoid hypoglycaemia, weight gain, and drug interactions further complicate the treatment proce

179 To assess potential drug interactions, geometric mean ratios and 90% confide

180 Drug-drug interactions have been demonstrated between bocepre

181 LC) have been established for measuring drug-drug interactions; however, they are low-throughput.

182 clinicians to interactively explore the gene-drug interactions identified in the context of TCGA, and

183 icacy of TKIs through lysosome-mediated drug-drug interaction in addition to the commonly proposed au

184 n DA neuron VMAT vesicles and suggests a new drug interaction in which amphetamine induces CYAM depro

185 The collection of all analyzed gene-drug interactions in 32 cancer types are organized and p

186 modifications of silk further modulated the drug interactions in a controlled fashion.

187 use of data mining to discover unknown drug-drug interactions in cardiovascular medicine.

188 e of multiple medical comorbidities and drug-drug interactions in case of polypharmacy.

189 dren requires consideration of critical drug-drug interactions in coinfected children, as these may s

190 tribution of BEV, but also indicate negative drug interactions in concomitant DDP/PTX treatments, sug

191 dherence and decrease the likelihood of drug-drug interactions in HIV-1-infected patients is through

192 , suggested low off-target toxicity and drug-drug interactions in humans.

193 promising tool for understanding tumor cell-drug interactions in patient-derived samples including r

194 DDIs will help clinicians to avoid hazardous drug interactions in their prescriptions and will aid ph

195 Because of contraindications and drug-drug interactions, in 2030, 40% of patients could have c

196 e a high potential to cause the toxicity and drug interactions involving CYP enzymes.

197 The current understanding of drug-drug interactions involving the first-line antituberculo

198 Drug-drug interaction is an important element of modern drug

199 We hypothesized that this drug-drug interaction is reversed by taking erlotinib with th

200 A drug-drug interaction is the suspected cause whereby CYP3A4 i

201 The study of protein-drug interactions is a significant issue for drug develo

202 Awareness of drug-drug interactions is critical in organ transplant recipi

203 Attention to possible drug-drug interactions is important.

204 Thus, predicting and characterizing microbe-drug interactions is necessary to develop and implement

205 Meticulous attention to drug-drug interactions is required to avoid toxicity and phar

206 The mSTAT3-drug interaction leads to mitochondrial dysfunction, acc

207 graft and patient survival rates, but severe drug interactions may limit the usefulness of this thera

208 These drug-drug interactions may reduce the effectiveness of PI/r a

209 Analyzing drug-drug interactions may unravel previously unknown drug ac

210 results suggest that the likelihood of drug-drug interactions mediated by these transporters is stro

211 e the two models imply two extreme limits of drug interaction (mutually exclusive and mutually non-ex

212 We present a new approach to analyzing drug-drug interaction networks, based on clustering and topol

213 l-world examples ranging from social to drug-drug interaction networks.

214 We investigated the safety and drug interactions of a combination of azithromycin (AZI)

215 efficacy, tolerability, and absence of drug-drug interactions of ledipasvir-sofosbuvir suggest that

216 We found a significant sleep condition by drug interaction on the analgesia index (95% CI - 0.57,

217 ever, the clinical significance of this drug-drug interaction on transplantation outcomes has not bee

218 Changes in transport activity based on drug-drug interactions or genetic variability may therefore i

219 study physiology or pathophysiology, examine drug interactions or toxicities, and engineer cardiac ti

220 erbation by direct myocardial toxicity, drug-drug interactions, or both.

221 iciency virus (HIV) is challenging, owing to drug interactions, overlapping toxicities, and immune re

222 s (p=0.004), and 24 (6%) versus six (2%) had drug interactions (p=0.0005).

223 g key terms, drug interaction sentences, and drug interaction pairs.

224 voltammetry for the determination of albumin-drug interaction parameters, including the replacement o

225 Prevalence of potential drug-drug interactions (PDDIs) between antiretroviral drugs (

226 ion should be considered when assessing drug-drug interaction potential at the transporter.

227 We describe the clinical pharmacology and drug interaction potential of the DAAs, review the inter

228 epressive symptoms and is known for its drug-drug interaction potential when enhanced expression of C

229 necessary for extrapolation of clinical drug-drug interaction potential.

230 oped PPARalpha-targeted drugs for their drug-drug interaction potential.

231 implification, anticipation of potential new drug interactions, pregnancy or plans for pregnancy, eli

232 We used drug interaction profile correlation as a proxy for drug

233 Interaction Profile (GIP) kernel on the drug-drug interaction profiles and the Regularized Least Squa

234 QT interval-prolonging drug-drug interactions (QT-DDIs) may increase the risk of lif

235 results indicative of synergistic anticancer drug interactions rarely translate clinically and that t

236 combination drug regimens are evaluated for drug interaction relationships based on order, timing, a

237 ues related to intrinsic toxicities and drug-drug interactions remain.

238 Analysis of protein-drug interactions revealed the structural basis of avana

239 Systemic pathways as drug-drug interactions seem to be unlikely involved.

240 s proposed and implemented to tag key terms, drug interaction sentences, and drug interaction pairs.

241 fixed-dose combinations without bedaquiline drug interactions should be strongly considered.

242 ws for extraction of reproducible novel gene-drug interaction signatures as well as accurate test set

243 Drug-drug interaction studies between ART, DAAs, and opiate s

244 es, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction

245 LCs can be used for pharmacokinetic and drug-drug interaction studies.

246 vivo drug interaction studies, and in vitro drug interaction studies.

247 s, is hampered by chronic inflammation, drug-drug interactions, suboptimum adherence to drug treatmen

248 Analysis of the enzyme-drug interactions suggests that some hydrogen bonds may

249 serious adverse effects, and had fewer drug-drug interactions than those noted with voriconazole.

250 lizing enzyme is a common mechanism for drug-drug interactions that can lead to altered kinetics in d

251 utility to identify possible beneficial gene-drug interactions that could improve patient survival an

252 data by providing access to putative protein-drug interactions that cover the entire structural human

253 data and patient survival data to infer gene-drug interactions that impact survival.

254 ions for enhancing the understanding of drug-drug interactions that will further facilitate the devel

255 for the design of agents that minimize drug-drug interactions, the development of isoform-specific P

256 mplifying the simulation of variant specific drug interactions, the workflow enables large scale comp

257 However, unlike drug-drug interactions, these drug-nutrient interactions rece

258 platform may enable drug metabolism and drug-drug interactions to be interrogated at a scale that can

259 CYP3A4 inhibition may lead to drug-drug interactions, toxicity, and other adverse effects b

260 peline for identifying disease specific gene-drug interactions using CNV (Copy Number Variation) and

261 (CTX-OCT-Alg), which were characterized for drug interactions using differential scanning calorimetr

262 nd rat liver and evaluate the potential herb-drug interactions using the cocktail approach.

263 A predicted group by drug interaction was noted in the dorsal medial prefront

264 rnal separation by itself nor the rearing-by-drug interaction was significant for either marker.

265 Our aim was to investigate whether drug-drug interactions were discoverable without prior hypoth

266 reactivity between groups, ruling out a drug-drug interaction when cangrelor and ticagrelor are conco

267 ) causes a prominent class of dangerous drug-drug interactions wherein one drug accelerates the metab

268 haracterization of extreme antagonistic gene-drug interactions, which can be used to identify targets

269 erpowered to assess intravenous/intraosseous drug interactions, which were not statistically signific

270 fen, naproxen, and celecoxib-to cause a drug-drug interaction with aspirin in vivo by measuring the t

271 uice, previous data indicate a possible food-drug interaction with substrates of key enzymes responsi

272 e channel pore, should be revised to include drug interaction with the Domain III-VSD.

273 m, from the specific nature of proarrhythmic drug interaction with the hERG channel, to the fundament

274 ings may help to predict and prevent adverse drug interaction with therapeutic [(131)I]mIBG and devel

275 ficiency virus (HIV) has been limited due to drug interactions with antiretroviral therapies (ARTs) a

276 by clinically significant toxic effects and drug interactions with antiretroviral therapy.

277 Protein-drug interactions with both GP1 and GP2 are predominatel

278 e to statin-related adverse events from drug-drug interactions with certain antiretroviral regimens.

279 pecific isoenzyme increases the risk of drug-drug interactions with co-administered drugs.

280 tools can successfully describe metal-based drug interactions with DNA.

281 Providers must address drug-drug interactions with EBR/GZR and monitor for changes i

282 d selectivity were manipulated by optimizing drug interactions with enzyme binding pockets, while var

283 This study is the first to predict drug interactions with equilibrative nucleoside transpor

284 The quad does not have drug interactions with H2-receptor antagonists or proton

285 nisms of antiarrhythmic and local anesthetic drug interactions with hNa(V)1.5 and will be useful for

286 s are thought to differentially regulate ACT drug interactions with host haem, a product of parasite-

287 er transplantation (LT) patients due to drug-drug interactions with immunosuppression agents.

288 No drug-drug interactions with immunosuppressive drugs were repo

289 It does have substantial drug interactions with medications that are metabolized

290 of DHR ("pseudo-allergy") is represented by drug interactions with receptors or enzymes of inflammat

291 olerated, and can be adjusted to manage drug-drug interactions with rifampicin.

292 hematologic side effects and appears to lack drug interactions with selective serotonin reuptake inhi

293 regimens exhibited no clinically meaningful drug interactions with the 3D regimen.

294 d it is widely accepted that the kinetics of drug interactions with the channel are a critical compon

295 ared to other tetracyclines, possibly due to drug interactions with the mRNA, thereby blocking accomm

296 Determining drug interactions with these transporters can be useful

297 Determining drug interactions with these transporters can be useful

298 erplay in BSEP as a basis for exploration of drug interactions with this transporter.

299 proteins to bind a drug, occurrence of drug-drug interactions within protein binding sites, enzymati

300 We were able to identify known warfarin-drug interactions without a prior hypothesis using clini