4.2 Article

The EU-ADR Web Platform: delivering advanced pharmacovigilance tools

Journal

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY
Volume 22, Issue 5, Pages 459-467

Publisher

WILEY
DOI: 10.1002/pds.3375

Keywords

pharmacoepidemiology; pharmacovigilance; adverse drug reactions; drug safety; in silico pharmacology

Funding

  1. European Commission (EU-ADR) [ICT-215847]
  2. FCT [PTDC/EIA-CCO/100541/2008]
  3. Instituto de Salud Carlos III FEDER [CP10/00524]

Ask authors/readers for more resources

Purpose Pharmacovigilance methods have advanced greatly during the last decades, making post-market drug assessment an essential drug evaluation component. These methods mainly rely on the use of spontaneous reporting systems and health information databases to collect expertise from huge amounts of real-world reports. The EU-ADR Web Platform was built to further facilitate accessing, monitoring and exploring these data, enabling an in-depth analysis of adverse drug reactions risks. Methods The EU-ADR Web Platform exploits the wealth of data collected within a large-scale European initiative, the EU-ADR project. Millions of electronic health records, provided by national health agencies, are mined for specific drug events, which are correlated with literature, protein and pathway data, resulting in a rich drugevent dataset. Next, advanced distributed computing methods are tailored to coordinate the execution of data-mining and statistical analysis tasks. This permits obtaining a ranked drugevent list, removing spurious entries and highlighting relationships with high risk potential. Results The EU-ADR Web Platform is an open workspace for the integrated analysis of pharmacovigilance datasets. Using this software, researchers can access a variety of tools provided by distinct partners in a single centralized environment. Besides performing standalone drugevent assessments, they can also control the pipeline for an improved batch analysis of custom datasets. Drugevent pairs can be substantiated and statistically analysed within the platform's innovative working environment. Conclusions A pioneering workspace that helps in explaining the biological path of adverse drug reactions was developed within the EU-ADR project consortium. This tool, targeted at the pharmacovigilance community, is available online at https://bioinformatics.ua.pt/euadr/. Copyright (c) 2012 John Wiley & Sons, Ltd.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.2
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Sport Sciences

Mechanical loading prediction through accelerometry data during walking and running

Lucas Veras, Florencio Diniz-Sousa, Giorjines Boppre, Ana Resende-Coelho, Edgar Moutinho-Ribeiro, Vitor Devezas, Hugo Santos-Sousa, John Preto, Joao Paulo Vilas-Boas, Leandro Machado, Jose Oliveira, Helder Fonseca

Summary: This study developed accelerometry-based equations to predict pGRF and pLR during walking and running, and compared the predicted values with actual values, demonstrating high accuracy of these equations.

EUROPEAN JOURNAL OF SPORT SCIENCE (2023)

Article Computer Science, Interdisciplinary Applications

Querying semantic catalogues of biomedical databases

Arnaldo Pereira, Joao Rafael Almeida, Rui Pedro Lopes, Jose Luis Oliveira

Summary: This study proposes a strategy for retrieving semantically annotated biomedical datasets using a natural language interface. The method converts data to a semantic format using open biomedical ontologies and enables users to issue complex queries without using formal query languages. The approach was validated using Alzheimer's disease datasets, and the performance and limitations of the question-answering module were analyzed.

JOURNAL OF BIOMEDICAL INFORMATICS (2023)

Article Toxicology

A continuous in silico learning strategy to identify safety liabilities in compounds used in the leather and textile industry

Eric March-Vila, Giacomo Ferretti, Emma Terricabras, Ines Ardao, Jose Manuel Brea, Maria Jose Varela, Alvaro Arana, Juan Andres Rubiolo, Ferran Sanz, Maria Isabel Loza, Laura Sanchez, Hector Alonso, Manuel Pastor

Summary: In order to reduce the impact of human activity on the environment, many industries in the leather and textile sector are adopting measures to characterize the chemical safety of substances commonly used in their processes. This study compiles and annotates the substances used in this sector, using a combination of data collection, experimental methods, and in silico predictions. The results show that in silico methods can provide reasonably good hazard estimations and fill knowledge gaps in the chemical space of the leather and textile industry.

ARCHIVES OF TOXICOLOGY (2023)

Article Biology

Methodology to identify a gene expression signature by merging microarray datasets

Olga Fajarda, Joao Rafael Almeida, Sara Duarte-Pereira, Raquel M. Silva, Jose Luis Oliveira

Summary: A large amount of microarray datasets have been produced to identify differentially expressed genes and gene expression signatures, which can contribute to disease diagnosis, prognosis, and therapeutic response. However, most datasets have limited statistical power due to their small sample sizes. To address this issue, we propose a methodology that merges microarray datasets and uses statistical methods along with supervised machine learning algorithms to identify gene expression signatures. This methodology has been validated in heart failure and autism spectrum disorder datasets, achieving high classification accuracy.

COMPUTERS IN BIOLOGY AND MEDICINE (2023)

Article Chemistry, Medicinal

Illuminating the Chemical Space of Untargeted Proteins

Maria J. Falaguera, Jordi Mestres

Summary: According to the IDG initiative, 90% of the proteins encoded by the human genome lack identified active ligands. A new computational strategy has been introduced to identify privileged structures that are likely to contain active small molecules for untargeted proteins. This strategy has shown promise in identifying potential active ligands for cancer-associated proteins.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2023)

Article Chemistry, Analytical

Using Raw Accelerometer Data to Predict High-Impact Mechanical Loading

Lucas Veras, Florencio Diniz-Sousa, Giorjines Boppre, Vitor Devezas, Hugo Santos-Sousa, John Preto, Joao Paulo Vilas-Boas, Leandro Machado, Jose Oliveira, Helder Fonseca

Summary: The purpose of this study was to develop prediction equations for peak ground reaction force (pGRF) and peak loading rate (pLR) in high-impact activities for adults with various body masses. Regression equations were developed using accelerometry data, with body mass and peak acceleration or acceleration rate as predictors. The equations had high accuracy for predicting pGRF, with a coefficient of determination (R-2) of at least 0.83 and a mean absolute percentage error (MAPE) below 14.5%. However, the accuracy of the pLR prediction equations was lower than that of the pGRF equations.

SENSORS (2023)

Article Mathematical & Computational Biology

Study of NAD-interacting proteins highlights the extent of NAD regulatory roles in the cell and its potential as a therapeutic target

Sara Duarte-Pereira, Sergio Matos, Jose Luis Oliveira, Raquel M. Silva

Summary: The study aimed to identify NAD-binding and NAD-interacting proteins and explore novel proteins and functions regulated by NAD. Datasets of NAD-binding proteins and NAD-protein-protein interactions were defined using experimental databases. Pathway enrichment analysis revealed their involvement in metabolic and signaling pathways, including neurodegenerative disorders. TRPC3 and isoforms of DAG kinases were identified as potential NADBPs involved in calcium signaling. Potential therapeutic targets interacting with NAD were also identified, with regulatory and signaling functions in cancer and neurodegenerative diseases.

JOURNAL OF INTEGRATIVE BIOINFORMATICS (2023)

Article Biology

FSM-DDTR: End-to-end feedback strategy for multi-objective De Novo drug design using transformers

Nelson R. C. Monteiro, Tiago O. Pereira, Ana Catarina D. Machado, Jose L. Oliveira, Maryam Abbasi, Joel P. Arrais

Summary: This study proposes a multi-objective Transformer-based architecture for generating drug candidates with desired molecular properties and increased selectivity towards a specific biological target. The results demonstrate that the proposed architecture can generate novel and synthesizable small compounds with desired pharmacological properties. Overall, this research study validates the applicability of a Transformer-based architecture in the context of drug design. Rating: 8/10.

COMPUTERS IN BIOLOGY AND MEDICINE (2023)

Article Biochemistry & Molecular Biology

The role of PPAR-gamma in memory deficits induced by prenatal and lactation alcohol exposure in mice

Alba Garcia-Baos, Antoni Pastor, Ines Gallego-Landin, Rafael de la Torre, Ferran Sanz, Olga Valverde

Summary: Patients with Fetal Alcohol Spectrum Disorder (FASD) exhibit long-lasting cognitive disabilities, including memory deficits, but the underlying neurobiological mechanisms are not clear. By studying alcohol-exposed mice, researchers found that prenatal and lactation alcohol exposure induces FASD-like memory impairments through the reduction of N-acylethanolamines (NAEs) and peroxisome proliferator-activated receptor gamma (PPAR-gamma) in the hippocampus during a childhood-like period. Pharmacological interventions targeting NAEs and PPAR-gamma were able to improve memory deficits, and overexpression of PPAR-gamma in hippocampal astrocytes mitigated memory impairments induced by alcohol exposure.

MOLECULAR PSYCHIATRY (2023)

Article Biochemistry & Molecular Biology

Myocardial RNA Sequencing Reveals New Potential Therapeutic Targets in Heart Failure with Preserved Ejection Fraction

Jose M. Inacio, Fernando Cristo, Miguel Pinheiro, Francisco Vasques-Novoa, Francisca Saraiva, Mafalda M. Nunes, Graca Rosas, Andreia Reis, Rita Coimbra, Jose Luis Oliveira, Gabriela Moura, Adelino Leite-Moreira, Jose Antonio Belo

Summary: In this study, RNA sequencing was performed on myocardial biopsies from heart failure patients with preserved ejection fraction (HFpEF) to identify distinctive transcriptomic signatures. A total of 306 differentially expressed mRNAs and 152 differentially expressed microRNAs were identified, revealing potential therapeutic targets and mechanisms underlying HFpEF.

BIOMEDICINES (2023)

Editorial Material Computer Science, Artificial Intelligence

Editorial: Explainable artificial intelligence for critical healthcare applications

Zhe He, Rui Zhang, Gayo Diallo, Zhengxing Huang, Benjamin S. Glicksberg

FRONTIERS IN ARTIFICIAL INTELLIGENCE (2023)

Article Biochemistry & Molecular Biology

Maximal Exercise Improves the Levels of Endothelial Progenitor Cells in Heart Failure Patients

Suiane Cavalcante, Sofia Viamonte, Rui S. Cadilha, Ilda P. Ribeiro, Ana Cristina Goncalves, Joao Sousa-Venancio, Marisol Gouveia, Manuel Teixeira, Mario Santos, Jose Oliveira, Fernando Ribeiro

Summary: This study aims to evaluate the effects of a single exercise bout on the circulating levels of EPCs and CECs in heart failure patients. The results showed that a single exercise bout increased the levels of EPCs but didn't change the levels of CECs. Heart failure patients had lower levels of EPCs compared to the age-matched group, but the exercise bout restored their EPCs levels to a level similar to the age-matched group.

CURRENT ISSUES IN MOLECULAR BIOLOGY (2023)

Article Chemistry, Medicinal

CIPSI: An open chemical intellectual property service for medicinal chemists

Maria Martinez-Sevillano, Maria J. Falaguera, Jordi Mestres

Summary: The availability of patent chemical data provides public access to a chemical space not covered by other sources, but there is still a lack of open applications for easy search and analysis of biologically-relevant molecular structures in patents. We have developed CIPSI, an open Chemical Intellectual Property Service, to assist medicinal chemists in searching and analyzing molecules in SureChEMBL patents.

MOLECULAR INFORMATICS (2023)

Article Multidisciplinary Sciences

The OREGANO knowledge graph for computational drug repurposing

Marina Boudin, Gayo Diallo, Martin Drance, Fleur Mougin

Summary: Drug repositioning is a faster and more affordable solution than traditional drug discovery approaches. Computational drug repositioning using knowledge graphs shows great promise. However, there is a lack of a holistically constructed knowledge graph with the broadest possible features and drug characteristics that is freely available to the community. The OREGANO knowledge graph aims to fill this gap.

SCIENTIFIC DATA (2023)

Article Computer Science, Information Systems

Open Source Solutions for Vulnerability Assessment: A Comparative Analysis

Dinis Barroqueiro Cruz, Joao Rafael Almeida, Jose Luis Oliveira

Summary: This article introduces three main approaches to application security: Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), and Software Composition Analysis (SCA). It proposes a baseline comparison model to help select the best solutions and discusses future opportunities and challenges in application security. A workflow for vulnerability assessment is also proposed.

IEEE ACCESS (2023)

No Data Available