1,300 research outputs found

    DMET-Miner: Efficient discovery of association rules from pharmacogenomic data

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    AbstractMicroarray platforms enable the investigation of allelic variants that may be correlated to phenotypes. Among those, the Affymetrix DMET (Drug Metabolism Enzymes and Transporters) platform enables the simultaneous investigation of all the genes that are related to drug absorption, distribution, metabolism and excretion (ADME). Although recent studies demonstrated the effectiveness of the use of DMET data for studying drug response or toxicity in clinical studies, there is a lack of tools for the automatic analysis of DMET data. In a previous work we developed DMET-Analyzer, a methodology and a supporting platform able to automatize the statistical study of allelic variants, that has been validated in several clinical studies. Although DMET-Analyzer is able to correlate a single variant for each probe (related to a portion of a gene) through the use of the Fisher test, it is unable to discover multiple associations among allelic variants, due to its underlying statistic analysis strategy that focuses on a single variant for each time. To overcome those limitations, here we propose a new analysis methodology for DMET data based on Association Rules mining, and an efficient implementation of this methodology, named DMET-Miner. DMET-Miner extends the DMET-Analyzer tool with data mining capabilities and correlates the presence of a set of allelic variants with the conditions of patient’s samples by exploiting association rules. To face the high number of frequent itemsets generated when considering large clinical studies based on DMET data, DMET-Miner uses an efficient data structure and implements an optimized search strategy that reduces the search space and the execution time. Preliminary experiments on synthetic DMET datasets, show how DMET-Miner outperforms off-the-shelf data mining suites such as the FP-Growth algorithms available in Weka and RapidMiner. To demonstrate the biological relevance of the extracted association rules and the effectiveness of the proposed approach from a medical point of view, some preliminary studies on a real clinical dataset are currently under medical investigation

    Strategies for Automating Pharmacovigilance Adverse Event Case Processing

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    Business leaders who fail to implement innovative technology solutions in their companies face economic distress in these organizations. Guided by the task technology fit model as the conceptual framework, the purpose of this qualitative single case study was to explore strategies used by pharmacovigilance (PV) systems leaders to implement innovative technology solutions. The participants were 4 PV systems managers working in a pharmaceutical company in the Boston area of Massachusetts, United States, who used successful strategies to implement innovative technology solutions to automate adverse events case processing. Data were collected using semistructured interviews and company documents. The collected data were analyzed using Yinâs 5-step data analysis, which included compiling, disassembling, reassembling, interpreting data, and concluding the findings. Three key themes emerged: automation solution selection and implementation strategies, business operation model changes, and communication and training strategies. The key recommendation is for PV leaders to implement automation solutions and redirect the savings from PV operations in terms of cost and workforce tasks toward investing in the actual PV tasks such as benefit-risk assessments of products. The implications for positive social change include the potential to identify strategies to improve patient outcomes and assist in making pharmaceutical medicines more efficacious and safer for human use in reducing unnecessary deaths

    Towards a Learning Health System: a SOA based platform for data re-use in chronic infectious diseases

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    Abstract Information and Communication Technology (ICT) tools can efficiently support clinical research by providing means to collect automatically huge amount of data useful for the management of clinical trials conduction. Clinical trials are indispensable tools for Evidence-Based Medicine and represent the most prevalent clinical research activity. Clinical trials cover only a restricted part of the population that respond to particular and strictly controlled requirements, offering a partial view of the overall patients\u2019 status. For instance, it is not feasible to consider patients with comorbidities employing only one kind of clinical trial. Instead, a system that have a comprehensive access to all the clinical data of a patient would have a global view of all the variables involved, reflecting real-world patients\u2019 experience. The Learning Health System is a system with a broader vision, in which data from various sources are assembled, analyzed by various means and then interpreted. The Institute of Medicine (IOM) provides this definition: \u201cIn a Learning Health System, progress in science, informatics, and care culture align to generate new knowledge as an ongoing, natural by-product of the care experience, and seamlessly refine and deliver best practices for continuous improvement in health and health care\u201d. The final goal of my project is the realization of a platform inspired by the idea of Learning Health System, which will be able to re-use data of different nature coming from widespread health facilities, providing systematic means to learn from clinicians\u2019 experience to improve both the efficiency and the quality of healthcare delivery. The first approach is the development of a SOA-based architecture to enable data collection from sparse facilities into a single repository, to allow medical institutions to share information without an increase in costs and without the direct involvement of users. Through this architecture, every single institution would potentially be able to participate and contribute to the realization of a Learning Health System, that can be seen as a closed cycle constituted by a sequential process of transforming patient-care data into knowledge and then applying this knowledge to clinical practice. Knowledge, that can be inferred by re-using the collected data to perform multi-site, practice-based clinical trials, could be concretely applied to clinical practice through Clinical Decision Support Systems (CDSS), which are instruments that aim to help physicians in making more informed decisions. With 4 this objective, the platform developed not only supports clinical trials execution, but also enables data sharing with external research databases to participate in wider clinical trials also at a national level without effort. The results of these studies, integrated with existing guidelines, can be seen as the knowledge base of a decision support system. Once designed and developed, the adoption of this system for chronical infective diseases management at a regional level helped in unifying data all over the Ligurian territory and actively monitor the situation of specific diseases (like HIV, HCV and HBV) for which the concept of retention in care assumes great importance. The use of dedicated standards is essential to grant the necessary level of interoperability among the structures involved and to allow future extensions to other fields. A sample scenario was created to support antiretroviral drugs prescription in the Ligurian HIV Network setting. It was thoroughly tested by physicians and its positive impact on clinical care was measured in terms of improvements in patients\u2019 quality of life, prescription appropriateness and therapy adherence. The benefits expected from the employment of the system developed were verified. Student\u2019s T test was used to establish if significant differences were registered between data collected before and after the introduction of the system developed. The results were really acceptable with the minimum p value in the order of 10 125 and the maximum in the order of 10 123. It is reasonable to assess that the improvements registered in the three analysis considered are ascribable to this system introduction and not to other factors, because no significant differences were found in the period before its release. Speed is a focal point in a system that provides decision support and it is highly recognized the importance of velocity optimization. Therefore, timings were monitored to evaluate the responsiveness of the system developed. Extremely acceptable results were obtained, with the waiting times of the order of 10 121 seconds. The importance of the network developed has been widely recognized by the medical staff involved, as it is also assessed by a questionnaire they compiled to evaluate their level of satisfaction

    Preface

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    Composição de serviços para aplicações biomédicas

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    Doutoramento em Engenharia InformáticaA exigente inovação na área das aplicações biomédicas tem guiado a evolução das tecnologias de informação nas últimas décadas. Os desafios associados a uma gestão, integração, análise e interpretação eficientes dos dados provenientes das mais modernas tecnologias de hardware e software requerem um esforço concertado. Desde hardware para sequenciação de genes a registos electrónicos de paciente, passando por pesquisa de fármacos, a possibilidade de explorar com precisão os dados destes ambientes é vital para a compreensão da saúde humana. Esta tese engloba a discussão e o desenvolvimento de melhores estratégias informáticas para ultrapassar estes desafios, principalmente no contexto da composição de serviços, incluindo técnicas flexíveis de integração de dados, como warehousing ou federação, e técnicas avançadas de interoperabilidade, como serviços web ou LinkedData. A composição de serviços é apresentada como um ideal genérico, direcionado para a integração de dados e para a interoperabilidade de software. Relativamente a esta última, esta investigação debruçou-se sobre o campo da farmacovigilância, no contexto do projeto Europeu EU-ADR. As contribuições para este projeto, um novo standard de interoperabilidade e um motor de execução de workflows, sustentam a sucesso da EU-ADR Web Platform, uma plataforma para realizar estudos avançados de farmacovigilância. No contexto do projeto Europeu GEN2PHEN, esta investigação visou ultrapassar os desafios associados à integração de dados distribuídos e heterogéneos no campo do varíoma humano. Foi criada uma nova solução, WAVe - Web Analyses of the Variome, que fornece uma coleção rica de dados de variação genética através de uma interface Web inovadora e de uma API avançada. O desenvolvimento destas estratégias evidenciou duas oportunidades claras na área de software biomédico: melhorar o processo de implementação de software através do recurso a técnicas de desenvolvimento rápidas e aperfeiçoar a qualidade e disponibilidade dos dados através da adopção do paradigma de web semântica. A plataforma COEUS atravessa as fronteiras de integração e interoperabilidade, fornecendo metodologias para a aquisição e tradução flexíveis de dados, bem como uma camada de serviços interoperáveis para explorar semanticamente os dados agregados. Combinando as técnicas de desenvolvimento rápidas com a riqueza da perspectiva "Semantic Web in a box", a plataforma COEUS é uma aproximação pioneira, permitindo o desenvolvimento da próxima geração de aplicações biomédicas.The demand for innovation in the biomedical software domain has been an information technologies evolution driver over the last decades. The challenges associated with the effective management, integration, analyses and interpretation of the wealth of life sciences information stemming from modern hardware and software technologies require concerted efforts. From gene sequencing hardware to pharmacology research up to patient electronic health records, the ability to accurately explore data from these environments is vital to further improve our understanding of human health. This thesis encloses the discussion on building better informatics strategies to address these challenges, primarily in the context of service composition, including warehousing and federation strategies for resource integration, as well as web services or LinkedData for software interoperability. Service composition is introduced as a general principle, geared towards data integration and software interoperability. Concerning the latter, this research covers the service composition requirements within the pharmacovigilance field, namely on the European EU-ADR project. The contributions to this area, the definition of a new interoperability standard and the creation of a new workflow-wrapping engine, are behind the successful construction of the EUADR Web Platform, a workspace for delivering advanced pharmacovigilance studies. In the context of the European GEN2PHEN project, this research tackles the challenges associated with the integration of heterogeneous and distributed data in the human variome field. For this matter, a new lightweight solution was created: WAVe, Web Analysis of the Variome, provides a rich collection of genetic variation data through an innovative portal and an advanced API. The development of the strategies underlying these products highlighted clear opportunities in the biomedical software field: enhancing the software implementation process with rapid application development approaches and improving the quality and availability of data with the adoption of the Semantic Web paradigm. COEUS crosses the boundaries of integration and interoperability as it provides a framework for the flexible acquisition and translation of data into a semantic knowledge base, as well as a comprehensive set of interoperability services, from REST to LinkedData, to fully exploit gathered data semantically. By combining the lightness of rapid application development strategies with the richness of its "Semantic Web in a box" approach, COEUS is a pioneering framework to enhance the development of the next generation of biomedical applications

    Managing Risk to the Patient: Recoding Quality Risk Management for the Pharmaceutical and Biopharmaceutical Industries

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    This thesis explores the application of quality risk management (QRM) in pharmaceutical and biopharmaceutical companies and its effectiveness at managing risk to the patient. The objective of the research described in this thesis was to characterize a maturity state of QRM implementation in which the patient is adequately protected from the risks associated with medicinal products of inadequate quality. The research was conducted over three phases: first, to determine whether patients are better protected since the publication of ICH Q9, a commonly employed guidance on the application of QRM; second, to characterize the industry with regard to QRM maturity, including the effectiveness of QRM application, the behaviors, attitudes, and motivations of the people working with and within QRM, and the governance and oversight of QRM efforts; and third, to construct a mature QRM program and associated maturity measurement tool to accelerate improvements in QRM and better protect the patient. The research employed a mixed methods approach, including the research methods of literature review, philosophical dialogues, benchmarking survey, semi-structured interview, and pilot case studies. The research concluded that the patient is no better protected since the inception of QRM and the level of QRM maturity throughout the pharmaceutical and biopharmaceutical industries remains rather low. However, the research also indicated that progression towards the more mature QRM model proposed in thesis may help firms perform QRM in a more effective manner, resulting in improved management of risk to the patient

    Technology market transfer plan launch of DELIVES to E.U. Market©

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    Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em BiotecnologiaThe pharmaceutical industry faces one of the biggest waves of patent expirations. The magnitude of the potential loss of sales is such that Datamonitor, predicts that between 2011 and 2012 the revenue from the drug will decrease for the first time in four decades. Alternatively, the technologies for Drug Delivery (DD), which consist of the science of delivering an active ingredient in place of the body where this is necessary, in the right quantities at the right time in the most effective and convenient, are boosting the growth of pharmaceutical companies, increasing its revenue by extending the product life cycle and through new formulations and combinations. According to this perception, this marketing plan was developed for a future company, LIFE DELIVERY, which holds the patent of a new biomaterial, and intends to launch a new product - Deliver | Improving life quality - for the market. DELIVES is a New Targeted Drug Delivery (TDD), which consists of a DD directed to release the drug locally in the area of interest, extremely versatile and can be precisely adjusted to achieve the specific objectives of each client, providing a controlled release of drugs and elaborated through a process environmentally friendly. Using three types of segmentation (geographic, industry type and application) and applying different evaluation criteria to selected segments, the final conclusions point to the following target customers: large pharmaceutical companies, the European Union, acting in the markets of the following therapeutic areas: inflammation and Musculosketal, metabolic disorders and cardiovascular diseases, the latter being the ideal customers for market entry strategy. According to the perceived value, of target customers - translated in cost-saving -, LIFE DELIEVERY will adopt a position based on three main pillars: quality, innovation and organizational image. The business model adopted aims to license the technology, using different communication strategies, and € 322.078.48, is the cost to implement this marketing plan in the first year of life of the company

    Products and Services

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    Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge
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