Clinical and economic burden of adverse drug reactions

The PrescIT platform: An interoperable Clinical Decision Support System for ePrescription to Prevent Adverse Drug Reactions and Drug-Drug Interactions

INTRODUCTION

Preventable medication errors have been proven to cause significant public health burden, and ePrescription is a key part of the process where medication errors and adverse effects could be prevented. Information systems and "intelligent" computational approaches could provide a valuable tool to prevent such errors with profound impact in clinical practice.

OBJECTIVES

The PrescIT platform is a Clinical Decision Support System (CDSS) that aims to facilitate the prevention of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) in the phase of ePrescription in Greece. The proposed platform could be relatively easily localized for use in other contexts too.

METHODS

The PrescIT platform is based on the use of Knowledge Engineering (ΚΕ) approaches, i.e., the use of Ontologies and Knowledge Graphs (KGs) developed upon openly available data sources. Open standards (i.e., RDF, OWL, SPARQL) are used for the development of the platform enabling the integration with already existing IT systems or for standalone use. The main KG is based on the use of DrugBank, MedDRA, SemMedDB and OpenPVSignal. In addition, the Business Process Management Notation (BPMN) has been used to model long-term therapeutic protocols used during the ePrescription process. Finally, the produced software has been pilot tested in three hospitals by 18 clinical professionals via in-person think-aloud sessions.

RESULTS

The PrescIT platform has been successfully integrated in a transparent fashion in a proprietary Hospital Information System (HIS), and it has also been used as a standalone application. Furthermore, it has been successfully integrated with the Greek National ePrescription system. During the pilot phase, one psychiatric therapeutic protocol was used as a testbed to collect end-users' feedback. Summarizing the feedback from the end-users, they have generally acknowledged the usefulness of such a system while also identifying some challenges in terms of usability and the overall user experience.

CONCLUSIONS

The PrescIT platform has been successfully deployed and piloted in real-world environments to evaluate its ability to support safer medication prescriptions.

Exploring the factors influencing the health-related quality of life in patients experiencing adverse drug reactions: a cross-sectional study

BACKGROUND

This study aimed to assess the factors influencing health-related quality of life (HRQoL) in patients experiencing adverse drug reactions (ADRs) at a tertiary care public sector hospital. A cross-sectional study was conducted over a period of 18 months, and included both male and female patients aged 18 years and above. Patients who visited the outpatient and inpatient departments with complaints associated with ADRs were included in this study. HRQoL data were collected using the EuroQol-5 Dimension-5 Level (EQ-5D-5L) questionnaire to assess five dimensions of health on a five-level scale. Descriptive statistics, t-tests, and analysis of variance were used to analyze the data. Multivariate regression analysis was performed to identify the potential determinants of HRQoL.

RESULTS

A total of 316 patients were included in the study among these participants, of which 54% were female, and 65% were from rural areas. The majority (68%) of the patients had moderately severe ADRs, and 63% of the participants had an income < 2.5 lakh Indian rupees (3009 USD). The mean EQ-5D-5L and EuroQoL Visual Analog Scale (EQ VAS) scores of the study participants were 0.714 and 69.73, respectively. The variables ADR severity, income, and age showed a significant difference (p < 0.05) in HRQoL.

CONCLUSION

This study provides insights into HRQoL among patients with ADRs and identifies the determinants of HRQoL. The findings of this study will contribute to improving patient-centered care and optimizing patient outcomes.

Potential of pharmacogenetics in minimizing drug therapy problems in cystic fibrosis

BACKGROUND

With advancements in CF drug development, people with cystic fibrosis (PwCF) now take a median of seven medications daily, increasing treatment complexity, risk of drug therapy problems (DTPs), and interference with treatment goals. Given that some of these DTPs can be prevented with preemptive pharmacogenetic testing, the overall goal of this study was to test the clinical utility of a multi-gene pharmacogenetics (PGx) panel in potentially reducing DTPs in PwCF.

METHODS

A population based retrospective study of patients with CF was conducted at the University of Utah Health Care System. The patients were genotyped for CYP450 enzymes using a pharmacogenomic assay, and their drug utilization information was obtained retrospectively. This pharmacogenomic information was combined with clinical guidelines to predict the number of actionable PGx interventions in this patient cohort.

RESULTS

A total of 52 patients were included in this study. In the patient sample, a minimum of one order of actionable PGx medication was observed in 75 % of the cases. Results revealed that 4.2 treatment modifications per 10 patients can be enabled with the help of a PGx intervention in this patient population. Additionally, our findings suggest that polymorphisms in CYP2D6 and CYP2C19 are most likely to be the primary contributors to DTP's within PwCF.

CONCLUSION

This study provides evidence that the PGx panel has the potential to help alleviate the clinical burden of DTPs in PwCF and can assist in informing pharmacotherapy recommendations. Future research should validate these findings and evaluate which subgroups of PwCF would most benefit from pharmacogenetic testing.

Trends in Drug Duplications in Swedish Older Adults: A Nationwide Register Study from 2006 to 2021

BACKGROUND

Drug duplication (DD), the use of two identical drugs simultaneously, is a medication error increasing the risk of adverse drug events. We describe the trends and implicated drugs in potential DD in older adults in Sweden from 2006 to 2021.

METHODS

We conducted a register-based, repeated cross-sectional study of all older adults (aged ≥65 years) dispensed drugs at a community pharmacy in 2006-2021. DD was defined as a ≥30-day overlap of two dispensations of drugs with the same 5th level (chemical substance) Anatomical Therapeutic Chemical (ATC) classification, but with different brand names, within a 3-month period each year.

RESULTS

Among Swedish older adults with ordinary prescriptions (i.e. multidose excluded; n ≈ 1,200,000-1,600,000 per year), the prevalence of potential DD increased from 5.2% to 10.6% in 65- to 79-year-olds and from 7.0% to 11.7% in those aged ≥80 years. The drug groups (ATC level 3; pharmacological subgroup) most frequently implicated in DD in 2006 were β-blocking agents, angiotensin-converting enzyme (ACE) inhibitors, and calcium channel blockers, and in 2021 Vitamin B12 and folic acid, β-blocking agents and angiotensin II receptor blockers.

CONCLUSIONS

DD represents a common but unnecessary and potentially hazardous medication error. Our results indicate that during the last two decades, the prevalence has almost doubled in older adults with ordinary prescriptions, reaching 11% in 2021. More national efforts are needed to revert this trend, including a nationally available complete drug list for all patients, and prescriber support to detect DD.

Healthcare provider and patient perspectives on the implementation of pharmacogenetic-guided treatment in routine clinical practice

OBJECTIVE

This study aims to understand patient and healthcare provider perspectives on the integration and application of pharmacogenetics (PGx) testing in routine clinical practice.

METHODS

Two anonymous online surveys were distributed globally for healthcare providers and patients respectively on the Qualtrics platform (version 3.24). The surveys were distributed through social platforms, email, and posters with QR codes from 27 October 2023 to 7 March 2024. The surveys evaluated participant familiarity with PGx, previous experience with PGx testing, perceived implementation challenges, and opinions on point-of-care (PoC) PGx testing devices.

RESULTS

This study collected 78 responses from healthcare providers and 98 responses from patients. The results revealed that 64% of healthcare providers had some level of familiarity with PGx, however, PGx testing in clinical practice was low. The primary challenges identified by healthcare providers included limited access to testing and lack of knowledge on PGx test interpretation. In contrast, 52% of patient respondents were aware of PGx testing, with a significant association between awareness and positive opinions toward PGx. Both healthcare providers and patients recognized the value of PoC PGx testing devices, with 98% of healthcare providers and 71% of patients believing PoC devices would improve the accessibility and implementation of PGx testing. Comparative analysis revealed a statistically significant difference in PGx awareness between healthcare providers and patients, with providers being more informed.

CONCLUSION

Improved PGx awareness, training, clinical guidelines, and PoC PGx testing devices may help promote the implementation of PGx-guided treatments in routine clinical practice.

Dispensed prescription medications and short-term risk of pulmonary embolism in Norway and Sweden

Scandinavian electronic health-care registers provide a unique setting to investigate potential unidentified side effects of drugs. We analysed the association between prescription drugs dispensed in Norway and Sweden and the short-term risk of developing pulmonary embolism. A total of 12,104 pulmonary embolism cases were identified from patient- and cause-of-death registries in Norway (2004-2014) and 36,088 in Sweden (2005-2014). A case-crossover design was used to compare individual drugs dispensed 1-30 days before the date of pulmonary embolism diagnosis with dispensation in a 61-90 day time-window, while controlling for the receipt of other drugs. A BOLASSO approach was used to select drugs that were associated with short-term risk of pulmonary embolism. Thirty-eight drugs were associated with pulmonary embolism in the combined analysis of the Norwegian and Swedish data. Drugs associated with increased risk of pulmonary embolism included certain proton-pump inhibitors, antibiotics, antithrombotics, vasodilators, furosemide, anti-varicose medications, corticosteroids, immunostimulants (pegfilgrastim), opioids, analgesics, anxiolytics, antidepressants, antiprotozoals, and drugs for cough and colds. Mineral supplements, hydrochlorothiazide and potassium-sparing agents, beta-blockers, angiotensin 2 receptor blockers, statins, and methotrexate were associated with lower risk. Most associations persisted, and several additional drugs were associated, with pulmonary embolism when using a longer time window of 90 days instead of 30 days. These results provide exploratory, pharmacopeia-wide evidence of medications that may increase or decrease the risk of pulmonary embolism. Some of these findings were expected based on the drugs' indications, while others are novel and require further study as potentially modifiable precipitants of pulmonary embolism.

Awareness, knowledge, attitude, and practice of adverse drug reaction reporting among health workers in primary health centres participating in seasonal malaria chemoprevention campaign in Nigeria in 2022: a cross-sectional survey

BACKGROUND

Evaluating health workers' knowledge and practice of adverse drug reaction (ADR) reporting is an important step in identifying gaps in quality ADR reporting during public health interventions like the seasonal malaria chemoprevention (SMC) campaign. Pharmacovigilance (PV) monitoring is vital in SMC due to the number of children exposed to malaria medicines for a period of 4 or 5 months during the campaign. In Nigeria more than 10 million children are exposed to SMC medicines every year. The scale of this intervention emphasised the need for efficient and effective safety monitoring during the campaign. Thus, the objective of this study was to evaluate healthcare workers' (HCW) awareness, knowledge, attitude and practice (KAP) of ADR reporting in health facilities participating in SMC campaign to identify pharmacovigilance gaps which may suggest possible ways to ensure safety during the campaign.

METHODS

World Health Organization's service availability and readiness assessment (SARA) recommendations were used to sample 2,598 out of 5,195 used as supervising health facilities (HFs) during the 2022 SMC campaign across nine states of the country. Out of the sampled HFs, 2,144 eligible and consented health facility workers (HFWs) were assessed for awareness, and KAP of ADR using the validated 45-item self-administered questionnaire. The data was analysed using descriptive statistics and correlation analysis at p < 0.05.

RESULTS

The majority of the respondents are males (n = 1,333, 62.2%). The HFWs showed good awareness (n = 2,037, 95.0%) of pharmacovigilance (PV). However, only 809 (37.7%) of them had good knowledge scores. The mean ADR reporting attitude score (85.0 ± 15.3%) was good with many of the respondents (n = 1,548, 72.2%) having a good score. However, the respondents' ADR practice was suboptimal, only 1,356 (63.2%) of them had encounters with ADR, and a lot of negative perceived barriers to ADR reporting were identified in the study. For example, 493 (23%) believed that ADRs were not reported because they were not serious and life-threatening while 248 (11.6%) reported a fear of liability. Correlation analysis revealed female gender (r = 0.163, p < 0.001), older age (r = 0.207, p < 0.001) and years of practice (r = 0.050, p = 0.021) as factors significantly associated with ADR knowledge and attitude scores.

CONCLUSION

The study indicated that HCWs across health facilities participating in SMC campaigns have ADR reporting knowledge and practice gaps. The study suggest training alone may not be effective in addressing gaps in ADR reporting. In addition to PV training, implementers can include continuous mentoring of health care workers or other similar interventions as part of strategy to improve ADR reporting. Also, context specific strategies to improve ADR reporting among health care worker needs to be implemented to address under-reporting of ADRs during SMC campaigns and other malaria public health interventions.

Impact of a Pharmacist-Led Telemedicine Visit in a Geriatric Primary Care Clinic

Purpose: Unintentional medication discrepancies (UMD) are common amongst geriatric patients. If not addressed, these UMD can lead to suboptimal care and increased health care spending. Ambulatory care pharmacists are trained to identify and resolve UMD, and help tailor medication regimens to assure optimized and safe patient-centered care. The purpose of this retrospective study was to highlight the role of a remote, ambulatory care pharmacist in a geriatric primary care setting. Methods: This was a multicenter, single cohort, retrospective chart review of patients enrolled in a geriatric primary care initiative. Patients met with an ambulatory care pharmacist for a 60-minute telemedicine appointment. The primary endpoint was the percent of patients seen by the ambulatory care pharmacist with at least 1 medication discrepancy identified. Results: A total of 275 visits were scheduled with the ambulatory care pharmacist during the 6-month study period. At least 1 unintentional medication discrepancy (UMD) was identified in 151 patients (66%). At least 1 edit was made to the patient's medication list in 224 patients (97%). The ambulatory care pharmacist made recommendations to the provider in 210 patients (91%). The CPA was utilized in 75 patients (33%). Conclusion: This study highlights the utility of a remote, ambulatory care pharmacist in a geriatric primary care setting. Two-thirds of patients were noted to have at least 1 UMD, and more than 90% of patients were identified as having suboptimal regimens. This initiative shows the impact of a remote, ambulatory care pharmacist on patient care.

Improvement in Adverse Drug Reaction (ADR) Knowledge: A Pre- and Post-video Intervention Study Among Doctors

Background Adverse drug reactions (ADRs) represent a significant public health concern, contributing to mortality, morbidity, and healthcare costs worldwide. Healthcare practitioners especially doctors play a vital role in identifying and reporting ADR. This study investigates the prevalence of knowledge regarding ADR among doctors and enhances it with educational intervention. It also explores the association between demographic factors and baseline ADR awareness. Methods A prospective cross-sectional interventional study was conducted among doctors in Ahmedabad, India, to evaluate their knowledge of ADR reporting and the effectiveness of an educational video intervention. Pre- and post-intervention questionnaires were administered to assess knowledge improvement. Statistical analysis, including paired t-tests and chi-square tests, was performed to evaluate the intervention's impact and explore associations between demographic factors and ADR awareness. Results Analysis of pre- and post-intervention questionnaires revealed a significant increase in correct response rates post-intervention, indicating the effectiveness of the educational video intervention. Demographic factors, particularly age, were associated with ADR awareness. Following the intervention, participants demonstrated an improved understanding of ADR definitions, WHO causality assessment, reporting mechanisms, and challenges faced by pharmacovigilance programs. All participants found the video helpful and expressed intent to share their knowledge post-intervention. Conclusion The results of the study suggest that educational video intervention can serve as an effective tool for understanding ADR concepts and pharmacovigilance practices. Moreover, the association of demographic factors, particularly age, with ADR awareness further emphasizes the importance of educational interventions in addressing specific population needs.

Adverse Drug Reactions Related with Antibiotic Medicines in Malawi: A Retrospective Analysis of Prevalence and Associated Factors

Objective

We aimed to assess the occurrence and characteristics of antibiotic-associated adverse drug reactions (ADRs) in Malawi.

Methods

We retrospectively reviewed 304 patient records from medical wards in three hospitals in Southern Malawi. A global trigger tool was applied for the detection of suspected ADRs, and we used the Naranjo scale, the World Health Organization classification and the Schumock and Thornton scale for causality, seriousness and preventability assessment respectively. ADRs were also further characterized according to anatomical systems. Statistical analysis was done in STATA 14.1. The Chi-square test was used to determine the association between categorical variables and logistic regression analysis was used to measure the strength of the association between various independent variables and the occurrence of ADRs.

Results

Suspected ADRs were detected in 24% (73/304) of patients, of which 1.4% were definite, 15.1% were probable and 83.6% were possible ADRs. Most of the sADRs were gastrointestinal events (42.5%), followed by: musculoskeletal (26.3%); cardiovascular (16.3%); central nervous system (13.8%; and urinary events (1.3%). About 27% of the sADRs were serious events such as convulsions. The geriatric age group (≥65 years) was more likely to experience sADRs as compared to the younger age group, with an adjusted odds ratio (aOR) of 4.53, 95% CI (2.21-9.28), P<0.001. Patients taking more than one antibiotic medicine had a higher risk of developing sADRs as compared to patients who were administered one type of antibiotic medicine, aOR 2.14, 95% CI (1.18-3.90), p < 0.012. A long hospital stay of >3days was associated with a higher risk of sADRs with aOR of 5.11, 95% CI (2.47-10.55), p < 0.001 than those who stayed ≤ 3 days in the hospital.

Conclusion

We found a higher prevalence of serious sADRs associated with antibiotic medicines than reported elsewhere. This may, among others, contribute to high patient mortality, poor treatment adherence, antibiotic resistance and increased cost of care.

Survey of Potential Drug Interactions, Use of Non-Medical Health Products, and Immunization Status among Patients Receiving Targeted Therapies

In recent years, several changes have occurred in the management of chronic immunological conditions with the emerging use of targeted therapies. This two-phase cross-sectional study was conducted through structured in-person interviews in 2018-2019 and 2022. Additional data sources included ambulatory medical records and the itemized reimbursement reporting interface of the National Health Insurance Fund. Drug interactions were analyzed using the UpToDate Lexicomp, Medscape drug interaction checker, and Drugs.com databases. The chi-square test was used, and odds ratios (ORs) were calculated. In total, 185 patients participated. In 53% of patients (n = 53), a serious drug-drug interaction (DDI) was identified (mean number: 1.07 ± 1.43, 0-7), whereas this value was 38% (n = 38) for potential drug-supplement interactions (mean number: 0.58 ± 0.85, 0-3) and 47% (n = 47) for potential targeted drug interactions (0.72 ± 0.97, 0-5) in 2018. In 2022, 78% of patients (n = 66) were identified as having a serious DDI (mean number: 2.27 ± 2.69, 0-19), 66% (n = 56) had a potential drug-supplement interaction (mean number: 2.33 ± 2.69, 0-13), and 79% (n = 67) had a potential targeted drug interactions (1.35 ± 1.04, 0-5). Older age (>60 years; OR: 2.062), female sex (OR: 3.387), and polypharmacy (OR: 5.276) were identified as the main risk factors. Screening methods and drug interaction databases do not keep pace with the emergence of new therapeutics.

Sex as a Biological Variable in Early-Phase Oncology Clinical Trials: Enhancing the Path to Personalised Medicine

Sex is an essential biological variable that influences the development, progression and response to treatment in cancer. Despite this, early-phase cancer clinical trials frequently neglect to consider sex as a variable, creating a barrier to the development of personalised medicine. This article argues that failure to identify and infer sex differences in early-phase clinical trials may result in suboptimal dosing, underestimation of toxicity, and the failure to identify potential sex-specific responses to new systemic anticancer therapies. There should be a greater focus on sex as a biological variable in drug development so that thoughtful and deliberate study design can bring precision to the development of new systemic cancer therapies.

Antiseizure adverse drug reaction and associated factors among epileptic patients at Jimma Medical Center: a prospective observational study

A growing body of evidence suggests that adverse drug reactions (ADRs) are a major cause of morbidity and mortality in the healthcare system. Fifteen to twenty-five percent of patients with epilepsy discontinued antiseizure drugs (ASDs) within 6 months of therapy owing to intolerable adverse drug reactions. In Ethiopia, the prevalence of antiseizure adverse drug reactions and associated factors was not extensively conducted in advanced settings like Jimma Medical Centers. Hence, the objective of this study is to assess patterns of adverse drug reactions and associated factors among ambulatory epileptic patients at tertiary hospitals in Ethiopia. A hospital-based prospective observational study was spanned for 1 year. Two hundred ninety patients were consecutively recruited into the study from all epileptic patients attending the ambulatory clinic. Relevant data were collected through patient interviews and medical chart reviews. The causality assessment was done by using the Naranjo Probability Scale. Epi-Data manager version 4.6.0.4 was used for data entry and statistical analysis was performed by Statistical Package for Social Science version 25.0 (SPSS). Stepwise backward logistic regression analysis was done to identify factors that increase the risk of antiseizure adverse drug reactions. The mean (± SD) age of the participants were 29.91(± 11.26) years. The overall prevalence of ADR was 33.8% (95% CI 29.2-39.9%). A total of 110 adverse drug reactions were identified among 98 patients with an average of 1.12 per patient. ADRs were frequently reported with phenobarbital (52.04%) and phenytoin (34.70%). The commonly identified adverse drug reactions were epigastric pain (27.55%) and central nervous system drowsiness (23.46%). Comorbidity (AOR = 5.91, 95% CI (2.14-16.32), seizure-free period of fewer than 2 years (AOR = 1.94, 95% CI (1.18-3.19), and polytherapy (AOR = 1.35, 95% CI (1.80-2.26) were significantly associated with adverse drug reactions. This trial had a comparatively high percentage of adverse medication reactions. Adverse medication reactions were more common in patients with polytherapy, comorbidities, and seizure-free durations less than two years. Therefore, medical practitioners should advise patients who exhibit these traits on how to reduce or avoid bad drug responses or provide comfort in the event of small incidents.

Precision Medicine-Are We There Yet? A Narrative Review of Precision Medicine's Applicability in Primary Care

Precision medicine (PM), also termed stratified, individualised, targeted, or personalised medicine, embraces a rapidly expanding area of research, knowledge, and practice. It brings together two emerging health technologies to deliver better individualised care: the many "-omics" arising from increased capacity to understand the human genome and "big data" and data analytics, including artificial intelligence (AI). PM has the potential to transform an individual's health, moving from population-based disease prevention to more personalised management. There is however a tension between the two, with a real risk that this will exacerbate health inequalities and divert funds and attention from basic healthcare requirements leading to worse health outcomes for many. All areas of medicine should consider how this will affect their practice, with PM now strongly encouraged and supported by government initiatives and research funding. In this review, we discuss examples of PM in current practice and its emerging applications in primary care, such as clinical prediction tools that incorporate genomic markers and pharmacogenomic testing. We look towards potential future applications and consider some key questions for PM, including evidence of its real-world impact, its affordability, the risk of exacerbating health inequalities, and the computational and storage challenges of applying PM technologies at scale.

Nivolumab Safety in Renal Cell Carcinoma: A Case Report

Nivolumab is used to treat several different types of cancers. Although it is generally considered to be effective and well-tolerated, it has been associated with adverse effects requiring discontinuation of treatment, like many other drugs used for cancer. A 70-year-old male was switched from sunitinib to nivolumab for renal cell carcinoma. The patient developed persistent hypothyroidism, onycholysis, and pneumonitis at nivolumab cycle 6, 10, and 11, respectively. Using the Naranjo causality method, the likelihood of causality was deemed "probable" for pneumonitis and hypothyroidism and "possible" for onycholysis. Nivolumab was eventually discontinued due to disease progression, rather than safety concerns. Eudravigilance, the European pharmacovigilance database, was searched for all nivolumab-related individual case safety reports from Malta, up to September 4, 2023. Six reports were identified in Malta, although the 3 events identified in this case report were not reported, suggesting under-reporting in Malta. This case report identified an uncommon nivolumab adverse drug reaction (ADR), onycholysis and showed how, despite the occurrence of 3 ADRs, it was its lack of efficacy rather than its safety which led to its discontinuation in this particular patient.

Just how transformative will AI/ML be for immuno-oncology?

Immuno-oncology involves the study of approaches which harness the patient's immune system to fight malignancies. Immuno-oncology, as with every other biomedical and clinical research field as well as clinical operations, is in the midst of technological revolutions, which vastly increase the amount of available data. Recent advances in artificial intelligence and machine learning (AI/ML) have received much attention in terms of their potential to harness available data to improve insights and outcomes in many areas including immuno-oncology. In this review, we discuss important aspects to consider when evaluating the potential impact of AI/ML applications in the clinic. We highlight four clinical/biomedical challenges relevant to immuno-oncology and how they may be able to be addressed by the latest advancements in AI/ML. These challenges include (1) efficiency in clinical workflows, (2) curation of high-quality image data, (3) finding, extracting and synthesizing text knowledge as well as addressing, and (4) small cohort size in immunotherapeutic evaluation cohorts. Finally, we outline how advancements in reinforcement and federated learning, as well as the development of best practices for ethical and unbiased data generation, are likely to drive future innovations.

Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip

Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

Genetic diversity of variants involved in drug response among Tunisian and Italian populations toward personalized medicine

Adverse drug reactions (ADR) represent a significant contributor to morbidity and mortality, imposing a substantial financial burden. Genetic ancestry plays a crucial role in drug response. The aim of this study is to characterize the genetic variability of selected pharmacogenes involved with ADR in Tunisians and Italians, with a comparative analysis against global populations. A cohort of 135 healthy Tunisians and 737 Italians were genotyped using a SNP array. Variants located in 25 Very Important Pharmacogenes implicated in ADR were extracted from the genotyping data. Distribution analysis of common variants in Tunisian and Italian populations in comparison to 24 publicly available worldwide populations was performed using PLINK and R software. Results from Principle Component and ADMIXTURE analyses showed a high genetic similarity among Mediterranean populations, distinguishing them from Sub-Saharan African and Asian populations. The Fst comparative analysis identified 27 variants exhibiting significant differentiation between the studied populations. Among these variants, four SNPs rs622342, rs3846662, rs7294, rs5215 located in SLC22A1, HMGCR, VKORC1 and KCNJ11 genes respectively, are reported to be associated with ethnic variability in drug responses. In conclusion, correlating the frequencies of genotype risk variants with their associated ADRs would enhance drug outcomes and the implementation of personalized medicine in the studied populations.

Drug therapy problems and contributing factors among patients with epilepsy

BACKGROUND

Although antiseizure medications play a crucial role in the management of epilepsy, their benefit can be compromised due to drug-related problems. Drug therapy problems can lead to poor seizure control, reduced quality of life, and increased morbidity and mortality in patients with epilepsy. However, in our setting, there is limited knowledge about drug therapy problems and the factors that contribute to them.

OBJECTIVE

The aim of this study was to investigate the prevalence and contributing factors of drug-therapy problems among patients with epilepsy.

METHODOLOGY

A hospital-based prospective observational study was conducted at the neurologic clinic of Ayder Comprehensive Specialized Hospital, located in the Tigray region of Northern Ethiopia. The study included adult patients diagnosed with epilepsy who had been taking at least one antiseizure medication for a minimum of six months. Data were collected by conducting patient interviews and expert reviews of medical and medication records. Prior to data review and interviews, each patient provided written informed consent. Drug therapy problems were identified and classified using Cipolle's method, followed by a consensus review conducted with a panel of experts. Statistical analysis was performed using a statistical software package; SPSS version 22. Binary logistic regression analysis was conducted to determine the contributing factors of drug therapy problems. Statistical significance was determined at p<0.05.

RESULTS

A study conducted on 250 participants revealed that 55.2% of the patients experienced one or more drug therapy problems. Our analysis identified a total of 282 drug therapy problems, with a mean of 2±0.52 drug therapy problems per patient. The most commonly observed drug therapy problems were dosage too low (30.0%), noncompliance (22%), adverse drug reaction (18%), and unnecessary drug therapy (16.4%). The commonly involved antiseizure medications in these drug therapy problems were phenytoin (22.8%), Valproic acid (20.8%), and Phenobarbital (18.4%). Furthermore, our findings revealed that combination therapy (AOR: 3.92, 95%CI: 1.19-12.97) and uncontrolled seizure (AOR: 108.37, 95%CI: 38.7-303.6) exhibited significant associations with drug therapy problems.

CONCLUSION

Drug therapy problems were prevalent among patients with epilepsy. The use of combination therapy and the presence of uncontrolled seizures were identified as significant indicators of drug therapy problems. Therefore, more emphasis should be given to patients with multiple medications and uncontrolled seizures.

The Application of Knowledge-Based Clinical Decision Support Systems to Detect Antibiotic Allergy

Prevention of drug allergies is important for patient safety. The objective of this study was to evaluate the outcomes of antibiotic allergy-checking clinical decision support system (CDSS), K-CDSTM. A retrospective chart review study was performed in 29 hospitals and antibiotic allergy alerts data were collected from May to August 2022. A total of 15,535 allergy alert cases from 1586 patients were reviewed. The most frequently prescribed antibiotics were cephalosporins (48.5%), and there were more alerts of potential cross-reactivity between beta-lactam antibiotics than between antibiotics with the same ingredients or of the same class. Regarding allergy symptoms, dermatological disorders were the most common (38.8%), followed by gastrointestinal disorders (28.4%). The 714 cases (4.5%) of immune system disorders included 222 cases of anaphylaxis and 61 cases of severe cutaneous adverse reactions. Alerts for severe symptoms were reported in 6.4% of all cases. This study confirmed that K-CDS can effectively detect antibiotic allergies and prevent the prescription of potentially allergy-causing antibiotics among patients with a history of antibiotic allergies. If K-CDS is expanded to medical institutions nationwide in the future, it can prevent an increase in allergy recurrence related to drug prescriptions through cloud-based allergy detection CDSSs.

Promoting Collaboration of Regulators and Patients in Improving Drug Safety and Regulatory Decision Making

Pharmacovigilance involves a continuous process of evaluating, monitoring and communicating the safety profile of a medicine throughout its life cycle. This process involves a range of stakeholders, including national regulatory authorities, industry, health organisations, healthcare providers and patients. Although patients are the end users of medicines and experts in their medical conditions, patient involvement is still nascent in the Asia-Pacific region. While there are positive examples and encouraging trends, several key challenges currently hinder systemic patient involvement in drug safety and regulatory decision making. Systemic issues such as a lack of formalised frameworks or platforms, underdeveloped communication and information exchange channels, and paternalistic health systems constrain greater patient involvement and collaborative regulator-patient activities. Addressing these challenges will greatly advance collaboration among regulators, patients, and patient advocates to enhance drug safety and regulatory decision making.

Retrospective Analysis of Patient-Reported Adverse Drug Reactions in an Italian Allergy Unit: ALLERG-RAF Study

INTRODUCTION

The Italian Medicines Agency indicates that about 5% of hospital admissions are due to adverse drug reactions (ADRs). Several factors are recognized to be associated with an increased risk for ADRs, such as the female gender and polytherapy. The aim of this study was to retrospectively analyze the suspected ADRs reported by patients during the anamnestic interview at the Allergy Unit.

PATIENTS AND METHODS

ALLERG-RAF study is a retrospective analysis of the medical records of patients evaluated in the Allergy Unit of ASST Spedali Civili and the University of Brescia from 2000 to 2016. The inclusion criteria were age ≥18 years and medical consultation requested for suspected ADRs. Data relating to the patient's intrinsic characteristics, the drug supposed to be the cause, and the prescribed pharmacological therapy were collected. Pseudonymized data from each patient were collected in an informatics database.

RESULTS

From 2000 to 2016, 35,817 accesses to the Allergy Unit were made, and 2,171 unique events related to a suspected ADR were collected in 1,840 patients. More than two-thirds of the reports concerned females (70.4%). Antibiotics were involved in the majority of the self-reported suspected ADRs (48.7%), particularly beta-lactams (61.1%). Anti-inflammatory drugs, mainly NSAIDs, were second in incidence and suspected in 25.2% of reports. As a site of ADR manifestation, most of the reported reactions involve the skin. No clinical sequelae were reported.

CONCLUSIONS

Our results underline the importance of patient reporting in pharmacovigilance. Furthermore, gender gap data emphasizes the importance of the gender-specific medicine approach.

A prospective intervention study to identify drug-related emergency department visits comparing a standard care group and a pharmaceutical care group

BACKGROUND AND IMPORTANCE

Adverse drug reactions impose a major burden. Those adverse drug reactions might lead to hospitalization but are often not correctly identified in the emergency department (ED). Clinical pharmacists, although not routinely implemented, can help identify adverse drug reactions.

OBJECTIVE

The primary objective was to examine the drug association of ED visits in a pharmaceutical group with a clinical pharmacist integrated in the ED team compared with a standard group without additional support.

DESIGN/SETTING/PARTICIPANTS

This prospective intervention study was performed in the ED of a tertiary care university hospital in Leipzig, Germany. Patients who were ≥50 years old were included. From 1 March 2020 to May 31, 2020 patients were enrolled in the standard group. From 1 March 2021 to 31 May 2021, the pharmaceutical group was enrolled. The clinical pharmacist supported the ED team with patient´s detailed medication history and medication analysis. In both groups, patients were evaluated whether their ED visit was drug-related.

OUTCOME MEASURES AND ANALYSIS

The number of identified drug-related ED presentations were compared between the two groups. Interventions performed on adverse drug reaction management, causative drugs and patient characteristics were evaluated.

MAIN RESULTS

A total of 798 patients were enrolled in the standard group and 827 patients in the pharmaceutical group. Patients whose ED visit was drug-related had a median age of 77 years [(Q25-Q75) 63.5-83.5] and took 7 [(Q25-Q75) 5-8] drugs in standard group. In the pharmaceutical group median age was 78 years [(Q25-Q75) 66-83] and number of drugs taken was 9 [(Q25-Q75) 5.25-11]. 31 (3.9%) drug-related ED visits were identified in the standard group compared to 104 (12.6%) in the pharmaceutical group (OR 3.56; 95% CI 2.35-5.38). An intervention on the patient's pharmacotherapy was performed in 16 drug-related ED visits in standard group compared to 77 in the pharmaceutical group.

CONCLUSION

In this study the implementation of a clinical pharmacist was associated with improved identification of drug-related ED visits. Discontinuations of causal medications and dose reductions were significantly higher in the pharmaceutical group compared to the standard care group.

Establishing a trigger tool based on global trigger tools to identify adverse drug events in obstetric inpatients in China

BACKGROUND

Pregnant women belong to the special population of drug therapy, and their physiological state, pharmacokinetics and pharmacodynamics are significantly different from the general population. Drug safety during pregnancy involves two generations, which is a hot issue widely concerned in the whole society. Global Trigger Tool (GTT) of the Institute for Healthcare Improvement (IHI) has been wildly used as a patient safety measurement strategy by several institutions and national programs, and the effectiveness had been demonstrated. But only one study reports the use of GTT in obstetric delivery until now. The aim of the study is to establish triggers detecting adverse drug events (ADEs) suitable for obstetric inpatients on the basis of the GTT, to examine the performance of the obstetric triggers in detecting ADEs experienced by obstetric units compared with the spontaneous reporting system and GTT, and to assess the utility and value of the obstetric trigger tool in identifying ADEs of obstetric inpatients.

METHODS

Based on a literature review searched in PubMed and CNKI from January of 1997 to October of 2023, retrospective local obstetric ADEs investigations, relevant obstetric guidelines and the common adverse reactions of obstetric therapeutic drugs were involved to establish the initial obstetric triggers. According to the Delphi method, two rounds of expert questionnaire survey were conducted among 16 obstetric and neonatological physicians and pharmacists until an agreement was reached. A retrospective study was conducted to identity ADEs in 300 obstetric inpatient records at the Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital from June 1 to September 30, 2018. Two trained junior pharmacists analyzed the first eligible records independently, and the included records reviewed by trained pharmacist and physician to identify ADEs. Sensitivity and specificity of the established obstetric triggers were assessed by the number of ADEs/100 patients and positive predictive value with the spontaneous reporting system (SRS) and GTT. Excel 2010 and SPSS22 were used for data analysis.

RESULTS

Through two rounds of expert investigation, 39 preliminary triggers were established that comprised four modules (12 laboratory tests, 9 medications, 14 symptoms, and 4 outcomes). A total of 300 medical records were reviewed through the obstetric triggers, of which 48 cases of ADEs were detected, with an incidence of ADEs of 16%. Among the 39 obstetric triggers, 22 (56.41%) were positive and 11 of them detected ADEs. The positive predictive value (PPV) was 36.36%, and the number of ADEs/100 patients was 16.33 (95% CI, 4.19-17.81). The ADE detection rate, positive trigger rate, and PPV for the obstetric triggers were significantly augmented, confirming that the obstetric triggers were more specific and sensitive than SRS and GTT.

CONCLUSION

The obstetric triggers were proven to be sensitive and specific in the active monitoring of ADE for obstetric inpatients, which might serve as a reference for ADE detection of obstetric inpatients at medical institutions.

Why Pharmacovigilance of Non-steroidal Anti-inflammatory Drugs is Important in India?

BACKGROUND

Non-steroidal Anti-Inflammatory Drugs (NSAIDs) are among the drugs that are most regularly administered to manage inflammation and pain. Over-the-Counter (OTC) NSAIDs are widely accessible, particularly in developing countries like India. This casual approach to using NSAIDs may operate as a magnet for NSAID-related adverse drug reactions (ADRs) among patients.

OBJECTIVES

As patients in India are less informed about the appropriate use of NSAIDs and consumption patttern, adverse drug reactions, and the importance of reporting ADRs, the current study's objective is to promote patient safety by using pharmacovigilance as a tool to educate patients.

METHODS

A targeted literature methodology was utilized to gather the data pertaining to NSAIDs, their ADRs and their pharmacovigilance. Different scientific databases, such as Science Direct, PubMed, Wiley Online Library, Springer, and Google Scholar, along with authentic textbooks, were explored as reference literature.

RESULTS

In general, NSAIDs consumption pattern depends upon the different age groups. Around 1.6 billion tablets of NSAIDs are consumed in India for ailments, such as headaches, arthritis, menstrual cramps, osteoarthritis, back pain, rheumatoid arthritis, gout, osteoporosis, tendinitis, cancer pain and chronic pain. Common ADRs of NSAIDs include nausea, vomiting, headache, gastritis, abdominal pain, and diarrhoea. Also, they can cause renal damage and cardiovascular problems if not consumed in a dose-dependent manner. However, Diclofenac and Ibuprofen have both been linked to depression and dementia. There have been reports of aplastic anaemia, agranulocytosis linked to phenylbutazone, Stevens-Johnson, and Lyell's syndrome linked to isoxicam and piroxicam, as well as the vulnerability of new-borns to Reye's syndrome after aspirin use. Lack of awareness, time constraints and unpredictability, poor training in ADRs identification, etc., are some of the reasons for the under-reporting of ADR of NSAIDs in India.

CONCLUSION

In order to rationally prescribe NSAIDs, it is essential to be aware of probable ADR's and establish prescription guidelines. Prescribers' behaviour can be changed toward excellent prescribing practices by conducting routine prescription assessments dealing with NSAIDs and providing feedback. In the near future, it will be critical to strengthen ADR data management and expand the reach of pharmacovigilance programs, ADR monitoring centers, and healthcare professionals' especially pharmacists' training in rural locations.

Strategies to Overcome Antimicrobial Resistance in Nosocomial Infections, A Review and Update

Nosocomial infections, also known as healthcare-associated infections, are a significant global concern due to their strong association with high mortality and morbidity in both developed and developing countries. These infections are caused by a variety of pathogens, particularly the ESKAPE group of bacteria, which includes the six pathogens Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. These bacteria have demonstrated noteworthy resistance to different antibiotics. Antimicrobial resistance mechanisms can manifest in various forms, including restricting drug uptake, modifying drug targets, inactivating drugs, active drug efflux, and biofilm formation. Accordingly, various strategies have been developed to combat antibiotic-resistant bacteria. These strategies encompass the development of new antibiotics, the utilization of bacteriophages that specifically target these bacteria, antimicrobial combination therapy and the use of peptides or enzymes that target the genomes or essential proteins of resistant bacteria. Among promising approaches to overcome antibiotic resistance, the CRISPR/Cas system stands out and offers many advantages. This system enables precise and efficient editing of genetic material at specific locations in the genome. Functioning as a bacterial "adaptive immune system," the CRISPR/Cas system recognizes, degrades, and remembers foreign DNA sequences through the use of spacer DNA segments that are transcribed into CRISPR RNAs (crRNA). This paper has focused on nosocomial infections, specifically the pathogens involved in hospital infections, the mechanisms underlying bacterial resistance, and the strategies currently employed to address this issue. Special emphasis has been placed on the application of CRISPR/Cas technology for overcoming antimicrobial resistance.

Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database

Drug repurposing is an emerging approach to reassigning existing pre-approved therapies for new indications. The FDA Adverse Event Reporting System (FAERS) is a large database of over 28 million adverse event reports submitted by medical providers, patients, and drug manufacturers and provides extensive drug safety signal data. In this review, four common drug repurposing strategies using FAERS are described, including inverse signal detection for a single disease, drug-drug interactions that mitigate a target ADE, identifying drug-ADE pairs with opposing gene perturbation signatures and identifying drug-drug pairs with congruent gene perturbation signatures. The purpose of this review is to provide an overview of these different approaches using existing successful applications in the literature. With the fast expansion of adverse drug event reports, FAERS-based drug repurposing represents a promising strategy for discovering new uses for existing therapies.

Tumor Necrosis Alpha (TNF-α) Antagonists Used in Chronic Inflammatory Rheumatic Diseases: Risks and their Minimization Measures

Tumor necrosis factor alpha (TNF- α) inhibitors are widely employed for the management of chronic inflammatory rheumatism. However, their usage carries significant risks, including site and infusion reactions, serious infections, malignancy, heart failure autoimmune and demyelinating disorders. These risks are comprehensively outlined in risk management plans (RMPs) associated with these molecules. RMP provides information on the safety profile of a medicinal product as well as the measures that will be taken to minimize risks; these are known as risk minimization measures. These measures are divided into routine measures related to elements, such as the summary of product characteristics, labeling, pack size, package leaflet, or legal supply status of the product, while additional measures may include educational programs, including tools for healthcare providers and patients, controlled access or pregnancy prevention programs, among others. Additional measures can consist of one or more interventions that need to be implemented in a sustainable way in a defined target group, while respecting the timing and frequency of any intervention and procedures to reach the target population. An evaluation of the effectiveness of these measures is required to determine whether or not an intervention has been effective. This comprehensive review offers an in-depth exploration of the current treatment, uses, and associated risks of TNF-α inhibitors. Additionally, it provides a detailed account of risk minimization measures and risk management practices while shedding light on their real-world implementation and effectiveness.

The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice

Precision medicine (PM), through the integration of omics and environmental data, aims to provide a more precise prevention, diagnosis, and treatment of disease. Currently, PM is one of the emerging approaches in modern healthcare and public health, with wide implications for health care delivery, public health policy making formulation, and entrepreneurial endeavors. In spite of its growing popularity and the buzz surrounding it, PM is still in its nascent phase, facing considerable challenges that need to be addressed and resolved for it to attain the acclaim for which it strives. In this article, we discuss some of the current methodological pitfalls of PM, including the use of big data, and provide a perspective on how these challenges can be overcome by bringing PM closer to evidence-based medicine (EBM). Furthermore, to maximize the potential of PM, we present real-world illustrations of how EBM principles can be integrated into a PM approach.

[Update of triggers for detection of adverse drug events in hematologic patients]

The use of triggers for the active search and detection of adverse drug events (ADEs) has been gaining ground within pharmacovigilance services. Thus, the main objective of the study was to propose a new list of triggers to be used in a center specialized in hematology in Rio de Janeiro, Brazil. The update of the list of triggers consisted of revising the current list, with the exclusion and inclusion of new triggers. To verify the performance of the new list of triggers, a cross-sectional study was conducted in which the new triggers were used to investigate the occurrence of ADEs in patients attended in the emergency unit or hospitalized from January to March 2022. For each suspected ADEs, the patient's profile and adverse drug reactions (ADRs) were characterized regarding causality and severity. The performance of the triggers and their ability to capture ADEs were estimated using the following indicators: frequency of the trigger per 100 medical records, frequency of ADEs per 100 records, and positive predictive value (PPV). To evaluate the overall performance of the proposed new list, the PPV was estimated. A total of 374 prescriptions for triggers were identified in 186 medical records. The most efficient in the detection of possible ADEs were: lidocaine, loperamide, bisacodyl, filgrastim and glycerin clyster. The overall PPV of the new suggested list was 48% versus 10% of the previous list. This study demonstrated the importance of an updated list of triggers for the monitoring of ADEs and improvement of the care provided.

Database screening as a strategy to identify endogenous candidate metabolites to probe and assess mitochondrial drug toxicity

Adverse drug reactions (ADRs) are considered an inherent risk of medication use, and some ADRs have been associated with off-target drug interactions with mitochondria. Metabolites that reflect mitochondrial function may help identify patients at risk of mitochondrial toxicity. We employed a database strategy to identify candidate mitochondrial metabolites that could be clinically useful to identify individuals at increased risk of mitochondrial-related ADRs. This led to L-carnitine being identified as the candidate mitochondrial metabolite. L-carnitine, its acetylated metabolite, acetylcarnitine and other acylcarnitines are mitochondrial biomarkers used to detect inborn errors of metabolism. We hypothesized that changes in L-carnitine disposition, induced by a "challenge test" of intravenous L-carnitine, could identify mitochondrial-related ADRs by provoking variation in L-carnitine and/or acetylcarnitine blood levels. To test this hypothesis, we induced mitochondrial drug toxicity with clofazimine (CFZ) in a mouse model. Following CFZ treatment, mice received an L-carnitine "challenge test". CFZ-induced changes in weight were consistent with previous work and reflect CFZ-induced catabolism. L-carnitine induced differences in whole blood acetylcarnitine concentrations in a manner that was dependent on CFZ treatment. This supports the usefulness of a database strategy for the discovery of candidate metabolite biomarkers of drug toxicity and substantiates the potential of the L-carnitine "challenge test" as a "probe" to identify drug-related toxicological manifestations.

Quantitative Raman chemical imaging of intracellular drug-membrane aggregates and small molecule drug precipitates in cytoplasmic organelles

Raman confocal microscopes have been used to visualize the distribution of small molecule drugs within different subcellular compartments. This visualization allows the discovery, characterization, and detailed analysis of the molecular transport phenomena underpinning the Volume of Distribution - a key parameter governing the systemic pharmacokinetics of small molecule drugs. In the specific case of lipophilic small molecules with large Volumes of Distribution, chemical imaging studies using Raman confocal microscopes have revealed how weakly basic, poorly soluble drug molecules can accumulate inside cells by forming stable, supramolecular complexes in association with cytoplasmic membranes or by precipitating out within organelles. To study the self-assembly and function of the resulting intracellular drug inclusions, Raman chemical imaging methods have been developed to measure and map the mass, concentration, and ionization state of drug molecules at a microscopic, subcellular level. Beyond the field of drug delivery, Raman chemical imaging techniques relevant to the study of microscopic drug precipitates and drug-lipid complexes which form inside cells are also being developed by researchers with seemingly unrelated scientific interests. Highlighting advances in data acquisition, calibration methods, and computational data management and analysis tools, this review will cover a decade of technological developments that enable the conversion of spectral signals obtained from Raman confocal microscopes into new discoveries and information about previously unknown, concentrative drug transport pathways driven by soluble-to-insoluble phase transitions occurring within the cytoplasmic organelles of eukaryotic cells.

Pharmacovigilance and Adverse Drug Reactions Reporting: Healthcare Providers' Experiences from Southern Highland Tanzania

Purpose

This exploratory qualitative study aimed to analyze the experiences of healthcare providers (HCPs) in pharmacovigilance (PV) and ADR reporting in the southern highland zone of Tanzania.

Methods

In 2022, an exploratory qualitative case study using in-depth interviews (IDIs) was conducted to explore the experiences of PV and ADR reporting among HCPs (doctors, nurses, and pharmacists). The study was carried out in a zonal referral hospital and a regional referral hospital of the Tanzanian southern highlands zone. Inductive-deductive thematic analysis was adopted for data analysis.

Results

Participants demonstrated adequate knowledge of PV and its related activities including ADR reporting. Knowing the interactions and wrong medication dosage as sources of ADR, signs, and symptoms, stopping the drug, and treating the symptoms following ADR emerged as subthemes linked with adequate knowledge in identifying and managing ADR. Participants perceived reporting ADR as laborious, posing a subjective burden and that not all ADRs needed to be reported. The latter contributed to limited participation in ADR reporting despite that participants were conversant with both physical and online ADR reporting platforms.

Conclusion

Although HCPs are well informed about PV and ADR reporting including the benefits to public health, their involvement in ADR reporting is low. In addition to the ongoing on-the-job training and regular supportive supervision for HCPs to improve the ADR practice, there is still a need to explore other strategies to be used as motives for HCPs to report ADR regularly.

Opportunities and challenges of pharmacovigilance in special populations: a narrative review of the literature

The relatively new discipline of pharmacovigilance (PV) aims to monitor the safety of drugs throughout their evolution and is essential to discovering new drug risks. Due to their specific and complex physiology, children, pregnant women, and elderly adults are more prone to adverse drug reactions (ADRs). Additionally, the lack of clinical trial data exacerbates the challenges faced with pharmacotherapy in these populations. Elderly patients tend to have multiple comorbidities often requiring more extensive medication, which adds additional challenges for healthcare professionals (HCPs) in delivering safe and effective pharmacotherapy. Clinical trials often have inherent limitations, including insufficient sample size and limited duration of research; as some ADRs are attributed to long-term use of a drug, these may go undetected during the course of the trial. Therefore, the implementation of PV is key to insuring the safe and effective use of drugs in special populations. We conducted a thorough review of the scientific literature on PV systems across the European Union, the United States, and China. Our review focused on basic physiological characteristics, drug use, and PV for specific populations (children, pregnant women, and the elderly). This article aims to provide a reference for the development of follow-up policies and improvement of existing policies as well as provide insight into drug safety with respect to patients of special populations.

Monitoring the appropriate prescription of low molecular weight heparins and Fondaparinux through administrative data. A retrospective observational study in the Tuscany region

INTRODUCTION

Low Molecular Weight Heparins (LMWHs) and Fondaparinux have been widely used as anticoagulants. Mass prescription may lead to prescriptive inappropriateness, which causes Heparin-induced thrombocytopenia and other side effects.

OBJECTIVES

The study investigates the appropriate prescription of LMWHs and Fondaparinux in Tuscany. We aim to validate the crude measure of prescription appropriateness of the Key Performance Indicator (KPI) "Patients treated with LMWHs and Fondaparinux every hundred residents in Tuscany" as a proxy for monitoring prescription appropriateness.

METHODS

To compare a crude KPI based only on drug consumption with a refined KPI based on exclusions listed in the clinical guidelines, a retrospective observational cohort study was carried out, using the RECORD guidelines for the year 2019. The refined indicator is computed via record linkage of different datasets regarding (a) pharmaceutical services; (b) hospital discharge records; (c) outpatient services; and (d) birth certificates. We apply exclusion criteria to identify the cohort of patients. Values of the KPI are compared, by ranking, with those obtained from its refined version. A Spearman test was performed to validate the use of the crude KPI as a proxy.

RESULTS

208,717 LMWH and Fondaparinux users are identified, of which 103,299 fall within the study's inclusion criteria. 16,817 (16%) of LMWHs and Fondaparinux users are classified as high consumption. The refined version of the KPI produces the same ranking results in terms of local health districts (rho = 0.98 p<0.01).

CONCLUSIONS

Although the crude KPI is less refined and detailed than the adjusted indicator computed by our study, it has proven capable to provide an accurate snapshot of the use of these drugs across the region. This analysis is useful to enable regional and local managers to run rapid and simple indicators to monitor the appropriateness of LMWHs and Fondaparinux. This analysis should be reviewed periodically to confirm its accuracy.

Under-reporting of adverse drug reactions: Surveillance system evaluation in Ho Municipality of the Volta Region, Ghana

BACKGROUND

Adverse Drug Reactions (ADRs) can occur with all medicines even after successful extensive clinical trials. ADRs result in more than 10% of hospital admissions worldwide. In Ghana, there has been an increase of 13 to 126 ADR reports per million population from 2012 to 2018. ADR Surveillance System (ADRSS) also known as pharmacovigilance has been put in place by the Ghana Food and Drugs Authority (FDA) to collect and manage suspected ADR reports and communicate safety issues to healthcare professionals and the general public. The ADRSS in Ho Municipality was evaluated to assess the extent of reporting of ADRs and the system's attributes; determine its usefulness, and assess if the ADRSS is achieving its objectives.

METHODS

We evaluated the ADRSS of the Ho Municipality from January 2015 to December 2019. Quantitative data were collected through interviews and review of records. We adapted the updated CDC guidelines to develop interview guides and a checklist for data collection. Attributes reviewed included simplicity, data quality, acceptability, representativeness, timeliness, sensitivity, predictive value positive and stability.

RESULTS

We found a total of 1,237 suspected ADR during the period, of which only 36 (3%) were reported by healthcare professionals in the Ho Municipality to the National Pharmacovigilance Centre (NPC). Only 43.9% of health staff interviewed were familiar with the ADRSS and its reporting channel. Staff who could mention at least one objective of the ADRSS were 34.2%, and 12.2% knew the timelines for reporting ADR. Reports took a median time of 41 (IQR = 25, 81) days from reporter to NPC. Reports sent on time constituted 37.5%. Fully completed case forms constituted 77.1% and the predictive value positive (PVP) was 20%. About 53% of ADRs were reported for female patients. Up to 88.9% of ADRs were classified as drug related. Anti-tuberculosis agents and other antibiotics constituted (40.6%) and (18.8%) of all reports. The ADRSS was not integrated into the disease surveillance and response system of Ghana's Health Service and so was not flexible to changes. A dedicated ADR surveillance officer in regions helped with the system's stability. Data from Ghana feeds into a WHO database for global decision making.

CONCLUSIONS

There was under-reporting of ADRs in the Ho Municipality from January 2015 to December 2019. The ADR surveillance system was simple, stable, acceptable, representative, had a strong PVP but was not flexible or timely. The ADRSS was found useful and partially met its objectives.

Maximizing patient safety when prescribing opioids for pain management

ABSTRACT

Cytochrome P450 enzyme metabolism is altered by environmental and genetic factors, which can affect the efficacy and safety of opioids. This article describes CYP polymorphisms and how pharmacogenetic testing could be used to help clinicians make safer decisions about opioid use in patients.

Hospitalisations Related to Adverse Drug Reactions in Switzerland in 2012-2019: Characteristics, In-Hospital Mortality, and Spontaneous Reporting Rate

INTRODUCTION

Adverse drug reactions (ADRs) contribute to morbidity, and serious ADRs may cause hospitalisation and death. This study characterises and quantifies ADR-related hospitalisations and subsequent in-hospital deaths, and estimates the spontaneous reporting rate to regulatory authorities in Switzerland, where healthcare professionals are legally obliged to report ADRs.

METHODS

This retrospective cohort study from 2012 to 2019 analysed nationwide data from the Federal Statistical Office. ICD-10 coding rules identified ADR-related hospitalisations. To estimate the reporting rate, individual case safety reports (ICSRs) collected in the Swiss spontaneous reporting system during the same period were considered.

RESULTS

Among 11,240,562 inpatients, 256,550 (2.3%) were admitted for ADRs, 132,320 (51.6%) were female, 120,405 (46.9%) were aged ≥ 65 (median of three comorbidities, interquartile range [IQR] 2-4), and 16,754 (6.5%) were children/teenagers (0 comorbidities, IQR 0-1). Frequent comorbidities were hypertension (89,938 [35.1%]), fluid/electrolyte disorders (54,447 [21.2%]), renal failure (45,866 [17.9%]), cardiac arrhythmias (37,906 [14.8%]), and depression (35,759 [13.9%]). Physicians initiated 113,028 (44.1%) of hospital referrals, and patients/relatives 73,494 (28.6%). Frequently ADR-affected were the digestive system (48,219 [18.8%], e.g. noninfective gastroenteritis and colitis), the genitourinary system (39,727 [15.5%], e.g. acute renal failure), and the mental/behavioural state (39,578 [15.4%], e.g. opioid dependence). In-hospital mortality was 2.2% (5669). Since ICSRs indicated 14,109 hospitalisations and 700 in-hospital deaths, estimated reporting rates were 5% and 12%, respectively.

CONCLUSIONS

This 8-year observation in Switzerland revealed that 2.3%, or roughly 32,000 admissions per year, were caused by ADRs. The majority of ADR-related admissions were not reported to the regulatory authorities, despite legal obligations.

Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study

INTRODUCTION

Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associated bleeding.

METHODS

The AoU program, beginning in 05/2018, continues to recruit ≥ 18 years old individuals across the United States. Participants completed surveys and consented to contribute electronic health record (EHR) for research. Using the EHR, we determined participants who were exposed to SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vortioxetine). Features (n = 88) were selected with clinicians' input and comprised sociodemographic, lifestyle, comorbidities, and medication use information. We identified bleeding events with validated EHR algorithms and applied logistic regression, decision tree, random forest, and extreme gradient boost to predict bleeding during SSRI exposure. We assessed model performance with area under the receiver operating characteristic curve statistic (AUC) and defined clinically significant features as resulting in > 0.01 decline in AUC after removal from the model, in three of four ML models.

RESULTS

There were 10,362 participants exposed to SSRIs, with 9.6% experiencing a bleeding event during SSRI exposure. For each SSRI, performance across all four ML models was relatively consistent. AUCs from the best models ranged 0.632-0.698. Clinically significant features included health literacy for escitalopram, and bleeding history and socioeconomic status for all SSRIs.

CONCLUSIONS

We demonstrated feasibility of predicting ADEs using ML. Incorporating genomic features and drug interactions with deep learning models may improve ADE prediction.

How to Run the Pharmacogenomics Clinical Annotation Tool (PharmCAT)

Pharmacogenomics (PGx) investigates the genetic influence on drug response and is an integral part of precision medicine. While PGx testing is becoming more common in clinical practice and may be reimbursed by Medicare/Medicaid and commercial insurance, interpreting PGx testing results for clinical decision support is still a challenge. The Pharmacogenomics Clinical Annotation Tool (PharmCAT) has been designed to tackle the need for transparent, automatic interpretations of patient genetic data. PharmCAT incorporates a patient's genotypes, annotates PGx information (allele, genotype, and phenotype), and generates a report with PGx guideline recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and/or the Dutch Pharmacogenetics Working Group (DPWG). PharmCAT has introduced new features in the last 2 years, including a variant call format (VCF) Preprocessor, the inclusion of DPWG guidelines, and functionalities for PGx research. For example, researchers can use the VCF Preprocessor to prepare biobank-scale data for PharmCAT. In addition, PharmCAT enables the assessment of novel partial and combination alleles that are composed of known PGx variants and can call CYP2D6 genotypes based on single and deletions in the input VCF file. This tutorial provides materials and detailed step-by-step instructions for how to use PharmCAT in a versatile way that can be tailored to users' individual needs.

Drug_SNSMiner: standard pharmacovigilance pipeline for detection of adverse drug reaction using SNS data

As society continues to age, it is becoming increasingly important to monitor drug use in the elderly. Social media data have been used for monitoring adverse drug reactions. The aim of this study was to determine whether social network studies (SNS) are useful sources of drug side effects information. We propose a method for utilizing SNS data to plot the known side effects of geriatric drugs in a dosing map. We developed a lexicon of drug terms associated with side effects and mapped patterns from social media data. We confirmed that well-known side effects may be obtained by utilizing SNS data. Based on these results, we propose a pharmacovigilance pipeline that can be extended to unknown side effects. We propose the standard analysis pipeline Drug_SNSMiner for monitoring side effects using SNS data and evaluated it as a drug prescription platform for the elderly. We confirmed that side effects may be monitored from the consumer's perspective based on SNS data using only drug information. SNS data were deemed good sources of information to determine ADRs and obtain other complementary data. We established that these learning data are invaluable for AI requiring the acquisition of ADR posts on efficacious drugs.

Pharmacogenetics in the Treatment of Huntington’s Disease: Review and Future Perspectives

Huntington’s disease (HD) is an autosomal dominant progressive brain disorder, caused by a pathological expansion of a CAG repeat that encodes the huntingtin gene. This genetic neurodegenerative rare disease is characterized by cognitive, motor, and neuropsychiatric manifestations. The aim of the treatment is symptomatic and addresses the hyperkinetic disorders (chorea, dystonia, myoclonus, tics, etc.) and the behavioural and cognitive disturbances (depression, anxiety, psychosis, etc.) associated with the disease. HD is still a complex condition in need of innovative and efficient treatment. The long-term goal of pharmacogenetic studies is to use genotype data to predict the effective treatment response to a specific drug and, in turn, prevent potential undesirable effects of its administration. Chorea, depression, and psychotic symptoms have a substantial impact on HD patients’ quality of life and could be better controlled with the help of pharmacogenetic knowledge. We aimed to carry out a review of the available publications and evidence related to the pharmacogenetics of HD, with the objective of compiling all information that may be useful in optimizing drug administration. The impact of pharmacogenetic information on the response to antidepressants and antipsychotics is well documented in psychiatric patients, but this approach has not been investigated in HD patients. Future research should address several issues to ensure that pharmacogenetic clinical use is appropriately supported, feasible, and applicable.

Pharmacists' role in detection and evaluation of adverse drug reactions: Developing proactive systems for pharmacosurveillance

PURPOSE

To identify current challenges in detection of medication-related symptoms, and review technology-based opportunities to increase the patient-centeredness of postmarketing pharmacosurveillance to promote more accountable, safer, patient-friendly, and equitable medication prescribing.

SUMMARY

Pharmacists have an important role to play in detection and evaluation of adverse drug reactions (ADRs). The pharmacist's role in medication management should extend beyond simply dispensing drugs, and this article delineates the rationale and proactive approaches for pharmacist detection and assessment of ADRs. We describe a stepwise approach for assessment, best practices, and lessons learned from a pharmacist-led randomized trial, the CEDAR (Calling for Detection of Adverse Drug Reactions) project.

CONCLUSION

Health systems need to be redesigned to more fully utilize health information technologies and pharmacists in detecting and responding to ADRs.

Integrating metabolomics, bionics, and culturomics to study probiotics-driven drug metabolism

Many drugs have been shown to be metabolized by the human gut microbiome, but probiotic-driven drug-metabolizing capacity is rarely explored. Here, we developed an integrated metabolomics, culturomics, and bionics framework for systematically studying probiotics-driven drug metabolism. We discovered that 75% (27/36 of the assayed drugs) were metabolized by five selected probiotics, and drugs containing nitro or azo groups were more readily metabolized. As proof-of-principle experiments, we showed that Lacticaseibacillus casei Zhang (LCZ) could metabolize racecadotril to its active products, S-acetylthiorphan and thiorphan, in monoculture, in a near-real simulated human digestion system, and in an ex vivo fecal co-culture system. However, a personalized effect was observed in the racecadotril-metabolizing activity of L. casei Zhang, depending on the individual's host gut microbiome composition. Based on data generated by our workflow, we proposed a possible mechanism of interactions among L. casei Zhang, racecadotril, and host gut microbiome, providing practical guidance for probiotic-drug co-treatment and novel insights into precision probiotics.

Adverse drug reactions and associated patient characteristics in older community-dwelling adults: a 6-year prospective cohort study

BACKGROUND

To date, research on adverse drug reactions (ADRs) has focused on secondary care, and there is a paucity of studies that have prospectively examined ADRs affecting older adults in general practice.

AIM

To examine the cumulative incidence and severity of ADRs and associated patient characteristics in a sample of community-dwelling older adults.

DESIGN AND SETTING

Prospective cohort study of older adults (aged ≥70 years, N = 592) recruited from 15 general practices in the Republic of Ireland.

METHOD

Manual review of the participant's general practice electronic medical record, linked to the national dispensed prescription medicine database, and a detailed, self-reported patient postal questionnaire. The primary outcomes were ADR occurrence and severity over a 6-year period (2010-2016). Unadjusted and adjusted logistic regression models examined potential associations between patient characteristics and ADR occurrence.

RESULTS

A total of 211 ADRs were recorded for 159 participants, resulting in a cumulative incidence of 26.9% over 6 years. The majority of ADRs detected were mild (89.1%), with the remainder classified as moderate (10.9%). Eight moderate ADRs, representing 34.8% of moderate ADRs and 3.8% of all ADRs, required an emergency hospital admission. ADRs were independently associated with female sex (adjusted odds ratio [OR] 1.83, 95% confidence interval [CI] = 1.17 to 2.85; P = 0.008), polypharmacy (5-9 drug classes) (adjusted OR 1.81, 95% CI = 1.17 to 2.82; P = 0.008), and major polypharmacy (≥10 drug classes) (adjusted OR = 3.33, 95% CI = 1.62 to 6.85; P = 0.001).

CONCLUSION

This prospective cohort study of ADRs in general practice shows that over one-quarter of older adults experienced an ADR over a 6-year period. Polypharmacy is independently associated with ADR risk in general practice and older adults on ≥10 drug classes should be prioritised for regular medication review.

Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital

BACKGROUND

Natural language processing (NLP) based clinical decision support systems (CDSSs) have demonstrated the ability to extract vital information from patient electronic health records (EHRs) to facilitate important decision support tasks. While obtaining accurate, medical domain interpretable results is crucial, it is demanding because real-world EHRs contain many inconsistencies and inaccuracies. Further, testing of such machine learning-based systems in clinical practice has received limited attention and are yet to be accepted by clinicians for regular use.

METHODS

We present our results from the evaluation of an NLP-driven CDSS developed and implemented in a Norwegian Hospital. The system incorporates unsupervised and supervised machine learning combined with rule-based algorithms for clinical concept-based searching to identify and classify allergies of concern for anesthesia and intensive care. The system also implements a semi-supervised machine learning approach to automatically annotate medical concepts in the narrative.

RESULTS

Evaluation of system adoption was performed by a mixed methods approach applying The Unified Theory of Acceptance and Use of Technology (UTAUT) as a theoretical lens. Most of the respondents demonstrated a high degree of system acceptance and expressed a positive attitude towards the system in general and intention to use the system in the future. Increased detection of patient allergies, and thus improved quality of practice and patient safety during surgery or ICU stays, was perceived as the most important advantage of the system.

CONCLUSIONS

Our combined machine learning and rule-based approach benefits system performance, efficiency, and interpretability. The results demonstrate that the proposed CDSS increases detection of patient allergies, and that the system received high-level acceptance by the clinicians using it. Useful recommendations for further system improvements and implementation initiatives are reducing the quantity of alarms, expansion of the system to include more clinical concepts, closer EHR system integration, and more workstations available at point of care.

Twenty-First Century Global ADR Management: A Need for Clarification, Redesign, and Coordinated Action

Adverse drug reactions (ADRs) are estimated to be between the fourth and sixth most common cause of death worldwide, taking their place among other prevalent causes of mortality such as heart disease, cancer, and stroke. ADRs impact a broad range of populations across a wide variety of global geography and demographics, with significant mortality and morbidity burden in vulnerable groups such as older people, pediatric populations, and individuals in low-income settings. Too large a share of medicines risk management remains limited to signal detection in big ADR databases (USFDA, EMA, WHO, etc.) This resource allocation is antiquated and applied statistical signal detection methodologies have reached their limits of usefulness. In addition, existing databases are designed for short-term reactions, closely related to medication use and, thus, can only partially assess important broader consequences across geography, time, and clinical relevance. There is an urgent need change the dynamic. We need to identify (earlier and more regularly) many of the important but often overlooked or missed ADRs. Rather than assigning blame, we need to identify the root causes of the problem so they can be clearly addressed and fixed. The public health implications are profound-particularly as we recognize the importance of predicting and mitigating the next pandemic. Consequently, medicines risk management must be integrated within a broader global public health vision. To accomplish this, we need to develop the new tools and methodologies critical to assessing these public health imperatives.

Development of a multivariate prediction model to identify individual case safety reports which require clinical review

BACKGROUND

The number of Individual Case Safety Reports (ICSRs) in pharmacovigilance databases are rapidly increasing world-wide. The majority of ICSRs at the Netherlands Pharmacovigilance Centre Lareb is reviewed manually to identify potential signal triggering reports (PSTR) or ICSRs which need further clinical assessment for other reasons.

OBJECTIVES

To develop a prediction model to identify ICSRs that require clinical review, including PSTRs. Secondly, to identify the most important features of these reports.

METHODS

All ICSRs (n = 30 424) received by Lareb between October 1, 2017 and February 26, 2021 were included. ICSRs originating from marketing authorisation holders and ICSRs reported on vaccines were excluded. The outcome was defined as PSTR (yes/no), where PSTR 'yes' was defined as an ICSR discussed at a signal detection meeting. Nineteen features were included, concerning structured information on: patients, adverse drug reactions (ADR) or drugs. Data were divided into a training (70%) and test set (30%) using a stratified split to maintain the PSTR/no PSTR ratio. Logistic regression, elastic net logistic regression and eXtreme Gradient Boosting models were trained and tuned on a training set. Random down-sampling of negative controls was applied on the training set to adjust for the imbalanced dataset. Final models were evaluated on the test set. Model performances were assessed using the area under the curve (AUC) with 95% confidence interval of a receiver operating characteristic (ROC), and specificity and precision were assessed at a threshold for perfect sensitivity (100%, to not miss any PSTRs). Feature importance plots were inspected and a selection of features was used to re-train and test model performances with fewer features.

RESULTS

1439 (4.7%) of reports were PSTR. All three models performed equally with a highest AUC of 0.75 (0.73-0.77). Despite moderate model performances, specificity (5%) and precision (5%) were low. Most important features were: 'absence of ADR in the Summary of product characteristics', 'ADR reported as serious', 'ADR labelled as an important medical event', 'ADR reported by physician' and 'positive rechallenge'. Model performances were similar when using only nine of the most important features.

CONCLUSIONS

We developed a prediction model with moderate performances to identify PSTRs with nine commonly available features. Optimisation of the model using more ICSR information (e.g., free text fields) to increase model precision is required before implementation.