Drug-drug interaction(DDI)refers to the interaction between two or more drugs in the body,altering their efficacy or pharmacokinetics.Fully considering and accurately predicting DDI has become an indispensable part of...Drug-drug interaction(DDI)refers to the interaction between two or more drugs in the body,altering their efficacy or pharmacokinetics.Fully considering and accurately predicting DDI has become an indispensable part of ensuring safe medication for patients.In recent years,many deep learning-based methods have been proposed to predict DDI.However,most existing computational models tend to oversimplify the fusion of drug structural and topological information,often relying on methods such as splicing or weighted summation,which fail to adequately capture the potential complementarity between structural and topological features.This loss of information may lead to models that do not fully leverage these features,thus limiting their performance in DDI prediction.To address these challenges,we propose a relation-aware cross adversarial network for predicting DDI,named RCAN-DDI,which combines a relationship-aware structure feature learning module and a topological feature learning module based on DDI networks to capture multimodal features of drugs.To explore the correlations and complementarities among different information sources,the cross-adversarial network is introduced to fully integrate features from various modalities,enhancing the predictive performance of the model.The experimental results demonstrate that the RCAN-DDI method outperforms other methods.Even in cases of labelled DDI scarcity,the method exhibits good robustness in the DDI prediction task.Furthermore,the effectiveness of the cross-adversarial module is validated through ablation experiments,demonstrating its superiority in learning multimodal complementary information.展开更多
Identifying drug-drug interactions(DDIs)is essential to prevent adverse effects from polypharmacy.Although deep learning has advanced DDI identification,the gap between powerful models and their lack of clinical appli...Identifying drug-drug interactions(DDIs)is essential to prevent adverse effects from polypharmacy.Although deep learning has advanced DDI identification,the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits.Here,we developed a Multi-Dimensional Feature Fusion model named MDFF,which integrates one-dimensional simplified molec-ular input line entry system sequence features,two-dimensional molecular graph features,and three-dimensional geometric features to enhance drug representations for predicting DDIs.MDFF was trained and validated on two DDI datasets,evaluated across three distinct scenarios,and compared with advanced DDI prediction models using accuracy,precision,recall,area under the curve,and F1 score metrics.MDFF achieved state-of-the-art performance across all metrics.Ablation experiments showed that integrating multi-dimensional drug features yielded the best results.More importantly,we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs.Among 12 real-world adverse drug reaction reports,the predictions of 9 reports were supported by relevant evidence.Additionally,MDFF demon-strated the ability to explain adverse DDI mechanisms,providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.展开更多
To quantify drug-drug-interactions (DDIs) encountered in patients prescribed hepatitis C virus (HCV) treatment, the interventions made, and the time spent in this process.METHODSAs standard of care, a clinical pharmac...To quantify drug-drug-interactions (DDIs) encountered in patients prescribed hepatitis C virus (HCV) treatment, the interventions made, and the time spent in this process.METHODSAs standard of care, a clinical pharmacist screened for DDIs in patients prescribed direct acting antiviral (DAA) HCV treatment between November 2013 and July 2015 at the University of Colorado Hepatology Clinic. HCV regimens prescribed included ledipasvir/sofosbuvir (LDV/SOF), paritaprevir/ritonavir/ombitasvir/dasabuvir (OBV/PTV/r + DSV), simeprevir/sofosbuvir (SIM/SOF), and sofosbuvir/ribavirin (SOF/RBV). This retrospective analysis reviewed the work completed by the clinical pharmacist in order to measure the aims identified for the study. The number and type of DDIs identified were summarized with descriptive statistics.RESULTSSix hundred and sixty four patients (83.4% Caucasian, 57% male, average 56.7 years old) were identified; 369 for LDV/SOF, 48 for OBV/PTV/r + DSV, 114 for SIM/SOF, and 133 for SOF/RBV. Fifty-one point five per cent of patients were cirrhotic. Overall, 5217 medications were reviewed (7.86 medications per patient) and 781 interactions identified (1.18 interactions per patient). The number of interactions were fewest for SOF/RBV (0.17 interactions per patient) and highest for OBV/PTV/r + DSV (2.48 interactions per patient). LDV/SOF and SIM/SOF had similar number of interactions (1.28 and 1.48 interactions per patient, respectively). Gastric acid modifiers and vitamin/herbal supplements commonly caused interactions with LDV/SOF. Hypertensive agents, analgesics, and psychiatric medications frequently caused interactions with OBV/PTV/r + DSV and SIM/SOF. To manage these interactions, the pharmacists most often recommended discontinuing the medication (28.9%), increasing monitoring for toxicities (24.1%), or separating administration times (18.2%). The pharmacist chart review for each patient usually took approximately 30 min, with additional time for more complex patients.CONCLUSIONDDIs are common with HCV medications and management can require medication adjustments and increased monitoring. An interdisciplinary team including a clinical pharmacist can optimize patient care.展开更多
BACKGROUND New direct-acting antivirals(DAAs)-based anti-hepatitis C virus(HCV)therapies are highly effective in patients with HCV infection.However,safety data are lacking regarding HCV treatment with DAAs and drugs ...BACKGROUND New direct-acting antivirals(DAAs)-based anti-hepatitis C virus(HCV)therapies are highly effective in patients with HCV infection.However,safety data are lacking regarding HCV treatment with DAAs and drugs for comorbidities.CASE SUMMARY Herein,we reported a case of HCV-infection in a 46-year-old man with benign prostatic hypertrophy.The patient received sofosbuvir/velpatasvir as well as methadone maintenance therapy for drug abuse.The viral load became negative at week 1 post treatment.He developed facial and bilateral lower extremity edema 48 h after starting receiving tamsulosin.Edema disappeared 10 d after treatment with oral furosemide and spironolactone.CONCLUSION In conclusion,this is the first case of an acute edema in the course of treatment with new DAAs,methadone and tamsulosin.These agents are useful in clinical management of patients with HCV infection,particularly in men with benign prostatic hypertrophy.Clinicians should be aware of potential drug-drug interactions in this subset of patients.展开更多
Objective: To analyze the use of all subsidized prescription drugs including their use of drug combination generally accepted as carrying a risk of severe interactions. Methodology: In a cross sectional study, we anal...Objective: To analyze the use of all subsidized prescription drugs including their use of drug combination generally accepted as carrying a risk of severe interactions. Methodology: In a cross sectional study, we analyzed all prescriptions (n = 1014) involving two or more drugs dispensed to the population (age range 4-85 years) from all pharmacies, clinics and hospitals. Data were stratified by age and sex, and frequency of common interacting drugs. Potential drug interactions were classified according to clinical relevance as significance of severity (types A: major, B: moderate, and C: minor) and documented evidence (types 1, 2, 3, and 4). Result and Discussion: The growing use of pharmacological agents means that drug interactions are of increasing interest for public health. Monitoring of potential drug interactions may improve the quality of drug prescribing and dispensing, and it might form a basis for education focused on appropriate prescribing. To make the manifestation of adverse interaction subside, management strategies must be exercised if two interacting drugs have to be taken with each other, involving: adjusting the dose of the object drug;spacing dosing times to avoid the interaction. The pharmacist, along with the prescriber has a duty to ensure that patients are aware of the risk of side effects and a suitable course of action they should take. Conclusion: It is unrealistic to expect clinicians to memorize the thousands of drug-drug interactions and their clinical significance, especially considering the rate of introduction of novel drugs and the escalating appreciation of the importance of pharmacogenomics. Reliable regularly updated decision support systems and information technology are necessary to help avert dangerous drug combinations.展开更多
Repaglinide is type 2 short acting anti-diabetic drug which is primarily metabolized by CYP2C8 and CYP3A4 and is also a substrate of influx transporter OATP1B1. HIV drugs are potent inhibitors of CYP3A4 and OATP trans...Repaglinide is type 2 short acting anti-diabetic drug which is primarily metabolized by CYP2C8 and CYP3A4 and is also a substrate of influx transporter OATP1B1. HIV drugs are potent inhibitors of CYP3A4 and OATP transporters. Several drug-drug interactions (DDIs) were noticed when protease inhibitors (PIs) coadministered with drugs metabolized by CYP3A4. The PIs are also potent mechanism based inhibitors, out which ritonavir is most potent. In the current study we evaluated in vitro (mouse and human liver microsomes) and in vivo DDIs of repaglinide with anti-HIV drugs. Out of the following tested drugs (Amprenavir, Indinavir, Nelfinavir, Ritonavir, Saquinavir, Delavirdine, Maraviroc, Efavirenz, Nevirapine and Ketoconazole) Amprenavir (APV), Ritonavir (RTV) and Ketoconazole (KTZ) showed inhibition of OH-repaglinide formation in human and mouse liver microsomes. The positive reversible inhibitions were further tested for irreversible inhibitions where we didn’t observe any irreversible inhibitions. In vitro inhibitions were further evaluated in the in vivo pharmacokinetics (mouse) where repaglinide pharmacokinetics was altered by RTV and KTZ. The DDIs in both studies were very strong;the dose of repaglinide is reduced to 20 fold. In conclusion, there could be possible DDIs when RTV dosed with repaglinide;we have also demonstrated that mouse could be useful preclinical tool when used in conjunction with in vitro screening models for DDIs.展开更多
The assay of acyclovir in plasma seems to be a challenge because of its high hydrophily.In our present study,a reversed-phase high-performance liquid chromatography(RP-HPLC)method for the determination of acyclovir in...The assay of acyclovir in plasma seems to be a challenge because of its high hydrophily.In our present study,a reversed-phase high-performance liquid chromatography(RP-HPLC)method for the determination of acyclovir in rat plasma was described and validated in drug-drug interaction(DDI)between gefitinib and acyclovir in rats.The analytes were separated with gradient elution on C18 column(4.6 mm×250 mm,5μm),and the peaks were recorded using ultraviolet detector at a wavelength of 254 nm.Protein precipitation followed by methyl tertiary butyl ether extraction was used for sample preparation.The calibration curve was established between 0.2 and 40μg/mL(r^(2)=0.9999).The intra-and inter-day precisions were all less than 8%,and all the biases were not more than 10%.This new method was successfully applied to a DDI study between gefitinib and acyclovir in rats.Gefitinib up-regulated the absorption of acyclovir by about three times,and our findings guided the clinical co-administration of epidermal growth factor receptor-tyrosine kinase inhibitors(EGFR-TKIs)with acyclovir.展开更多
Nowadays,smart healthcare and biomedical research have marked a substantial growth rate in terms of their presence in the literature,computational approaches,and discoveries,owing to which a massive quantity of experi...Nowadays,smart healthcare and biomedical research have marked a substantial growth rate in terms of their presence in the literature,computational approaches,and discoveries,owing to which a massive quantity of experimental datasets was published and generated(Big Data)for describing and validating such novelties.Drug-drug interaction(DDI)significantly contributed to drug administration and development.It continues as the main obstacle in offering inexpensive and safe healthcare.It normally happens for patients with extensive medication,leading them to take many drugs simultaneously.DDI may cause side effects,either mild or severe health problems.This reduced victims’quality of life and increased hospital healthcare expenses by increasing their recovery time.Several efforts were made to formulate new methods for DDI prediction to overcome this issue.In this aspect,this study designs a new Spotted Hyena Optimizer Driven Deep Learning based Drug-Drug Interaction Prediction(SHODL-DDIP)model in a big data environment.In the presented SHODL-DDIP technique,the relativity and characteristics of the drugs can be identified from different sources for prediction.The input data is preprocessed at the primary level to improve its quality.Next,the salp swarm optimization algorithm(SSO)is used to select features.In this study,the deep belief network(DBN)model is exploited to predict the DDI accurately.The SHO algorithm is involved in improvising the DBN model’s predictive outcomes,showing the novelty of the work.The experimental result analysis of the SHODL-DDIP technique is tested using drug databases,and the results signified the improvements of the SHODLDDIP technique over other recent models in terms of different performance measures.展开更多
Sildenafil and bosentan are often co-administered for pulmonary arterial hypertension (PAH) treatment. The plasma concentration of sildenafil can be decreased by half if co-administered with bosentan. Many patients ta...Sildenafil and bosentan are often co-administered for pulmonary arterial hypertension (PAH) treatment. The plasma concentration of sildenafil can be decreased by half if co-administered with bosentan. Many patients take these agents simultaneously in the morning and the evening. The aim of this study was to examine the pharmacokinetics of sildenafil which was interfered with bosentan administration to ascertain whether these agents should be given concomitantly or separately. A two-way crossover study was conducted in 6 PAH patients with combination therapy of sildenafil and bosentan. Participants underwent the sequence of treatment phases: phase S (sildenafil administered 3 h before bosen-tan);phase B (bosentan administered 3 h before sildenafil);and phase C (administered concomitantly). Blood samples were collected on the last day of each phase. There was no significant difference in maximum plasma concentration or area under the plasma concentration-time curve (AUC0-8) between phase C and phase S (95.5 ± 24.8 vs. 72.9 ± 40.9 (p = 0.07), 209.7 ± 81.8 vs. 180.2 ± 126.4 (p = 0.24), respectively) or between phases C and B (87.8 ± 42.0 vs. 99.6 ± 33.9 (p = 0.59), 197.2 ± 88.2 vs. 240.7 ± 121.8 (p = 0.19), respectively) (ng/mL, mean ± standard deviation). Large intra-and inter-individual variability in sildenafil concentration was noted. The timing of administration of sildenafil and bosentan does not significantly influence the plasma concentration of sildenafil. Physicians do not need to be overly concerned about the timing of administration of these drugs to maximize the sildenafil concentration.展开更多
The objective of the study was to evaluate the drug-drug interaction studies of levoceterizine with atenolol. Calibration curve studies of working standard solutions of levocetirizine and atenolol （0.01-0.1 mmol） we...The objective of the study was to evaluate the drug-drug interaction studies of levoceterizine with atenolol. Calibration curve studies of working standard solutions of levocetirizine and atenolol （0.01-0.1 mmol） were scanned. Maxima appeared at 231 nm for levocetirizine and 224 nm for atenolol. The calibration curve obeyed Beer Lambert＇s Law. Lone availabilities of both the drugs were studied in pH 1, pH 4, pH 7.4 and pH 9 at 37℃ on B.P. （British Pharmacopoeia） dissolution apparatus. To study the drug-drug interaction of levocetirizine （5 mg tablet） and atenolol （100 mg tablet）, both the drugs were introduced to the dissolution apparatus in simulated gastric juice （pH 1）, pH 4, pH 7.4 and pH 9 at 37℃ at zero time and measured the absorbance maxima of both the drugs at the corresponding wavelength. Graphs were plotted for availability percentage （%） of drug versus time at each set of experiment. The availability percentage （%） of levocetirizine in the buffers of pH simulated to gastric pH 4, pH 7.4 and pH 9 in the presence of atenolol was 436.78%, 376.90%, 436.78% and 436.78%, respectively, but the availability of atenolol was increased up to 214.80%, 212.96%, 214.93% and 231.51% in simulated to gastric pH and in the buffers ofpH 4, pH 7.4 and pH 9, respectively. On the basis of these studies, it is concluded that levocetirizine forms a charge-complex with atenolol; therefore, co-administration of these drugs should be avoided.展开更多
The objective of this study is to estimate the prevalence and describe the characteristics of pDDIs （potential drug-drug interactions） in medical prescriptions of hospitalized surgical patients. In this cross-sectio...The objective of this study is to estimate the prevalence and describe the characteristics of pDDIs （potential drug-drug interactions） in medical prescriptions of hospitalized surgical patients. In this cross-sectional study, we analyzed 370 medical prescriptions from the surgery unit of a Mexican public teaching hospital. The identification and classification of potential drug-drug interactions were performed with the Micromedex 2.0 electronic drug information database. Results were analyzed with descriptive statistics and we estimated OR （odds ratio） to determine associated risk factors. From the study, it was found that the prevalence of potential drug-drug interactions was 45.9%. A total of 385 interactions were identified. Of these, 54.3% were classified as major and 60.5% as pharmacodynamic. Prescriptions for more than seven drugs （OR =7.33, CI （confidence interval） = 4.59-11.71） and advanced age 〉 60 years, （OR = 1.79, CI = 1.06-2.74） were positively associated with the presence of potential drug-drug interactions. We found a high prevalence of clinically relevant pDDIs in the surgery unit. In view of this outcome, the safety of drug combinations in hospitalized surgical patients should be evaluated during the prescription process in order to prevent adverse events.展开更多
The research paper investigates the intricate landscape of drug-drug interactions (DDIs) within the context of breast cancer treatment, with a particular focus on the elderly population and the use of complementary an...The research paper investigates the intricate landscape of drug-drug interactions (DDIs) within the context of breast cancer treatment, with a particular focus on the elderly population and the use of complementary and alternative medicine (CAM). The study underscores the heightened susceptibility of elderly patients to DDIs due to the prevalence of polypharmacy and the widespread utilization of CAM among breast cancer patients. The potential ramifications of DDIs, encompassing adverse drug events and diminished treatment efficacy, are elucidated. The paper accentuates the imperative for healthcare providers to comprehensively understand both conventional and CAM therapies, enabling them to provide patients with informed guidance regarding safe and efficacious treatment options, culminating in enhanced patient outcomes.展开更多
The direct acting antivirals(DAAs)are now the standard of care for hepatitis C virus(HCV)treatment with high and effective sustained virologic responserate(SVR)and great safety profile,including solid organ transplant...The direct acting antivirals(DAAs)are now the standard of care for hepatitis C virus(HCV)treatment with high and effective sustained virologic responserate(SVR)and great safety profile,including solid organ transplant patients.There are increasing reports showing DAAs are effective with high SVR rates and safety profile in kidney transplant recipients.There are reports on drug-drug interaction(DDI)between tacrolimus with DAAs.However,data remain lacking on potential DDIs between tacrolimus and DAA regimens and the management process.This case series reports three kidney transplant patients on tacrolimus who were successfully treated for HCV with multidisciplinary approach,although there was DDI between tacrolimus with sofosbuvir/velpatasvir and glecaprevir/pibrentasvir,which required tacrolimus dose adjustment to maintain therapeutic level during and after DAA treatment.Such DDIs should be aware of and closely monitored by pharmacist and physicians with tacrolimus dose adjustment as needed during and right after DAA treatment in post-kidney transplant patients.展开更多
This study aimed to clarify that organic anion transporters(OATs)mediate the drug–drug interaction(DDI)between imipenem and cilastatin.After co-administration with imipenem,the plasma concentrations and the plasma co...This study aimed to clarify that organic anion transporters(OATs)mediate the drug–drug interaction(DDI)between imipenem and cilastatin.After co-administration with imipenem,the plasma concentrations and the plasma concentration-time curve(AUC)of cilastatin were significantly increased,while renal clearance and cumulative urinary excretion of cilastatin were decreased.At the same time,imipenem significantly inhibited the uptake of cilastatin in rat kidney slices and in human OAT1(hOAT1)-HEK293 and human OAT3(hOAT3)-HEK293 cells.Probenecid,p-aminohippurate,and benzylpenicillin inhibited the uptake of imipenem and cilastatin in rat kidney slices and in hOAT1-and hOAT3-HEK 293 cells,respectively.The uptakes of imipenem and cilastatin in hOAT1-and hOAT3-HEK 293 cells were significantly higher than that in mock-HEK-293 cells.Moreover,the K m values of cilastatin were increased in the presence of imipenem with unchanged V max,indicating that imipenem inhibited the uptake of cilastatin in a competitive manner.When imipenem and cilastatin were co-administered,the level of imipenem was higher compared with imipenem alone both in vivo and in vitro.But,cilastatin significantly inhibited the uptake of imipenem when dehydropeptidase-1(DPEP1)was silenced by RNAi technology in hOAT1-and hOAT3-HEK 293 cells.In conclusion,imipenem and cilastatin are the substrates of OAT1 and OAT3.OAT1 and OAT3 mediate the DDI between imipenem and cilastatin.Meanwhile,cilastatin also reduces the hydrolysis of imipenem by inhibiting the uptake of imipenem mediated by OAT1 and OAT3 in the kidney as a complement.展开更多
Glycyrrhizin is a major bioactive component of liquorice, which exerts multiple biochemical and pharmacological activities and is frequently used in combination with other drugs in the clinic. Mycophenolate mofetil(MM...Glycyrrhizin is a major bioactive component of liquorice, which exerts multiple biochemical and pharmacological activities and is frequently used in combination with other drugs in the clinic. Mycophenolate mofetil(MMF), an immunosuppressant widely used in transplant patients, is metabolized by UDP-glucuronyltransferases(UGTs). Although significant evidence supports that glycyrrhizin could interact with the cytochrome P450s(CYPs), few studies have addressed its effects on UGTs. The present study aimed at investigating the regulatory effects of diammonium glycyrrhizinate(GLN) on UGTs in vitro and in vivo. We found that long-term administration of GLN in rats induced overall metabolism of MMF, which might be due to the induction of UGT1A protein expression. Hepatic UGT1A activity and UGT1A mRNA and protein expression were significantly increased in GLN-treated rats. UGT1A expression levels were also increased in the intestine, contradicting with the observed decrease in intestinal UGT1A activities. This phenomenon may be attributed to different concentrations of glycyrrhetinic acid(GA) in liver and intestine and the inhibitory effects of GA on UGT1A activity. In conclusion, our study revealed that GLN had multiple effects on the expression and activities of UGT1A isoforms, providing a basis for a better understanding of interactions between GLN and other drugs.展开更多
In the present study,we aimed to investigate the interactions of pharmacokinetics and liver distributions between rosuvastatin and repaglinide in rats.Coadministration of repaglinide（0.5 mg/kg,1 mg/kg and 2 mg/kg） f...In the present study,we aimed to investigate the interactions of pharmacokinetics and liver distributions between rosuvastatin and repaglinide in rats.Coadministration of repaglinide（0.5 mg/kg,1 mg/kg and 2 mg/kg） for 7 d significantly increased the AUC0–24 and Cmax of rosuvastatin（P〈0.01）,but dramatically decreased the CL/F of rosuvastatin（P〈0.01） after a single dose of rosuvastatin（10 mg/kg）.There were no obviously changes in the parameters of Tmax and t1/2.Coadministration of repaglinide also decreased the liver distribution of rosuvastatin（P〈0.01）.Coadministration of rosuvastatin（20 mg/kg） for 7 days significantly increased the AUC0–12 and Cmax of repaglinide（P〈0.05）,and decreased the CL/F of repaglinide（P〈0.01） after a single dose of repaglinide（1 mg/kg）.The liver distribution of repaglinide was also decreased（P〈0.01）.Our animal study indicated that repaglinide could significantly affect the pharmacokinetics and liver distribution of rosuvastatin in rats and vice versa.展开更多
Quantum correlation, measured by measurement-induced disturbance （MID）, between two two-level atoms is investi- gated in detail in Tavis-Cummings model with dipole--dipole interaction （DDI）. We find that MID can b...Quantum correlation, measured by measurement-induced disturbance （MID）, between two two-level atoms is investi- gated in detail in Tavis-Cummings model with dipole--dipole interaction （DDI）. We find that MID can be determined only by the dipole-dipole interaction between the two atoms when the cavity and atoms are at resonance. Moreover, DDI will have different effects on MID for two different kinds of initial states.展开更多
Assigning causality in drug-induced liver injury is challenging particularly when more than one drug could be responsible. We report a woman on long-term therapy with raloxifen who developed acute cholestasis shortly ...Assigning causality in drug-induced liver injury is challenging particularly when more than one drug could be responsible. We report a woman on long-term therapy with raloxifen who developed acute cholestasis shortly after starting fenofibrate. The picture evolved into chronic cholestasis. We hypothesized that an interaction at the metabolic level could have triggered the presentation of hepatotoxicity after a very short time of exposure to fenofibrate in this patient. The findings of an overexpression of vascular endothelial growth factor in the liver biopsy suggest that angiogenesis might play a role in the persistance of toxic cholestasis.展开更多
Automatically extracting Drug-Drug Interactions (DDIs) from text is a crucial and challenging task, particularly when multiple medications are taken concurrently. In this study, we propose a novel approach, called Enh...Automatically extracting Drug-Drug Interactions (DDIs) from text is a crucial and challenging task, particularly when multiple medications are taken concurrently. In this study, we propose a novel approach, called Enhanced Attention-driven Dynamic Graph Convolutional Network (E-ADGCN), for DDI extraction. Our model combines the Attention-driven Dynamic Graph Convolutional Network (ADGCN) with a feature fusion method and multi-task learning framework. The ADGCN effectively utilizes entity information and dependency tree information from biomedical texts to extract DDIs. The feature fusion method integrates User-Generated Content (UGC) and molecular information with drug entity information from text through dynamic routing. By leveraging external resources, our approach maximizes the auxiliary effect and improves the accuracy of DDI extraction. We evaluate the E-ADGCN model on the extended DDIExtraction2013 dataset and achieve an F1-score of 81.45%. This research contributes to the advancement of automated methods for extracting valuable drug interaction information from textual sources, facilitating improved medication management and patient safety.展开更多
基金supported by the Natural Science Foundation of Shandong Province(Grant No.:ZR2023MF053)the National Natural Science Foundation of China(Grant No.:61902430).
文摘Drug-drug interaction(DDI)refers to the interaction between two or more drugs in the body,altering their efficacy or pharmacokinetics.Fully considering and accurately predicting DDI has become an indispensable part of ensuring safe medication for patients.In recent years,many deep learning-based methods have been proposed to predict DDI.However,most existing computational models tend to oversimplify the fusion of drug structural and topological information,often relying on methods such as splicing or weighted summation,which fail to adequately capture the potential complementarity between structural and topological features.This loss of information may lead to models that do not fully leverage these features,thus limiting their performance in DDI prediction.To address these challenges,we propose a relation-aware cross adversarial network for predicting DDI,named RCAN-DDI,which combines a relationship-aware structure feature learning module and a topological feature learning module based on DDI networks to capture multimodal features of drugs.To explore the correlations and complementarities among different information sources,the cross-adversarial network is introduced to fully integrate features from various modalities,enhancing the predictive performance of the model.The experimental results demonstrate that the RCAN-DDI method outperforms other methods.Even in cases of labelled DDI scarcity,the method exhibits good robustness in the DDI prediction task.Furthermore,the effectiveness of the cross-adversarial module is validated through ablation experiments,demonstrating its superiority in learning multimodal complementary information.
基金supported by the National Key R&D Program of China(Grant No.:2023YFC2604400)the National Natural Science Foundation of China(Grant No.:62103436).
文摘Identifying drug-drug interactions(DDIs)is essential to prevent adverse effects from polypharmacy.Although deep learning has advanced DDI identification,the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits.Here,we developed a Multi-Dimensional Feature Fusion model named MDFF,which integrates one-dimensional simplified molec-ular input line entry system sequence features,two-dimensional molecular graph features,and three-dimensional geometric features to enhance drug representations for predicting DDIs.MDFF was trained and validated on two DDI datasets,evaluated across three distinct scenarios,and compared with advanced DDI prediction models using accuracy,precision,recall,area under the curve,and F1 score metrics.MDFF achieved state-of-the-art performance across all metrics.Ablation experiments showed that integrating multi-dimensional drug features yielded the best results.More importantly,we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs.Among 12 real-world adverse drug reaction reports,the predictions of 9 reports were supported by relevant evidence.Additionally,MDFF demon-strated the ability to explain adverse DDI mechanisms,providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.
文摘To quantify drug-drug-interactions (DDIs) encountered in patients prescribed hepatitis C virus (HCV) treatment, the interventions made, and the time spent in this process.METHODSAs standard of care, a clinical pharmacist screened for DDIs in patients prescribed direct acting antiviral (DAA) HCV treatment between November 2013 and July 2015 at the University of Colorado Hepatology Clinic. HCV regimens prescribed included ledipasvir/sofosbuvir (LDV/SOF), paritaprevir/ritonavir/ombitasvir/dasabuvir (OBV/PTV/r + DSV), simeprevir/sofosbuvir (SIM/SOF), and sofosbuvir/ribavirin (SOF/RBV). This retrospective analysis reviewed the work completed by the clinical pharmacist in order to measure the aims identified for the study. The number and type of DDIs identified were summarized with descriptive statistics.RESULTSSix hundred and sixty four patients (83.4% Caucasian, 57% male, average 56.7 years old) were identified; 369 for LDV/SOF, 48 for OBV/PTV/r + DSV, 114 for SIM/SOF, and 133 for SOF/RBV. Fifty-one point five per cent of patients were cirrhotic. Overall, 5217 medications were reviewed (7.86 medications per patient) and 781 interactions identified (1.18 interactions per patient). The number of interactions were fewest for SOF/RBV (0.17 interactions per patient) and highest for OBV/PTV/r + DSV (2.48 interactions per patient). LDV/SOF and SIM/SOF had similar number of interactions (1.28 and 1.48 interactions per patient, respectively). Gastric acid modifiers and vitamin/herbal supplements commonly caused interactions with LDV/SOF. Hypertensive agents, analgesics, and psychiatric medications frequently caused interactions with OBV/PTV/r + DSV and SIM/SOF. To manage these interactions, the pharmacists most often recommended discontinuing the medication (28.9%), increasing monitoring for toxicities (24.1%), or separating administration times (18.2%). The pharmacist chart review for each patient usually took approximately 30 min, with additional time for more complex patients.CONCLUSIONDDIs are common with HCV medications and management can require medication adjustments and increased monitoring. An interdisciplinary team including a clinical pharmacist can optimize patient care.
基金Supported by the National Natural Science Foundation of China,No.81701632Shanxi Province Social Development Project,No.2018SF-269.
文摘BACKGROUND New direct-acting antivirals(DAAs)-based anti-hepatitis C virus(HCV)therapies are highly effective in patients with HCV infection.However,safety data are lacking regarding HCV treatment with DAAs and drugs for comorbidities.CASE SUMMARY Herein,we reported a case of HCV-infection in a 46-year-old man with benign prostatic hypertrophy.The patient received sofosbuvir/velpatasvir as well as methadone maintenance therapy for drug abuse.The viral load became negative at week 1 post treatment.He developed facial and bilateral lower extremity edema 48 h after starting receiving tamsulosin.Edema disappeared 10 d after treatment with oral furosemide and spironolactone.CONCLUSION In conclusion,this is the first case of an acute edema in the course of treatment with new DAAs,methadone and tamsulosin.These agents are useful in clinical management of patients with HCV infection,particularly in men with benign prostatic hypertrophy.Clinicians should be aware of potential drug-drug interactions in this subset of patients.
文摘Objective: To analyze the use of all subsidized prescription drugs including their use of drug combination generally accepted as carrying a risk of severe interactions. Methodology: In a cross sectional study, we analyzed all prescriptions (n = 1014) involving two or more drugs dispensed to the population (age range 4-85 years) from all pharmacies, clinics and hospitals. Data were stratified by age and sex, and frequency of common interacting drugs. Potential drug interactions were classified according to clinical relevance as significance of severity (types A: major, B: moderate, and C: minor) and documented evidence (types 1, 2, 3, and 4). Result and Discussion: The growing use of pharmacological agents means that drug interactions are of increasing interest for public health. Monitoring of potential drug interactions may improve the quality of drug prescribing and dispensing, and it might form a basis for education focused on appropriate prescribing. To make the manifestation of adverse interaction subside, management strategies must be exercised if two interacting drugs have to be taken with each other, involving: adjusting the dose of the object drug;spacing dosing times to avoid the interaction. The pharmacist, along with the prescriber has a duty to ensure that patients are aware of the risk of side effects and a suitable course of action they should take. Conclusion: It is unrealistic to expect clinicians to memorize the thousands of drug-drug interactions and their clinical significance, especially considering the rate of introduction of novel drugs and the escalating appreciation of the importance of pharmacogenomics. Reliable regularly updated decision support systems and information technology are necessary to help avert dangerous drug combinations.
文摘Repaglinide is type 2 short acting anti-diabetic drug which is primarily metabolized by CYP2C8 and CYP3A4 and is also a substrate of influx transporter OATP1B1. HIV drugs are potent inhibitors of CYP3A4 and OATP transporters. Several drug-drug interactions (DDIs) were noticed when protease inhibitors (PIs) coadministered with drugs metabolized by CYP3A4. The PIs are also potent mechanism based inhibitors, out which ritonavir is most potent. In the current study we evaluated in vitro (mouse and human liver microsomes) and in vivo DDIs of repaglinide with anti-HIV drugs. Out of the following tested drugs (Amprenavir, Indinavir, Nelfinavir, Ritonavir, Saquinavir, Delavirdine, Maraviroc, Efavirenz, Nevirapine and Ketoconazole) Amprenavir (APV), Ritonavir (RTV) and Ketoconazole (KTZ) showed inhibition of OH-repaglinide formation in human and mouse liver microsomes. The positive reversible inhibitions were further tested for irreversible inhibitions where we didn’t observe any irreversible inhibitions. In vitro inhibitions were further evaluated in the in vivo pharmacokinetics (mouse) where repaglinide pharmacokinetics was altered by RTV and KTZ. The DDIs in both studies were very strong;the dose of repaglinide is reduced to 20 fold. In conclusion, there could be possible DDIs when RTV dosed with repaglinide;we have also demonstrated that mouse could be useful preclinical tool when used in conjunction with in vitro screening models for DDIs.
基金Discipline and Master's Site Construction Project of Guiyang University by Guiyang City Financial Support Guiyang University (Grant No. SY-2020)Guizhou Biopharmaceutical Engineering Research Center (Grant No. QJH KYZ[2019]051)。
文摘The assay of acyclovir in plasma seems to be a challenge because of its high hydrophily.In our present study,a reversed-phase high-performance liquid chromatography(RP-HPLC)method for the determination of acyclovir in rat plasma was described and validated in drug-drug interaction(DDI)between gefitinib and acyclovir in rats.The analytes were separated with gradient elution on C18 column(4.6 mm×250 mm,5μm),and the peaks were recorded using ultraviolet detector at a wavelength of 254 nm.Protein precipitation followed by methyl tertiary butyl ether extraction was used for sample preparation.The calibration curve was established between 0.2 and 40μg/mL(r^(2)=0.9999).The intra-and inter-day precisions were all less than 8%,and all the biases were not more than 10%.This new method was successfully applied to a DDI study between gefitinib and acyclovir in rats.Gefitinib up-regulated the absorption of acyclovir by about three times,and our findings guided the clinical co-administration of epidermal growth factor receptor-tyrosine kinase inhibitors(EGFR-TKIs)with acyclovir.
文摘Nowadays,smart healthcare and biomedical research have marked a substantial growth rate in terms of their presence in the literature,computational approaches,and discoveries,owing to which a massive quantity of experimental datasets was published and generated(Big Data)for describing and validating such novelties.Drug-drug interaction(DDI)significantly contributed to drug administration and development.It continues as the main obstacle in offering inexpensive and safe healthcare.It normally happens for patients with extensive medication,leading them to take many drugs simultaneously.DDI may cause side effects,either mild or severe health problems.This reduced victims’quality of life and increased hospital healthcare expenses by increasing their recovery time.Several efforts were made to formulate new methods for DDI prediction to overcome this issue.In this aspect,this study designs a new Spotted Hyena Optimizer Driven Deep Learning based Drug-Drug Interaction Prediction(SHODL-DDIP)model in a big data environment.In the presented SHODL-DDIP technique,the relativity and characteristics of the drugs can be identified from different sources for prediction.The input data is preprocessed at the primary level to improve its quality.Next,the salp swarm optimization algorithm(SSO)is used to select features.In this study,the deep belief network(DBN)model is exploited to predict the DDI accurately.The SHO algorithm is involved in improvising the DBN model’s predictive outcomes,showing the novelty of the work.The experimental result analysis of the SHODL-DDIP technique is tested using drug databases,and the results signified the improvements of the SHODLDDIP technique over other recent models in terms of different performance measures.
文摘Sildenafil and bosentan are often co-administered for pulmonary arterial hypertension (PAH) treatment. The plasma concentration of sildenafil can be decreased by half if co-administered with bosentan. Many patients take these agents simultaneously in the morning and the evening. The aim of this study was to examine the pharmacokinetics of sildenafil which was interfered with bosentan administration to ascertain whether these agents should be given concomitantly or separately. A two-way crossover study was conducted in 6 PAH patients with combination therapy of sildenafil and bosentan. Participants underwent the sequence of treatment phases: phase S (sildenafil administered 3 h before bosen-tan);phase B (bosentan administered 3 h before sildenafil);and phase C (administered concomitantly). Blood samples were collected on the last day of each phase. There was no significant difference in maximum plasma concentration or area under the plasma concentration-time curve (AUC0-8) between phase C and phase S (95.5 ± 24.8 vs. 72.9 ± 40.9 (p = 0.07), 209.7 ± 81.8 vs. 180.2 ± 126.4 (p = 0.24), respectively) or between phases C and B (87.8 ± 42.0 vs. 99.6 ± 33.9 (p = 0.59), 197.2 ± 88.2 vs. 240.7 ± 121.8 (p = 0.19), respectively) (ng/mL, mean ± standard deviation). Large intra-and inter-individual variability in sildenafil concentration was noted. The timing of administration of sildenafil and bosentan does not significantly influence the plasma concentration of sildenafil. Physicians do not need to be overly concerned about the timing of administration of these drugs to maximize the sildenafil concentration.
文摘The objective of the study was to evaluate the drug-drug interaction studies of levoceterizine with atenolol. Calibration curve studies of working standard solutions of levocetirizine and atenolol （0.01-0.1 mmol） were scanned. Maxima appeared at 231 nm for levocetirizine and 224 nm for atenolol. The calibration curve obeyed Beer Lambert＇s Law. Lone availabilities of both the drugs were studied in pH 1, pH 4, pH 7.4 and pH 9 at 37℃ on B.P. （British Pharmacopoeia） dissolution apparatus. To study the drug-drug interaction of levocetirizine （5 mg tablet） and atenolol （100 mg tablet）, both the drugs were introduced to the dissolution apparatus in simulated gastric juice （pH 1）, pH 4, pH 7.4 and pH 9 at 37℃ at zero time and measured the absorbance maxima of both the drugs at the corresponding wavelength. Graphs were plotted for availability percentage （%） of drug versus time at each set of experiment. The availability percentage （%） of levocetirizine in the buffers of pH simulated to gastric pH 4, pH 7.4 and pH 9 in the presence of atenolol was 436.78%, 376.90%, 436.78% and 436.78%, respectively, but the availability of atenolol was increased up to 214.80%, 212.96%, 214.93% and 231.51% in simulated to gastric pH and in the buffers ofpH 4, pH 7.4 and pH 9, respectively. On the basis of these studies, it is concluded that levocetirizine forms a charge-complex with atenolol; therefore, co-administration of these drugs should be avoided.
文摘The objective of this study is to estimate the prevalence and describe the characteristics of pDDIs （potential drug-drug interactions） in medical prescriptions of hospitalized surgical patients. In this cross-sectional study, we analyzed 370 medical prescriptions from the surgery unit of a Mexican public teaching hospital. The identification and classification of potential drug-drug interactions were performed with the Micromedex 2.0 electronic drug information database. Results were analyzed with descriptive statistics and we estimated OR （odds ratio） to determine associated risk factors. From the study, it was found that the prevalence of potential drug-drug interactions was 45.9%. A total of 385 interactions were identified. Of these, 54.3% were classified as major and 60.5% as pharmacodynamic. Prescriptions for more than seven drugs （OR =7.33, CI （confidence interval） = 4.59-11.71） and advanced age 〉 60 years, （OR = 1.79, CI = 1.06-2.74） were positively associated with the presence of potential drug-drug interactions. We found a high prevalence of clinically relevant pDDIs in the surgery unit. In view of this outcome, the safety of drug combinations in hospitalized surgical patients should be evaluated during the prescription process in order to prevent adverse events.
文摘The research paper investigates the intricate landscape of drug-drug interactions (DDIs) within the context of breast cancer treatment, with a particular focus on the elderly population and the use of complementary and alternative medicine (CAM). The study underscores the heightened susceptibility of elderly patients to DDIs due to the prevalence of polypharmacy and the widespread utilization of CAM among breast cancer patients. The potential ramifications of DDIs, encompassing adverse drug events and diminished treatment efficacy, are elucidated. The paper accentuates the imperative for healthcare providers to comprehensively understand both conventional and CAM therapies, enabling them to provide patients with informed guidance regarding safe and efficacious treatment options, culminating in enhanced patient outcomes.
文摘The direct acting antivirals(DAAs)are now the standard of care for hepatitis C virus(HCV)treatment with high and effective sustained virologic responserate(SVR)and great safety profile,including solid organ transplant patients.There are increasing reports showing DAAs are effective with high SVR rates and safety profile in kidney transplant recipients.There are reports on drug-drug interaction(DDI)between tacrolimus with DAAs.However,data remain lacking on potential DDIs between tacrolimus and DAA regimens and the management process.This case series reports three kidney transplant patients on tacrolimus who were successfully treated for HCV with multidisciplinary approach,although there was DDI between tacrolimus with sofosbuvir/velpatasvir and glecaprevir/pibrentasvir,which required tacrolimus dose adjustment to maintain therapeutic level during and after DAA treatment.Such DDIs should be aware of and closely monitored by pharmacist and physicians with tacrolimus dose adjustment as needed during and right after DAA treatment in post-kidney transplant patients.
基金supported by a grant from the National Natural Science Foundation of China (No. 81874324,81473280,U1608283)the Natural Science Foundation of Liaoning (No. 20170540293)Dalian Science and technology innovation fund (No. 2018J12SN065).
文摘This study aimed to clarify that organic anion transporters(OATs)mediate the drug–drug interaction(DDI)between imipenem and cilastatin.After co-administration with imipenem,the plasma concentrations and the plasma concentration-time curve(AUC)of cilastatin were significantly increased,while renal clearance and cumulative urinary excretion of cilastatin were decreased.At the same time,imipenem significantly inhibited the uptake of cilastatin in rat kidney slices and in human OAT1(hOAT1)-HEK293 and human OAT3(hOAT3)-HEK293 cells.Probenecid,p-aminohippurate,and benzylpenicillin inhibited the uptake of imipenem and cilastatin in rat kidney slices and in hOAT1-and hOAT3-HEK 293 cells,respectively.The uptakes of imipenem and cilastatin in hOAT1-and hOAT3-HEK 293 cells were significantly higher than that in mock-HEK-293 cells.Moreover,the K m values of cilastatin were increased in the presence of imipenem with unchanged V max,indicating that imipenem inhibited the uptake of cilastatin in a competitive manner.When imipenem and cilastatin were co-administered,the level of imipenem was higher compared with imipenem alone both in vivo and in vitro.But,cilastatin significantly inhibited the uptake of imipenem when dehydropeptidase-1(DPEP1)was silenced by RNAi technology in hOAT1-and hOAT3-HEK 293 cells.In conclusion,imipenem and cilastatin are the substrates of OAT1 and OAT3.OAT1 and OAT3 mediate the DDI between imipenem and cilastatin.Meanwhile,cilastatin also reduces the hydrolysis of imipenem by inhibiting the uptake of imipenem mediated by OAT1 and OAT3 in the kidney as a complement.
基金supported by the Key Lab of Drug Metabolism and Pharmacokinetics of Jiangsu Province(No.BM2012012)
文摘Glycyrrhizin is a major bioactive component of liquorice, which exerts multiple biochemical and pharmacological activities and is frequently used in combination with other drugs in the clinic. Mycophenolate mofetil(MMF), an immunosuppressant widely used in transplant patients, is metabolized by UDP-glucuronyltransferases(UGTs). Although significant evidence supports that glycyrrhizin could interact with the cytochrome P450s(CYPs), few studies have addressed its effects on UGTs. The present study aimed at investigating the regulatory effects of diammonium glycyrrhizinate(GLN) on UGTs in vitro and in vivo. We found that long-term administration of GLN in rats induced overall metabolism of MMF, which might be due to the induction of UGT1A protein expression. Hepatic UGT1A activity and UGT1A mRNA and protein expression were significantly increased in GLN-treated rats. UGT1A expression levels were also increased in the intestine, contradicting with the observed decrease in intestinal UGT1A activities. This phenomenon may be attributed to different concentrations of glycyrrhetinic acid(GA) in liver and intestine and the inhibitory effects of GA on UGT1A activity. In conclusion, our study revealed that GLN had multiple effects on the expression and activities of UGT1A isoforms, providing a basis for a better understanding of interactions between GLN and other drugs.
文摘In the present study,we aimed to investigate the interactions of pharmacokinetics and liver distributions between rosuvastatin and repaglinide in rats.Coadministration of repaglinide（0.5 mg/kg,1 mg/kg and 2 mg/kg） for 7 d significantly increased the AUC0–24 and Cmax of rosuvastatin（P〈0.01）,but dramatically decreased the CL/F of rosuvastatin（P〈0.01） after a single dose of rosuvastatin（10 mg/kg）.There were no obviously changes in the parameters of Tmax and t1/2.Coadministration of repaglinide also decreased the liver distribution of rosuvastatin（P〈0.01）.Coadministration of rosuvastatin（20 mg/kg） for 7 days significantly increased the AUC0–12 and Cmax of repaglinide（P〈0.05）,and decreased the CL/F of repaglinide（P〈0.01） after a single dose of repaglinide（1 mg/kg）.The liver distribution of repaglinide was also decreased（P〈0.01）.Our animal study indicated that repaglinide could significantly affect the pharmacokinetics and liver distribution of rosuvastatin in rats and vice versa.
基金Project supported by Beijing City Talent Plan for Middle School Student and the Open Fund of IPOC(BUPT),China(Grant No.IPOC2013B007)the National Natural Science Foundation of China(Grant Nos.11174024 and 61227902)+1 种基金the Fundamental Research Funds for the Central Universities,China(Grant No.YWF-13-D2-JC-19)the Beijing City Youth Talent Plan
文摘Quantum correlation, measured by measurement-induced disturbance （MID）, between two two-level atoms is investi- gated in detail in Tavis-Cummings model with dipole--dipole interaction （DDI）. We find that MID can be determined only by the dipole-dipole interaction between the two atoms when the cavity and atoms are at resonance. Moreover, DDI will have different effects on MID for two different kinds of initial states.
基金Supported by a research grant from the Agencia Espanola del Medicamento and Fondo de Investigaciones Sanitarias, No. FIS PI 04/1759 and PI 04/1688
文摘Assigning causality in drug-induced liver injury is challenging particularly when more than one drug could be responsible. We report a woman on long-term therapy with raloxifen who developed acute cholestasis shortly after starting fenofibrate. The picture evolved into chronic cholestasis. We hypothesized that an interaction at the metabolic level could have triggered the presentation of hepatotoxicity after a very short time of exposure to fenofibrate in this patient. The findings of an overexpression of vascular endothelial growth factor in the liver biopsy suggest that angiogenesis might play a role in the persistance of toxic cholestasis.
基金supported by the National Natural Science Foundation of China(No.62476025)the Shaanxi Provincial Department of Science and Technology Projects(No.2013K06-39).
文摘Automatically extracting Drug-Drug Interactions (DDIs) from text is a crucial and challenging task, particularly when multiple medications are taken concurrently. In this study, we propose a novel approach, called Enhanced Attention-driven Dynamic Graph Convolutional Network (E-ADGCN), for DDI extraction. Our model combines the Attention-driven Dynamic Graph Convolutional Network (ADGCN) with a feature fusion method and multi-task learning framework. The ADGCN effectively utilizes entity information and dependency tree information from biomedical texts to extract DDIs. The feature fusion method integrates User-Generated Content (UGC) and molecular information with drug entity information from text through dynamic routing. By leveraging external resources, our approach maximizes the auxiliary effect and improves the accuracy of DDI extraction. We evaluate the E-ADGCN model on the extended DDIExtraction2013 dataset and achieve an F1-score of 81.45%. This research contributes to the advancement of automated methods for extracting valuable drug interaction information from textual sources, facilitating improved medication management and patient safety.
