98 research outputs found
Regulation of pharmaceuticals in EU and liability arising out of medicinal products
The very nature of pharmaceutical products implies the need for their diligent
regulation under the law, regardless of the jurisdiction in question, in order to
alleviate the possibility of product liability. Yet, the pharmaceutical industry is
continuously exposed to the threat of product liability litigation, since it is in itself
innovative and dynamic, and is in direct connection with the health of human beings,
carrying an inherent risk. That having said it is more than likely that a certain
pharmaceutical product manufactured in an EU country can have an effect in other
EU and non-EU countries alike. In this research the basic regulatory tools of the EU
will be presented in the context of pharmaceutical law. The main aim of the research
will be to examine if the current state of the laws in Europe satisfies the objective of
providing safe and effective medicines for patients, promoting their overall health,
whilst minimizing risks of consumption. An inevitable component of this will
nevertheless be regulation of the safety of medicines through the European
pharmacovigilance system and reporting adverse drug reactions (ADRâs). Thus, in
this thesis I have made a comparative study of the reporting system in various EU
states to analyze the level of harmonization of their laws and regulations in this area.
Furthermore, the medical product liability schemes will be analyzed in different EU
Member states and a comparison will be made from the latter. Finally, the notion of
development risk defense that pharmaceutical companies usually evoke will be
considered. The results will be based on a previous discussion on the retrospective
and comparative analysis of case studies from the domain of EU law, and similar
national laws of countries in Europe with regards to product liability litigation for
pharmaceutical products. The results would be that with the recent evolvement and
amendments in the law of pharmaceuticals in Europe grater power has been given to
consumers both from the aspect of receiving adequate information, protection and
access to safe medicines. Despite the fact that big pharmaceutical companies are
already bound by soft law rules of regulatory agencies, and have per se product
liability limitations imposed by informing consumers, the research will suggest that
with recent progress in this domain of the law an even greater precaution has been
imposed on pharmaceutical companies in manufacturing their products, by
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strengthening the legal framework for protecting consumers within the various
countries in Europe. In that respect the work of the EMA, the Spanish Agency of
Medicines and Medical Devices (AEMPS), the French Agency of Medicines (ANSM)
and similar regulatory agencies will be put forward, as well as the theoretical
question of pros and cons of too much regulation in the pharmaceutical sector, in
terms of promoting public health.Programa de Doctorado en Derecho por la Universidad Carlos III de MadridPresidente: Alfonso Luis Calvo Caravaca.- Secretaria: Julia Suderow.- Vocal: Carmen Herrero SuĂĄre
Biomedical Literature Mining and Knowledge Discovery of Phenotyping Definitions
Indiana University-Purdue University Indianapolis (IUPUI)Phenotyping definitions are essential in cohort identification when conducting
clinical research, but they become an obstacle when they are not readily available.
Developing new definitions manually requires expert involvement that is labor-intensive,
time-consuming, and unscalable. Moreover, automated approaches rely mostly on
electronic health recordsâ data that suffer from bias, confounding, and incompleteness.
Limited efforts established in utilizing text-mining and data-driven approaches to automate
extraction and literature-based knowledge discovery of phenotyping definitions and to
support their scalability. In this dissertation, we proposed a text-mining pipeline combining
rule-based and machine-learning methods to automate retrieval, classification, and
extraction of phenotyping definitionsâ information from literature. To achieve this, we first
developed an annotation guideline with ten dimensions to annotate sentences with evidence
of phenotyping definitions' modalities, such as phenotypes and laboratories. Two
annotators manually annotated a corpus of sentences (n=3,971) extracted from full-text
observational studiesâ methods sections (n=86). Percent and Kappa statistics showed high
inter-annotator agreement on sentence-level annotations. Second, we constructed two
validated text classifiers using our annotated corpora: abstract-level and full-text sentence-level.
We applied the abstract-level classifier on a large-scale biomedical literature of over
20 million abstracts published between 1975 and 2018 to classify positive abstracts
(n=459,406). After retrieving their full-texts (n=120,868), we extracted sentences from
their methods sections and used the full-text sentence-level classifier to extract positive
sentences (n=2,745,416). Third, we performed a literature-based discovery utilizing the
positively classified sentences. Lexica-based methods were used to recognize medical
concepts in these sentences (n=19,423). Co-occurrence and association methods were used
to identify and rank phenotype candidates that are associated with a phenotype of interest.
We derived 12,616,465 associations from our large-scale corpus. Our literature-based
associations and large-scale corpus contribute in building new data-driven phenotyping
definitions and expanding existing definitions with minimal expert involvement
Usability analysis of contending electronic health record systems
In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe
Front-Line Physicians' Satisfaction with Information Systems in Hospitals
Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe
White Paper 11: Artificial intelligence, robotics & data science
198 p. : 17 cmSIC white paper on Artificial Intelligence, Robotics and Data Science sketches a preliminary roadmap for addressing current R&D challenges associated with automated and autonomous machines. More than 50 research challenges investigated all over Spain by more than 150 experts within CSIC are presented in eight chapters. Chapter One introduces key concepts and tackles the issue of the integration of knowledge (representation), reasoning and learning in the design of artificial entities. Chapter Two analyses challenges associated with the development of theories âand supporting technologiesâ for modelling the behaviour of autonomous agents. Specifically, it pays attention to the interplay between elements at micro level (individual autonomous agent interactions) with the macro world (the properties we seek in large and complex societies). While Chapter Three discusses the variety of data science applications currently used in all fields of science, paying particular attention to Machine Learning (ML) techniques, Chapter Four presents current development in various areas of robotics. Chapter Five explores the challenges associated with computational cognitive models. Chapter Six pays attention to the ethical, legal, economic and social challenges coming alongside the development of smart systems. Chapter Seven engages with the problem of the environmental sustainability of deploying intelligent systems at large scale. Finally, Chapter Eight deals with the complexity of ensuring the security, safety, resilience and privacy-protection of smart systems against cyber threats.18 EXECUTIVE SUMMARY ARTIFICIAL INTELLIGENCE, ROBOTICS AND DATA SCIENCE Topic Coordinators Sara Degli Esposti ( IPP-CCHS, CSIC ) and Carles Sierra ( IIIA, CSIC ) 18 CHALLENGE 1 INTEGRATING KNOWLEDGE, REASONING AND LEARNING Challenge Coordinators Felip ManyĂ ( IIIA, CSIC ) and AdriĂ ColomĂ© ( IRI, CSIC â UPC ) 38 CHALLENGE 2 MULTIAGENT SYSTEMS Challenge Coordinators N. Osman ( IIIA, CSIC ) and D. LĂłpez ( IFS, CSIC ) 54 CHALLENGE 3 MACHINE LEARNING AND DATA SCIENCE Challenge Coordinators J. J. Ramasco Sukia ( IFISC ) and L. Lloret Iglesias ( IFCA, CSIC ) 80 CHALLENGE 4 INTELLIGENT ROBOTICS Topic Coordinators G. AlenyĂ ( IRI, CSIC â UPC ) and J. Villagra ( CAR, CSIC ) 100 CHALLENGE 5 COMPUTATIONAL COGNITIVE MODELS Challenge Coordinators M. D. del Castillo ( CAR, CSIC) and M. Schorlemmer ( IIIA, CSIC ) 120 CHALLENGE 6 ETHICAL, LEGAL, ECONOMIC, AND SOCIAL IMPLICATIONS Challenge Coordinators P. Noriega ( IIIA, CSIC ) and T. AusĂn ( IFS, CSIC ) 142 CHALLENGE 7 LOW-POWER SUSTAINABLE HARDWARE FOR AI Challenge Coordinators T. Serrano ( IMSE-CNM, CSIC â US ) and A. Oyanguren ( IFIC, CSIC - UV ) 160 CHALLENGE 8 SMART CYBERSECURITY Challenge Coordinators D. Arroyo Guardeño ( ITEFI, CSIC ) and P. Brox JimĂ©nez ( IMSE-CNM, CSIC â US )Peer reviewe
Telemedicine
Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios
Computational Approaches for Screening Drugs for Bioactivation, Reactive Metabolite Formation, and Toxicity
Cytochrome P450 enzymes aid in the elimination of a preponderance of small molecule drugs, but can generate reactive metabolites that may adversely conjugate to protein and DNA, in a process known as bioactivation, and prompt adverse reaction, drug candidate attrition, or market withdrawal. Experimental assays are low-throughput and expensive to perform, so they are often reserved until later stages of the drug development pipeline when the drug candidate pools are already significantly narrowed. Reactive metabolites also elude in vivo detection, as they are transitory and generally do not circulate. In contrast, computational methods are high-throughput and cheap to screen millions of potentially toxic molecules during early stages of the drug development pipeline. This work computationally models sequences of metabolic transformations, i.e., pathways, between an input molecule and a corresponding, optional reactive metabolite(s). Additionally, an accurate graph neural network model was developed to assess importance of intermediate metabolites and extract connected subnetworks of relevance to bioactivation. Connecting multiple site of metabolism and structure inference models, we developed an integrated model of metabolism and reactivity to evaluate bioactivation risk driven by epoxidation, quinone formation, thiophene sulfur-oxidation, and nitroaromatic reduction. We applied this framework to an understudied substructure, the isoxazole ring, that is gaining traction in a class of drugs known as bromodomain inhibitors that may potentially drive quinone formation. Finally, we attend to toxicity associated with drug-drug interactions, particularly with NSAID usage reported in electronic health records
Effects of dance therapy on balance, gait and neuro-psychological performances in patients with Parkinson's disease and postural instability
Postural Instability (PI) is a core feature of
Parkinsonâs Disease (PD) and a major cause of falls and disabilities. Impairment of executive functions has been called as an aggravating factor on motor performances. Dance therapy has been shown effective for improving gait and has been suggested as an alternative rehabilitative method.
To evaluate gait performance, spatial-temporal (S-T) gait
parameters and cognitive performances in a cohort of patients with PD and PI modifications in balance after a cycle of dance therapy
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