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Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation
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Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Pharmacology".

Deadline for manuscript submissions: closed (20 September 2024) | Viewed by 32590

Special Issue Editor

Dr. Jacques Turgeon

E-Mail Website
Guest Editor
1.GalenusRx, Orlando, FL, USA
2. Faculty of Pharmacy, Université de Montréal, Montréal, QC H3C 3J7, Canada
Interests: drug metabolism; multi-drug interactions; clinical decision support systems; drug safety; drug-induced long QT syndrome
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Medicines, whether they are small molecules, natural products, or biologics used to treat various diseases and conditions, inherently possess not only desired and expected effects but also, to a certain degree, unexpected and unwanted side-effects. The monitoring of the efficacy and toxicity of medicines within our armamentarium is at the heart of pharmacovigilance programs. Through pharmacovigilance programs, we can detect, assess, understand, and prevent adverse effects related to any medicine. Pharmacovigilance programs monitor medicine effectiveness, efficacy and safety not just under controlled product development conditions, but under real-world situations as well, i.e., in patients within their individualized environment and exposure to different food products, with their various diseases, treated with multiple drugs, history of allergies, ethnicity, preferences, use of recreational drugs, alcohol and tobacco, etc. One of the drawbacks of pharmacovigilance programs is the necessary exposure of patients to medicine and their side-effects. Today, would it be possible to develop new ways to assess medicine safety without exposing many patients to medicines? What are the tools and technologies available such as simulation studies, artificial intelligence, virtual trials, pharmacogenomics, or real-world databases that we could take advantage of and use to better predict drug safety? How could we better predict drug interactions, drug–food interactions, drug–disease interactions, drug–gene interactions, and drug–drug–gene interactions. The objective of this Special Issue, entitled “Pharmacovigilance in Drug-Therapy: Drug–Drug Interactions and Safety Evaluation”, is to collect a series of publications that would better inform the scientific community and the public about medication safety.

As the editor of this Special Issue in Pharmaceutics, I hope that you will accept my invitation to contribute to an original paper.

Sincerely,

Dr. Jacques Turgeon
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceuticals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • pharmacovigilance
  • multi-drug interactions
  • clinical decision support systems
  • drug safety
  • drug side-effects
  • drug–drug interactions

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Published Papers (10 papers)

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22 pages, 1432 KiB  
Article
Individual Pharmacotherapy Management (IPM-II) for Patient and Drug Safety in Polypharmacy via Clinical Electronic Health Record Is Associated with Significant Fall Prevention
by Ursula Wolf, Luise Drewas, Hassan Ghadir, Christian Bauer, Lars Becherer, Karl-Stefan Delank and Rüdiger Neef
Pharmaceuticals 2024, 17(12), 1587; https://doi.org/10.3390/ph17121587 - 25 Nov 2024
Viewed by 1832
Abstract
Background/Objectives: Falls and fractures are emerging as a near-pandemic and major global health concern, placing an enormous burden on ageing patients and public health economies. Despite the high risk of polypharmacy in the elderly patients, falls are usually attributed to age-related changes. For [...] Read more.
Background/Objectives: Falls and fractures are emerging as a near-pandemic and major global health concern, placing an enormous burden on ageing patients and public health economies. Despite the high risk of polypharmacy in the elderly patients, falls are usually attributed to age-related changes. For the “Individual Pharmacotherapy Management (IPM)” established at the University Hospital Halle, the IPM medication adjustments and their association with in-hospital fall prevention were analysed. Methods: On the basis of the most updated digital overall patient view via his inpatient electronic health record (EHR), IPM adapts each drug’s Summary of Product Characteristics to the patient’s condition. A retrospective pre-post intervention study in geriatric traumatology on ≥70 years old patients compared 200 patients before IPM implementation (CG) with 204 patients from the IPM intervention period (IG) for the entire medication list, organ, cardiovascular and vital functions and fall risk parameters. Results: Statistically similar baseline data allowed a comparison of the average 80-year-old patient with a mean of 11.1 ± 4.9 (CG) versus 10.4 ± 3.6 (IG) medications. The IPM adjusted for drug-drug interactions, drug-disease interactions, overdoses, anticholinergic burden, adverse drug reactions, esp. from opioids inducing increased intrasynaptic serotonin, psychotropic drugs, benzodiazepines, contraindications and missing prescriptions. IPM was associated with a significant reduction in in-hospital falls from 18 (9%) in CG to 3 (1.5%) in IG, a number needed to treat of 14, relative risk reduction 83%, OR 0.17 [95% CI 0.04; 0.76], p = 0.021 in multivariable regression analysis. Factors associated with falls were antipsychotics, digitoxin, corticosteroids, Würzburg pain drip (combination of tramadol, metamizole, metoclopramide), head injury, cognitive impairment and aspects of the Huhn Fall Risk Scale including urinary catheter. Conclusion: The results indicate medication risks constitute a major iatrogenic cause of falls in this population and support the use of EHR-based IPM in standard care for the prevention of falls in the elderly and for patient and drug safety. In terms of global efforts, IPM contributes to the running WHO and United Nations Decade of Healthy Ageing (2021–2030). Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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27 pages, 1397 KiB  
Article
Analysis of Adverse Reactions Associated with the Use of Crataegus-Containing Herbal Products
by Herman J. Woerdenbag, Melissa Ursidae, Corine Ekhart, Martina Schmidt, Annabella Vitalone and Florence P. A. M. van Hunsel
Pharmaceuticals 2024, 17(11), 1490; https://doi.org/10.3390/ph17111490 - 6 Nov 2024
Cited by 1 | Viewed by 2256
Abstract
Background/Objectives: Products from various parts of Crataegus species are traditionally applied as a cardiotonic. In Europe and the USA, mainly Crataegus monogyna Jacq. (Lindm.) and Crataegus laevigata (Poir.) DC (synonym Crataegus oxyacantha L.) are used, but worldwide, other Crataegus species are also used. [...] Read more.
Background/Objectives: Products from various parts of Crataegus species are traditionally applied as a cardiotonic. In Europe and the USA, mainly Crataegus monogyna Jacq. (Lindm.) and Crataegus laevigata (Poir.) DC (synonym Crataegus oxyacantha L.) are used, but worldwide, other Crataegus species are also used. Phytotherapeutic preparations with a standardised content of flavonoids and/or oligomeric procyanidins are commercially available. The products are generally considered as safe and are at most associated with minor and atypical adverse reactions. The aim of this study was to critically assess the information about the safety of Crataegus-containing products in humans. Methods: A scoping review of the literature about adverse reactions associated with Crataegus-containing products was performed. Next, individual case safety reports (ICSRs) were assessed, which were included in VigiBase (the World Health Organisation’s global database of adverse event reports for medicines and vaccines) and in the database of the Netherlands Pharmacovigilance Centre Lareb. The findings are discussed in relation to the literature. Results: The scoping review yielded 23 clinical studies with single-herb and 14 with multi-herb preparations, from which only a few minor gastrointestinal and cardiac events had been reported. A total of 1527 reports from VigiBase, from 1970 to 2023, were analysed, as well as 13 reports from Lareb. The most frequently reported adverse reactions belonged to the system organ classes ‘gastrointestinal disorders’, ‘skin and subcutaneous tissue disorders’, ‘general disorders and administration site conditions’, ‘cardiac disorders’ or ‘nervous system disorders’. In 277 reports of VigiBase, a single-herb product was the only suspect for causing the adverse reaction(s). Of these, 12.6% were graded as serious. Conclusions: The results of our study provide deeper insight in the adverse reaction profile of Crataegus-containing products and should contribute to their safe application in the treatment of less severe forms of cardiac failure. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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19 pages, 1345 KiB  
Article
Adverse Event Profiles of Adalimumab in Children: A Disproportionality Analysis
by Wenting Zhang, Ziqi Xu, Yamin Shu, Sainan Shu and Qilin Zhang
Pharmaceuticals 2024, 17(8), 1028; https://doi.org/10.3390/ph17081028 - 5 Aug 2024
Cited by 4 | Viewed by 2037
Abstract
Background: Adalimumab has been approved by the U.S. Food and Drug Administration (FDA) for the treatment of adult rheumatoid arthritis (RA), and subsequently approved for pediatric treatment of various autoimmune diseases in children of different ages. Due to genetic differences between children and [...] Read more.
Background: Adalimumab has been approved by the U.S. Food and Drug Administration (FDA) for the treatment of adult rheumatoid arthritis (RA), and subsequently approved for pediatric treatment of various autoimmune diseases in children of different ages. Due to genetic differences between children and adults in terms of physiology and immunity, there is a need to explore the safety of adalimumab in children in the real world. The aim of this study is to identify potential adverse event (AE) signals associated with the use of adalimumab in pediatric patients (<18 years old) using data from the FDA Adverse Event Reporting System (FAERS). Methods: AEs associated with adalimumab in pediatric patients reported in the FAERS database from the first quarter (Q1) of 2017 to the third quarter (Q3) of 2022 were systematically gathered. Reporting odds ratio (ROR), the proportional reporting ratio (PRR), the information component (IC), and the empirical Bayes geometric mean (EBGM) were used to assess the relationship between adalimumab and AEs in children. Results: Out of 8,363,304 reports collected from the FAERS database during the study period, 3819 reports on children on adalimumab were identified. Adalimumab-related AEs reports were concentrated on 10 toxicity areas and a total of 202 positive signals were detected, of which injection site papule (ROR = 261.97) and intestinal fistula (ROR = 122.09) had the strongest signals. Unexpected significant AEs, including intestinal obstruction, immunodeficiency, abdominal abscess, and Takayasu’s arteritis might also occur. In comparison with patients of all ages in the same time window, the median onset time of children was shorter (99 vs. 149 days). Most of the AE cases occurred in children within the first 1 (1.71%), 2 (8.12%), and 3 months (8.39%) and had early failure types after adalimumab initiation. Methotrexate, folic acid, prednisone, azathioprine, and mesalamine were the top five drugs used concomitantly for adalimumab-associated AEs. Conclusions: When adalimumab is used in children, especially in the first 3 months of treatment, in addition to the AEs recorded in the drug package insert, close attention should be paid to the new potential AEs off-label to ensure the safety of adalimumab in children. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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19 pages, 903 KiB  
Article
Survey of Potential Drug Interactions, Use of Non-Medical Health Products, and Immunization Status among Patients Receiving Targeted Therapies
by Réka Rajj, Nóra Schaadt, Katalin Bezsila, Orsolya Balázs, Marcell B. Jancsó, Milán Auer, Dániel B. Kiss, András Fittler, Anna Somogyi-Végh, István G. Télessy, Lajos Botz and Róbert Gy. Vida
Pharmaceuticals 2024, 17(7), 942; https://doi.org/10.3390/ph17070942 - 14 Jul 2024
Viewed by 1993
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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18 pages, 2267 KiB  
Article
Descriptive Analysis of Adverse Events Reported for New Multiple Myeloma Medications Using FDA Adverse Event Reporting System (FAERS) Databases from 2015 to 2022
by Marwan A. Alrasheed, Khalid A. Alamer, Mashael Albishi, Abdulrahman A. Alsuhibani, Omar A. Almohammed, Abdulrahman Alwhaibi, Abdullah N. Almajed and Jeff J. Guo
Pharmaceuticals 2024, 17(7), 815; https://doi.org/10.3390/ph17070815 - 21 Jun 2024
Viewed by 2130
Abstract
Background: New multiple myeloma (MM) medications have revolutionized the treatment landscape, but they are also associated with a range of adverse events (AEs). This study aims to provide a comprehensive overview of AEs reported for four new MM medications: daratumumab, ixazomib, elotuzumab, and [...] Read more.
Background: New multiple myeloma (MM) medications have revolutionized the treatment landscape, but they are also associated with a range of adverse events (AEs). This study aims to provide a comprehensive overview of AEs reported for four new MM medications: daratumumab, ixazomib, elotuzumab, and panobinostat. Methods: This study uses a descriptive retrospective approach to analyze the FDA Adverse Event Reporting System (FAERS) from 2015 to 2022. It includes variables like medication names, report details, patient demographics, adverse events, and reporter types. The initial dataset consists of over 3700 adverse events, which are categorized into 21 groups for clarity and comparison. Results: The FAERS database revealed 367,756 adverse events (AEs) associated with novel multiple myeloma drugs from 2015–2022. Ixazomib had the highest number of reported AEs with 206,243 reports, followed by daratumumab with 98,872 reports, then elotuzumab with 26,193 AEs. Ixazomib’s AE reports increased dramatically over the study period, rising approximately 51-fold from 1183 in 2015 to 60,835 in 2022. Of the medications studied, ixazomib also recorded the highest number of deaths (24,206), followed by daratumumab (11,624), panobinostat (7227), and elotuzumab (3349). The majority of AEs occurred in patients aged 55–64 and 65–74 years. Conclusions: Ixazomib, a new MM medication, had the highest number of AEs reported. Also, it has the highest rate of reported deaths compared to other new MM medications. Clinicians should be aware of the potential AEs associated with this medication and further research is needed to understand the reasons for the high number of AEs and to develop mitigation strategies. More attention should also be paid to the safety of new multiple myeloma medications in younger patients. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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14 pages, 936 KiB  
Article
Pharmacovigilance Practices by Healthcare Providers in Oncology: A Cross-Sectional Study
by Hadeel Alkofide, Haya M. Almalag, Mashael Alromaih, Lama Alotaibi, Njoud Altuwaijri, Noha Al Aloola, Jawza F. Alsabhan, Ghada A. Bawazeer, Lobna Al Juffali, Rihaf Alfaraj, Nora Alkhudair, Raniah Aljadeed, Rana Aljadeed and Lamya S. Alnaim
Pharmaceuticals 2024, 17(6), 683; https://doi.org/10.3390/ph17060683 - 26 May 2024
Viewed by 2551
Abstract
Investigating pharmacovigilance (PV) practices among oncology healthcare providers (HCPs) is crucial for patient safety in oncology settings. This study aimed to assess the awareness, attitudes, and practices towards PV and identify barriers to effective adverse drug reaction (ADR) reporting for HCPs working in [...] Read more.
Investigating pharmacovigilance (PV) practices among oncology healthcare providers (HCPs) is crucial for patient safety in oncology settings. This study aimed to assess the awareness, attitudes, and practices towards PV and identify barriers to effective adverse drug reaction (ADR) reporting for HCPs working in oncology-related settings. Employing a cross-sectional survey design, we collected data from 65 HCPs, focusing on their experiences with ADR reporting, education on ADR management, and familiarity with PV protocols. The results showed that about half of the responders were pharmacists. Around 58.9% of the respondents reported ADRs internally, and 76.9% had received some form of ADR-related education. However, only 38.5% were aware of formal ADR review procedures. Methotrexate and paclitaxel emerged as the drugs most frequently associated with ADRs. The complexity of cancer treatments was among the common reasons for the low reporting of ADRs by the study participants. The findings highlight the need for enhanced PV education and standardized reporting mechanisms to improve oncology care. We conclude that reinforcing PV training and streamlining ADR-reporting processes are critical to optimizing patient outcomes and safety in oncology, advocating for targeted educational interventions and the development of unified PV guidelines. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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19 pages, 1320 KiB  
Article
An Assessment of Different Decision Support Software from the Perspective of Potential Drug–Drug Interactions in Patients with Chronic Kidney Diseases
by Muhammed Yunus Bektay, Aysun Buker Cakir, Meltem Gursu, Rumeyza Kazancioglu and Fikret Vehbi Izzettin
Pharmaceuticals 2024, 17(5), 562; https://doi.org/10.3390/ph17050562 - 28 Apr 2024
Cited by 1 | Viewed by 2213
Abstract
Chronic kidney disease (CKD) is a multifaceted disorder influenced by various factors. Drug–drug interactions (DDIs) present a notable risk factor for hospitalization among patients with CKD. This study aimed to assess the frequency and attributes of potential DDIs (pDDIs) in patients with CKD [...] Read more.
Chronic kidney disease (CKD) is a multifaceted disorder influenced by various factors. Drug–drug interactions (DDIs) present a notable risk factor for hospitalization among patients with CKD. This study aimed to assess the frequency and attributes of potential DDIs (pDDIs) in patients with CKD and to ascertain the concordance among different Clinical Decision Support Software (CDSS). A cross-sectional study was conducted in a nephrology outpatient clinic at a university hospital. The pDDIs were identified and evaluated using Lexicomp® and Medscape®. The patients’ characteristics, comorbidities, and medicines used were recorded. The concordance of different CDSS were evaluated using the Kendall W coefficient. An evaluation of 1121 prescribed medications for 137 patients was carried out. The mean age of the patients was 64.80 ± 14.59 years, and 41.60% of them were male. The average year with CKD was 6.48 ± 5.66. The mean number of comorbidities was 2.28 ± 1.14. The most common comorbidities were hypertension, diabetes, and coronary artery disease. According to Medscape, 679 pDDIs were identified; 1 of them was contraindicated (0.14%), 28 (4.12%) were serious-use alternative, and 650 (9.72%) were interventions that required closely monitoring. According to Lexicomp, there were 604 drug–drug interactions. Of these interactions, 9 (1.49%) were in the X category, 60 (9.93%) were in the D category, and 535 (88.57%) were in the C category. Two different CDSS systems exhibited statistically significant concordance with poor agreement (W = 0.073, p < 0.001). Different CDSS systems are commonly used in clinical practice to detect pDDIs. However, various factors such as the operating principles of these programs and patient characteristics can lead to incorrect guidance in clinical decision making. Therefore, instead of solely relying on programs with lower reliability and consistency scores, multidisciplinary healthcare teams, including clinical pharmacists, should take an active role in identifying and preventing pDDIs. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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12 pages, 706 KiB  
Article
Serious Safety Signals and Prediction Features Following COVID-19 mRNA Vaccines Using the Vaccine Adverse Event Reporting System
by Jung Yoon Choi, Yongjoon Lee, Nam Gi Park, Mi Sung Kim and Sandy Jeong Rhie
Pharmaceuticals 2024, 17(3), 356; https://doi.org/10.3390/ph17030356 - 10 Mar 2024
Cited by 1 | Viewed by 6425
Abstract
We aimed to analyze the characteristics of serious adverse events following immunizations (AEFIs) to identify potential safety information and prediction features. We screened the individual case safety reports (ICSRs) in adults who received mRNA-based COVID-19 vaccines using the Vaccine Adverse Event Reporting System [...] Read more.
We aimed to analyze the characteristics of serious adverse events following immunizations (AEFIs) to identify potential safety information and prediction features. We screened the individual case safety reports (ICSRs) in adults who received mRNA-based COVID-19 vaccines using the Vaccine Adverse Event Reporting System until December 2021. We identified the demographic and clinical characteristics of ICSRs and performed signal detection. We developed prediction models for serious AEFIs and identified the prognostic features using logistic regression. Serious ICSRs and serious AEFIs were 51,498 and 271,444, respectively. Hypertension was the most common comorbidity (22%). Signal detection indicated that the reporting odds ratio of acute myocardial infarction (AMI) was more than 10 times. Those who had experienced myocardial infarction (MI) were 5.7 times more likely to suffer from MI as an AEFI (95% CI 5.28–6.71). Moreover, patients who had atrial fibrillation (AF), acute kidney injury (AKI), cardiovascular accident (CVA), or pulmonary embolism (PE) were 7.02 times, 39.09 times, 6.03 times, or 3.97 times more likely to suffer from each AEFI, respectively. Our study suggests that vaccine recipients who had experienced MI, AF, AKI, CVA, or PE could require further evaluation and careful monitoring to prevent those serious AEFIs. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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16 pages, 1192 KiB  
Article
Antipsychotics and Risks of Cardiovascular and Cerebrovascular Diseases and Mortality in Dwelling Community Older Adults
by Sylvie Perreault, Laurie-Anne Boivin Proulx, Judith Brouillette, Stéphanie Jarry and Marc Dorais
Pharmaceuticals 2024, 17(2), 178; https://doi.org/10.3390/ph17020178 - 30 Jan 2024
Cited by 6 | Viewed by 4555
Abstract
This study aims to investigate the effect of antipsychotic agents on cardiovascular and cerebrovascular diseases (CVD/CEV) and mortality risks in the older population living in a community. A cohort of 42,650 new users of antipsychotic agents was built using Quebec healthcare databases (1998–2011). [...] Read more.
This study aims to investigate the effect of antipsychotic agents on cardiovascular and cerebrovascular diseases (CVD/CEV) and mortality risks in the older population living in a community. A cohort of 42,650 new users of antipsychotic agents was built using Quebec healthcare databases (1998–2011). The outcomes were CVD/CEV and mortality incidence in 5 years of follow-up in the total cohort, sub-cohort of patients with no schizophrenia/dementia, sub-cohort with schizophrenia, and sub-cohort with dementia. Comparisons were made between the new users who continued the treatment (adherent level ≥ 60%) vs. those ceasing treatment (adherence level < 60%) using inverse probability of treatment weighting and Cox models. Comparing high adherence vs. low levels, CVD/CEV risk was increased by 36% in the sub-cohort with schizophrenia for atypical antipsychotic users and by 25% in the sub-cohort with dementia for typical antipsychotic users. An increasing mortality risk of 2- to 3-fold was linked with the typical antipsychotic use in all cohorts except the sub-cohort with schizophrenia; in addition, mortality risk is linked with the use of high vs. low doses. Antipsychotics were not linked with CVD/CEV risk, except for atypical antipsychotics in patients with schizophrenia and typical antipsychotics in patients with dementia. The mortality risk was linked with the use of typical antipsychotics and the dose used. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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22 pages, 537 KiB  
Systematic Review
Machine Learning Techniques for Predicting Drug-Related Side Effects: A Scoping Review
by Esmaeel Toni, Haleh Ayatollahi, Reza Abbaszadeh and Alireza Fotuhi Siahpirani
Pharmaceuticals 2024, 17(6), 795; https://doi.org/10.3390/ph17060795 - 17 Jun 2024
Cited by 6 | Viewed by 4695
Abstract
Background: Drug safety relies on advanced methods for timely and accurate prediction of side effects. To tackle this requirement, this scoping review examines machine-learning approaches for predicting drug-related side effects with a particular focus on chemical, biological, and phenotypical features. Methods: This was [...] Read more.
Background: Drug safety relies on advanced methods for timely and accurate prediction of side effects. To tackle this requirement, this scoping review examines machine-learning approaches for predicting drug-related side effects with a particular focus on chemical, biological, and phenotypical features. Methods: This was a scoping review in which a comprehensive search was conducted in various databases from 1 January 2013 to 31 December 2023. Results: The results showed the widespread use of Random Forest, k-nearest neighbor, and support vector machine algorithms. Ensemble methods, particularly random forest, emphasized the significance of integrating chemical and biological features in predicting drug-related side effects. Conclusions: This review article emphasized the significance of considering a variety of features, datasets, and machine learning algorithms for predicting drug-related side effects. Ensemble methods and Random Forest showed the best performance and combining chemical and biological features improved prediction. The results suggested that machine learning techniques have some potential to improve drug development and trials. Future work should focus on specific feature types, selection techniques, and graph-based methods for even better prediction. Full article
(This article belongs to the Special Issue Pharmacovigilance in Drug Therapy: Drug–Drug Interactions and Safety Evaluation)
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