How intervention studies measure the effectiveness of medication safety-related clinical decision support systems in primary and long-term care: a systematic review.

BACKGROUND: Medication errors and associated adverse drug events (ADE) are a major cause of morbidity and mortality worldwide. In recent years, the prevention of medication errors has become a high priority in healthcare systems. In order to improve medication safety, computerized Clinical Decision Support Systems (CDSS) are increasingly being integrated into the medication process. Accordingly, a growing number of studies have investigated the medication safety-related effectiveness of CDSS. However, the outcome measures used are heterogeneous, leading to unclear evidence. The primary aim of this study is to summarize and categorize the outcomes used in interventional studies evaluating the effects of CDSS on medication safety in primary and long-term care. METHODS: We systematically searched PubMed, Embase, CINAHL, and Cochrane Library for interventional studies evaluating the effects of CDSS targeting medication safety and patient-related outcomes. We extracted methodological characteristics, outcomes and empirical findings from the included studies. Outcomes were assigned to three main categories: process-related, harm-related, and cost-related. Risk of bias was assessed using the Evidence Project risk of bias tool. RESULTS: Thirty-two studies met the inclusion criteria. Almost all studies (n = 31) used process-related outcomes, followed by harm-related outcomes (n = 11). Only three studies used cost-related outcomes. Most studies used outcomes from only one category and no study used outcomes from all three categories. The definition and operationalization of outcomes varied widely between the included studies, even within outcome categories. Overall, evidence on CDSS effectiveness was mixed. A significant intervention effect was demonstrated by nine of fifteen studies with process-related primary outcomes (60%) but only one out of five studies with harm-related primary outcomes (20%). The included studies faced a number of methodological problems that limit the comparability and generalizability of their results. CONCLUSIONS: Evidence on the effectiveness of CDSS is currently inconclusive due in part to inconsistent outcome definitions and methodological problems in the literature. Additional high-quality studies are therefore needed to provide a comprehensive account of CDSS effectiveness. These studies should follow established methodological guidelines and recommendations and use a comprehensive set of harm-, process- and cost-related outcomes with agreed-upon and consistent definitions. PROSPERO REGISTRATION: CRD42023464746.

Association of Pharmacist Interventions With Adverse Drug Events and Potential Adverse Drug Events.

BACKGROUND: Adverse drug events (ADEs) are a frequent cause of injury in patients. Our aim was to assess whether pharmacist interventions compared with no pharmacist intervention results in reduced ADEs and potential adverse drug events (PADEs). METHODS: We searched MEDLINE, Embase, and two other databases through September 19, 2022 for any RCT assessing the effect of a pharmacist intervention compared with no pharmacist intervention and reporting on ADEs or PADEs. The risk of bias was assessed using the Cochrane tool for RCTs. A random-effects model was used to pool summary results from individual RCTs. RESULTS: Fifteen RCTs met the inclusion criteria. The pooled results showed a statistically significant reduction in ADE associated with pharmacist intervention compared with no pharmacist intervention (RR = 0.86; [95% CI 0.80-0.94]; p = 0.0005) but not for PADEs (RR = 0.79; [95% CI 0.47-1.32]; p = 0.37). The heterogeneity was insignificant (I2 = 0%) for ADEs and substantial (I2 = 77%) for PADEs. Patients receiving a pharmacist intervention were 14% less likely for ADE than those who did not receive a pharmacist intervention. The estimated number of patients needed to prevent one ADE across all patient locations was 33. CONCLUSIONS: To our knowledge, this is the first systematic review and meta-analysis of RCTs seeking to understand the association of pharmacist interventions with ADEs and PADEs. The risk of having an ADE is reduced by a seventh for patients receiving a pharmacist care intervention versus no such intervention. The estimated number of patients needed to be followed across all patient locations to prevent one preventable ADE across all patient locations is 33.

Advancing medical imaging: detecting polypharmacy and adverse drug effects with Graph Convolutional Networks (GCN).

Polypharmacy involves an individual using many medications at the same time and is a frequent healthcare technique used to treat complex medical disorders. Nevertheless, it also presents substantial risks of negative medication responses and interactions. Identifying and addressing adverse effects caused by polypharmacy is crucial to ensure patient safety and improve healthcare results. This paper introduces a new method using Graph Convolutional Networks (GCN) to identify polypharmacy side effects. Our strategy involves developing a medicine interaction graph in which edges signify drug-drug intuitive predicated on pharmacological properties and hubs symbolize drugs. GCN is a well-suited profound learning procedure for graph-based representations of social information. It can be used to anticipate the probability of medicate unfavorable impacts and to memorize important representations of sedate intuitive. Tests were conducted on a huge dataset of patients' pharmaceutical records commented on with watched medicate unfavorable impacts in arrange to approve our strategy. Execution of the GCN show, which was prepared on a subset of this dataset, was evaluated through a disarray framework. The perplexity network shows the precision with which the show categories occasions. Our discoveries demonstrate empowering advance within the recognizable proof of antagonistic responses related with polypharmaceuticals. For cardiovascular system target drugs, GCN technique achieved an accuracy of 94.12%, precision of 86.56%, F1-Score of 88.56%, AUC of 89.74% and recall of 87.92%. For respiratory system target drugs, GCN technique achieved an accuracy of 93.38%, precision of 85.64%, F1-Score of 89.79%, AUC of 91.85% and recall of 86.35%. And for nervous system target drugs, GCN technique achieved an accuracy of 95.27%, precision of 88.36%, F1-Score of 86.49%, AUC of 88.83% and recall of 84.73%. This research provides a significant contribution to pharmacovigilance by proposing a data-driven method to detect and reduce polypharmacy side effects, thereby increasing patient safety and healthcare decision-making.

Monitoring Adverse Drug Events in Web Forums: Evaluation of a Pipeline and Use Case Study.

BACKGROUND: To mitigate safety concerns, regulatory agencies must make informed decisions regarding drug usage and adverse drug events (ADEs). The primary pharmacovigilance data stem from spontaneous reports by health care professionals. However, underreporting poses a notable challenge within the current system. Explorations into alternative sources, including electronic patient records and social media, have been undertaken. Nevertheless, social media's potential remains largely untapped in real-world scenarios. OBJECTIVE: The challenge faced by regulatory agencies in using social media is primarily attributed to the absence of suitable tools to support decision makers. An effective tool should enable access to information via a graphical user interface, presenting data in a user-friendly manner rather than in their raw form. This interface should offer various visualization options, empowering users to choose representations that best convey the data and facilitate informed decision-making. Thus, this study aims to assess the potential of integrating social media into pharmacovigilance and enhancing decision-making with this novel data source. To achieve this, our objective was to develop and assess a pipeline that processes data from the extraction of web forum posts to the generation of indicators and alerts within a visual and interactive environment. The goal was to create a user-friendly tool that enables regulatory authorities to make better-informed decisions effectively. METHODS: To enhance pharmacovigilance efforts, we have devised a pipeline comprising 4 distinct modules, each independently editable, aimed at efficiently analyzing health-related French web forums. These modules were (1) web forums' posts extraction, (2) web forums' posts annotation, (3) statistics and signal detection algorithm, and (4) a graphical user interface (GUI). We showcase the efficacy of the GUI through an illustrative case study involving the introduction of the new formula of Levothyrox in France. This event led to a surge in reports to the French regulatory authority. RESULTS: Between January 1, 2017, and February 28, 2021, a total of 2,081,296 posts were extracted from 23 French web forums. These posts contained 437,192 normalized drug-ADE couples, annotated with the Anatomical Therapeutic Chemical (ATC) Classification and Medical Dictionary for Regulatory Activities (MedDRA). The analysis of the Levothyrox new formula revealed a notable pattern. In August 2017, there was a sharp increase in posts related to this medication on social media platforms, which coincided with a substantial uptick in reports submitted by patients to the national regulatory authority during the same period. CONCLUSIONS: We demonstrated that conducting quantitative analysis using the GUI is straightforward and requires no coding. The results aligned with prior research and also offered potential insights into drug-related matters. Our hypothesis received partial confirmation because the final users were not involved in the evaluation process. Further studies, concentrating on ergonomics and the impact on professionals within regulatory agencies, are imperative for future research endeavors. We emphasized the versatility of our approach and the seamless interoperability between different modules over the performance of individual modules. Specifically, the annotation module was integrated early in the development process and could undergo substantial enhancement by leveraging contemporary techniques rooted in the Transformers architecture. Our pipeline holds potential applications in health surveillance by regulatory agencies or pharmaceutical companies, aiding in the identification of safety concerns. Moreover, it could be used by research teams for retrospective analysis of events.

Using electronic health records for clinical pharmacology research: Challenges and considerations.

Electronic health records (EHRs) contain a vast array of phenotypic data on large numbers of individuals, often collected over decades. Due to the wealth of information, EHR data have emerged as a powerful resource to make first discoveries and identify disparities in our healthcare system. While the number of EHR-based studies has exploded in recent years, most of these studies are directed at associations with disease rather than pharmacotherapeutic outcomes, such as drug response or adverse drug reactions. This is largely due to challenges specific to deriving drug-related phenotypes from the EHR. There is great potential for EHR-based discovery in clinical pharmacology research, and there is a critical need to address specific challenges related to accurate and reproducible derivation of drug-related phenotypes from the EHR. This review provides a detailed evaluation of challenges and considerations for deriving drug-related data from EHRs. We provide an examination of EHR-based computable phenotypes and discuss cutting-edge approaches to map medication information for clinical pharmacology research, including medication-based computable phenotypes and natural language processing. We also discuss additional considerations such as data structure, heterogeneity and missing data, rare phenotypes, and diversity within the EHR. By further understanding the complexities associated with conducting clinical pharmacology research using EHR-based data, investigators will be better equipped to design thoughtful studies with more reproducible results. Progress in utilizing EHRs for clinical pharmacology research should lead to significant advances in our ability to understand differential drug response and predict adverse drug reactions.

[Risk management with regard to QT-prolonging drugs]. / Risicomanagement rond QT-verlengende geneesmiddelen.

Drug-induced QT prolongation increases the risk of Torsade de Pointes (TdP). Drug-induced QT prolongation is a complex and unpredictable system due to many uncertainties. Risk factors such as electrolyte disturbances, heart failure and genetics play an important role in estimating the effect on QT prolongation. Moreover, the degree of QT prolongation is not always directly related to the risk of TdP and the assessment of the QT-interval is variable depending on the type and timing of QT measurement. Therefore, the variation in QT measurement may be larger than the effect of certain drugs on the QT interval. Because of the potentially lethal risk, several measures are undertaken to reduce the risk of QT prolongation and TdP, while their effect and proportionality are unclear. We suggest we should be less stringent in certain settings when risk of TdP is extremely low given the limited availability of our resources.

Doses Evaluated in Clinical Pharmacology Studies Investigating the Effect of Intrinsic and Extrinsic Factors on PK and Safety: Case Examples from Approved Drug Development Programs.

Dose selection for investigations of intrinsic and extrinsic factors of pharmacokinetic variability as well as safety is a challenging question in the early clinical stage of drug development. The dose of an investigational product is chosen considering the compound information available to date, feasibility of the assessments, regulatory requirements, and the intent to maximize information for later regulatory submission. This review selected 37 programs as case examples of recently approved drugs to explore the doses selected with focus on studies of drug interaction, renal and hepatic impairment, food effect and concentration-QTc assessment.The review found that regulatory agencies may consider alternative approaches if justified and safe as illustrated in these examples. It is thus recommendable to use the first in human trial as an opportunity to assess QT-prolongation and drug interactions using probes or endogenous markers while maximizing the DDI potential, increasing sensitivity and ensuring safety. Early understanding of dose proportionality assists dose finding and simple and fast to conduct DDI study designs are advantageous. Single dose impairment studies despite non-proportional/time-dependent PK are often acceptability.Overall, the early understanding of the drug's safety profile is essential to ensure the safety of doses selected while preventing clinical trials with unnecessary exposure when using high doses or multiple doses. The information collected in this retrospective survey is a good reminder to tailor the early clinical program to the profile and needs of the molecule and consider regulatory opportunities to streamline the development path.

[Prevention of drug iatrogenicity]. / Prévention de la «iatrogénie médicamenteuse¼.

Adverse events related to drug therapy are a major cause of iatrogenicity. They are responsible of increased morbidity, leading to hospitalization, sometimes in emergency, and mortality, not only in ambulatory care but also during hospitalization itself. Causes are multiple : among them, confusion leading to an erroneous drug administration, mistakes regarding dosage, risks associated to self-medication, drug-drug interactions or even food-drug interactions. Elderly population is exposed to an increased incidence of drug iatrogenicity because older patients cumulate numerous risk factors, especially polypharmacy and cognitive disorders. Prevention of drug iatrogenicity is a key objective from a public health point of view. Preventive measures should target the prescriber (physician), the dispenser (pharmacist), the user (patient) and the supplier (pharmaceutical industry).

Les manifestations indésirables liées à la prise des médicaments représentent une cause non négligeable d'iatrogénie. Elles sont responsables d'une morbidité, amenant des hospitalisations parfois en urgence, voire d'une mortalité, non seulement en ambulatoire mais aussi au sein même de l'hôpital. Les causes sont multiples. Citons, notamment, la confusion aboutissant à la prise d'un médicament erroné, les erreurs dans la posologie, les risques liés à l'auto-médication, les interactions médicamenteuses, ou encore, les interactions aliments- médicaments. La population âgée est particulièrement exposée car elle cumule nombre de facteurs de risque, dont la polymédication et les troubles cognitifs. La prévention de la iatrogénie médicamenteuse est donc un objectif prioritaire dans le domaine de la pharmacothérapie. Les mesures préventives devraient cibler le prescripteur (médecin), le délivreur (pharmacien), l'utilisateur (patient) et le fournisseur (industrie pharmaceutique).

Assessing the benefit-risk balance of drugs. Some lessons from the COVID pandemic.

INTRODUCTION: Drug efficacy and effectiveness are assessed respectively through clinical trials and pharmaco-epidemiological studies. However, relative and absolute benefits of drugs are distinct measures that must be considered in relation to the baseline risk of disease incidence, complication or progression. On the other hand, adverse drug reactions are independent of the basic risk but depend on the characteristics of the population treated. Given these prerequisites, how can we balance the benefits and risks of drugs? AREAS COVERED: We use the example of therapeutics evaluated during Covid to describe how assessing the benefit-risk balance of drugs is a complex process. EXPERT OPINION: Clinical trials are not designed to identify rare adverse events, underscoring the necessity for a pharmacovigilance system. Evaluating the balance between the benefits and risks of drugs is an ongoing process, demanding the simultaneous analysis of data from clinical trials, potential drug-drug interactions, pharmacovigilance monitoring and pharmaco-epidemiological studies, to identify potential safety concerns. In addition, pharmacologists must play a major role in educating the general public about drugs, aiding in the accurate interpretation of the benefit-risk balance and preventing misinformation.

Optimizing drug therapy for older adults: shifting away from problematic polypharmacy.

INTRODUCTION: The accelerated discovery and production of pharmaceutical products has resulted in many positive outcomes. However, this progress has also contributed to problematic polypharmacy, one of the rapidly growing threats to public health in this century. Problematic polypharmacy results in adverse patient outcomes and imposes increased strain and financial burden on healthcare systems. AREAS COVERED: A review was conducted on the current body of evidence concerning factors contributing to and consequences of problematic polypharmacy. Recent trials investigating interventions that target polypharmacy and emerging solutions, including incorporation of artificial intelligence, are also examined in this article. EXPERT OPINION: To shift away from problematic polypharmacy, a multifaceted interdisciplinary approach is necessary. Any potentially successful strategy must be adapted to suit various healthcare settings and must utilize all available resources, including artificial intelligence.

Deprescribing: An umbrella review.

This umbrella review examined systematic reviews of deprescribing studies by characteristics of intervention, population, medicine, and setting. Clinical and humanistic outcomes, barriers and facilitators, and tools for deprescribing are presented. The Medline database was used. The search was limited to systematic reviews and meta-analyses published in English up to April 2022. Reviews reporting deprescribing were included, while those where depre-scribing was not planned and supervised by a healthcare professional were excluded. A total of 94 systematic reviews (23 meta--analyses) were included. Most explored clinical or humanistic outcomes (70/94, 74 %); less explored attitudes, facilitators, or barriers to deprescribing (17/94, 18 %); few focused on tools (8/94, 8.5 %). Reviews assessing clinical or humanistic outcomes were divided into two groups: reviews with deprescribing intervention trials (39/70, 56 %; 16 reviewing specific deprescribing interventions and 23 broad medication optimisation interventions), and reviews with medication cessation trials (31/70, 44 %). Deprescribing was feasible and resulted in a reduction of inappropriate medications in reviews with deprescribing intervention trials. Complex broad medication optimisation interventions were shown to reduce hospitalisation, falls, and mortality rates. In reviews of medication cessation trials, a higher frequency of adverse drug withdrawal events underscores the importance of prioritizing patient safety and exercising caution when stopping medicines, particularly in patients with clear and appropriate indications.

[INTERPOLAR-prospective, interventional studies as part of the Medical Informatics Initiative to improve medication therapy safety in healthcare]. / INTERPOLAR ­ prospektive, interventionelle Studien im Rahmen der Medizininformatik-Initiative zur Verbesserung der Arzneimitteltherapiesicherheit in der Krankenversorgung.

Medication analyses by ward pharmacists are an important measure of drug therapy safety (DTS). Medication-related problems (MRPs) are identified and resolved with the attending clinicians. However, staff resources for extended medication analyses and complete documentation are often limited. Until now, data required for the identification of risk patients and for an extended medication analysis often had to be collected from various parts of the institution's internal electronic medical record (EMR). This error-prone and time-consuming process is to be improved in the INTERPOLAR (INTERventional POLypharmacy-Drug interActions-Risks) project using an IT tool provided by the data integration centers (DIC).INTERPOLAR is a use case of the Medical Informatics Initiative (MII) that focuses on the topic of DTS. The planning phase took place in 2023, with routine implementation planned from 2024. DTS-relevant data from the EMR is to be presented and the documentation of MRPs in routine care is to be facilitated. The prospective multicenter, cluster-randomized INTERPOLAR­1 study serves to evaluate the benefits of IT support in routine care. The aim is to show that more MRPs can be detected and resolved with the help of IT support. For this purpose, six normal wards will be selected at each of eight university hospitals, so that 48 clusters (with a total of at least 70,000 cases) are available for randomization.

The state of the art in secondary pharmacology and its impact on the safety of new medicines.

Secondary pharmacology screening of investigational small-molecule drugs for potentially adverse off-target activities has become standard practice in pharmaceutical research and development, and regulatory agencies are increasingly requesting data on activity against targets with recognized adverse effect relationships. However, the screening strategies and target panels used by pharmaceutical companies may vary substantially. To help identify commonalities and differences, as well as to highlight opportunities for further optimization of secondary pharmacology assessment, we conducted a broad-ranging survey across 18 companies under the auspices of the DruSafe leadership group of the International Consortium for Innovation and Quality in Pharmaceutical Development. Based on our analysis of this survey and discussions and additional research within the group, we present here an overview of the current state of the art in secondary pharmacology screening. We discuss best practices, including additional safety-associated targets not covered by most current screening panels, and present approaches for interpreting and reporting off-target activities. We also provide an assessment of the safety impact of secondary pharmacology screening, and a perspective on opportunities and challenges in this rapidly developing field.

Preclinical side effect prediction through pathway engineering of protein interaction network models.

Modeling tools aim to predict potential drug side effects, although they suffer from imperfect performance. Specifically, protein-protein interaction models predict drug effects from proteins surrounding drug targets, but they tend to overpredict drug phenotypes and require well-defined pathway phenotypes. In this study, we used PathFX, a protein-protein interaction tool, to predict side effects for active ingredient-side effect pairs extracted from drug labels. We observed limited performance and defined new pathway phenotypes using pathway engineering strategies. We defined new pathway phenotypes using a network-based and gene expression-based approach. Overall, we discovered a trade-off between sensitivity and specificity values and demonstrated a way to limit overprediction for side effects with sufficient true positive examples. We compared our predictions to animal models and demonstrated similar performance metrics, suggesting that protein-protein interaction models do not need perfect evaluation metrics to be useful. Pathway engineering, through the inclusion of true positive examples and omics measurements, emerges as a promising approach to enhance the utility of protein interaction network models for drug effect prediction.

Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children (MARVEL- PIC): protocol for a national randomised controlled trial of pharmacogenomics implementation.

INTRODUCTION: DNA-informed prescribing (termed pharmacogenomics, PGx) is the epitome of personalised medicine. Despite international guidelines existing, its implementation in paediatric oncology remains sparse. METHODS AND ANALYSIS: Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children is a national prospective, multicentre, randomised controlled trial assessing the impact of pre-emptive PGx testing for actionable PGx variants on adverse drug reaction (ADR) incidence in patients with a new cancer diagnosis or proceeding to haematopoetic stem cell transplant. All ADRs will be prospectively collected by surveys completed by parents/patients using the National Cancer Institute Pediatric Patient Reported [Ped-PRO]-Common Terminology Criteria for Adverse Events (CTCAE) (weeks 1, 6 and 12). Pharmacist will assess for causality and severity in semistructured interviews using the CTCAE and Liverpool Causality Assessment Tool. The primary outcome is a reduction in ADRs among patients with actionable PGx variants, where an ADR will be considered as any CTCAE grade 2 and above for non-haematological toxicities and any CTCAE grade 3 and above for haematological toxicities Cost-effectiveness of pre-emptive PGx (secondary outcome) will be compared with standard of care using hospital inpatient and outpatient data along with the validated Childhood Health Utility 9D Instrument. Power and statistics considerations: A sample size of 440 patients (220 per arm) will provide 80% power to detect a 24% relative risk reduction in the primary endpoint of ADRs (two-sided α=5%, 80% vs 61%), allowing for 10% drop-out. ETHICS AND DISSEMINATION: The ethics approval of the trial has been obtained from the Royal Children's Hospital Ethics Committee (HREC/89083/RCHM-2022). The ethics committee of each participating centres nationally has undertaken an assessment of the protocol and governance submission. TRIAL REGISTRATION NUMBER: NCT05667766.

Risk assessments of drug-related problems for cardiac surgery patients.

OBJECTIVES: Patients undergoing cardiac surgery are considered at high risk for developing drug-related problems (DRPs) due to comorbidities and complexity of drug treatment. This study aimed to identify DRPs in patients undergoing cardiac surgery and to develop and implement a framework to reduce potential risks associated with drug treatment. STUDY DESIGN: Prospectively designed quasi-experimental study. METHODS: This study consisted of observational (risk assessment and framework development) and interventional (framework implementation) periods and was conducted at a department of cardiovascular surgery in a university hospital. An expert panel evaluated the causes of DRPs. Then a framework was developed in consensus to identify safeguards to be implemented during the interventional period. RESULTS: A total of 200 patients (100 patients per study period) were included. During the observational period, a total of 275 DRPs and 487 causes were identified; 74.5% of DRPs were not solved. For the risk analysis, 487 causes were evaluated and only 32.6% were considered acceptable risk. By implementing the framework in the interventional period, 215 DRPs and 304 causes were identified and 386 interventions were recommended by a clinical pharmacist. A total of 342 (88.6%) interventions were accepted by a health care team, and 128 (59.5%) DRPs were completely solved. For the risk analysis, 304 causes were evaluated and 84.9% were considered acceptable risk ( P < .001 compared with the observational period). CONCLUSIONS: It is possible to reduce risk levels or prevent occurrence of DRPs by implementing a framework for risk management developed by a multidisciplinary care team in areas such as cardiac surgery where time is limited.

Collaborative science in action: A 20 year perspective from the Health and Environmental Sciences Institute (HESI) Cardiac Safety Committee.

The Health and Environmental Sciences Institute (HESI) is a nonprofit organization dedicated to resolving global health challenges through collaborative scientific efforts across academia, regulatory authorities and the private sector. Collaborative science across non-clinical disciplines offers an important keystone to accelerate the development of safer and more effective medicines. HESI works to address complex challenges by leveraging diverse subject-matter expertise across sectors offering access to resources, data and shared knowledge. In 2008, the HESI Cardiac Safety Committee (CSC) was established to improve public health by reducing unanticipated cardiovascular (CV)-related adverse effects from pharmaceuticals or chemicals. The committee continues to significantly impact the field of CV safety by bringing together experts from across sectors to address challenges of detecting and predicting adverse cardiac outcomes. Committee members have collaborated on the organization, management and publication of prospective studies, retrospective analyses, workshops, and symposia resulting in 38 peer reviewed manuscripts. Without this collaboration these manuscripts would not have been published. Through their work, the CSC is actively addressing challenges and opportunities in detecting potential cardiac failure modes using in vivo, in vitro and in silico models, with the aim of facilitating drug development and improving study design. By examining past successes and future prospects of the CSC, this manuscript sheds light on how the consortium's multifaceted approach not only addresses current challenges in detecting potential cardiac failure modes but also paves the way for enhanced drug development and study design methodologies. Further, exploring future opportunities and challenges will focus on improving the translational predictability of nonclinical evaluations and reducing reliance on animal research in CV safety assessments.

Deprescribing in older adults with polypharmacy.

Polypharmacy is common in older adults and is associated with adverse drug events, cognitive and functional impairment, increased healthcare costs, and increased risk of frailty, falls, hospitalizations, and mortality. Many barriers exist to deprescribing, but increased efforts have been made to develop and implement deprescribing interventions that overcome them. This narrative review describes intervention components and summarizes findings from published randomized controlled trials that have tested deprescribing interventions in older adults with polypharmacy, as well as reports on ongoing trials, guidelines, and resources that can be used to facilitate deprescribing. Most interventions were medication reviews in primary care settings, and many contained components such as shared decision making and/or a focus on patient care priorities, training for healthcare professionals, patient facing education materials, and involvement of family members, representing great heterogeneity in interventions addressing polypharmacy in older adults. Just over half of study interventions were found to perform better than usual care in at least one of their primary outcomes, and most study interventions were assessed over 12 months or less.