Drug-Drug Interactions in Patients with Breast Cancer

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.

Spotted Hyena Optimizer Driven Deep Learning-Based Drug-Drug Interaction Prediction in Big Data Environment

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.

Evidence-based expert consensus on clinical management of safety of Bruton’s tyrosine kinase inhibitors(2024)

Bruton’s tyrosine kinase inhibitors(BTKis)have revolutionized the treatment of B-cell lymphomas.However,safety issues related to the use of BTKis may hinder treatment continuity and further affect clinical efficacy.A comprehensive and systematic expert consensus from a pharmacological perspective is lacking for safety issues associated with BTKi treatment.A multidisciplinary consensus working group was established,comprising 35 members from the fields of hematology,cardiovascular disease,cardio-oncology,clinical pharmacy,and evidencebased medicine.This evidence-based expert consensus was formulated using an evidence-based approach and the Delphi method.The Joanna Briggs Institute Critical Appraisal(JBI)tool and Grading of Recommendations Assessment,Development,and Evaluation(GRADE)approach were used to rate the quality of evidence and grade the strength of recommendations,respectively.This consensus provides practical recommendations for BTKis medication based on nine aspects within three domains,including the management of common adverse drug events such as bleeding,cardiovascular events,and hematological toxicity,as well as the management of drug-drug interactions and guidance for special populations.This multidisciplinary expert consensus could contribute to promoting a multi-dimensional,comprehensive and standardized management of BTKis.

Tuberculosis-diabetes comorbidities: Mechanistic insights for clinical considerations and treatment challenges

Tuberculosis(TB)remains a leading cause of death among infectious diseases,particularly in poor countries.Viral infections,multidrug-resistant and ex-tensively drug-resistant TB strains,as well as the coexistence of chronic illnesses such as diabetes mellitus(DM)greatly aggravate TB morbidity and mortality.DM[particularly type 2 DM(T2DM)]and TB have converged making their control even more challenging.Two contemporary global epidemics,TB-DM behaves like a syndemic,a synergistic confluence of two highly prevalent diseases.T2DM is a risk factor for developing more severe forms of multi-drug resistant-TB and TB recurrence after preventive treatment.Since a bidirectional relationship exists between TB and DM,it is necessary to concurrently treat both,and promote recommendations for the joint management of both diseases.There are also some drug-drug interactions resulting in adverse treatment outcomes in TB-DM patients including treatment failure,and reinfection.In addition,autophagy may play a role in these comorbidities.Therefore,the TB-DM comorbidities present several health challenges,requiring a focus on multidisciplinary collaboration and integrated strategies,to effectively deal with this double burden.To effectively manage the comorbidity,further screening in affected countries,more suitable drugs,and better treatment strategies are required.

Zonal Coupling Analysis Method of Seismic Response of Offshore Monopile Wind Turbine

The seismic safety of offshore wind turbines is an important issue that needs to be solved urgently.Based on a unified computing framework,this paper develops a set of seawater-seabed-wind turbine zoning coupling analysis methods.A 5 MW wind turbine and a site analysis model are established,and a seismic wave is selected to analyze the changes in the seismic response of offshore monopile wind turbines under the change of seawater depth,seabed wave velocity and seismic wave incidence angle.The analysis results show that when the seawater increases to a certain depth,the seismic response of the wind turbine increases.The shear wave velocity of the seabed affects the bending moment and displacement at the bottom of the tower.When the angle of incidence increases,the vertical displacement and the acceleration of the top of the tower increase in varying degrees.

Drug-drug cocrystals:Opportunities and challenges

Recently,drug-drug cocrystal attracts more and more attention.It offers a low risk,low-cost but high reward route to new and better medicines and could improve the physiochemical and biopharmaceutical properties of a medicine by addition of a suitable therapeutically effective component without any chemical modification.Having so many advantages,to date,the reported drug-drug cocrystals are rare.Here we review the drug-drug cocrystals that reported in last decade and shed light on the opportunities and challenges for the development of drug-drug cocrystals.

Optimizing hepatitis C virus treatment through pharmacist interventions: Identification and management of drug-drug interactions

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.

Facial and bilateral lower extremity edema due to drug-drug interactions in a patient with hepatitis C virus infection and benign prostate hypertrophy: A case report

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.

Possibility of Drug-Drug Interaction in Prescription Dispensed by Community and Hospital Pharmacy

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.

<i>In Vitro</i>and <i>in Vivo</i>(Mouse) Evaluation of Drug-Drug Interactions of Repaglinide with Anti-HIV Drugs

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.

Short-Term Drug-Drug Interaction between Sildenafil and Bosentan under Long-Term Use in Patients with Pulmonary Arterial Hypertension

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.

Drug-Drug Interaction Studies of Levocetirizine with Atenolol

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.

Prevalence of Potential Drug-Drug Interactions in Hospitalized Surgical Patients

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.

Multidisciplinary Approach to Drug-Drug Interactions between Tacrolimus and Sofosbuvir/Velpatasvir and Glecaprevir/Pibrentasvir in Kidney Transplant Patients during Hepatitis C Treatment:A Case Series Report

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.

Deep learning for drug-drug interaction prediction:A comprehensive review

The prediction of drug-drug interactions(DDIs)is a crucial task for drug safety research,and identifying potential DDIs helps us to explore the mechanism behind combinatorial therapy.Traditional wet chemical experiments for DDI are cumbersome and time-consuming,and are too small in scale,limiting the efficiency of DDI predictions.Therefore,it is particularly crucial to develop improved computational methods for detecting drug interactions.With the development of deep learning,several computational models based on deep learning have been proposed for DDI prediction.In this review,we summarized the high-quality DDI prediction methods based on deep learning in recent years,and divided them into four categories:neural network-based methods,graph neural network-based methods,knowledge graph-based methods,and multimodal-based methods.Furthermore,we discuss the challenges of existing methods and future potential perspectives.This review reveals that deep learning can significantly improve DDI prediction performance compared to traditional machine learning.Deep learning models can scale to large-scale datasets and accept multiple data types as input,thus making DDI predictions more efficient and accurate.

肝脏转运体介导药物相互作用的研究进展

转运体是位于细胞膜上的功能性膜蛋白,在肝脏表达广泛,其生理功能是将大多数内源性物质、外源性化学异物或药物等摄取进入肝脏,在肝脏经过一定的代谢转化,最终将其经胆汁排至肝外.肝脏转运体在药物肝胆转运中起重要作用,转运体与药物在肝脏的摄取、代谢及排泄等功能密切相关,转运体的功能抑制、缺失是生理疾病和药物之间相互作用的重要因素.临床联合应用与转运体有关的药物时可能发生由转运体介导的药物相互作用,如西立伐他汀不良反应事件.本文从肝脏转运体的抑制、诱导和单核苷酸多态性出发,对由肝脏转运体引起的药物相互作用作一综述.

A substructure-aware graph neural network incorporating relation features for drug-drug interaction prediction

Identifying drug–drug interactions(DDIs)is an important aspect of drug design research,and predicting DDIs serves as a crucial guarantee for avoiding potential adverse effects.Current substructure-based prediction methods still have some limitations:(i)The process of substructure extraction does not fully exploit the graph structure information of drugs,as it only evaluates the importance of different radius substructures from a single perspective.(ii)The process of constructing drug representations has overlooked the significant impact of relation embedding on optimizing drug representations.In this work,we propose a substructure-aware graph neural network incorporating relation features(RFSA-DDI)for DDI prediction,which introduces a directed message passing neural network with substructure attention mechanism based on graph self-adaptive pooling(GSP-DMPNN)and a substructure-aware interaction module incorporating relation features(RSAM).GSP-DMPNN utilizes graph self-adaptive pooling to comprehensively consider node features and local drug information for adaptive extraction of substructures.RSAM interacts drug features with relation representations to enhance their respective features individually,highlighting substructures that significantly impact predictions.RFSA-DDI is evaluated on two real-world datasets.Compared to existing methods,RFSA-DDI demonstrates certain advantages in both transductive and inductive settings,effectively handling the task of predicting DDIs for unseen drugs and exhibiting good generalization capability.The experimental results show that RFSA-DDI can effectively capture valuable structural information of drugs more accurately for DDI prediction,and provide more reliable assistance for potential DDIs detection in drug development and treatment stages.

生理药动学模型定量预测依诺沙星/环丙沙星对茶碱/咖啡因代谢的影响

将依诺沙星/环丙沙星在混合人肝微粒体中与非那西丁共温孵,以非那西丁的去乙基反应表示CYP1A2的活性,估算相应的酶动力学参数,并建立基于机制性抑制生理药动学模型,定量预测依诺沙星/环丙沙星与茶碱/咖啡因的体内相互作用。结果显示,依诺沙星/环丙沙星为弱的CYP1A2可逆性抑制剂,但在与NADPH预温孵的条件下,依诺沙星/环丙沙星明显抑制非那西丁代谢,且抑制呈NADPH、预温孵时间、依诺沙星/环丙沙星浓度依赖性,符合机制性抑制的特征,进一步用建立的基于机制性抑制生理药动学能较好的模型预测依诺沙星/环丙沙星与茶碱/咖啡因的相互作用,预测值与观察值基本吻合。

Real life efficacy and safety of direct-acting antiviral therapy for treatment of patients infected with hepatitis C virus genotypes 1, 2and 3 in northwest China

BACKGROUND Regimens involving direct-acting antiviral agents(DAAs)are recommended for the treatment of infection with hepatitis C virus(HCV)genotypes 1,2 and 3.But real-world data is still not enough,especially in Asia.AIM To investigate the efficacy and safety of DAA-based regimens in a real-life setting in China.METHODS This study included 366 patients infected with HCV genotypes 1,2 and 3,with or without cirrhosis,who were observed between May 2015 and December 2018.They were treated with ledipasvir and sofosbuvir(SOF)(genotype 1)with or without ribavirin(RBV),SOF and RBV(genotype 2),or SOF and daclatasvir(genotype 3),with or without RBV,for 12 or more wk.The participants’sustained virological responses(SVR)at post-treatment week 12(SVR12)was the primary endpoint.The occurrence of adverse events and drug-drug interactions were recorded.RESULTS In the 366 patients,genotype 1(59.0%)was the most common genotype,followed by genotypes 2(34.4%)and 3(6.6%).Liver cirrhosis was diagnosed in 154(42.1%)patients.Fifty(13.7%)patients were treatment-experienced.Intention-to-treat analysis revealed that SVR12 was 86.3%(316/366).For modified intention-totreat analysis,SVR12 was achieved in 96.6%of overall patients(316/327),96.3%in patients with genotype 1,97.5%in those with genotype 2,and 95.0%in those with genotype 3.Most of the treatment failures were due to lack of follow-up(3cases had non-responses,1 had virological breakthrough,11 relapsed and 36 did not participate in the follow-up).There was no significant difference in SVR between different genotypes and liver statuses(P<0.05).Patients with lower alanine aminotransferase levels at baseline who achieved an end of treatment response were more likely to achieve SVR12(P<0.05).High SVR was observed regardless of age,gender,liver status,alpha-fetoprotein,HCV RNA levels or history of antiviral therapy(P>0.05 for all).The cumulative hepatocellular carcinoma occurrence and recurrence rate after using the DAAs was 0.9%.Most of the adverse events were mild.We found two cases of special adverse events.One case involved facial and bilateral lower extremity edema,and the other case showed an interesting change in lipid levels while on medication.No severe adverse events were noted.CONCLUSION The DAA-based regimens tested in this study have excellent effectiveness and safety in all patients infected with HCV genotypes 1,2 and 3,including those with cirrhosis.

Organic anion transporters also mediate the drug–drug interaction between imipenem and cilastatin

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.