Three-dimensional aspects of formulation excipients in drug discovery:a critical assessment on orphan excipients,matrix effects and drug interactions

Formulation/pharmaceutical excipients play a major role in formulating drug candidates,with the objectives of ease of administration,targeted delivery and complete availability.Many excipients used in pharmaceutical formulations are orphanized in preclinical drug discovery.These orphan excipients could enhance formulatability of highly lipophilic compounds.Additionally,they are safe in preclinical species when used below the LD50 values.However,when the excipients are used in formulating compounds with diverse physico-chemical properties,they pose challenges by modulating study results through their bioanalytical matrix effects.Excipients invariably present in study samples and not in the calibration curve standards cause over-/under-estimation of exposures.Thus,the mechanism by which excipients cause matrix effects and strategies to nullify these effects needs to be revisited.Furthermore,formulation excipients cause drug interactions by moderating the pathways of drug metabolizing enzymes and drug transport proteins.Although it is not possible to get rid of excipient driven interactions,it is always advised to be aware of these interactions and apply the knowledge to draw meaningful conclusions from study results.In this review,we will comprehensively discuss a)orphan excipients that have wider applications in preclinical formulations,b)bioanalytical matrix effects and possible approaches to mitigating these effects,and c)excipient driven drug interactions and strategies to alleviate the impacts of drug interactions.

Major bleeding events in octagenarians associated with drug interactions between dabigatran and P-gp inhibitors

Background The direct oral anticoagulant dabigatran does not require any routine therapeutic drug monitoring.Yet,concerns about possible drug interactions susceptible to increase its inherent bleeding risk,especially in very elderly patients,have been raised recently.The aim of our study was to evaluate to what extent the co-prescription of P-gp inhibitors with dabigatran may increase its plasma levels and lead to bleeding complications,in usual conditions of care of the very elderly.Methods Fifty-eight patients over 85 years old with non valvular atrial fibrillation receiving dabigatran were included in a prospective cohort.Prescriptions were screened for the presence of P-gp inhibitors(Group A)or not(Group B).Results Patients from Group A had increased dabigatran mean plasma concentrations as compared with patients from Group B(A vs.B:182.2±147.3 vs.93.7±64.9 ng/m L).One third of the patients from Group A had dabigatran concentrations that were deemed"out of range"versus none in Group B(P=0.05).This was associated with more frequent bleeding complications in Group A(A:30.4%,B:8.6%,P=0.04).Conclusion In our cohort of very elderly patients,at least,the co-prescription of dabigatran with P-gp inhibitors in usual conditions of care resulted in higher dabigatran plasma concentrations and more frequent bleeding occurrences.

Impact of Drug-Drug Interaction between CDK4/6 Inhibitors and Proton Pump Inhibitors on Survival Outcomes in the Treatment of Metastatic Breast Cancer—Real World Data from a Portuguese Center

Introduction: Proton pump inhibitors (PPi) are widely prescribed, including in patients undergoing treatment for advanced breast cancer (ABC). Due to the pharmacokinetic characteristics of the CDK4/6 inhibitor (Ci) palbociclib a drug interaction with PPi was hypothesized. It was shown in a retrospective study that this association was an independent predictive factor for worse progression-free survival (PFS). Objective: To verify the impact of concomitant administration of PPi with Ci on overall survival (OS) and PFS. Material and Methods: This is a retrospective cohort study of patients treated with Ci for HR+HER2-ABC in the period from Feb/2017 to Aug/2020. SPSS software was used for data processing. Univariate analysis was done by the Kaplan-Meier method and log-rank test, and multivariate analysis by COX regression. P-value < 0.05 was considered significant. Results: 80 patients were included. The median age at diagnosis of ABC was 56 years (25 - 75). Treatment with Ci was 1st line for ABC in 68.8%. Choice of Ci was palbociclib in 73.8% (n = 59) and ribociclib in 26.3% (n = 21). The hormone partner was a nonsteroidal aromatase inhibitor in 45.0%, and fulvestrant in 55.0% of cases. 37.5% of patients were on PPi, and 70.0% of them were during the entire treatment (23.3% omeprazole, 73.4% pantoprazole, 3.3% others). Patients taking concomitant PPi and Ci had lower OS (OS-3 years 42.6% vs. 63.4%, p = 0.254) and PFS (PFS med 15 m. vs. 21 m., p = 0.733), although with no statistically significant difference. Discussion: In the sample, there was a numerical difference, without the statistical significance in the use of PPi in the survival of patients under Ci. This difference could be more evident with a longer follow-up and a larger sample size. This study intends to alert to the growing importance of checking for drug interactions. Polymedication, advanced age and the presence of several comorbidities are real problems in patients with ABC. Conclusion: Real-world data from this center demonstrate a negative, non-statistically significant impact of PPi treatment on survival outcomes, in patients treated with Ci for HR+HER2-ABC.

Measuring drug similarity using drug–drug interactions

Combination therapy is a promising approach to address the challenge of antimicrobial resistance,and computational models have been proposed for predicting drug–drug interactions.Most existing models rely on drug similarity measures based on characteristics such as chemical structure and the mechanism of action.In this study,we focus on the network structure itself and propose a drug similarity measure based on drug–drug interaction networks.We explore the potential applications of this measure by combining it with unsupervised learning and semi-supervised learning approaches.In unsupervised learning,drugs can be grouped based on their interactions,leading to almost monochromatic group–group interactions.In addition,drugs within the same group tend to have similar mechanisms of action(MoA).In semi-supervised learning,the similarity measure can be utilized to construct affinity matrices,enabling the prediction of unknown drug–drug interactions.Our method exceeds existing approaches in terms of performance.Overall,our experiments demonstrate the effectiveness and practicability of the proposed similarity measure.On the one hand,when combined with clustering algorithms,it can be used for functional annotation of compounds with unknown MoA.On the other hand,when combined with semi-supervised graph learning,it enables the prediction of unknown drug–drug interactions.

Activation of PXR causes drug interactions with Paxlovid in transgenic mice

Paxlovid is a nirmatrelvir(NMV)and ritonavir(RTV)co-packaged medication used for the treatment of coronavirus disease 2019(COVID-19).The active component of Paxlovid is NMV and RTV is a pharmacokinetic booster.Our work aimed to investigate the drug/herb-drug interactions associated with Paxlovid and provide mechanism-based guidance for the clinical use of Paxlovid.By using recombinant human cytochrome P450s(CYPs),we confirmed that CYP3A4 and 3A5 are the major enzymes responsible for NMV metabolism.The role of CYP3A in Paxlovid metabolism were further verified in Cyp3a-null mice,which showed that the deficiency of CYP3A significantly suppressed the metabolism of NMV and RTV.Pregnane X receptor(PXR)is a ligand-dependent transcription factor that upregulates CYP3A4/5 expression.We next explored the impact of drug-and herb-mediated PXR activation on Paxlovid metabolism in a transgenic mouse model expressing human PXR and CYP3A4/5.We found that PXR activation increased CYP3A4/5 expression,accelerated NMV metabolism,and reduced the systemic exposure of NMV.In summary,our work demonstrated that PXR activation can cause drug interactions with Paxlovid,suggesting that PXR-activating drugs and herbs should be used cautiously in COVID-19 patients receiving Paxlovid.

Development of Extraction and Detection Method for a Chemotherapeutic Drug with Phenytoin in Biological Samples

Dexamethasone is classified as a corticosteroid and is commonly used among cancer patients to decrease the amount of swelling around the tumor. Among patients with cancer, in particular brain tumors, seizures can become a daily routine in their everyday lives. To counteract the seizures, an antiepileptic drug such as phenytoin is administered to act as an anticonvulsant. Phenytoin and dexamethasone are frequently administrated concurrently to brain cancer patients. A previous study has shown that phenytoin serum concentration decreases when administrated concurrently with dexamethasone. Thus, it is important to monitor the concentration of these two drugs in biological samples to ensure that the proper dosages are administrated to the patients. This study aims to develop an effective extraction and detection method for dexamethasone and phenytoin. A reverse-phase high-performance liquid chromatography (HPLC) method with UV/Vis detection has been developed to separate phenytoin and dexamethasone at 219 nm and 241 nm respectively from urine samples. The mobile phase consists of a mixture of 0.01 M KH2PO4, acetonitrile, and methanol adjusted to pH 5.6 (48:32:20) and is pumped at a flow rate of 1.0 mL/min. Calibration curves were prepared for phenytoin and dexamethasone (r2 > 0.99). An efficient solid-phase extraction (SPE) method for the extraction of dexamethasone and phenytoin from urine samples was developed with the use of C-18 cartridges. The percent recovery for phenytoin and dexamethasone is 95.4% (RSD = 1.15%) and 81.1% (RSD = 3.56%) respectively.

Assessment of the potential interactions between favipiravir and radiocontrast agents

BACKGROUND In cases of coronavirus disease 2019(COVID-19),favipiravir is commonly included to the therapy regimen.Drug interactions between favipiravir and other COVID-19 therapy drugs are frequently researched.However,no research on possible drug interactions between Favipiravir and radiocontrast agents,which have become almost crucial in diagnostic processes while not being part of the treatment,has been found.AIM To determine potential medication interactions between Favipiravir and radiocontrast agents.METHODS The study comprised patients who were taking Favipiravir for COVID-19 therapy and underwent a contrast-enhanced computed tomography(CT)or magnetic resonance imaging(MRI)test while taking the medicine.The computerized patient files of the cases included in the study,as well as the pharmacovigilance forms in the designated hospital,were evaluated for this purpose.RESULTS The study included the evaluation of data from 1046 patients.The study sample's mean age was 47.23±9.48 years.The mean age of cases with drug interactions was statistically significant greater than that of cases with no drug interactions(P=0.003).When evaluated with logistic regression analysis,a 1-year raises in age increases the risk of developing drug interactions by 1.63 times(P=0.023).There was no statistically significant difference in the occurrence of medication interactions between the sexes(P=0.090).Possible medication interactions were discovered in 42 cases(4%).CONCLUSION The findings of this study revealed that the most notable findings as a result of the combined use of contrast agents and favipiravir were increased creatinine and transaminase values,as well as an increase in the frequency of nausea and vomiting.The majority of drug interactions discovered were modest enough that they were not reflected in the clinic.Drug interactions become more common as people get older.

Drug–Target Interaction Prediction Model Using Optimal Recurrent Neural Network

Drug-target interactions prediction(DTIP)remains an important requirement in thefield of drug discovery and human medicine.The identification of interaction among the drug compound and target protein plays an essential pro-cess in the drug discovery process.It is a lengthier and complex process for pre-dicting the drug target interaction(DTI)utilizing experimental approaches.To resolve these issues,computational intelligence based DTIP techniques were developed to offer an efficient predictive model with low cost.The recently devel-oped deep learning(DL)models can be employed for the design of effective pre-dictive approaches for DTIP.With this motivation,this paper presents a new drug target interaction prediction using optimal recurrent neural network(DTIP-ORNN)technique.The goal of the DTIP-ORNN technique is to predict the DTIs in a semi-supervised way,i.e.,inclusion of both labelled and unlabelled instances.Initially,the DTIP-ORNN technique performs data preparation process and also includes class labelling process,where the target interactions from the database are used to determine thefinal label of the unlabelled instances.Besides,drug-to-drug(D-D)and target-to-target(T-T)interactions are used for the weight initia-tion of the RNN based bidirectional long short term memory(BiLSTM)model which is then utilized to the prediction of DTIs.Since hyperparameters signifi-cantly affect the prediction performance of the BiLSTM technique,the Adam optimizer is used which mainly helps to improve the DTI prediction outcomes.In order to ensure the enhanced predictive outcomes of the DTIP-ORNN techni-que,a series of simulations are implemented on four benchmark datasets.The comparative result analysis shows the promising performance of the DTIP-ORNN method on the recent approaches.

Local drug interaction of metformin with carvedilol increases drug accumulation in the liver and kidney of rats

Drug transporters determine plasma and tissue exposure of a broad variety of drugs and play a critical role in drug-drug interaction （DDI）. In the present study, we aimed to investigate the effects of carvedilol on pharmacokinetics of metformin as well as the mechanism of their interaction. Results showed that plasma concentration of metformin was not significantly altered after single or 7-day co-administration of carvedilol, and the urinary excretion of metformin was also not influenced by carvedilol. However, the concentration of metformJn in the liver and kidney was markedly elevated. Similarly, carvedilol did not affect the renal elimination of metformin, but increased renal concentration in isolated kidney perfusion. On the other hand, carvedilol treatment did not affect the expressions of rOCTs and rMATE 1 in the liver and kidney of rats. After long-term co-administration, there were no differences in lactic acid （LCA）, uric acid （URIC） and creatinine （CREA） levels between two groups. These results indicated that carvedilol increased hepatic and renal distribution of metformin, resulting in local drug interaction.

Rational prescription of drugs within similar therapeutic or structural class for gastrointestinal disease treatment: Drug metabolism and its related interactions

AIM:To review and summarize drug metabolism and its related interactions in prescribing drugs within the similar therapeutic or structural class for gastrointestinal disease treatment so as to promote rational use of medicines in clinical practice.METHODS:Relevant literature was identified by performing MEDLINE/Pubmed searches covering the period from 1988 to 2006.RESULTS:Seven classes of drugs were chosen,including gastric proton pump inhibitors,histamine H2-receptor antagonists,benzamide-type gastroprokinetic agents,selective 5-HT3 receptor antagonists,fluoroquinolones,macrolide antibiotics and azole antifungals.They showed significant differences in metabolic profile(i.e.,the fraction of drug metabolized by cytochrome P450(CYP),CYP reaction phenotype,impact of CYP genotype on interindividual pharmacokinetics variability and CYP-mediated drug-drug interaction potential).Many events of severe adverse drug reactions and treatment failures were closely related to the ignorance of the above issues.CONCLUSION:Clinicians should acquaint themselves with what kind of drug has less interpatient variability in clearance and whether to perform CYP genotyping prior to initiation of therapy.The relevant CYP knowledgehelps clinicians to enhance the management of patients with gastrointestinal disease who may require treatment with polytherapeutic regimens.

HIV/HCV Antiviral Drug Interactions in the Era of Direct-acting Antivirals

Therapy for human immunodeficiency virus (HIV) and chronic hepatitis C has evolved over the past decade,resulting in better control of infection and clinical outcomes;however,drug-drug interactions remain a significant hazard.Joint recommendations from the American Association for the Study of Liver Diseases and the Infectious Diseases Society of America regarding drug-drug interactions between HIV antiretroviral agents and direct-acting antiviral agents for treatment of hepatitis C virus (HCV) infection are reviewed here.This review is oriented to facilitate appropriate selection of an antiviral therapy regimen for HCV infection based on the choice of antiretroviral therapy being administered and,if necessary,switching antiretroviral regimens.

Review of Clinically Relevant Drug Interactions with Next Generation Hepatitis C Direct-acting Antiviral Agents

In this review,we examine the pharmacokinetics and clinically relevant drug interactions of the newer generation direct-acting antivirals(DAAs)for the treatment of chronic hepatitis C,specifically sofosbuvir/velpatasvir(Epclusa®),sofosbuvir/velpatasvir/voxilaprevir(Vosevi®),glecaprevir/pibrentasvir(Maviret®),and elbasvir/grazoprevir(Zepatier®).We searched MEDLINE(1948-January 2020),Embase(1964-January 2020),Google,and GoogleScholar using the terms pharmacokinetics,drug interaction,drug metabolism,sofosbuvir,velpatasvir,Epclusa,voxilaprevir,Vosevi,glecaprevir,pibrentasvir,Maviret,elbasvir,grazoprevir,and Zepatier,from inception to January 13,2020.The search was limited to randomized controlled trials,in vitro studies,prospective and retrospective human studies,drug monographs,abstracts,and conference proceedings.All relevant published literature on pharmacokinetic and pharmacodynamic interactions involving DAAs were reviewed and the data extracted.Numerous clinically relevant drug-drug interactions(DDIs)were identified with the newer generation DAAs and commonly prescribed drugs.NS3/4A protease inhibitors are more likely to be involved in DDIs,followed by NS5A inhibitors and NS5B polymerase inhibitor.The majority of clinically relevant DDIs are predictable,according to known pharmacokinetic,pharmacodynamics,and physicochemical properties of DAAs;however,in select cases,unpredictable DDIs do occur.As expected,many drug interactions exist between newer generation DAAs and commonly prescribed medications.While the majority of clinically relevant interactions are predictable,many require therapeutic dose adjustment or careful selection of non-interacting drugs.In select cases,severe and unpredictable drug interactions can occur.Clinicians should consult hepatitis C virus pharmacotherapy experts and tertiary drug interaction resources when initiating DAA therapy in patients taking other medications.

P-glycoprotein mediated interactions between Chinese materia medica and pharmaceutical drugs

P-glycoprotein(P-gp)is an important transmembrane ATP-binding cassette(ABC)drug efflux transporter expressed in various human tissues such as the intestines,liver,kidneys,and bloodbrain barrier.It limits the intracellular concentration of xenobiotics by pumping them out of the cells,affecting drug pharmacokinetics and therapeutic effects.With its broad substrate specificity,it has the potential to remove a wide range of drugs from Chinese materia medica(CMM),including conventional medicines and active compounds.Increasing evidence has confirmed the superior therapeutic effectiveness of CMM in treating a wide range of diseases worldwide,as well as in conjunction with western drugs.As a result,herbal medicine-drug compounds have prompted widespread concern,with the majority of these interactions involving transporters such as P-gp.This review systematically summarizes the inhibition or induction of P-gp expression/function by active CMM compounds and the underlying regulatory mechanisms.It will aid in improving understanding of the synergistic or inhibiting effects associated with transporter P-gp as well as rational safety concerns for using CMM,particularly in combination with drugs.

Drug utilization of clarithromycin for gastrointestinal disease treatment

AIM： To evaluate the patterns of use of clarithromycin for gastrointestinal disease treatment and promote its rational use.METHODS： Using a structured pro forma, we conducted a two-month survey of the electronic prescriptions containing immediate-release （IR） or sustained-release （SR） product of clarithromycin for outpatients with gastrointestinal diseases in a 2200-bed general hospital. Suitability of the prescription was audited retrospectively. RESULTS： One hundred and sixty-four prescriptions of SR product and 110 prescriptions of IR product were prescribed for gastrointestinal disease treatment. Among prescriptions for anti-Helicobacter pylori （H pylori） therapy, triple therapy take the dominant position （91.8%）, followed by quadruple therapy （4.3%） and dual therapy （3.9%）. Amoxicillin was the most frequently co-prescribed antibiotic.Furazolidone and levofloxacin are used more widely than metronidazole or tinidazole. Clarithromycin SR was administered at inappropriate time points in all prescriptions. Fifty percent of all prescriptions of clarithromycin SR, and 6.4% of prescriptions of clarithromycin IR, were prescribed at inappropriate dosing intervals. Surprisingly, disconcordance between diagnoses and indications was observed in all prescriptions of clarithromycin SR which has not been approved for treating Hpy/ori infection although off-label use for this purpose was reported in literature. On the contrary, only one prescription （0.9%） of clarithromycin IR was prescribed for unapproved indication （i.e. gastro-oesophageal reflux disease）. 1.4% of prescriptions for chronic gastritis or peptic ulcer treatment were irrational in that clarithromycin was not co-prescribed with gastric acid inhibitors. Clinical significant CYP3A based drug interactions with clarithromycin were identified. CONCLUSION： There is a great scope to improve the quality of clarithromycin prescribing in patients with gastrointestinal disease, especially with regard to administration schedule, concordance between indications and diagnoses and management of drug interactions.

Relative efficacy of some prokinetic drugs in morphine-induced gastrointestinal transit delay in mice

AIM:To study the relative efficacy of cisapride, metoclopramide,domperidone,erythromycin and mosapride on gastric emptying(GE)and small intestinal transit(SIT) in morphine treated mice. METHODS:Phenol red marker meal was employed to estimate GE and SIT in Swiss albino mice of either sex.The groups included were control,morphine 1 mg/kg(s.c.15 rain before test meal)alone or with(45 rain before test meal p.o.)cisapride 10 mg/kg,metoclopramide 20 mg/kg, domperidone 20 mg/kg,erythromycin 6 mg/kg and mosapride 20 mg/kg. RESULTS:Cisapride,metoclopramide and mosapride were effective in enhancing gastric emptying significantly(P<0.001) whereas other prokinetic agents failed to do so in normal mice.Metoclopramide completely reversed morphine induced delay in gastric emptying followed by mosapride. Metoclopramide alone was effective when given to normal mice in increasing the SIT.Cisapride,though it did not show any significant effect on SIT in normal mice,was able to reverse morphine induced delay in SIT significantly(P<0.001) followed by metoclopramide and mosapride. CONCLUSION:Metoclopramide and cisapride are most effective in reversing morphine-induced delay in gastric emptying and small intestinal transit in mice respectively.

GCARDTI:Drug–target interaction prediction based on a hybrid mechanism in drug SELFIES

The prediction of the interaction between a drug and a target is the most critical issue in the fields of drug development and repurposing.However,there are still two challenges in current deep learning research:(i)the structural information of drug molecules is not fully explored in most drug target studies,and the previous drug SMILES does not correspond well to effective drug molecules and(ii)exploration of the potential relationship between drugs and targets is in need of improvement.In this work,we use a new and better representation of the effective molecular graph structure,SELFIES.We propose a hybrid mechanism framework based on convolutional neural network and graph attention network to capture multi-view feature information of drug and target molecular structures,and we aim to enhance the ability to capture interaction sites between a drug and a target.In this study,our experiments using two different datasets show that the GCARDTI model outperforms a variety of different model algorithms on different metrics.We also demonstrate the accuracy of our model through two case studies.

COVID-19 infection in a kidney transplant recipient—special emphasis on pharmacokinetic interactions:A case report

BACKGROUND Solid organ transplant recipients are considered to be at high-risk of developing coronavirus disease 2019(COVID-19)-related complications.The optimal treatment for this patient group is unknown.Consequently,the treatment of COVID-19 in kidney transplant recipients should be determined individually,considering patient age and comorbidities,as well as graft function,time of transplant,and immunosuppressive treatment.Immunosuppressive treatments may give rise to severe COVID-19.On the contrary,they may also lead to a milder and atypical presentation by diminishing the immune system overdrive.CASE SUMMARY A 50-year old female kidney transplant recipient presented to the transplant clinic with a progressive dry cough and fever that started three days ago.Although the COVID-19 test was found to be negative,chest computed tomography images showed consolidation typical of the disease;thus,following hospital admission,anti-bacterial and COVID-19 treatments were initiated.However,despite clinical improvement of the lung consolidation,her creatinine levels continued to increase.Ultrasound of the graft showed no pathology.The tacrolimus blood level was determined and the elevation in creatinine was found to be related to an interaction between tacrolimus and azithromycin.CONCLUSION During the COVID-19 pandemic,various single or combination drugs have been utilized to find an effective treatment regimen.This has increased the possibility of drug interactions.A limited number of studies published in the literature have highlighted some of these pharmacokinetic interactions.Treatments used for COVID-19 therapy;azithromycin,atazanavir,lopinavir/ritonavir,remdesivir,favipiravir,chloroquine,hydroxychloroquine,nitazoxanide,ribavirin,and tocilizumab,interact with immunosuppressive treatments,most importantly with calcineurin inhibitors.Thus,their levels should be frequently monitored to prevent toxicity.

Prevalence and risk factors for acquired long QT syndrome in the emergency department:a retrospective observational study

BACKGROUND: Long QT syndrome(LQTS) is a heterogeneous syndrome that may be congenital or, more frequently, acquired. The real-world prevalence of acquired LQTS(aLQTS) in the emergency department(ED) remains to be determined. The aim of this study was to determine prevalence of aLQTS and its impact on symptoms on ED admissions.METHODS: Electrocardiograms(ECG) of 5,056 consecutively patients admitted in the ED of a tertiary hospital between January 28th and March 17th of 2020 were reviewed. All patients with aLQTS were included. Clinical data with a focus on QT prolonging drugs and clinical factors were recorded. Statistical comparison was made between the groups with and without corrected QT(QTc) interval greater than 500 ms(value that is considered severely increased).RESULTS: A total of 383 ECGs with prolonged QTc were recognized, corresponding to a prevalence of aLQTS at admission of 7.82%. Patients with aLQTS were more commonly men(53.3%) with an age of(73.49±14.79) years old and QTc interval of(505.3±32.4) ms. Only 20.4% of these patients with aLQTS were symptomatic. No ventricular arrhythmias were recorded. Patients with QT interval greater than 500 ms were more frequently female(59.5%;P<0.001) and were more frequently on QT prolonging drugs(77.3%;P=0.025). Main contributing factor was intake of antibiotics(odds ratio [OR] 4.680) followed by female gender(OR 2.473) and intake of antipsychotics(OR 1.925).CONCLUSION: aLQTS is particularly prevalent in the ED. Female patients on antibiotics and antipsychotics are at particularly high risk. Efforts must be made to avoid, detect and treat aLQTS as early as possible.

Hepatitis C virus treatment with glecaprevir and pibrentasvir in patients co-prescribed carbamazepine:Three case reports

BACKGROUND Highly effective and well-tolerated direct-acting antiviral(DAA)therapies have revolutionised the management of hepatitis C virus(HCV);however,niche populations face treatment barriers.DAAs co-prescribed with several firstgeneration anti-epileptic drugs(AEDs)are contraindicated due to drug-drug interactions.A common example is carbamazepine whereby steady-state carbamazepine reduces the maximum concentration and area under the curve of velpatasvir,glecaprevir and pibrentasvir due to potent cytochrome P450(CYP)3A4 induction.Carbamazepine also induces P-glycoprotein which reduces glecaprevir and pibrentasvir’s area under curve to infinite time.Sofosbuvirvelpatasvir and glecaprevir-pibrentasvir are contraindicated in patients who are co-prescribed carbamazepine due to the risk of reduced DAA therapeutic effect and consequently,virological treatment failure.This presents a challenge for patients in whom carbamazepine substitution is medically unfeasible,impractical or unacceptable.However,the properties of current generation DAA therapies,including high-potency non-structural protein 5A inhibitory effect,may be sufficient to overcome reduced bioavailability arising from carbamazepine related CYP 3A4 and P-glycoprotein induction.CASE SUMMARY We present a case series of three patients with non-cirrhotic,treatment-naïve,genotype 1a,1b,and 3a HCV who were treated with a 12 wk course of glecaprevir-pibrentasvir,while co-prescribed carbamazepine for seizure disorders.Glecaprevir-pibrentasvir combination therapy was chosen due to its potent in vitro activity and low barrier to pan-genotypic resistance associated variants.DAA therapy was dose-separated from carbamazepine to maximise time to peak concentration,and taken with meals to improve absorption.Sustained virological response at 12 wk was achieved in each patient with no adverse outcomes.CONCLUSION DAA therapies,including glecaprevir-pibrentasvir,warrant consideration as a therapeutic agent in people with HCV who are co-prescribed carbamazepine,particularly if AED substitution is not feasible.

Clinical utilities and end-user experience of pharmacogenomics:39 mo of clinical implementation experience in an Australian hospital setting

BACKGROUND Pharmacogenomics(PG)testing is under-utilised in Australia.Our research provides Australia-specific data on the perspectives of patients who have had PG testing and those of the clinicians involved in their care,with the aim to inform wider adoption of PG into routine clinical practice.AIM To investigate the frequency of actionable drug gene interactions and assess the perceived utility of PG among patients and clinicians.METHODS We conducted a retrospective audit of PG undertaken by 100 patients at an Australian public hospital genetics service from 2018 to 2021.Via electronic surveys we compared and contrasted the experience,understanding and usage of results between these patients and their clinicians.RESULTS Of 100 patients who had PG,84% were taking prescription medications,of which 67% were taking medications with actionable drug-gene interactions.Twenty-five out of 81 invited patients and 17 out of 89 invited clinicians completed the surveys.Sixty-eight percent of patients understood their PG results and 48% had medications changed following testing.Paired patient-clinician surveys showed patient-perceived utility and experience was positive,contrasting their clinicians’hesitancy on PG adoption who identified insufficient education/training,lack of clinical support,test turnaround time and cost as barriers to adoption.CONCLUSION Our dichotomous findings between the perspectives of our patient and clinician cohorts suggest the uptake of PG is likely to be driven by patients and clinicians need to be prepared to provide information and guidance to their patients.