Clinical and economic burden of adverse drug reactions

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.

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.

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.

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.

Patients’ perception of the pharmacovigilance system: A pre-diagnostic and post-interventional cross-sectional survey

Background and objective: The risk of adverse reactions necessitated the pharmacovigilance system for patient safety. A literature search documented better health literacy of patients through intervention. This investigation aims to assess the perception and the effect of an intervention on patients regarding adverse reactions caused by drugs.

Methods: A pre-diagnostic and post-interventional cross-sectional investigation was designed with a sample size of 423 patients in hospitals of Islamabad. The proportion of patients was selected based on a stratified probability technique. A prevalidated tool was used to collect the response twice through a health promotion brochure with counseling, which was applied as an intervention.

Results: The outcome of the investigation revealed that the prerequisite of the pharmacovigilance center in the hospital among respondents was improved significantly by 41.2% after intervention. Knowledge, communication, and practice were significantly different with respect to gender. There was a moderate Pearson correlation between diagnostic and interventional responses of patient’s knowledge of adverse reactions by drugs (r = 0.66, p &lt; 0.01) and patient’s communication in pharmacovigilance (r = 0.62, p &lt; 0.01) and a strong correlation between diagnostic and interventional responses of patient’s practice in the pharmacovigilance system (r = 0.72, p &lt; 0.01).

Conclusion: The finding of the investigation provided evidence that patient awareness was significantly improved by the health promotion model. Patient participation in the reporting of adverse reactions of drugs will complement the hospital staff reporting. These reports will construct an authentic, cross-checked database for rational drug safety practices in Pakistan.

Prevalence and factors associated with adverse drug reactions among heart failure patients hospitalized at Mbarara Regional Referral Hospital, Uganda

BACKGROUND

Adverse drug reaction (ADR) of medications remains an obstacle to achieving optimal disease outcomes. This study aimed to assess the prevalence and associated factors of ADR among Heart failure (HF) patients hospitalized at Mbarara Regional and Referral Hospital.

METHOD

A prospective observational study was conducted among hospitalized HF patients from November 2021 to January 2022. Univariate and multivariate logistic regression was employed to determine factors associated with the ADR.

RESULT

Overall, 118 HF patients were included in the study with a median age of 43 years. A total of 164 ADRs were identified during the follow-up period of 1011 days. The incidence of new ADRs was 106 ADRs/1000 person-days. The prevalence of ADR was 59.3%. Of the 164 ADRs, 118(71.9%) were probable. The gastrointestinal system was the most frequently (27.5%) affected system. Over half (86, 52.4%) of the ADRs were mild and 96(58.5%) were preventable. Age group 19-59(AOR 0.15[0.03-0.35] at 95%CI, p = 0.013), herbal use (AOR 3.07[1.01-9.32] at 95%CI, p = 0.048), poly-pharmacy (AOR 8.7[2.4-15.77] at 95%CI, p &lt; 0.001) and drug-drug interaction (AOR 6.06[2.79-12.5] at 95%CI, p = 0.004) were significantly associated with ADRs among HF patients.

CONCLUSION

More than half of the hospitalized HF patients experienced at least one ADR during their hospital stay. The use of herbal medicines, poly-pharmacy, and drug-drug interaction were associated with a high risk of ARDs whereas the age group 19-59 years was less likely to experience ADRs.

Knowledge, attitudes and practice regarding pharmacovigilance and adverse drug reaction reporting among physicians and pharmacists in Egypt: a step toward personalized medicine implementation

Aim: To assess the knowledge, attitudes, and practices of the healthcare professionals working at Children's Cancer Hospital Egypt regarding pharmacovigilance (PV) and adverse drug reaction (ADR) reporting, in addition to the ADR reporting barriers. Materials & methods: A cross-sectional study was conducted at Children's Cancer Hospital Egypt from July to September 2021 using a validated questionnaire. Results: About 37 physicians (20.3%) and 145 pharmacists (79.7%) responded to the survey. Overall, the knowledge (median: 40%) and practice (median: 50%) of PV and the reporting of ADRs were low; however, attitudes were mostly positive. The main barrier to reporting ADRs was The difficulty of determining whether or not ADRs occurred (42.3%). Conclusion: Understanding of PV and ADR reporting could improve the huge gap between ADRs experienced and ADRs reported. In order to be able to assess the impact of personalized medicine implementation, adequate ADR reporting should be well established.

Artificial Intelligent Context-Aware Machine-Learning Tool to Detect Adverse Drug Events from Social Media Platforms

INTRODUCTION

Pharmacovigilance (PV) has proven to detect post-marketing adverse drug events (ADE). Previous research used the natural language processing (NLP) tool to extract unstructured texts relevant to ADEs. However, texts without context reduce the efficiency of such algorithms. Our objective was to develop and validate an innovative NLP tool, aTarantula, using a context-aware machine-learning algorithm to detect existing ADEs from social media using an aggregated lexicon.

METHOD

aTarantula utilized FastText embeddings and an aggregated lexicon to extract contextual data from three patient forums (i.e., MedHelp, MedsChat, and PatientInfo) taking warfarin. The lexicon used warfarin package inserts and synonyms of warfarin ADEs from UMLS and FAERS databases. Data was stored on SQLite and then refined and manually checked by three clinical pharmacists for validation.

RESULTS

Multiple organ systems where the most frequent ADE were reported at 1.50%, followed by CNS side effects at 1.19%. Lymphatic system ADEs were the least common side effect reported at 0.09%. The overall Spearman rank correlation coefficient between patient-reported data from the forums and FAERS was 0.19. As determined by pharmacist validation, aTarantula had a sensitivity of 84.2% and a specificity of 98%. Three clinical pharmacists manually validated our results. Finally, we created an aggregated lexicon for mining ADEs from social media.

CONCLUSION

We successfully developed aTarantula, a machine-learning algorithmn based on artificial intelligence to extract warfarin-related ADEs from online social discussion forums automatically. Our study shows that it is feasible to use aTarantula to detect ADEs. Future researchers can validate aTarantula on the diverse dataset.

Ali S, Ting KN, Boardman H. Pharmacists’ experiences on adverse drug reaction: 10 years later

Adverse drug reaction (ADR) is one of the leading public health concerns associated with high mortality rate. Healthcare professionals, particularly pharmacists, have a significant role in monitoring and preventing ADRs. This study was conducted on Malaysian Pharmaceutical Society (MPS) pharmacists who worked at the hospitals, health clinics, and community pharmacies to determine if pharmacists’ experiences on ADRs are still the same 10 years later. In 2010, a postal survey and in 2020, an online survey were conducted among these pharmacists. A total of 472 pharmacists and 208 participated in 2010 and 2020, respectively. About 82% and 90% of hospital/health clinic pharmacists (HCPs) observed an ADR over the last 6 months in 2010 and 2020, while 60% and 100% community pharmacists in 2010 and 2020 observed an ADR, respectively. Perindopril was the top drug (HCPs: p = 0.657; CPs: p = 0.98), and rash was the top ADR reported by the pharmacists in both years (HCPs: p &lt; 0.001; CPs: p = 0.679). The most common actions taken by HCPs in 2010 were to report the ADR (p = 0.343), while in 2020, most HCPs explained to patients regarding the reaction (p = 0.061), which was also the same in the CP group in 2020 (p = 0.958). The top factor encouraging ADR reporting in both years and both pharmacist groups was the high degree of severity of the reaction (HCPs: p &lt; 0.001; CPs: p = 0.769). While the top factors discouraging ADR reporting were a lack of information from the affected patients (HCPs: p = 0.2; CPs: p = 0.656), reaction is widely known (HCPs: p = 0.001; CPs: p = 0.144) and uncertainty of the causal relationship (HCPs: p = 0.169; CPs: p = 0.609). Majority of the pharmacists agreed that severe reactions should be reported (HCPs: p = 0.158; CPs: p = 0.501) and the main aim for reporting is to measure the incidence of ADRs (HCPs: p = 0.148; CPs: p = 0.762). Despite being able to identify ADRs during the daily practice, many pharmacists especially community pharmacists are not reporting them. There is a misconception on the purpose of reporting ADRs. An interventional program and ADR reporting training would be a useful step in improving ADR reporting practice.

An Assessment of Mentions of Adverse Drug Events on Social Media With Natural Language Processing: Model Development and Analysis

Background

Adverse reactions to drugs attract significant concern in both clinical practice and public health monitoring. Multiple measures have been put into place to increase postmarketing surveillance of the adverse effects of drugs and to improve drug safety. These measures include implementing spontaneous reporting systems and developing automated natural language processing systems based on data from electronic health records and social media to collect evidence of adverse drug events that can be further investigated as possible adverse reactions.

Objective

While using social media for collecting evidence of adverse drug events has potential, it is not clear whether social media are a reliable source for this information. Our work aims to (1) develop natural language processing approaches to identify adverse drug events on social media and (2) assess the reliability of social media data to identify adverse drug events.

Methods

We propose a collocated long short-term memory network model with attentive pooling and aggregated, contextual representation generated by a pretrained model. We applied this model on large-scale Twitter data to identify adverse drug event–related tweets. We conducted a qualitative content analysis of these tweets to validate the reliability of social media data as a means to collect such information.

Results

The model outperformed a variant without contextual representation during both the validation and evaluation phases. Through the content analysis of adverse drug event tweets, we observed that adverse drug event–related discussions had 7 themes. Mental health–related, sleep-related, and pain-related adverse drug event discussions were most frequent. We also contrast known adverse drug reactions to those mentioned in tweets.

Conclusions

We observed a distinct improvement in the model when it used contextual information. However, our results reveal weak generalizability of the current systems to unseen data. Additional research is needed to fully utilize social media data and improve the robustness and reliability of natural language processing systems. The content analysis, on the other hand, showed that Twitter covered a sufficiently wide range of adverse drug events, as well as known adverse reactions, for the drugs mentioned in tweets. Our work demonstrates that social media can be a reliable data source for collecting adverse drug event mentions.

Costs Associated with Adverse Drug Reactions Among HIV/TB Patients in Thailand

Purpose

To assess the direct and indirect costs associated with adverse drug reactions (ADRs) in patients receiving treatment regimens for human immunodeficiency virus (HIV) infection and tuberculosis (TB) in selected Thai hospitals.

Patients and Methods

This was a retrospective study conducted between October 2014 and September 2019 at three public hospitals in Thailand. Data were obtained from a medical database and spontaneous ADR reporting system of each study site. The out-of-pocket health payments and indirect costs were determined via interviewing. All costs were updated to 2021.

Results

A total of 432 eligible patients who experienced ADRs due to HIV and TB treatment, and 93 patients were interviewed to determine direct non-medical and indirect costs. The average direct medical cost for ADR was USD 5.65 for mild cases, USD 156.54 for moderate cases, and USD 1,242.45 for severe cases. For direct non-medical costs, the average cost per episode was USD 27.29 in mild ADR, USD 70.86 in moderate ADR and USD 270.66 in severe ADR. The indirect cost incurred in each mild, moderate and severe ADR was USD 41.86, USD 89.34, and USD 552.60, respectively. The Stevens-Johnson syndrome (SJS) had the highest management costs.

Conclusion

ADRs associated with anti-tuberculosis drugs and antiretroviral drugs seem to have a substantial economic impact from a societal perspective. These findings would be useful for increasing awareness and encouraging early avoidance of ADRs.

Quality of Active versus Spontaneous Reporting of Adverse Drug Reactions in Pediatric Patients: Relevance for Pharmacovigilance and Knowledge in Pediatric Medical Care

For drug safety in pediatric patients, knowledge about adverse drug reactions (ADRs) is essential to balance benefits and risks, especially because of the high incidence of off-label drug use. However, underreporting of ADRs is a serious problem, leading to a deficit in knowledge affecting clinical practice. The aim of this study is to find a method by which we can improve the quantity of ADR reporting while maintaining or improving the quality of the ADR reports. This was done in several steps. First, health care providers were educated to increase awareness of ADRs. Thereafter, a novel active supporting system was introduced, where reporting ADRs was simplified; if clinical physicians suspected an ADR, they only had to send the name or hospital number of the patient, the observed ADR, and the suspected drug to a supportive team. This team collects all information needed about the possible ADR from the patient’s medical records and hospital charts. With this information, the supportive team fills in the forms necessary for reporting ADRs to the nationwide pharmacovigilance centre Lareb. With this system, the quantity of ADR reports from both inpatients and outpatients rose dramatically. Subsequently, the quality of the obtained ADR reports was measured using the ClinDoc and vigiGrade systems. This study shows there is no loss of quality of the ADR reports in the active reporting system compared to spontaneous reporting systems. Based on the data of the present study, we suggest that an active reporting system has the potential to increase our knowledge about ADRs in pediatric patients.

Precision medicine from a citizen perspective: a survey of public attitudes towards pharmacogenomics in Flanders

BACKGROUND

Personalized medicine is an emerging field, aiming to improve the safety and efficacy of pharmacotherapy. The field's implementation in clinical care is steadily increasing. Pharmacogenomics are one example of personalized approaches in the clinic and direct-to-consumer (DTC) pharmacogenomic tests have become publicly available. We aimed to assess public opinion on pharmacogenomic research and testing to foster integration within Belgian health care.

METHODS

A cross-sectional survey was created and disseminated online, focusing on the citizen perspective. Participants' willingness to engage in pharmacogenomic research was the primary outcome. In addition, their awareness, understanding, expectations and overall acceptance towards pharmacogenomic testing was investigated.

RESULTS

A total of 156 participants (54.5% aged between 18 and 30 years, 45.5% > 30 years; 73.1% females) completed the survey. Half ever experienced side effects (46.2%) and treatment failure (52.6%). Up to 45.5% (n = 71) were willing to participate in pharmacogenomics research, and the majority (78.8%) were convinced that pharmacogenomic tests could help doctors to prescribe them the right medications. Additionally, 76.3% (n = 118) supported a partial reimbursement of pharmacogenomics tests. A minority (5.1%, n = 8) of participants showed interest in DTC tests, and 15.4% (n = 24) expressed privacy concerns regarding pharmacogenomics testing. Participants preferred their healthcare professionals' to perform the test and access their data, but refused commercial providers.

CONCLUSION

Overall, participants showed a positive attitude towards precision medicine and pharmacogenomics research. Our findings may help guiding future pharmacogenomic implementation initiatives to optimize drug use by using pharmacogenomic information integrated within health care.

Simultaneous detection of a panel of nine sedatives and metabolites in plasma from critically ill pediatric patients via UPLC-MS/MS

Sedative use can result in adverse drug reactions. Intensive care unit patients are especially at risk and pharmacokinetic modeling of drug concentrations is an approach to develop precision dosing strategies. However, limited blood sampling availability in critically ill children and need for multiple assays to quantify a variety of commonly used sedatives creates logistical challenges. The goal of this project was to develop a sensitive and selective assay for the simultaneous quantification of a panel of sedatives comprised of midazolam (MDZ), alpha hydroxymidazolam (1- OH MDZ), dexmedetomidine (DEX), morphine (MOR), morphine-3-glucuronide (M3G), morphine-6-glucuronide (M6G), fentanyl (FEN), norfentanyl (NF), and hydromorphone (HM) in small volume pediatric plasma samples. A sensitive and efficient ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS/MS) method was developed following FDA guidance for bioanalytical validation. Minimal sample preparation consisting of simple protein precipitation extraction using acetonitrile with internal standards was utilized. Analyte separation was achieved using a gradient mixture of (A: 0.15% formic acid in water and B: Acetonitrile) and a Waters Acquity C18, 1.7 µm (2.1 × 100 mm) column. Assays were linear over the clinical concentration ranges: MDZ, MOR, HM: 0.5-125 ng/mL; 1-OH MDZ, M3G, M6G: 5-500 ng/mL; and DEX, FEN, NF: 0.05-7.5 ng/mL (R2 > 0.99 for all). Assay run time was 10 min and required only 100 μL of plasma. Initial testing of samples from pediatric patients demonstrates adequacy of assay to measure sedatives and metabolites at clinical concentrations confidently in low volumes of plasma. This novel highly-sensitive and specific method to measure a total of nine different analytes (five sedatives, four metabolites) simultaneously enables comprehensive analysis of a panel of sedatives in small volumes such as in pediatric ICU patients.

Associated factors of potential drug-drug interactions and drug-food interactions in patients with multiple sclerosis

Background:

Multiple sclerosis (MS) is the most common immune-mediated demyelinating disease in younger adults. Patients with MS (PwMS) are vulnerable to the presence of potential drug–drug interactions (pDDIs) and potential drug–food interactions (pDFIs) as they take numerous medications to treat MS, associated symptoms and comorbidities. Knowledge about pDDIs and pDFIs can increase treatment success and reduce side effects.

Objective:

We aimed at determining the frequency and severity of pDDIs and pDFIs in PwMS, with regard to polypharmacy.

Methods:

In the cross-sectional study, we analysed pDDIs and pDFIs of 627 PwMS aged ⩾18 years. Data collection was performed through patient record reviews, clinical examinations and structured patient interviews. pDDIs and pDFIs were identified using two DDI databases: Drugs.com Interactions Checker and Stockley’s Interactions Checker.

Results:

We identified 2587 pDDIs (counted with repetitions). Of 627 PwMS, 408 (65.1%) had ⩾ 1 pDDI. Polypharmacy (concomitant use of ⩾ 5 drugs) was found for 334 patients (53.3%). Patients with polypharmacy (Pw/P) were found to have a 15-fold higher likelihood of having ⩾ 1 severe pDDI compared with patients without polypharmacy (Pw/oP) (OR: 14.920, p < 0.001). The most frequently recorded severe pDDI was between citalopram and fingolimod. Regarding pDFIs, ibuprofen and alcohol was the most frequent severe pDFI.

Conclusion:

Pw/P were particularly at risk of severe pDDIs. Age and educational level were found to be factors associated with the occurrence of pDDIs, independent of the number of medications taken. Screening for pDDIs/pDFIs should be routinely done by the clinical physician to increase drug safety and reduce side effects.

Perceptions and barriers of adverse drug reaction reporting within inpatient state psychiatric facilities

Introduction

Adverse drug reactions (ADRs) are a leading cause of morbidity and mortality for hospitalized patients. Health care organizations track ADRs to reduce patient mortality, reduce hospital readmissions, decrease costs, and improve patient care. Differing definitions of ADRs cause confusion among providers, leading to hesitation with ADR reporting. The objective of this study was to understand health care professionals' perspectives of ADR reporting within inpatient state psychiatric facilities.

Methods

A survey was sent to 143 health care professionals throughout 25 inpatient state psychiatric facilities within 1 state. The survey assessed the definition of an ADR, confidence in reporting, barriers to reporting, the role of reporting, who should report and review ADRs, and strategies for process improvement.

Results

The survey had a 75.5% response rate with 108 respondents. Most respondents could identify the definition of an ADR, were moderately confident in reporting ADRs, and understood the importance of ADR reporting. Barriers to ADR reporting included the reaction not being serious, a lack of information about the ADR, or not enough clarity on how to report an ADR. Fear of retaliation was an additional barrier to ADR reporting. Training and direction on ADR reporting, education on real versus perceived consequences, a designated point person to aid in reporting, and better access to reporting technology were suggested improvements for ADR reporting.

Discussion

From this survey, it is evident that respondents believe improved education and training, improved communication regarding reporting consequences, and consensus on the definition of an ADR would encourage reporting.

Study of pattern & distribution of adverse drug reactions in acute coronary syndrome patients in a tertiary care hospital

Background & objectives

With the availability of a wide range of drugs to treat patients with acute coronary syndrome (ACS), adverse drug reactions (ADRs) have become inevitable in clinical practice. Thorough knowledge of such reactions is essential for the treating physician for optimal treatment and better outcomes. There are many scales to define, measure and assess the ADRs, but there is a dearth of data available on such drug reactions among ACS patients. Hence, this study attempted to analyze the pattern, causality, severity, predictability and preventability of ADRs in ACS patients. All the ADRs reported during the study period were analyzed for causality by the World Health Organization-Uppsala Monitoring Centre (WHO-UMC), Naranjo's and Karch and Lasagna scales; severity by modified Hartwig and Siegel scale; predictability by Rawlins and Thompson criterion and preventability by Schumock and Thornton scale.

Methods

A single-centre, record-based analysis for the occurrence of ADRs was done among ACS patients admitted to the department of Cardiology between January and October 2017. Demographic data, comorbid conditions, reported ADRs and ADR assessment details were noted from the hospital case records and ADR monitoring centre (AMC) records. The data were analyzed and presented in a descriptive manner using percentages, mean and standard deviation. The Pearson's chi-squared test was used to ascertain the significance of the association between different groups.

Results

Out of 324 patients under evaluation, 67 had developed one or more ADRs. There were 30 different types of ADRs reported, headache being the most common. Among the drugs, heparin was the most common factor, causing 27 per cent of ADRs. Definite causality of a suspected drug causing ADRs was seen in 11.9 (n=8), nine (n=6) and 7.5 (n=5) per cent cases as per WHO-UMC, Naranjo (Naranjo algorithm) and Karch and Lasagna scales, respectively. In the severity of ADRs, the most severe reactions according to the modified Hartwig-Siegel scale (level 4a in our study) were seen in 17.5 (n=12) per cent of patients, and the rest were either level 2 or 3 reactions. Nearly 92.5 (n=62) per cent of reactions were predictable according to the Rawlins and Thompson criterion. Application of the modified Schumock-Thornton scale showed that 22.4 per cent of ACS patients had preventable reactions, and the rest were not preventable.

Interpretation & conclusions

The study results suggest that ADRs are relatively common among ACS patients. Most of these can be identified and assessed for causality, severity, predictability and preventability using various available scales. Diligent pharmacovigilance for identifying and assessing ADRs may help manage and mitigate morbidity associated with these in high-risk ACS patients.