Clinical relevance of drug-drug interactions : a structured assessment procedure

Relevance of therapeutic prescription modifications in Dutch community pharmacies

OBJECTIVES

Community pharmacists modify prescriptions to solve or prevent drug-related problems. To assess the relevance of prescription modifications, they are usually judged on clinical outcomes only, overlooking their humanistic and economic impact. This study aims to evaluate therapeutic prescription modifications performed by Dutch community pharmacists in terms of clinical outcome, along with the humanistic aspect "usability" and economic aspect "efficiency."

METHODS

A multidisciplinary panel evaluated the relevance of 160 cases of therapeutic prescription modifications collected in community pharmacies. Cases were stratified for type of drug-related problem based on their frequency in the original set of modifications. Both the relevance in general and the impact on the individual aspects of effectiveness and medication safety, usability, and efficiency were evaluated.

KEY FINDINGS

Sixteen cases (10.0%) were excluded because of insufficient information for evaluation. Sixty percent of the 144 cases were evaluated as relevant (56.3% relevant and 4.2% highly relevant). The remaining cases (31.9%) were moderately relevant. For 7.6% of the cases, evaluations were inconclusive. In 25.0% of the cases, there was a major improvement on at least one of the aspects effectiveness, medication safety, usability, or efficiency.

CONCLUSIONS

The majority of therapeutic prescription modifications performed by Dutch community pharmacists were evaluated as relevant or highly relevant by a multidisciplinary panel. Modifications improved clinical, humanistic, and economic aspects. This shows the important role of community pharmacists in primary healthcare. Sharing more clinical information like indication, illness severity, and treatment plan will enable pharmacists to improve their contribution to safe medication use.

The Effect of Metformin and Hydrochlorothiazide on Cytochrome P450 3A4 Metabolism of Ivermectin: Insights from In Silico Experimentation

The spread of SARS-CoV-2 has led to an interest in using ivermectin (a potent antiparasitic agent) as an antiviral agent despite the lack of convincing in vivo clinical data for its use against COVID-19. The off-target prophylactic use of ivermectin adds a substantial risk of drug-drug interactions with pharmaceutical medications used to treat chronic conditions like diabetes and hypertension (metformin and hydrochlorothiazide, respectively). Therefore, this study aims to evaluate the potential drug-drug interactions between ivermectin with either metformin or hydrochlorothiazide. In silico experiments and high-throughput screening assays for CYP3A4 were conducted to understand how metformin and hydrochlorothiazide might affect CYP3A4's role in metabolizing ivermectin. The study findings indicated that hydrochlorothiazide is more stable than both ivermectin and metformin. This conclusion was further supported by root mean square fluctuation analysis, which showed that hydrochlorothiazide is more flexible. The variation in the principal component analysis scatter plot across the first three normal modes suggests hydrochlorothiazide has a more mobile conformation than ivermectin and metformin. Additionally, a strong inhibition of CYP3A4 by hydrochlorothiazide was observed, suggesting that hydrochlorothiazide's regulatory effects could significantly impede CYP3A4 activity, potentially leading to a reduced metabolism and clearance of ivermectin in the body. Concurrent administration of these drugs may result in drug-drug interactions and hinder the hepatic metabolism of ivermectin.

Model-informed dose optimization of mycophenolic acid in pediatric kidney transplant patients

PURPOSE

We aimed to develop and evaluate a population PK model of mycophenolic acid (MPA) in pediatric kidney transplant patients to aid MPA dose optimization.

METHODS

Data were collected from pediatric kidney transplant recipients from a Dutch academic hospital (Radboudumc, the Netherlands). Pharmacokinetic model-building and model-validation analyses were performed using NONMEM. Subsequently, we externally evaluated the final model using data from another academic hospital. The final model was used to develop an optimized dosing regimen.

RESULTS

Thirty pediatric patients were included of whom 266 measured MPA plasma concentrations, including 20 full pharmacokinetic (PK) curves and 24 limited sampling curves, were available. A two-compartment model with a transition compartment for Erlang-type absorption best described the data. The final population PK parameter estimates were Ktr (1.48 h-1; 95% CI, 1.15-1.84), CL/F (16.0 L h-1; 95% CI, 10.3-20.4), Vc/F (24.9 L; 95% CI, 93.0-6.71E25), Vp/F (1590 L; 95% CI, 651-2994), and Q/F (36.2 L h-1; 95% CI, 9.63-74.7). The performance of the PK model in the external population was adequate. An optimized initial dose scheme based on bodyweight was developed. With the licensed initial dose, 35% of patients were predicted to achieve the target AUC, compared to 42% using the optimized scheme.

CONCLUSION

We have successfully developed a pharmacokinetic model for MPA in pediatric renal transplant patients. The optimized dosing regimen is expected to result in better target attainment early in treatment. It can be used in combination with model-informed follow-up dosing to further individualize the dose when PK samples become available.

Potential drug-drug interactions and associated factors among hospitalized pediatric patients in Adigrat general hospital, Tigrai, north Ethiopia: a retrospective cross-sectional study

BACKGROUND

Drug-drug interactions (DDIs) are associated with increased or decreased adverse effects and decreased or decreased therapeutic effects. Hospitalized pediatric patients are exposed to a number of potential DDIs (pDDIs). There are limited studies on pDDIs among pediatric patients in Ethiopia. This study was aimed to evaluate the pDDIs and associated factors among hospitalized pediatric patients in Adigrat general hospital, Tigrai, northern Ethiopia.

METHODS

A retrospective cross-sectional study was carried out among hospitalized pediatric patients in Adigrat general hospital from 01 July 2020 to 31 August 2020. A simple random sampling technique was used to select medical charts. Micromedex 2.0 database was used to screen pDDIs. Data was analyzed using statistical package for social science version 21 and a P-value of ≤ 0.05 was considered statistically significant.

RESULTS

Of the total 146 patients studied, 100 (68.5%) were exposed for at least one pDDI. A total of 158 pDDIs consisting of 33 distinct interacting drug pairs were identified. About 19.3% of the patients had at least one major pDDI, 6.7% at least one moderate and 68.9% at least one minor pDDIs. On the other hand, 63.3% of the total pDDIs were minor and 25.9% major while 3. 8% were contraindicated pDDIs with 15.2% fair and 81.6% good level of documentation. The overall mean duration of pDDIs exposure was about 4.9 (1-23) days. The frequently occurring potential clinical consequences of pDDIs comprised increased risk of QT-interval prolongation (10.1%), theophylline toxicity (5.1%), antiepileptic toxicity (5.1%) and formation of ceftriaxone calcium precipitates (3.8%). Infant/toddler age group (adjusted odds ratio [AOR] = 31.961, 95% CI: 1.117-914.528), number of diseases (AOR = 0.255, 95% CI: 0.069-0.939) and polypharmacy (AOR = 0.276, 95% CI: 0.091-0.838) were associated with pDDIs exposures.

CONCLUSIONS

A large number of pediatric patients were exposed to a various pDDIs. Age, number of diseases and polypharmacy predicted for the occurrence of pDDIs. Besides, the major severity pDDIs encounted frequently in the current study can potentially lead to a life threatening cardio-vascular toxicicty from QT-interval prolongation. Clinicians should be vigilant to pDDIs to prevent potential clinical consequences of pDDIs. Moreover, computerized drug interaction screening and clincal pharmacy services should be practiced to improve patients' safety.

Herb-antitumour drug interaction risks: retrospective integrative oncology study

OBJECTIVES

The use of herbal medicine is widespread among oncology patients, with potentially negative interactions with anticancer drugs. This study identified herbal products being used among a cohort of oncology patients, assessing the risk for an herb-drug interaction.

METHODS

Herbal medicine use was examined among 42 oncology patients, identifying potential herb-drug interactions using four online sites. The risk for an interaction was scored using the Working Group on Pharmacotherapy and Drug Information of the Royal Dutch Association for the Advancement of Pharmacy (KNMP).

RESULTS

Most patients (62%) reported herbal medicine use, with 70 products identified; 8 herbs and 13 herbal formulas with unidentified components; and 24 anticancer drugs. Herbal medicine use was more prevalent among female patients (p=0.038), with only nine potential herb-drug interactions identified on at least one site. A maximal KNMP Score of 1 (ie, incomplete published case report) was found with only one interaction.

CONCLUSIONS

The risk for interactions between herbal products and anticancer drugs is difficult to predict, with online search engines providing limited and inconsistent information. Clinical implications of herb-antitumor drug interactions need to be better understood, enabling patients and their oncology healthcare providers to make informed decisions regarding their care.

Combined Effect of Basic Antiherpetic Drugs with a New Inhibitor of the Terminase Complex of Herpes Simplex Virus Type 1 in Vero Cell Cultures

Carriers of herpes simplex virus type 1 (HSV-1) account for more than 90% of the global population. Infection manifests itself in the formation of blisters and ulcers on the face or genitals and can cause blindness, encephalitis, and generalized infection. All first- and second-line modern antiherpetic drugs selectively inhibit viral DNA polymerase. The purine-benzoxazine conjugate LAS-131 ((S)-4-[6-(purin-6-yl)aminohexanoyl]-7,8-difluoro-3,4-dihydro-3-methyl-2H-[1,4]benzoxazine), which we have described earlier, uses the large subunit of the HSV-1 terminase complex as a biotarget and selectively inhibits HSV-1 reproduction in vitro. Basically new results were for the first time obtained to characterize the combined effect on human herpesvirus infection for LAS-131 used in combination with practically significant antiviral compounds, including the nucleoside analogs acyclovir (ACV), penciclovir (PCV), ganciclovir (GCV), brivudine (BVdU), iododeoxyuridine (IdU), and adenine arabinoside (Ara-A); the nucleoside phosphonate analog cidofovir (CDV); and the pyrophosphate analog foscarnet (FOS). A cytopathic effect (CPE) inhibition assay showed that the drug concentration that inhibited the virus-induced CPE by 50% decreased by a factor of 2 (an additive effect, FOS) or more (a synergistic effect; ACV, PCV, GCV, IdU, BVdU, Ara-A, and CDV) when the drugs were used in combination with LAS-131. Nonpermissive conditions for HSV-1 reproduction were thus created at lower drug concentrations, opening up new real possibilities to control human herpesvirus infection.

Developing practical recommendations for drug-disease interactions in patients with hypertension

Background

Hypertension, a significant risk factor for cardiovascular diseases, demands proactive management as cardiovascular diseases remain the leading cause of death worldwide. Reducing systolic and diastolic blood pressure levels below recommended reference values of <140/90 mmHg can lead to a significant reduction of the risk of CVD and all-cause mortality. However, treatment of hypertension can be difficult and the presence of comorbidities could further complicate this treatment. Drugs used to manage these comorbidities may inadvertently have an impact on blood pressure, resulting in a phenomenon known as drug-disease interaction. This study aims to assess the safety of medication that can affect blood pressure in patients with hypertension and provide practical recommendations for healthcare professionals.

Methods

For the development of recommendations for the drug-disease interaction (DDSI) hypertension, a six-step plan that combined literature selection and multidisciplinary expert opinion was used. The process involved (1) defining the scope of the DDSI and selecting relevant drugs, (2) collecting evidence, (3) data-extraction, (4) reaching of expert consensus, (5) publication and implementation of the recommendations in healthcare systems and (6) updating the information.

Results

An increase of 10 mmHg in systolic blood pressure and 5 mmHg in diastolic blood pressure was defined as clinically relevant. Corticosteroids, danazol, and yohimbine caused a clinically relevant DDSI with hypertension. Several other drugs with warnings for hypertension in the official product information were assessed to have no clinically relevant DDSI due to minor influence or lack of data on blood pressure. Drugs with evidence for a relevant change in blood pressure which are prescribed under close monitoring of blood pressure according to clinical guidelines, were deemed to be not clinically relevant for signalling.

Conclusion

This study provides specific recommendations that can be implemented directly in clinical practice, for example, in clinical decision support systems, potentially resulting in safer drug use in patients with hypertension and better healthcare by reducing alert fatigue. Future research should focus on evaluating the effectiveness of implementation strategies and their impact on reducing unsafe use of medication in patients with hypertension.

Comparative analysis of potential drug-drug interactions in a public and private hospital among chronic kidney disease patients in Khyber Pakhtunkhwa: A retrospective cross-sectional study

INTRODUCTION

Chronic kidney disease (CKD) is a significant public health challenge due to its rising incidence, mortality, and morbidity. Patients with kidney diseases often suffer from various comorbid conditions, making them susceptible to potential drug-drug interactions (pDDIs) due to polypharmacy and multiple prescribers. Inappropriate prescriptions for CKD patients and their consequences in the form of pDDIs are a major challenge in Pakistan.

AIM

This study aimed to compare the incidence and associated risk factors of pDDIs among a public and private sector hospital in Khyber Pakhtunkhwa, Pakistan.

METHOD

A retrospective cross-sectional study design was conducted to compare pDDIs among public and private sector hospitals from January 2023 to February 2023. Patients profile data for the full year starting from January 1 2022 to December 302022, was accessed All adult patients aged 18 years and above, of both genders, who currently have or have previously been diagnosed with end-stage renal disease (ESRD) were included. For assessing pDDIs, patient data was retrieved and checked using Lexicomp UpToDate® for severity and documentation of potential drug-drug interactions.

RESULTS

A total of 358 patients' data was retrieved (with n = 179 in each hospital); however, due to incomplete data, n = 4 patients were excluded from the final analysis. The prevalence of pDDIs was found to be significantly higher in private hospitals (84.7%) than in public hospitals (26.6%), with a p-value <0.001. Patients in the age category of 41-60 years (AOR = 6.2; p = 0.008) and those prescribed a higher number of drugs (AOR = 1.2; p = 0.027) were independently associated with pDDIs in private hospitals, while the higher number of prescribed drugs (AOR = 2.9; p = <0.001) was an independent risk factor for pDDIs in public hospitals. The majority of pDDIs (79.0%) were of moderate severity, and a significant number of patients (15.1%) also experienced major pDDIs, with a p-value <0.001. The majority of pDDIs had fair documentation for reliability rating in both public and private hospitals.

CONCLUSION

The prevalence of pDDIs was higher among CKD patients at private hospitals, and most of the pDDIs were of moderate severity. A considerable number of patients also experienced major pDDIs. The risk of experiencing pDDIs was found to be higher in older patients and among those prescribed a higher number of drugs.

Drug-drug Interaction between Psychotropic Medications and Medications Used in COVID-19: Comparison of Online Databases

Objective

COVID-19 has gravely affected patients with psychiatric conditions. Potential interactions may occur between psychotropic medications and medications used in treatment of COVID-19. This study aimed to compare the online databases in terms of the quality of drug-drug interaction related information available on them.

Methods

216 drug interactions which included fifty-four psychotropic medication interactions with four COVID-19 drugs across six databases were analyzed by four authors independently. The overall grading of the databases was done on Likert scale independently by the authors using the parameters of ease of understanding for consumers and professionals, level of completeness, discussion on level of evidence and the number of available drugs, congruity with other databases and the mean score was tabulated.

Results

Drugbank and Lexicomp had maximum discrepancy. The safety profile of Hydroxychloroquine was the best (eighteen moderate/severe psychotropic medication reactions) while Ritonavir has worst profile with thirty-nine medications. Drugbank had the highest SCOPE score (1.00) for completeness and covid19druginteractions.com had least (0.81). Overall, Liverpool© Drug Interaction Group and Lexicomp scored the highest (23/30 each) and were the best interaction checker software closely followed by Drugs.com (22/30). Medscape and WebMD were the poorest interaction checker databases.

Conclusion

There is significant variability in the available online databases. Liverpool© Drug Interaction Group and Lexicomp were the most reliable sources for healthcare workers whereas for patients, Drugs.com was the easiest to understand (as it segregates the needs of general consumers and professionals distinctly to explain the interaction).

Identification and Empiric Evaluation of New Inhibitors of the Multidrug Transporter P-Glycoprotein (ABCB1)

The expression of the drug efflux pump ABCB1 correlates negatively with cancer survival, making the transporter an attractive target for therapeutic inhibition. In order to identify new inhibitors of ABCB1, we have exploited the cryo-EM structure of the protein to develop a pharmacophore model derived from the best docked conformations of a structurally diverse range of known inhibitors. The pharmacophore model was used to screen the Chembridge compound library. We identified six new potential inhibitors with distinct chemistry compared to the third-generation inhibitor tariquidar and with favourable lipophilic efficiency (LipE) and lipophilicity (CLogP) characteristics, suggesting oral bioavailability. These were evaluated experimentally for efficacy and potency using a fluorescent drug transport assay in live cells. The half-maximal inhibitory concentrations (IC50) of four of the compounds were in the low nanomolar range (1.35 to 26.4 nM). The two most promising compounds were also able to resensitise ABCB1-expressing cells to taxol. This study demonstrates the utility of cryo-electron microscopy structure determination for drug identification and design.

Influenza Treatment: Limitations of Antiviral Therapy and Advantages of Drug Combination Therapy

Influenza infection is serious and debilitating for humans and animals. The influenza virus undergoes incessant mutation, segment recombination, and genome reassortment. As a result, new epidemics and pandemics are expected to emerge, making the elimination challenging of the disease. Antiviral therapy has been used for the treatment of influenza since the development of amantadine in the 1960s; however, its use is hampered by the emergence of novel strains and the development of drug resistance. Thus, combinational therapy with two or more antivirals or immunomodulators with different modes of action is the optimal strategy for the effective treatment of influenza infection. In this review, we describe current options for combination therapy, their performance, and constraints imposed by resistance, calling attention to the advantages of combination therapy against severe influenza infections. We also discuss the challenges of influenza therapy and the limitations of approved antiviral drugs.

Preclinical and clinical developments for combination treatment of influenza

Antiviral drugs are an important measure of control for influenza in the population, particularly for those that are severely ill or hospitalised. The neuraminidase inhibitor (NAI) class of drugs, including oseltamivir, have been the standard of care (SOC) for severe influenza illness for many years. The approval of drugs with novel mechanisms of action, such as baloxavir marboxil, is important and broadens potential treatment options for combination therapy. The use of antiviral treatments in combination for influenza is of interest; one potential benefit of this treatment strategy is that the combination of drugs with different mechanisms of action may lower the selection of resistance due to treatment. In addition, combination therapy may become an important treatment option to improve patient outcomes in those with severe illness due to influenza or those that are immunocompromised. Clinical trials increasingly evaluate drug combinations in a range of patient cohorts. Here, we summarise preclinical and clinical advances in combination therapy for the treatment of influenza with reference to immunocompromised animal models and clinical data in hospitalised patient cohorts where available. There is a wide array of drug categories in development that have also been tested in combination. Therefore, in this review, we have included polymerase inhibitors, monoclonal antibodies (mAbs), host-targeted therapies, and adjunctive therapies. Combination treatment regimens should be carefully evaluated to determine whether they provide an added benefit relative to effectiveness of monotherapy and in a variety of patient cohorts, particularly, if there is a greater chance of an adverse outcome. Safe and effective treatment of influenza is important not only for seasonal influenza infection, but also if a pandemic strain was to emerge.

Contextualized Drug-Drug Interaction Management Improves Clinical Utility Compared With Basic Drug-Drug Interaction Management in Hospitalized Patients

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context‐dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI‐CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P < 0.01), with 4.0 PIs/1,000 MOs (P < 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management.

Anti-DDI Resource: A Dataset for Potential Negative Reported Interaction Combinations to Improve Medical Research and Decision-Making

Potential drug-drug interactions (DDIs) are a core concern across medical decision support systems. Among healthcare practitioners, the common practice for screening these interactions is via computer software. However, as real-world negative reporting is missing, counterexamples that serve as contradictory evidence may exist. In this study, we have developed an anti-DDI resource, a set of drug combinations having negative reported interactions. This resource was created from a set of the top 200 most-used drugs, resulting in 14365 prospective negative reported DDI pairs. During analysis and filtering, 2110 DDIs (14.69%) were found in publicly free DDI resources, another 11130 (77.48%) were filtered by a rule-based inference engine incorporating ten mechanisms of interaction, and 208 were identified through commercial resources. Additionally, 90 pairs were removed due to recent FDA approvals or being unapplicable in clinical use. The final set of 827 drug pairs represents combinations potentially having negative reported interactions. The anti-DDI resource is intended to provide a distinctly different direction from the state of the art and establish a ground focus more centered on the evaluation and utilization of existing knowledge for performing thorough assessments. Our negative reported DDIs resource shall provide healthcare practitioners with a level of certainty on DDIs that is worth investigating.

Lithium surveillance by community pharmacists and physicians in ambulatory patients: a retrospective cohort study

BACKGROUND

Shared care agreements between clinical pharmacists and physicians can improve suboptimal lithium monitoring in in- and outpatient settings. However, it is unknown whether incorporating community pharmacists in such agreements can also improve lithium monitoring in an outpatient setting.

AIM

To assess the necessity for a shared care agreement for lithium monitoring in our region by investigating: intervention rates by community pharmacists and whether those are sufficient; lithium monitoring by physicians in ambulatory patients; the extent of laboratory parameter exchange to community pharmacists.

METHOD

Patient files of lithium users were surveyed in a retrospective cohort study among 21 community pharmacies in the Northern Netherlands. Outcome was the intervention rate by community pharmacists and whether those were deemed sufficient by an expert panel. Additionally, we investigated both the percentages of patients monitored according to current guidelines and of laboratory parameters exchanged to community pharmacists.

RESULTS

129 patients were included. Interventions were performed in 64.4% (n = 29), 20.8% (n = 5), and 25.0% (n = 1) of initiations, discontinuations, and dosage alterations of drugs interacting with lithium, respectively. The expert panel deemed 40.0% (n = 14) of these interventions as "insufficient". Physicians monitored 40.3% (n = 52) of the patients according to current guidelines for lithium serum levels and kidney functions combined. Approximately half of the requested laboratory parameters were available to the community pharmacist.

CONCLUSION

Intervention rates by community pharmacists and lithium monitoring by physicians can be improved. Therefore, a shared care agreement between community pharmacists, clinical pharmacists, and physicians is needed to improve lithium monitoring in ambulatory patients.

Man vs. machine: comparison of pharmacogenetic expert counselling with a clinical medication support system in a study with 200 genotyped patients

Background

Medication problems such as strong side effects or inefficacy occur frequently. At our university hospital, a consultation group of specialists takes care of patients suffering from medication problems. Nevertheless, the counselling of poly-treated patients is complex, as it requires the consideration of a large network of interactions between drugs and their targets, their metabolizing enzymes, and their transporters, etc.

Purpose

This study aims to check whether a score-based decision-support system (1) reduces the time and effort and (2) suggests solutions at the same quality level.

Patients and methods

A total of 200 multimorbid, poly-treated patients with medication problems were included. All patients were considered twice: manually, as clinically established, and using the Drug-PIN decision-support system. Besides diagnoses, lab data (kidney, liver), phenotype (age, gender, BMI, habits), and genotype (genetic variants with actionable clinical evidence I or IIa) were considered, to eliminate potentially inappropriate medications and to select individually favourable drugs from existing medication classes. The algorithm is connected to automatically updated knowledge resources to provide reproducible up-to-date decision support.

Results

The average turnaround time for manual poly-therapy counselling per patient ranges from 3 to 6 working hours, while it can be reduced to ten minutes using Drug-PIN. At the same time, the results of the novel computerized approach coincide with the manual approach at a level of > 90%. The holistic medication score can be used to find favourable drugs within a class of drugs and also to judge the severity of medication problems, to identify critical cases early and automatically.

Conclusion

With the computerized version of this approach, it became possible to score all combinations of all alternative drugs from each class of drugs administered (“personalized medication landscape “) and to identify critical patients even before problems are reported (“medication alert”). Careful comparison of manual and score-based results shows that the incomplete manual consideration of genetic specialties and pharmacokinetic conflicts is responsible for most of the (minor) deviations between the two approaches. The meaning of the reduction of working time for experts by about 2 orders of magnitude should not be underestimated, as it enables practical application of personalized medicine in clinical routine.

Integration of Clinical and Scientific Principles in the Teaching of Drug-Drug Interactions

Evaluation of drug-drug interactions (DDIs) is an integral part of pharmacy practice worldwide. An understanding of the scientific mechanisms behind and the clinical implications of DDIs is important for proper management of pharmacotherapy. Here, we describe an integrated approach to teaching both aspects of DDIs as a standalone module in diverse course settings. These include on-campus and online delivery to international and local audiences in small and large classes. We describe the scientific, clinical, and integrated learning objectives of the module, and we show how these can be achieved through group projects based on published DDI case reports.

Rifampicin Induces Gene, Protein, and Activity of P-Glycoprotein (ABCB1) in Human Precision-Cut Intestinal Slices

P-glycoprotein (ABCB1), an ATP-binding cassette efflux transporter, limits intestinal absorption of its substrates and is a common site of drug–drug interactions. Drug-mediated induction of intestinal ABCB1 is a clinically relevant phenomenon associated with significantly decreased drug bioavailability. Currently, there are no well-established human models for evaluating its induction, so drug regulatory authorities provide no recommendations for in vitro/ex vivo testing drugs’ ABCB1-inducing activity. Human precision-cut intestinal slices (hPCISs) contain cells in their natural environment and express physiological levels of nuclear factors required for ABCB1 induction. We found that hPCISs incubated in William’s Medium E for 48 h maintained intact morphology, ATP content, and ABCB1 efflux activity. Here, we asked whether rifampicin (a model ligand of pregnane X receptor, PXR), at 30 μM, induces functional expression of ABCB1 in hPCISs over 24- and 48-h incubation (the time to allow complete induction to occur). Rifampicin significantly increased gene expression, protein levels, and efflux activity of ABCB1. Moreover, we described dynamic changes in ABCB1 transcript levels in hPCISs over 48 h incubation. We also observed that peaks of induction are achieved among donors at different times, and the extent of ABCB1 gene induction is proportional to PXR mRNA levels in the intestine. In conclusion, we showed that hPCISs incubated in conditions comparable to those used for inhibition studies can be used to evaluate drugs’ ABCB1-inducing potency in the human intestine. Thus, hPCISs may be valuable experimental tools that can be prospectively used in complex experimental evaluation of drug–drug interactions.

Pharmacogenetic testing in psychiatry and neurology: an overview of reviews

Pharmacogenetic testing is available to healthcare professionals to guide drug selection and prevent adverse events. However, its implementation in the clinical practice of psychiatry/neurology still has barriers, mainly due to a lack of evidence. We conducted a literature search on Cochrane Library, Embase and Pubmed, from their inception to 18 June 2020. We included 16 published systematic reviews. The most studied drug categories were anticonvulsants and selective serotonin reuptake inhibitors associated with human leukocyte antigen and cytochrome P450 genes (HLA-A, HLA-B, CYP2C9, CYP2D6, CYP2C19), classified as critically low quality/low quality. There is a need for more robust studies with adequate design to assess the potential benefits of adopting pharmacogenetics in health systems and services.

A Minimal Information Model for Potential Drug-Drug Interactions

Despite the significant health impacts of adverse events associated with drug-drug interactions, no standard models exist for managing and sharing evidence describing potential interactions between medications. Minimal information models have been used in other communities to establish community consensus around simple models capable of communicating useful information. This paper reports on a new minimal information model for describing potential drug-drug interactions. A task force of the Semantic Web in Health Care and Life Sciences Community Group of the World-Wide Web consortium engaged informaticians and drug-drug interaction experts in in-depth examination of recent literature and specific potential interactions. A consensus set of information items was identified, along with example descriptions of selected potential drug-drug interactions (PDDIs). User profiles and use cases were developed to demonstrate the applicability of the model. Ten core information items were identified: drugs involved, clinical consequences, seriousness, operational classification statement, recommended action, mechanism of interaction, contextual information/modifying factors, evidence about a suspected drug-drug interaction, frequency of exposure, and frequency of harm to exposed persons. Eight best practice recommendations suggest how PDDI knowledge artifact creators can best use the 10 information items when synthesizing drug interaction evidence into artifacts intended to aid clinicians. This model has been included in a proposed implementation guide developed by the HL7 Clinical Decision Support Workgroup and in PDDIs published in the CDS Connect repository. The complete description of the model can be found at https://w3id.org/hclscg/pddi.

Pharmacogenetics Guidelines: Overview and Comparison of the DPWG, CPIC, CPNDS, and RNPGx Guidelines

Many studies have shown that the efficacy and risk of side effects of drug treatment is influenced by genetic variants. Evidence based guidelines are essential for implementing pharmacogenetic knowledge in daily clinical practice to optimize pharmacotherapy of individual patients. A literature search was performed to select committees developing guidelines with recommendations being published in English. The Dutch Pharmacogenetics Working Group (DPWG), the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and the French National Network (Réseau) of Pharmacogenetics (RNPGx) were selected. Their guidelines were compared with regard to the methodology of development, translation of genotypes to predicted phenotypes, pharmacotherapeutic recommendations and recommendations on genotyping. A detailed overview of all recommendations for gene-drug combinations is given. The committees have similar methodologies of guideline development. However, the objectives differed at the start of their projects, which have led to unique profiles and strengths of their guidelines. DPWG and CPIC have a main focus on pharmacotherapeutic recommendations for a large number of drugs in combination with a patient’s genotype or predicted phenotype. DPWG, CPNDS and RNPGx also recommend on performing genetic testing in daily clinical practice, with RNPGx even describing specific clinical settings or medical conditions for which genotyping is recommended. Discordances exist, however committees also initiated harmonizing projects. The outcome of a consensus project was to rename “extensive metabolizer (EM)” to “normal metabolizer (NM)”. It was decided to translate a CYP2D6 genotype with one nonfunctional allele (activity score 1.0) into the predicted phenotype of intermediate metabolizer (IM). Differences in recommendations are the result of the methodologies used, such as assessment of dose adjustments of tricyclic antidepressants. In some cases, indication or dose specific recommendations are given for example for clopidogrel, codeine, irinotecan. The following drugs have recommendations on genetic testing with the highest level: abacavir (HLA), clopidogrel (CYP2C19), fluoropyrimidines (DPYD), thiopurines (TPMT), irinotecan (UGT1A1), codeine (CYP2D6), and cisplatin (TPMT). The guidelines cover many drugs and genes, genotypes, or predicted phenotypes. Because of this and their unique features, considering the totality of guidelines are of added value. In conclusion, many evidence based pharmacogenetics guidelines with clear recommendations are available for clinical decision making by healthcare professionals, patients and other stakeholders.

Drug safety in hospitalized patients with tuberculosis: Drug interactions and adverse drug effects

BACKGROUND

Hospitalized patients with tuberculosis (TB) are prescribed with drugs having high risk of potential drug-drug interactions (pDDIs) and adverse drug effects (ADEs).

OBJECTIVES

To explore the adverse effects of anti-tuberculosis (anti-TB) drugs and the prevalence and predictors of pDDIs in hospitalized patients with TB.

METHODS

Clinical profiles of 436 TB patients were reviewed for adverse effects induced by anti-TB drugs and screened for pDDIs using Micromedex-DrugReax. Prevalence and severity levels of pDDIs were reported. Odds ratios for predictors were calculated using logistic regression analysis.

RESULTS

Of total 436 patients, adverse effects of anti-TB drugs were found in 36%. ADEs were highly prevalent in patients with high doses of anti-TB drugs. Hepatotoxicity, neuropathy, insomnia, arthralgia, psychosis, hematological alterations, skin rashes, red color stool, diplopia, and photophobia were the identified ADEs. All drugs types- and anti-TB drugs-pDDIs were reported in 78.2% and 55.7%, respectively. Major-pDDIs of anti-TB drugs were identified in 55.5%. Total 1090 anti-TB drugs pDDIs were found, among them, 55.6% were of major- and 40.5% were of moderate-severity. Significant association was observed for the pDDIs with ≥7 prescribed medicines (P < 0.001). Potential adverse outcomes of the most frequent interactions were hepatotoxicity, decreased drug's effectiveness, QT-interval prolongation, nephrotoxicity, and gastrointestinal ulceration.

CONCLUSIONS

Patients with TB present with a considerable number of clinically important pDDIs and ADEs (particularly hepatotoxicity). TB patients should be monitored for adverse effects of anti-TB drugs. Attention should be given to major-pDDIs. Patients more at risk to interactions should be identified and monitored for related adverse outcomes.

Potential drug-drug interactions associated with adverse clinical outcomes and abnormal laboratory findings in patients with malaria

BACKGROUND

Hospitalized patients with malaria often present with comorbidities or associated complications for which a variety of drugs are prescribed. Multiple drug therapy often leads to drug-drug interactions (DDIs). Therefore, the current study investigated the prevalence, levels, risk factors, clinical relevance, and monitoring parameters/management guidelines of potential DDIs (pDDIs) among inpatients with malaria.

METHODS

A retrospective cohort study was carried out at two tertiary care hospitals. A total of 398 patients' profiles were evaluated for pDDIs using the Micromedex Drug-Reax^®. Odds ratios were calculated to identify the strength of association between presence of DDIs and potential risk factors via logistic regression analysis. Further, the clinical relevance of frequent pDDIs was investigated.

RESULTS

Of 398 patients, pDDIs were observed in 37.2% patients, while major-pDDIs in 19.3% patients. A total of 325 interactions were found, of which 45.5% were of major- and 34.5% moderate-severity. Patients with the most common pDDIs were found with signs/symptoms and abnormalities in laboratory findings representing nephrotoxicity, hepatotoxicity, QT interval prolongation, and reduced therapeutic efficacy. The following drug pairs reported the highest frequency of adverse events associated with the interactions; calcium containing products-ceftriaxone, isoniazid-rifampin, pyrazinamide-rifampin, isoniazid-acetaminophen, and ciprofloxacin-metronidazole. The adverse events were more common in patients prescribed with the higher doses of interacting drugs. Multivariate regression analysis showed statistically significant association of pDDIs with 5-6 prescribed medicines (p = 0.01), > 6 prescribed medicines (p < 0.001), > 5 days of hospital stay (p = 0.03), and diabetes mellitus (p = 0.04).

CONCLUSIONS

PDDIs are commonly observed in patients with malaria. Healthcare professional's knowledge about the most common pDDIs could help in preventing pDDIs and their associated negative effects. Pertinent clinical parameters, such as laboratory findings and signs/symptoms need to be checked, particularly in patients with polypharmacy, longer hospital stay, and diabetes mellitus.

Improving antibacterial prescribing safety in the management of COPD exacerbations: systematic review of observational and clinical studies on potential drug interactions associated with frequently prescribed antibacterials among COPD patients

Background

Guidelines advise the use of antibacterials (ABs) in the management of COPD exacerbations. COPD patients often have multiple comorbidities, such as diabetes mellitus and cardiac diseases, leading to polypharmacy. Consequently, drug–drug interactions (DDIs) may frequently occur, and may cause serious adverse events and treatment failure.

Objectives

(i) To review DDIs related to frequently prescribed ABs among COPD patients from observational and clinical studies. (ii) To improve AB prescribing safety in clinical practice by structuring DDIs according to comorbidities of COPD.

Methods

We conducted a systematic review by searching PubMed and Embase up to 8 February 2018 for clinical trials, cohort and case–control studies reporting DDIs of ABs used for COPD. Study design, subjects, sample size, pharmacological mechanism of DDI and effect of interaction were extracted. We evaluated levels of DDIs and quality of evidence according to established criteria and structured the data by possible comorbidities.

Results

In all, 318 articles were eligible for review, describing a wide range of drugs used for comorbidities and their potential DDIs with ABs. DDIs between ABs and co-administered drugs could be subdivided into: (i) co-administered drugs altering the pharmacokinetics of ABs; and (ii) ABs interfering with the pharmacokinetics of co-administered drugs. The DDIs could lead to therapeutic failures or toxicities.

Conclusions

DDIs related to ABs with clinical significance may involve a wide range of indicated drugs to treat comorbidities in COPD. The evidence presented can support (computer-supported) decision-making by health practitioners when prescribing ABs during COPD exacerbations in the case of co-medication.

Pilot study: Evaluation of potential drug-drug interactions in hospitalized pediatric patients

PURPOSE

Evaluate the type and severity of potential drug-drug interactions and identify risk factors involved, in pediatric patients admitted in a hospital setting.

METHODS

Transversal retrospective analytical study was carried out with hospitalized pediatric patients from a Hospital in the West of Mexico, second and third level. The patients included were ≤18 years old hospitalized in the children wards; those admitted at the emergency room, neonatal intermediate and intensive therapy units were not included. Medical prescriptions were reviewed taking into consideration anthropometric characteristics, diagnosis and number of drugs prescribed to identify potential drug-drug interactions using Micromedex 2.0 database.

RESULTS

88 patients were included, an average of 4.6 ± 2.8 of drugs were prescribed per patient. 37 subjects (42%) presented some degree of potential drug-drug interactions of which 25.5% were major and 27.7% moderate according to the software. Identified risk factors were: age ≥ 4 years (OR 1.917; 95% CI 1.081-3.399), BSA ≥ 0.8m2(OR 1.825; 95% CI 1.021-3.263), height ≥ 1 m (OR 2.556;95% CI 1.322 - 4.941), and number of prescribed medications ≥ 4 (OR 2.106;95% CI 1.248 - 3.556).

CONCLUSION

Some of the interactions found were for the benefit of the patient, but others were considered undesirable because they altered the pharmacokinetics of some of the medications administered. Detecting in time the harmful interactions for a patient may favor the patient's safety.

The Development of Practice Recommendations for Drug-Disease Interactions by Literature Review and Expert Opinion

Background

Drug-disease interactions negatively affect the benefit/risk ratio of drugs for specific populations. In these conditions drugs should be avoided, adjusted, or accompanied by extra monitoring. The motivation for many drug-disease interactions in the Summary of Product Characteristics (SmPC) is sometimes insufficiently supported by (accessible) evidence. As a consequence the translation of SmPC to clinical practice may lead to non-specific recommendations. For the translation of this information to the real world, it is necessary to evaluate the available knowledge about drug-disease interactions, and to formulate specific recommendations for prescribers and pharmacists. The aim of this paper is to describe a standardized method how to develop practice recommendations for drug-disease interactions by literature review and expert opinion.

Methods

The development of recommendations for drug-disease interactions will follow a six-step plan involving a multidisciplinary expert panel (1). The scope of the drug-disease interaction will be specified by defining the disease and by describing relevant effects of this drug-disease interaction. Drugs possibly involved in this drug-disease interaction are selected by checking the official product information, literature, and expert opinion (2). Evidence will be collected from the official product information, guidelines, handbooks, and primary literature (3). Study characteristics and outcomes will be evaluated and presented in standardized reports, including preliminary conclusions on the clinical relevance and practice recommendations (4). The multidisciplinary expert panel will discuss the reports and will either adopt or adjust the conclusions (5). Practice recommendations will be integrated in clinical decision support systems and published (6). The results of the evaluated drug-disease interactions will remain up-to-date by screening new risk information, periodic literature review, and (re)assessments initiated by health care providers.

Actionable Recommendations

The practice recommendations will result in advices for specific DDSI. The content and considerations of these DDSIs will be published and implemented in all Clinical Decision Support Systems in the Netherlands.

Discussion

The recommendations result in professional guidance in the context of individual patient care. The professional will be supported in the decision making in concerning pharmacotherapy for the treatment of a medical problem, and the clinical risks of the proposed medication in combination with specific diseases.

Prevalence and Accuracy of Information on CYP2D6, CYP2C19, and CYP2C9 Related Substrate and Inhibitor Co-Prescriptions in the General Population: A Cross-Sectional Descriptive Study as Part of the PharmLines Initiative

BACKGROUND

Drug-drug interaction (DDI) is one of the main contributors to adverse drug reactions and therefore, it is important to study its frequency in the population. We aimed to investigate frequency and concordance on CYP2D6, CYP2C19, and CYP2C9 (CYP2D6/2C19/2C9)-mediated potential DDIs at the Lifelines cohort and linked data from the pharmacy database IADB.nl.

METHODS

As part of the University of Groningen PharmLines Initiative, data were collected on CYP2D6/2C19/2C9-related substrate/inhibitors from entry questionnaires of Lifelines participants and linked information from the pharmacy database IADB.nl. CYP2D6/2C19/2C9 related co-prescriptions were divided based on the type of drugs i.e. chronically used medication (CM) or occasionally used medication (OM). This resulted in the combination of two chronically used drugs (CM-CM), chronically and occasionally used medication (CM-OM), and two occasionally used drugs (OM-OM). To measure the agreement level, cohen's kappa statistics and test characteristics were used. Results were stratified by time window, gender, and age.

RESULTS

Among 80,837 medicine users in the Lifelines, about 1-2 per hundred participants were exposed to a CYP2D6/2C19/2C9-mediated potential DDI. Overall, the overlapping time window of three months produced the highest mean kappa values between the databases i.e. 0.545 (95% CI:0.544-0.545), 0.512 (95% CI:0.511-0.512), and 0.374 (95% CI:0.373-0.375), respectively. CM-CM had a better level of agreement (good) than CM-OM (fair to moderate) and OM-OM combination (poor to moderate). The influence of gender on concordance values was different for different CYPs. Among older persons, agreement levels were higher than for the younger population.

CONCLUSIONS

CYP2D6/2C19/2C9-mediated potential DDIs were frequent and concordance of data varied by time window, type of combination, sex and age. Subsequent studies should rather use a combination of self-reported and pharmacy database information.

Testing the face validity and inter-rater agreement of a simple approach to drug-drug interaction evidence assessment

Low concordance between drug-drug interaction (DDI) knowledge bases is a well-documented concern. One potential cause of inconsistency is variability between drug experts in approach to assessing evidence about potential DDIs. In this study, we examined the face validity and inter-rater reliability of a novel DDI evidence evaluation instrument designed to be simple and easy to use.

METHODS

A convenience sample of participants with professional experience evaluating DDI evidence was recruited. Participants independently evaluated pre-selected evidence items for 5 drug pairs using the new instrument. For each drug pair, participants labeled each evidence item as sufficient or insufficient to establish the existence of a DDI based on the evidence categories provided by the instrument. Participants also decided if the overall body of evidence supported a DDI involving the drug pair. Agreement was computed both at the evidence item and drug pair levels. A cut-off of ≥ 70% was chosen as the agreement threshold for percent agreement, while a coefficient > 0.6 was used as the cut-off for chance-corrected agreement. Open ended comments were collected and coded to identify themes related to the participants' experience using the novel approach.

RESULTS

The face validity of the new instrument was established by two rounds of evaluation involving a total of 6 experts. Fifteen experts agreed to participate in the reliability assessment, and 14 completed the study. Participant agreement on the sufficiency of 22 of the 34 evidence items (65%) did not exceed the a priori agreement threshold. Similarly, agreement on the sufficiency of evidence for 3 of the 5 drug pairs (60%) was poor. Chance-corrected agreement at the drug pair level further confirmed the poor interrater reliability of the instrument (Gwet's AC1 = 0.24, Conger's Kappa = 0.24). Participant comments suggested several possible reasons for the disagreements including unaddressed subjectivity in assessing an evidence item's type and study design, an infeasible separation of evidence evaluation from the consideration of clinical relevance, and potential issues related to the evaluation of DDI case reports.

CONCLUSIONS

Even though the key findings were negative, the study's results shed light on how experts approach DDI evidence assessment, including the importance situating evidence assessment within the context of consideration of clinical relevance. Analysis of participant comments within the context of the negative findings identified several promising future research directions including: novel computer-based support for evidence assessment; formal evaluation of a more comprehensive evidence assessment approach that requires consideration of specific, explicitly stated, clinical consequences; and more formal investigation of DDI case report assessment instruments.

Potential Drug-Drug Interactions in Patients With Urinary Tract Infections: A Contributing Factor in Patient and Medication Safety

Introduction: Hospitalized patients with urinary tract infections (UTIs) often present with comorbid illnesses and are subsequently prescribed multiple medications, which increases the likelihood of drug-drug interactions. Therefore, this study aimed to explore the prevalence, levels, risk factors, and clinical relevance of potential drug-drug interactions (pDDIs) in hospitalized patients with UTIs. Secondly, we aimed to develop management guidelines and identify monitoring parameters for the most frequent interactions.

Methods: A retrospective cross-sectional study was conducted in internal medicine wards of two tertiary care hospitals in Peshawar, Khyber Pakhtunkhwa, Pakistan. The clinical profiles of 422 patients with UTIs were reviewed for pDDIs using the Micromedex Drug-Reax^®. Logistic regression was applied to assess the association of pDDIs with various risk factors. The clinical relevance of frequent pDDIs was identified by assessing the potential adverse outcomes of pDDIs including patients’ signs, symptoms, and abnormal laboratory findings.

Results: Of 422 patients, at least one pDDI was identified in 62.3% patients, while 40% patients had at least one major pDDI. A total of 1,086 pDDIs were identified, of which 53.4% and 39.3% were of moderate and major severity, respectively. Patients with most frequent pDDIs were presented with hypoglycemia, hepatotoxicity, nephrotoxicity, hypertension, and decreased therapeutic response. These adverse events were more prevalent in patients taking higher doses of interacting drugs. Multivariate regression analysis revealed significant association of pDDIs with six or more medicines (p < 0.001), diabetes mellitus (p < 0.001), ischemic heart disease (p = 0.02), and congestive cardiac failure (p = 0.04).

Conclusions: Patients with UTIs present with a considerable number of clinically important pDDIs. Polypharmacy, diabetes mellitus, ischemic heart disease, and congestive cardiac failure increase the risk of pDDIs. Knowledge about the most frequent pDDIs will enable healthcare professionals to implement optimized monitoring and management strategies regarding associated adverse consequences in order to ensure patient safety. Most of the interactions can be managed by considering alternative therapy and dose reduction.

Polypharmacy and drug-drug interactions among older and younger male prisoners in Switzerland

PURPOSE

The purpose of this paper is to determine the prevalence of polypharmacy and drug-drug interactions (DDIs) in older and younger prisoners, and compared if age group is associated with risks of polypharmacy and DDIs.

DESIGN/METHODOLOGY/APPROACH

For 380 prisoners from Switzerland (190 were 49 years and younger; 190 were 50 years and older), data concerning their medication use were gathered. MediQ identified if interactions of two or more substances could lead to potentially adverse DDI. Data were analysed using descriptive statistics and generalised linear mixed models.

FINDINGS

On average, older prisoners took 3.8 medications, while younger prisoners took 2.1 medications. Number of medications taken on one reference day was higher by a factor of 2.4 for older prisoners when compared to younger prisoners (p = 0.002). The odds of polypharmacy was significantly higher for older than for younger prisoners (>=5 medications: odds ratio = 5.52, p = 0.035). Age group analysis indicated that for potentially adverse DDI there was no significant difference (odds ratio = 0.94; p = 0.879). However, when controlling for the number of medication, the risk of adverse DDI was higher in younger than older prisoners, but the result was not significant.

ORIGINALITY/VALUE

Older prisoners are at a higher risk of polypharmacy but their risk for potentially adverse DDI is not significantly different from that of younger prisoners. Special clinical attention must be given to older prisoners who are at risk for polypharmacy. Careful medication management is also important for younger prisoners who are at risk of very complex drug therapies.

Compliance with the guidelines for laboratory monitoring of patients treated with lithium: A retrospective follow-up study among ambulatory patients in the Netherlands

OBJECTIVES

Laboratory monitoring of patients using lithium is important to prevent harm and to increase effectiveness. The aim of this study is to determine compliance with the guidelines for laboratory monitoring of patients treated with lithium overall and within subgroups.

METHODS

Patients having at least one lithium dispensing for 6 months or longer between January 2010 and December 2015 were identified retrospectively using data from the Dutch PHARMO Database Network. Laboratory monitoring was defined as being compliant with the Dutch Multidisciplinary Clinical Guideline Bipolar Disorders when lithium serum levels, creatinine and thyroid-stimulating hormone (TSH) had been measured at least every 6 months during lithium use.

RESULTS

Data were analyzed from 1583 patients with a median duration of 7- to 6-months period of lithium use. Results indicated that patients had been monitored over 6-month period for lithium serum levels 65% of the time, for creatinine 73% of the time and for TSH 54% of the time. Just over one seventh (16%) of patients had been monitored in compliance with the guidelines for all three parameters during total follow-up. Especially males, patients aged below 65 years, patients receiving prescriptions solely from general practitioners, prevalent users of lithium, patients without interacting co-medication, and patients without other days with laboratory measurements had been monitored less frequently in compliance with the guidelines.

CONCLUSIONS

A considerable proportion of patients had not been monitored in accordance with the guidelines. Further research is needed to understand the reasons for noncompliance and to implement strategies with the ultimate goal of optimizing safety and effectiveness for patients treated with lithium.

Potential drug-drug interactions among pneumonia patients: do these matter in clinical perspectives?

BACKGROUND

Pneumonia patients are usually hospitalized due to severe nature of the disease or for the management of comorbid illnesses or associated symptoms. Such patients are prescribed with multiple medications which increase the likelihood of potential drug-drug interactions (pDDIs). Therefore, in this study the prevalence, levels (severity and documentation), predictors (risk factors), and clinical relevance of pDDIs among inpatients diagnosed with pneumonia have been investigated.

METHODS

Clinical records of 431 hospitalized patients with pneumonia were checked for pDDIs using drug interactions screening software (Micromedex-DrugReax). Odds-ratios for predictors were calculated using logistic regression analysis. Clinical relevance of pDDIs was assessed by evaluation of patients' clinical profiles for potential adverse outcomes of the most frequent pDDIs. Abnormal patients' signs/symptoms and laboratory investigations indicating adverse outcomes of interactions were reported.

RESULTS

Of total 431 profiles, pDDIs were reported in 73.1%. Almost half of the profiles were having major-pDDIs (53.8%). Total number of pDDIs were 1318, of which 606 were moderate- and 572 were major-pDDIs. Patient's profiles identified with the most frequent interactions were presented with signs, symptoms, and abnormalities in labs indicating decrease therapeutic response, electrolyte abnormalities, hypoglycemia, bleeding, hepatotoxicity, and hypertension. These adverse events were more prevalent in patients taking higher doses of the interacting drugs as compared to lower doses. Logistic regression analysis revealed significant association for major-pDDIs with 6-10 prescribed medicines (OR = 26.1; p = 0.002), > 10 prescribed medicines (OR = 144; p <  0.001), and tuberculosis (OR = 8.2; p = 0.004).

CONCLUSIONS

PDDIs are highly prevalent in patients with pneumonia. Most frequent and clinically important pDDIs need particular attention. Polypharmacy and tuberculosis increase the risk of pDDIs. Identifying patients more at risk to pDDIs and careful monitoring of pertinent signs/symptoms and laboratory investigations are important measures to reduce pDDIs and their related adverse consequences.

Effect of an educational intervention on the number potential drug-drug interactions

Background

The objective of this study was to evaluate effect of an Educational intervention on the number Potential Drug-Drug Interactions in the Emergency Hospital.

Methods

The prevalence and structure of Major Drug-Drug Interactions at Emergency care Hospitals of Aktobe, Uralsk, Atyrau cities (Kazakhstan) were studied (pharmacoepidemiological, cross-sectional study). Educational interventions were developed and implemented to improve pharmacotherapy in the Cardiology Department of the Aktobe Emergency Hospital, followed by an assessment of their effect.

Results

The effect of educational interventions was revealed, which led to a significant decrease in the indicators of drug interactions of the Major Drug-Drug Interactions by 18.2% (OR: 0.45; 95% CI, 0.25-to-0.82) in the cardiological patients of the Emergency Care Hospital of Aktobe city compared to the Regional Cardiology Center of Uralsk.

Conclusion

The implementation of educational pharmacotherapy programs decreased the number of clinically significant drug interactions in the Cardiology Department of Emergency Hospitals.

Herb-drug interactions: a novel algorithm-assisted information system for pharmacokinetic drug interactions with herbal supplements in cancer treatment

PURPOSE

To develop a system to estimate the risk of herb-drug interactions that includes the available evidence from clinical and laboratory studies, transparently delineates the algorithm for the risk estimation, could be used in practice settings and allows for adaptation and update.

METHODS

We systematically searched Drugbank, Transformer, Drug Information Handbook, European and German Pharmacopoeia and MEDLINE for studies on herb-drug interactions of five common medicinal plants (coneflower, ginseng, milk thistle, mistletoe and St. John's wort). A diverse set of data were independently extracted by two researchers and subsequently analysed by a newly developed algorithm. Results are displayed in the form of interaction risk categories. The development of the algorithm was guided by an expert panel consensus process.

RESULTS

From 882 publications retrieved by the search, 154 studies were eligible and provided 529 data sets on herbal interactions. The developed algorithm prioritises results from clinical trials over case reports over in vitro investigations and considers type of study, consistency of study results and study outcome for clinical trials as well as identification, permeability, bioavailability, and interaction potency of an identified herbal perpetrator for in vitro investigations. Risk categories were assigned to and dynamically visualised in a colour-coded matrix format.

CONCLUSIONS

The novel algorithm allows to transparently generate and dynamically display herb-drug interaction risks based on the available evidence from clinical and laboratory pharmacologic studies. It provides health professionals with readily available and easy updatable information about the risk of pharmacokinetic interactions between herbs and oncologic drugs.

Countrywide prevalence of critical drug interactions in Hungarian outpatients: a retrospective analysis of pharmacy dispensing data

Background

Drug-drug interactions (DDIs) present a significant source of adverse drug reactions. Despite being one of the commonly cited risks to patient safety, prevention of DDIs still poses a challenge to healthcare systems. The prevalence of DDIs can be used as a quality indicator for the safety of prescribing. With the analysis of drug utilization databases, real-world data on critical DDIs can be obtained. The aim of this study was to establish a list of critical DDIs and estimate their prevalence in the Hungarian outpatient population.

Methods

Since there is no conclusive and generally accepted repository of high-risk DDIs, a systematic search of the literature for consensus-based lists was performed. Based on these results and their analysis with 5 interaction compendia, we propose a simple methodology to identify critical combinations. Present study focused on DDIs which are (1) of high clinical importance thus being most likely to cause significant harm if not detected, (2) well-supported by available evidence and (3) affect drugs which are routinely dispensed in the community pharmacy setting. A retrospective analysis of prescriptions filled between 2013 and 2016 was performed. The source of drug utilization data was the IQVIA’s national prescription fill database. The number of interacting drug pairs dispensed at the same time to the same patient was established.

Results

After excluding drugs with low dispensing rates, the analysis covered 39 DDIs. The distribution of risk categories of the analysed DDIs was inconsistent among different drug interaction compendia. The total number of prescriptions filled varied between 173924449 and 176368468 per year. The prevalence of the selected potential DDIs ranged from 0.00 to 355.89 per 100000 prescriptions per year. There was significant variation between how the number of cases had changed for each DDI throughout the study period, no general tendency could have been described.

Conclusions

There were 1.8 million cases of co-dispensing each year, where prescribers’ and community pharmacists’ role in recognizing and managing potentially serious interactions was or would have been critical. The method presented to identify high-risk DDIs can serve as a starting point for the much-needed improvement of routine interaction screening.

Electronic supplementary material

The online version of this article (10.1186/s40360-019-0311-0) contains supplementary material, which is available to authorized users.

Preventing potential drug-drug interactions through alerting decision support systems: A clinical context based methodology

BACKGROUND

The effectiveness of the clinical decision support systems (CDSSs) is hampered by frequent workflow interruptions and alert fatigue because of alerts with little or no clinical relevance. In this paper, we reported a methodology through which we applied knowledge from the clinical context and the international recommendations to develop a potential drug-drug interaction (pDDI) CDSS in the field of kidney transplantation.

METHODS

Prescriptions of five nephrologists were prospectively recorded through non-participatory observations for two months. The Medscape multi-drug interaction checker tool was used to detect pDDIs. Alongside the Stockley's drug interactions reference, our clinicians were consulted with respect to the clinical relevance of detected pDDIs. We performed semi-structured interviews with five nephrologists and one informant nurse. Our clinically relevant pDDIs were checked with the Dutch "G-Standard". A multidisciplinary team decided the design characteristics of pDDI-alerts in a CDSS considering the international recommendations and the inputs from our clinical context. Finally, the performance of the CDSS in detecting DDIs was evaluated iteratively by a multidisciplinary research team.

RESULTS

Medication data of 595 patients with 788 visits were collected and analyzed. Fifty-two types of interactions were most common, comprising 90% of all pDDIs. Among them 33 interactions (comprising 77% of all pDDIs) were rated as clinically relevant and were included in the CDSS's knowledge-base. Of these pDDIs, 73% were recognized as either pseudoduplication of drugs or not a pDDI when checked with the Dutch G-standard. Thirty-three alerts were developed and physicians were allowed to customize the appearance of pDDI-alerts based on a proposed algorithm.

CONCLUSION

Clinical practice contexts should be studied to understand the complexities of clinical work and to learn the type, severity and frequency of pDDIs. In order to make the alerts more effective, clinicians' points of view concerning the clinical relevance of pDDIs are critical. Moreover, flexibility should be built into a pDDI-CDSS to allow clinicians to customize the appearance of pDDI-alerts based on their clinical context.

Impact of interactions between drugs and laboratory test results on diagnostic test interpretation – a systematic review

Intake of drugs may influence the interpretation of laboratory test results. Knowledge and correct interpretation of possible drug-laboratory test interactions (DLTIs) is important for physicians, pharmacists and laboratory specialists. Laboratory results may be affected by analytical or physiological effects of medication. Failure to take into account the possible unintended influence of drug use on a laboratory test result may lead to incorrect diagnosis, incorrect treatment and unnecessary follow-up. The aim of this review is to give an overview of the literature investigating the clinical impact and use of DLTI decision support systems on laboratory test interpretation. Particular interactions were reported in a large number of articles, but they were fragmentarily described and some papers even reported contradictory findings. To provide an overview of information that clinicians and laboratory staff need to interpret test results, DLTI databases have been made by several groups. In a literature search, only four relevant studies have been found on DLTI decision support applications for laboratory test interpretation in clinical practice. These studies show a potential benefit of automated DLTI messages to physicians for the correct interpretation of laboratory test results. Physicians reported 30–100% usefulness of DLTI messages. In one study 74% of physicians sometimes even refrained from further additional examination. The benefit of decision support increases when a refined set of clinical rules is determined in cooperation with health care professionals. The prevalence of DLTIs is high in a broad range of combinations of laboratory tests and drugs and these frequently remain unrecognized.

Potentially Serious Drug Interactions Resulting From the Pretravel Health Encounter

Travelers seen for pretravel health encounters are frequently prescribed new travel-related medications, which may interact with their previously prescribed medications. In a cohort of 76 324 travelers seen at 23 US clinics, we found that 2650 (3.5%) travelers were prescribed travel-related medications with potential for serious drug interactions.

Drug-Drug Interactions in Hepatitis Patients: Do these Interactions Matter in Clinical Perspectives?

INTRODUCTION AND AIM

Hepatitis patients usually present with comorbidities and polypharmacy which increases risk of potential drug-drug interactions (pDDIs). We explored frequency, levels, predictors, and clinical relevance of pDDIs in hospitalized hepatitis patients.

MATERIAL AND METHODS

Retrospective cohort study was used. Clinical profiles of 413 hepatitis patients were reviewed for pDDIs using Micromedex-DrugReax. Frequency, levels and clinical relevance of pDDIs were reported. Logistic regression analysis was used to calculate odds-ratios for predictors.

RESULTS

Of total 413 patients, pDDIs were reported in 55.2%. Major-pDDIs were found in 35% patients. Total 660 pDDIs were identified, of which, 304 (46%) were of major-severity and 299 (45%) of moderateseverity. Patient's profiles of top-10 major-pDDIs were presented with signs/symptoms such as fever, hepatomegaly, anorexia, jaundice, hypertension, tachycardia, bradycardia, & pedal edema; and abnormalities in labs such as electrolytes-level, alanine aminotransferase, blood urea nitrogen, bilirubin-level, & serum creatinine. Significant association was observed for the presence of pDDIs with > 9 prescribed medicines (p < 0.001), hospitalization of > 5 days (p = 0.03), and stroke as comorbidity (p = 0.05). Moreover, odds of exposure to major-pDDIs were significantly higher in patients taking > 9 prescribed medicines (p < 0.001), hospitalization of > 5 days (p = 0.002), and stroke as comorbidity (p = 0.002).

CONCLUSION

We observed hepatitis patients presented with a considerable number of clinically relevant pDDIs. Attention should be given to widespread major-pDDIs and their potential adverse outcomes. Clinically relevant parameters, such as labs and signs/symptoms should be monitored particularly in high risk patients having polypharmacy, prolong hospitalization, and stroke as comorbidity.

Effects of training physicians in electronic prescribing in the outpatient setting on clinical, learning and behavioural outcomes: a cluster randomized trial

AIMS

Electronic prescribing systems may improve medication safety, but only when used appropriately. The effects of task analysis-based training on clinical, learning and behavioural outcomes were evaluated in the outpatient setting, compared with the usual educational approach.

METHODS

This was a multicentre, cluster randomized trial [EDUCATional intervention for IT-mediated MEDication management (MEDUCATE trial)], with physicians as the unit of analysis. It took place in the outpatient clinics of two academic hospitals. Participants comprised specialists and residents (specialty trainees, in the UK) and their patients. Training took the form of a small-group session and an e-learning. The primary outcome was the proportion of medication discrepancies per physician, measured as discrepancies between medications registered by physicians in the electronic prescribing system and those reported by patients. Clinical consequences were estimated by the proportion of patients per physician with at least one missed drug-drug interaction with the potential for causing adverse drug events. A questionnaire assessed physicians' knowledge and skills.

RESULTS

Among 124 participating physicians, primary outcome data for 115 (93%) were available. A total of 1094 patients were included. A mean of 48% of registered medications per physician were discrepant with the medications that their patients reported in both groups (P = 0.14). Due to registration omissions, a mean of 4% of patients per physician had one or more missed drug-drug interactions with the potential to cause a clinically relevant adverse drug event in the intervention group, and 7% in controls (P = 0.11). The percentages of correct answers on the knowledge and skills test were higher in the intervention group (57%) compared with controls (51%; P = 0.01).

CONCLUSION

The training equipped outpatient physicians with the knowledge and skills for appropriate use of electronic prescribing systems, but had no effect on medication discrepancies.

Aspects influencing patients' preferences for the management of drug-drug interactions: A focus group study

OBJECTIVE

The management of drug-drug interactions (DDIs) involves a complex risk-benefit assessment, in which patients' preferences should be taken into account. The aim of this study was to examine the aspects influencing patients' preferences with regard to DDI management options.

METHODS

A qualitative study consisting of five focus groups with patients chronically using cardiovascular drugs was conducted. Key questions concerned preferences regarding DDI management options for a provided fictitious DDI. Thematic analysis of the verbatim transcripts was performed.

RESULTS

Despite their limited knowledge with respect to DDIs, patients easily chose a management option for the presented DDI. When additional information was provided, preferences showed to be fluid. Ten interdependent aspects influencing preferences were derived from patients' argumentations: risk perception, fear, acceptance of uncertainty, openness to change, willingness to take risk, trust in health care professional, financial & practical burdens, health condition, experience, and knowledge & assumptions.

CONCLUSION

Patients' preferences regarding DDI management options were often determined by provided information. Preferences were dependent on an interplay of diverse aspects.

PRACTICE IMPLICATIONS

Tailored provision of information and individualized counseling is needed for active patient involvement in DDI decision making.

Discontinuation and dose adjustment of metoprolol after metoprolol-paroxetine/fluoxetine co-prescription in Dutch elderly

Purpose

Co‐prescription of paroxetine/fluoxetine (a strong CYP2D6 inhibitor) in metoprolol (a CYP2D6 substrate) users is common, but data on the clinical consequences of this drug‐drug interaction are limited and inconclusive. Therefore, we assessed the effect of paroxetine/fluoxetine initiation on the existing treatment with metoprolol on the discontinuation and dose adjustment of metoprolol among elderly.

Methods

We performed a cohort study using the University of Groningen IADB.nl prescription database (www.IADB.nl). We selected all elderly (≥60 years) who had ever been prescribed metoprolol and had a first co‐prescription of paroxetine/fluoxetine, citalopram (weak CYP2D6 inhibitor), or mirtazapine (negative control) from 1994 to 2015. The exposure group was metoprolol and paroxetine/fluoxetine co‐prescription, and the other groups acted as controls. The outcomes were early discontinuation and dose adjustment of metoprolol. Logistic regression was applied to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI).

Results

Combinations of metoprolol‐paroxetine/fluoxetine, metoprolol‐citalopram, and metoprolol‐mirtazapine were started in 528, 673, and 625 patients, respectively. Compared with metoprolol‐citalopram, metoprolol‐paroxetine/fluoxetine was not significantly associated with the early discontinuation and dose adjustment of metoprolol (OR = 1.07, 95% CI:0.77‐1.48; OR = 0.87, 95% CI:0.57‐1.33, respectively). In comparison with metoprolol‐mirtazapine, metoprolol‐paroxetine/fluoxetine was associated with a significant 43% relative increase in early discontinuation of metoprolol (OR = 1.43, 95% CI:1.01‐2.02) but no difference in the risk of dose adjustment. Stratified analysis by gender showed that women have a significantly high risk of metoprolol early discontinuation (OR = 1.62, 95% CI:1.03‐2.53).

Conclusion

Paroxetine/fluoxetine initiation in metoprolol prescriptions, especially for female older patients, is associated with the risk of early discontinuation of metoprolol.

Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support

Objective

To compare 3 commercial knowledge bases (KBs) used for detection and avoidance of potential drug-drug interactions (DDIs) in clinical practice.

Methods

Drugs in the DDI tables from First DataBank (FDB), Micromedex, and Multum were mapped to RxNorm. The KBs were compared at the clinical drug, ingredient, and DDI rule levels. The KBs were evaluated against a reference list of highly significant DDIs from the Office of the National Coordinator for Health Information Technology (ONC). The KBs and the ONC list were applied to a prescription data set to simulate their use in clinical decision support.

Results

The KBs contained 1.6 million (FDB), 4.5 million (Micromedex), and 4.8 million (Multum) clinical drug pairs. Altogether, there were 8.6 million unique pairs, of which 79% were found only in 1 KB and 5% in all 3 KBs. However, there was generally more agreement than disagreement in the severity rankings, especially in the contraindicated category. The KBs covered 99.8-99.9% of the alerts of the ONC list and would have generated 25 (FDB), 145 (Micromedex), and 84 (Multum) alerts per 1000 prescriptions.

Conclusion

The commercial KBs differ considerably in size and quantity of alerts generated. There is less variability in severity ranking of DDIs than suggested by previous studies. All KBs provide very good coverage of the ONC list. More work is needed to standardize the editorial policies and evidence for inclusion of DDIs to reduce variation among knowledge sources and improve relevance. Some DDIs considered contraindicated in all 3 KBs might be possible candidates to add to the ONC list.

The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions: A review

Clinical practice guidelines (CPGs) document evidence-based information and recommendations on treatment and management of conditions. CPGs usually focus on management of a single condition; however, in many cases a patient will be at the centre of multiple health conditions (multimorbidity). Multiple CPGs need to be followed in parallel, each managing a separate condition, which often results in instructions that may interact with each other, such as conflicts in medication. Furthermore, the impetus to deliver customised care based on patient-specific information, results in the need to be able to offer guidelines in an integrated manner, identifying and managing their interactions. In recent years, CPGs have been formatted as computer-interpretable guidelines (CIGs). This enables developing CIG-driven clinical decision support systems (CDSSs), which allow the development of IT applications that contribute to the systematic and reliable management of multiple guidelines. This study focuses on understanding the use of CIG-based CDSSs, in order to manage care complexities of patients with multimorbidity. The literature between 2011 and 2017 is reviewed, which covers: (a) the challenges and barriers in the care of multimorbid patients, (b) the role of CIGs in CDSS augmented delivery of care, and (c) the approaches to alleviating care complexities of multimorbid patients. Generating integrated care plans, detecting and resolving adverse interactions between treatments and medications, dealing with temporal constraints in care steps, supporting patient-caregiver shared decision making and maintaining the continuity of care are some of the approaches that are enabled using a CIG-based CDSS.

Better specification of triggers to reduce the number of drug interaction alerts in primary care

OBJECTIVE

Drug interaction alerts (drug-drug and drug-disease interaction alerts) for chronic medications substantially contribute to alert fatigue in primary care. The aim of this study was to determine which events require (re)assessment of a drug interaction and whether using these events as triggers in clinical decision support systems (CDSSs) would affect the alert rate.

METHODS

Two random 5% data samples from the CDSSs of 123 community pharmacies were used: dataset 1 and 2. The top 10 of most frequent drug interaction alerts not involving laboratory values were selected. To reach consensus on events that should trigger alerts (e.g. first time dispensing, dose modification) for these drug interactions, a two-step consensus process was used. An expert panel of community pharmacists participated in an online survey and a subsequent consensus meeting. A CDSS with alerts based on the consensus was simulated in both datasets.

RESULTS

Dataset 1 and 2 together contained 1,672,169 prescriptions which led to 591,073 alerts. Consensus on events requiring alerts was reached for the ten selected drug interactions. The simulation showed a reduction of the alert rate of 93.0% for the ten selected drug interactions (comparable for dataset 1 and 2), corresponding with a 28.3% decrease of the overall drug interaction alert rate.

CONCLUSION

By consensus-based better specification of the events that trigger drug interaction alerts in primary care, the alert rate for these drug interactions was reduced by over 90%. This promising approach deserves further investigation to assess its consequences and applicability in daily practice.