890 resultados para Personalized medicine
Resumo:
Nanotechnology entails the manufacturing and manipulation of matter at length scales ranging from single atoms to micron-sized objects. The ability to address properties on the biologically-relevant nanometer scale has made nanotechnology attractive for Nanomedicine. This is perceived as a great opportunity in healthcare especially in diagnostics, therapeutics and more in general to develop personalized medicine. Nanomedicine has the potential to enable early detection and prevention, and to improve diagnosis, mass screening, treatment and follow-up of many diseases. From the biological standpoint, nanomaterials match the typical size of naturally occurring functional units or components of living organisms and, for this reason, enable more effective interaction with biological systems. Nanomaterials have the potential to influence the functionality and cell fate in the regeneration of organs and tissues. To this aim, nanotechnology provides an arsenal of techniques for intervening, fabricate, and modulate the environment where cells live and function. Unconventional micro- and nano-fabrication techniques allow patterning biomolecules and biocompatible materials down to the level of a few nanometer feature size. Patterning is not simply a deterministic placement of a material; in a more extended acception it allows a controlled fabrication of structures and gradients of different nature. Gradients are emerging as one of the key factors guiding cell adhesion, proliferation, migration and even differentiation in the case of stem cells. The main goal of this thesis has been to devise a nanotechnology-based strategy and tools to spatially and temporally control biologically-relevant phenomena in-vitro which are important in some fields of medical research.
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Nella presente tesi indaghiamo la potenzialità di LCM e Reverse Phase Protein microarray negli studi clinici. Si analizza la possibilità di creare una bio banca con line cellular primarie, al fine di conseguire drug test di sensibilità prima di decidere il trattamento da somministrare ai singoli pazienti. Sono stati ottenuti profili proteomici da biopsie pre e post terapia. I risultati dimostrano che questa piattaforma mostra il meccanismo di resistenza acquisito durante la terapia biologica. Questo ci ha portato ad analizzare una possibile stratificazione per pazienti con mCRC . I dati hanno rivelato distinti pathway di attivazione tra metastasi resecabile e non resecabili. I risultati mostrano inoltre due potenziali bersagli farmacologici. Ma la valutazione dell'intero tumore tramite singole biopsie sembra essere un problema a causa dell’eterogeneità intratumorale a livello genomico. Abbiamo indagato questo problema a livello dell'architettura del segnale in campioni di mCRC e ccRCC . I risultati indicano una somiglianza complessiva nei profili proteomici all'interno dello stesso tumore. Considerando che una singola biopsia è rappresentativa di un intera lesione , abbiamo studiato la possibilità di creare linee di cellule primarie, per valutare il profilo molecolare di ogni paziente. Fino ad oggi non c'era un protocollo per creare linee cellulari immortalizzate senza alcuna variazione genetica . abbiamo cosiderato, però, l'approccio innovativo delle CRCs. Ad oggi , non è ancora chiaro se tali cellule mimino il profilo dei tessuti oppure I passaggi in vitro modifichino i loro pathways . Sulla base di un modello di topo , i nostri dati mostrano un profilo di proteomica simile tra le linee di cellule e tessuti di topo LCM. In conclusione, i nostri dati dimostrano l'utilità della piattaforma LCM / RPPA nella sperimentazione clinica e la possibilità di creare una bio - banca di linee cellulari primarie, per migliorare la decisione del trattamento.
Resumo:
Die Entstehung der Atherosklerose ist ein komplexer Vorgang, der sich durch Ablagerung von Lipiden an der Gefäßwand sowie durch immunologische und inflammatorische Prozesse auszeichnet. Neben konventionellen Risikofaktoren wie Alter, Geschlecht, Rauchen, HDL-Cholesterin, Diabetes mellitus und einer positiven Familienanamnese werden zur Bestimmung des atherosklerotischen Risikos neue Biomarker der inflammatorischen Reaktion untersucht. Ziel dieser Arbeit war die Entwicklung einer Methode zur Diagnostik des Atheroskleroserisikos. Es wurde eine neuartige Chip-Technologie eingesetzt, um das Risiko für eine potentiell drohende atherosklerotische Erkrankung abzuschätzen. Dabei wurde ausgenutzt, dass molekulare Veränderungen in Genen bestimmte Krankheitsbilder auslösen können. rnEs wurde ein molekularbiologischer Test entwickelt, welcher die Untersuchung von genetischen Variationen aus genomischer DNA ermöglicht. Dafür fand die Entwicklung einer Multiplex-PCR statt, deren Produkt mit der Chip-Technologie untersucht werden kann. Dazu wurden auf einem Mikroarray Sonden immobilisiert, mit deren Hilfe genspezifische Mutationen nachgewiesen werden können. So wurden mehrere Gene mit einem geringen Aufwand gleichzeitig getestet. rnDie Auswahl der entsprechenden Marker erfolgte anhand einer Literaturrecherche von randomisierten und kontrollierten klinischen Studien. Der Mikroarray konnte für zwölf Variationen in den acht Genen Prostaglandinsynthase-1 (PTGS1), Endotheliale NO-Synthase (eNOS), Faktor V (F5), 5,10-Methylentetrahydrofolsäure-Reduktase (MTHFR), Cholesterinester-Transferprotein (CETP), Apolipoprotein E (ApoE), Prothrombin (F2) und Lipoproteinlipase (LPL) erfolgreich etabliert werden. Die Präzision des Biochips wurde anhand der Echtzeit-PCR und der Sequenzierung nachgewiesen. rnDer innovative Mikroarray ermöglicht eine einfache, schnelle und kosteneffektive Genotypisierung von wichtigen Allelen. Viele klinisch relevante Variationen für Atherosklerose können nun in nur einem Test überprüft werden. Zukünftige Studien müssen zeigen, ob die Methode eine Vorhersage über den Ausbruch der Erkrankung und eine gezielte Therapie ermöglicht. Dies wäre ein erster Schritt in Richtung präventive und personalisierter Medizin für Atherosklerose.rn
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Drug hypersensitivity research has progressed enormously in recent years, and a greater understanding of mechanisms has contributed to improved drug safety. Progress has been made in genetics, enabling personalized medicine for certain drugs, and in understanding drug interactions with the immune system. In a recent meeting in Rome, the clinical, chemical, pharmacologic, immunologic, and genetic aspects of drug hypersensitivity were discussed, and certain aspects are briefly summarized here. Small chemicals, including drugs, can induce immune reactions by binding as a hapten to a carrier protein. Park (Liverpool, England) demonstrated (1) that drug haptens bind to protein in patients in a highly restricted manner and (2) that irreversibly modified carrier proteins are able to stimulate CD4(+) and CD8(+) T cells from hypersensitive patients. Drug haptens might also stimulate cells of the innate immune system, in particular dendritic cells, and thus give rise to a complex and complete immune reaction. Many drugs do not have hapten-like characteristics but might gain them on metabolism (so-called prohaptens). The group of Naisbitt found that the stimulation of dendritic cells and T cells can occur as a consequence of the transformation of a prohapten to a hapten in antigen-presenting cells and as such explain the immune-stimulatory capacity of prohaptens. The striking association between HLA-B alleles and the development of certain drug reactions was discussed in detail. Mallal (Perth, Australia) elegantly described a highly restricted HLA-B∗5701-specific T-cell response in abacavir-hypersensitive patients and healthy volunteers expressing HLA-B∗5701 but not closely related alleles. Expression of HLA-B∗1502 is a marker known to be necessary but not sufficient to predict carbamazepine-induced Stevens-Johnson syndrome/toxic epidermal necrolysis in Han Chinese. The group of Chen and Hong (Taiwan) described the possible "missing link" because they showed that the presence of certain T-cell receptor (TCR) clonotypes was necessary to elicit T-cell responses to carbamazepine. The role of TCRs in drug binding was also emphasized by Pichler (Bern, Switzerland). Following up on their "pharmacological interactions of drugs with immune receptors" concept (p-i concept), namely that drugs can bind directly to TCRs, MHC molecules, or both and thereby stimulate T cells, they looked for drug-binding sites for the drug sulfamethoxazole in drug-specific TCRs: modeling revealed up to 7 binding sites on the CDR3 and CDR2 regions of TCR Vα and Vβ. Among many other presentations, the important role of regulatory T cells in drug hypersensitivity was addressed.
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Translating pharmacogenetics to clinical practice has been particularly challenging in the context of pain, due to the complexity of this multifaceted phenotype and the overall subjective nature of pain perception and response to analgesia. Overall, numerous genes involved with the pharmacokinetics and dynamics of opioids response are candidate genes in the context of opioid analgesia. The clinical relevance of CYP2D6 genotyping to predict analgesic outcomes is still relatively unknown; the two extremes in CYP2D6 genotype (ultrarapid and poor metabolism) seem to predict pain response and/or adverse effects. Overall, the level of evidence linking genetic variability (CYP2D6 and CYP3A4) to oxycodone response and phenotype (altered biotransformation of oxycodone into oxymorphone and overall clearance of oxycodone and oxymorphone) is strong; however, there has been no randomized clinical trial on the benefits of genetic testing prior to oxycodone therapy. On the other hand, predicting the analgesic response to morphine based on pharmacogenetic testing is more complex; though there was hope that simple genetic testing would allow tailoring morphine doses to provide optimal analgesia, this is unlikely to occur. A variety of polymorphisms clearly influence pain perception and behavior in response to pain. However, the response to analgesics also differs depending on the pain modality and the potential for repeated noxious stimuli, the opioid prescribed, and even its route of administration.
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Physicians and scientists use a broad spectrum of terms to classify contrast media (CM)-induced adverse reactions. In particular, the designation of hypersensitivity reactions is quite varied. Consequently, comparisons of different papers dealing with this subject are difficult or even impossible. Moreover, general descriptions may lead to problems in understanding reactions in patients with a history of adverse CM-reactions, and in efficiently managing these patients. Therefore, the goal of this paper is to suggest an easy system to clearly classify these reactions. The proposed three-step systems (3SS) is built up as follows: step 1 exactly describes the clinical features, including their severity; step 2 categorizes the time point of the onset (immediate or nonimmediate); and step 3 generally classifies the reaction (hypersensitivity or nonhypersensitivity reaction). The 3SS may facilitate better understanding of the clinical manifestations of adverse CM reactions and may support the prevention of these reactions on the basis of personalized medicine approaches.
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When comparing a new treatment with a control in a randomized clinical study, the treatment effect is generally assessed by evaluating a summary measure over a specific study population. The success of the trial heavily depends on the choice of such a population. In this paper, we show a systematic, effective way to identify a promising population, for which the new treatment is expected to have a desired benefit, using the data from a current study involving similar comparator treatments. Specifically, with the existing data we first create a parametric scoring system using multiple covariates to estimate subject-specific treatment differences. Using this system, we specify a desired level of treatment difference and create a subgroup of patients, defined as those whose estimated scores exceed this threshold. An empirically calibrated group-specific treatment difference curve across a range of threshold values is constructed. The population of patients with any desired level of treatment benefit can then be identified accordingly. To avoid any ``self-serving'' bias, we utilize a cross-training-evaluation method for implementing the above two-step procedure. Lastly, we show how to select the best scoring system among all competing models. The proposals are illustrated with the data from two clinical trials in treating AIDS and cardiovascular diseases. Note that if we are not interested in designing a new study for comparing similar treatments, the new procedure can also be quite useful for the management of future patients who would receive nontrivial benefits to compensate for the risk or cost of the new treatment.
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The basis of personalized medicine in oncology is the prediction of an individual's risk of relapse and death from disease. The presence of tumor budding (TB) at the tumor-host interface of gastrointestinal cancers has been recognized as a hallmark of unfavorable disease biology. TB is defined as the presence of dedifferentiated cells or small clusters of up to five cells at the tumor invasive front and can be observed in aggressive carcinomas of the esophagus, stomach, pancreas, ampulla, colon, and rectum. Presence of TB reproducibly correlates with advanced tumor stage, frequent lymphovascular invasion, nodal, and distant metastasis. The UICC has officially recognized TB as additional independent prognostic factor in cancers of the colon and rectum. Recent studies have also characterized TB as a promising prognostic indicator for clinical management of esophageal squamous cell carcinoma, adenocarcinoma of the gastro-esophageal junction, and gastric adenocarcinoma. However, several important issues have to be addressed for application in daily diagnostic practice: (1) validation of prognostic scoring systems for TB in large, multi-center studies, (2) consensus on the optimal assessment method, and (3) inter-observer reproducibility. This review provides a comprehensive analysis of TB in cancers of the upper gastrointestinal tract including critical appraisal of perspectives for further study.
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At issue is whether or not isolated DNA is patent eligible under the U.S. Patent Law and the implications of that determination on public health. The U.S. Patent and Trademark Office has issued patents on DNA since the 1980s, and scientists and researchers have proceeded under that milieu since that time. Today, genetic research and testing related to the human breast cancer genes BRCA1 and BRCA2 is conducted within the framework of seven patents that were issued to Myriad Genetics and the University of Utah Research Foundation between 1997 and 2000. In 2009, suit was filed on behalf of multiple researchers, professional associations and others to invalidate fifteen of the claims underlying those patents. The Court of Appeals for the Federal Circuit, which hears patent cases, has invalidated claims for analyzing and comparing isolated DNA but has upheld claims to isolated DNA. The specific issue of whether isolated DNA is patent eligible is now before the Supreme Court, which is expected to decide the case by year's end. In this work, a systematic review was performed to determine the effects of DNA patents on various stakeholders and, ultimately, on public health; and to provide a legal analysis of the patent eligibility of isolated DNA and the likely outcome of the Supreme Court's decision. ^ A literature review was conducted to: first, identify principle stakeholders with an interest in patent eligibility of the isolated DNA sequences BRCA1 and BRCA2; and second, determine the effect of the case on those stakeholders. Published reports that addressed gene patents, the Myriad litigation, and implications of gene patents on stakeholders were included. Next, an in-depth legal analysis of the patent eligibility of isolated DNA and methods for analyzing it was performed pursuant to accepted methods of legal research and analysis based on legal briefs, federal law and jurisprudence, scholarly works and standard practice legal analysis. ^ Biotechnology, biomedical and clinical research, access to health care, and personalized medicine were identified as the principle stakeholders and interests herein. Many experts believe that the patent eligibility of isolated DNA will not greatly affect the biotechnology industry insofar as genetic testing is concerned; unlike for therapeutics, genetic testing does not require tremendous resources or lead time. The actual impact on biomedical researchers is uncertain, with greater impact expected for researchers whose work is intended for commercial purposes (versus basic science). The impact on access to health care has been surprisingly difficult to assess; while invalidating gene patents might be expected to decrease the cost of genetic testing and improve access to more laboratories and physicians' offices that provide the test, a 2010 study on the actual impact was inconclusive. As for personalized medicine, many experts believe that the availability of personalized medicine is ultimately a public policy issue for Congress, not the courts. ^ Based on the legal analysis performed in this work, this writer believes the Supreme Court is likely to invalidate patents on isolated DNA whose sequences are found in nature, because these gene sequences are a basic tool of scientific and technologic work and patents on isolated DNA would unduly inhibit their future use. Patents on complementary DNA (cDNA) are expected to stand, however, based on the human intervention required to craft cDNA and the product's distinction from the DNA found in nature. ^ In the end, the solution as to how to address gene patents may lie not in jurisprudence but in a fundamental change in business practices to provide expanded licenses to better address the interests of the several stakeholders. ^
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Antecedentes Europa vive una situación insostenible. Desde el 2008 se han reducido los recursos de los gobiernos a raíz de la crisis económica. El continente Europeo envejece con ritmo constante al punto que se prevé que en 2050 habrá sólo dos trabajadores por jubilado [54]. A esta situación se le añade el aumento de la incidencia de las enfermedades crónicas, relacionadas con el envejecimiento, cuyo coste puede alcanzar el 7% del PIB de un país [51]. Es necesario un cambio de paradigma. Una nueva manera de cuidar de la salud de las personas: sustentable, eficaz y preventiva más que curativa. Algunos estudios abogan por el cuidado personalizado de la salud (pHealth). En este modelo las prácticas médicas son adaptadas e individualizadas al paciente, desde la detección de los factores de riesgo hasta la personalización de los tratamientos basada en la respuesta del individuo [81]. El cuidado personalizado de la salud está asociado a menudo al uso de las tecnologías de la información y comunicación (TICs) que, con su desarrollo exponencial, ofrecen oportunidades interesantes para la mejora de la salud. El cambio de paradigma hacia el pHealth está lentamente ocurriendo, tanto en el ámbito de la investigación como en la industria, pero todavía no de manera significativa. Existen todavía muchas barreras relacionadas a la economía, a la política y la cultura. También existen barreras puramente tecnológicas, como la falta de sistemas de información interoperables [199]. A pesar de que los aspectos de interoperabilidad están evolucionando, todavía hace falta un diseño de referencia especialmente direccionado a la implementación y el despliegue en gran escala de sistemas basados en pHealth. La presente Tesis representa un intento de organizar la disciplina de la aplicación de las TICs al cuidado personalizado de la salud en un modelo de referencia, que permita la creación de plataformas de desarrollo de software para simplificar tareas comunes de desarrollo en este dominio. Preguntas de investigación RQ1 >Es posible definir un modelo, basado en técnicas de ingeniería del software, que represente el dominio del cuidado personalizado de la salud de una forma abstracta y representativa? RQ2 >Es posible construir una plataforma de desarrollo basada en este modelo? RQ3 >Esta plataforma ayuda a los desarrolladores a crear sistemas pHealth complejos e integrados? Métodos Para la descripción del modelo se adoptó el estándar ISO/IEC/IEEE 42010por ser lo suficientemente general y abstracto para el amplio enfoque de esta tesis [25]. El modelo está definido en varias partes: un modelo conceptual, expresado a través de mapas conceptuales que representan las partes interesadas (stakeholders), los artefactos y la información compartida; y escenarios y casos de uso para la descripción de sus funcionalidades. El modelo fue desarrollado de acuerdo a la información obtenida del análisis de la literatura, incluyendo 7 informes industriales y científicos, 9 estándares, 10 artículos en conferencias, 37 artículos en revistas, 25 páginas web y 5 libros. Basándose en el modelo se definieron los requisitos para la creación de la plataforma de desarrollo, enriquecidos por otros requisitos recolectados a través de una encuesta realizada a 11 ingenieros con experiencia en la rama. Para el desarrollo de la plataforma, se adoptó la metodología de integración continua [74] que permitió ejecutar tests automáticos en un servidor y también desplegar aplicaciones en una página web. En cuanto a la metodología utilizada para la validación se adoptó un marco para la formulación de teorías en la ingeniería del software [181]. Esto requiere el desarrollo de modelos y proposiciones que han de ser validados dentro de un ámbito de investigación definido, y que sirvan para guiar al investigador en la búsqueda de la evidencia necesaria para justificarla. La validación del modelo fue desarrollada mediante una encuesta online en tres rondas con un número creciente de invitados. El cuestionario fue enviado a 134 contactos y distribuido en algunos canales públicos como listas de correo y redes sociales. El objetivo era evaluar la legibilidad del modelo, su nivel de cobertura del dominio y su potencial utilidad en el diseño de sistemas derivados. El cuestionario incluía preguntas cuantitativas de tipo Likert y campos para recolección de comentarios. La plataforma de desarrollo fue validada en dos etapas. En la primera etapa se utilizó la plataforma en un experimento a pequeña escala, que consistió en una sesión de entrenamiento de 12 horas en la que 4 desarrolladores tuvieron que desarrollar algunos casos de uso y reunirse en un grupo focal para discutir su uso. La segunda etapa se realizó durante los tests de un proyecto en gran escala llamado HeartCycle [160]. En este proyecto un equipo de diseñadores y programadores desarrollaron tres aplicaciones en el campo de las enfermedades cardio-vasculares. Una de estas aplicaciones fue testeada en un ensayo clínico con pacientes reales. Al analizar el proyecto, el equipo de desarrollo se reunió en un grupo focal para identificar las ventajas y desventajas de la plataforma y su utilidad. Resultados Por lo que concierne el modelo que describe el dominio del pHealth, la parte conceptual incluye una descripción de los roles principales y las preocupaciones de los participantes, un modelo de los artefactos TIC que se usan comúnmente y un modelo para representar los datos típicos que son necesarios formalizar e intercambiar entre sistemas basados en pHealth. El modelo funcional incluye un conjunto de 18 escenarios, repartidos en: punto de vista de la persona asistida, punto de vista del cuidador, punto de vista del desarrollador, punto de vista de los proveedores de tecnologías y punto de vista de las autoridades; y un conjunto de 52 casos de uso repartidos en 6 categorías: actividades de la persona asistida, reacciones del sistema, actividades del cuidador, \engagement" del usuario, actividades del desarrollador y actividades de despliegue. Como resultado del cuestionario de validación del modelo, un total de 65 personas revisó el modelo proporcionando su nivel de acuerdo con las dimensiones evaluadas y un total de 248 comentarios sobre cómo mejorar el modelo. Los conocimientos de los participantes variaban desde la ingeniería del software (70%) hasta las especialidades médicas (15%), con declarado interés en eHealth (24%), mHealth (16%), Ambient Assisted Living (21%), medicina personalizada (5%), sistemas basados en pHealth (15%), informática médica (10%) e ingeniería biomédica (8%) con una media de 7.25_4.99 años de experiencia en estas áreas. Los resultados de la encuesta muestran que los expertos contactados consideran el modelo fácil de leer (media de 1.89_0.79 siendo 1 el valor más favorable y 5 el peor), suficientemente abstracto (1.99_0.88) y formal (2.13_0.77), con una cobertura suficiente del dominio (2.26_0.95), útil para describir el dominio (2.02_0.7) y para generar sistemas más específicos (2_0.75). Los expertos también reportan un interés parcial en utilizar el modelo en su trabajo (2.48_0.91). Gracias a sus comentarios, el modelo fue mejorado y enriquecido con conceptos que faltaban, aunque no se pudo demonstrar su mejora en las dimensiones evaluadas, dada la composición diferente de personas en las tres rondas de evaluación. Desde el modelo, se generó una plataforma de desarrollo llamada \pHealth Patient Platform (pHPP)". La plataforma desarrollada incluye librerías, herramientas de programación y desarrollo, un tutorial y una aplicación de ejemplo. Se definieron cuatro módulos principales de la arquitectura: el Data Collection Engine, que permite abstraer las fuentes de datos como sensores o servicios externos, mapeando los datos a bases de datos u ontologías, y permitiendo interacción basada en eventos; el GUI Engine, que abstrae la interfaz de usuario en un modelo de interacción basado en mensajes; y el Rule Engine, que proporciona a los desarrolladores un medio simple para programar la lógica de la aplicación en forma de reglas \if-then". Después de que la plataforma pHPP fue utilizada durante 5 años en el proyecto HeartCycle, 5 desarrolladores fueron reunidos en un grupo de discusión para analizar y evaluar la plataforma. De estas evaluaciones se concluye que la plataforma fue diseñada para encajar las necesidades de los ingenieros que trabajan en la rama, permitiendo la separación de problemas entre las distintas especialidades, y simplificando algunas tareas de desarrollo como el manejo de datos y la interacción asíncrona. A pesar de ello, se encontraron algunos defectos a causa de la inmadurez de algunas tecnologías empleadas, y la ausencia de algunas herramientas específicas para el dominio como el procesado de datos o algunos protocolos de comunicación relacionados con la salud. Dentro del proyecto HeartCycle la plataforma fue utilizada para el desarrollo de la aplicación \Guided Exercise", un sistema TIC para la rehabilitación de pacientes que han sufrido un infarto del miocardio. El sistema fue testeado en un ensayo clínico randomizado en el cual a 55 pacientes se les dio el sistema para su uso por 21 semanas. De los resultados técnicos del ensayo se puede concluir que, a pesar de algunos errores menores prontamente corregidos durante el estudio, la plataforma es estable y fiable. Conclusiones La investigación llevada a cabo en esta Tesis y los resultados obtenidos proporcionan las respuestas a las tres preguntas de investigación que motivaron este trabajo: RQ1 Se ha desarrollado un modelo para representar el dominio de los sistemas personalizados de salud. La evaluación hecha por los expertos de la rama concluye que el modelo representa el dominio con precisión y con un balance apropiado entre abstracción y detalle. RQ2 Se ha desarrollado, con éxito, una plataforma de desarrollo basada en el modelo. RQ3 Se ha demostrado que la plataforma es capaz de ayudar a los desarrolladores en la creación de software pHealth complejos. Las ventajas de la plataforma han sido demostradas en el ámbito de un proyecto de gran escala, aunque el enfoque genérico adoptado indica que la plataforma podría ofrecer beneficios también en otros contextos. Los resultados de estas evaluaciones ofrecen indicios de que, ambos, el modelo y la plataforma serán buenos candidatos para poderse convertir en una referencia para futuros desarrollos de sistemas pHealth. ABSTRACT Background Europe is living in an unsustainable situation. The economic crisis has been reducing governments' economic resources since 2008 and threatening social and health systems, while the proportion of older people in the European population continues to increase so that it is foreseen that in 2050 there will be only two workers per retiree [54]. To this situation it should be added the rise, strongly related to age, of chronic diseases the burden of which has been estimated to be up to the 7% of a country's gross domestic product [51]. There is a need for a paradigm shift, the need for a new way of caring for people's health, shifting the focus from curing conditions that have arisen to a sustainable and effective approach with the emphasis on prevention. Some advocate the adoption of personalised health care (pHealth), a model where medical practices are tailored to the patient's unique life, from the detection of risk factors to the customization of treatments based on each individual's response [81]. Personalised health is often associated to the use of Information and Communications Technology (ICT), that, with its exponential development, offers interesting opportunities for improving healthcare. The shift towards pHealth is slowly taking place, both in research and in industry, but the change is not significant yet. Many barriers still exist related to economy, politics and culture, while others are purely technological, like the lack of interoperable information systems [199]. Though interoperability aspects are evolving, there is still the need of a reference design, especially tackling implementation and large scale deployment of pHealth systems. This thesis contributes to organizing the subject of ICT systems for personalised health into a reference model that allows for the creation of software development platforms to ease common development issues in the domain. Research questions RQ1 Is it possible to define a model, based on software engineering techniques, for representing the personalised health domain in an abstract and representative way? RQ2 Is it possible to build a development platform based on this model? RQ3 Does the development platform help developers create complex integrated pHealth systems? Methods As method for describing the model, the ISO/IEC/IEEE 42010 framework [25] is adopted for its generality and high level of abstraction. The model is specified in different parts: a conceptual model, which makes use of concept maps, for representing stakeholders, artefacts and shared information, and in scenarios and use cases for the representation of the functionalities of pHealth systems. The model was derived from literature analysis, including 7 industrial and scientific reports, 9 electronic standards, 10 conference proceedings papers, 37 journal papers, 25 websites and 5 books. Based on the reference model, requirements were drawn for building the development platform enriched with a set of requirements gathered in a survey run among 11 experienced engineers. For developing the platform, the continuous integration methodology [74] was adopted which allowed to perform automatic tests on a server and also to deploy packaged releases on a web site. As a validation methodology, a theory building framework for SW engineering was adopted from [181]. The framework, chosen as a guide to find evidence for justifying the research questions, imposed the creation of theories based on models and propositions to be validated within a scope. The validation of the model was conducted as an on-line survey in three validation rounds, encompassing a growing number of participants. The survey was submitted to 134 experts of the field and on some public channels like relevant mailing lists and social networks. Its objective was to assess the model's readability, its level of coverage of the domain and its potential usefulness in the design of actual, derived systems. The questionnaires included quantitative Likert scale questions and free text inputs for comments. The development platform was validated in two scopes. As a small-scale experiment, the platform was used in a 12 hours training session where 4 developers had to perform an exercise consisting in developing a set of typical pHealth use cases At the end of the session, a focus group was held to identify benefits and drawbacks of the platform. The second validation was held as a test-case study in a large scale research project called HeartCycle the aim of which was to develop a closed-loop disease management system for heart failure and coronary heart disease patients [160]. During this project three applications were developed by a team of programmers and designers. One of these applications was tested in a clinical trial with actual patients. At the end of the project, the team was interviewed in a focus group to assess the role the platform had within the project. Results For what regards the model that describes the pHealth domain, its conceptual part includes a description of the main roles and concerns of pHealth stakeholders, a model of the ICT artefacts that are commonly adopted and a model representing the typical data that need to be formalized among pHealth systems. The functional model includes a set of 18 scenarios, divided into assisted person's view, caregiver's view, developer's view, technology and services providers' view and authority's view, and a set of 52 Use Cases grouped in 6 categories: assisted person's activities, system reactions, caregiver's activities, user engagement, developer's activities and deployer's activities. For what concerns the validation of the model, a total of 65 people participated in the online survey providing their level of agreement in all the assessed dimensions and a total of 248 comments on how to improve and complete the model. Participants' background spanned from engineering and software development (70%) to medical specialities (15%), with declared interest in the fields of eHealth (24%), mHealth (16%), Ambient Assisted Living (21%), Personalized Medicine (5%), Personal Health Systems (15%), Medical Informatics (10%) and Biomedical Engineering (8%) with an average of 7.25_4.99 years of experience in these fields. From the analysis of the answers it is possible to observe that the contacted experts considered the model easily readable (average of 1.89_0.79 being 1 the most favourable scoring and 5 the worst), sufficiently abstract (1.99_0.88) and formal (2.13_0.77) for its purpose, with a sufficient coverage of the domain (2.26_0.95), useful for describing the domain (2.02_0.7) and for generating more specific systems (2_0.75) and they reported a partial interest in using the model in their job (2.48_0.91). Thanks to their comments, the model was improved and enriched with concepts that were missing at the beginning, nonetheless it was not possible to prove an improvement among the iterations, due to the diversity of the participants in the three rounds. From the model, a development platform for the pHealth domain was generated called pHealth Patient Platform (pHPP). The platform includes a set of libraries, programming and deployment tools, a tutorial and a sample application. The main four modules of the architecture are: the Data Collection Engine, which allows abstracting sources of information like sensors or external services, mapping data to databases and ontologies, and allowing event-based interaction and filtering, the GUI Engine, which abstracts the user interface in a message-like interaction model, the Workow Engine, which allows programming the application's user interaction ows with graphical workows, and the Rule Engine, which gives developers a simple means for programming the application's logic in the form of \if-then" rules. After the 5 years experience of HeartCycle, partially programmed with pHPP, 5 developers were joined in a focus group to discuss the advantages and drawbacks of the platform. The view that emerged from the training course and the focus group was that the platform is well-suited to the needs of the engineers working in the field, it allowed the separation of concerns among the different specialities and it simplified some common development tasks like data management and asynchronous interaction. Nevertheless, some deficiencies were pointed out in terms of a lack of maturity of some technological choices, and for the absence of some domain-specific tools, e.g. for data processing or for health-related communication protocols. Within HeartCycle, the platform was used to develop part of the Guided Exercise system, a composition of ICT tools for the physical rehabilitation of patients who suffered from myocardial infarction. The system developed using the platform was tested in a randomized controlled clinical trial, in which 55 patients used the system for 21 weeks. The technical results of this trial showed that the system was stable and reliable. Some minor bugs were detected, but these were promptly corrected using the platform. This shows that the platform, as well as facilitating the development task, can be successfully used to produce reliable software. Conclusions The research work carried out in developing this thesis provides responses to the three three research questions that were the motivation for the work. RQ1 A model was developed representing the domain of personalised health systems, and the assessment of experts in the field was that it represents the domain accurately, with an appropriate balance between abstraction and detail. RQ2 A development platform based on the model was successfully developed. RQ3 The platform has been shown to assist developers create complex pHealth software. This was demonstrated within the scope of one large-scale project, but the generic approach adopted provides indications that it would offer benefits more widely. The results of these evaluations provide indications that both the model and the platform are good candidates for being a reference for future pHealth developments.
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Parte de la investigación biomédica actual se encuentra centrada en el análisis de datos heterogéneos. Estos datos pueden tener distinto origen, estructura, y semántica. Gran cantidad de datos de interés para los investigadores se encuentran en bases de datos públicas, que recogen información de distintas fuentes y la ponen a disposición de la comunidad de forma gratuita. Para homogeneizar estas fuentes de datos públicas con otras de origen privado, existen diversas herramientas y técnicas que permiten automatizar los procesos de homogeneización de datos heterogéneos. El Grupo de Informática Biomédica (GIB) [1] de la Universidad Politécnica de Madrid colabora en el proyecto europeo P-medicine [2], cuya finalidad reside en el desarrollo de una infraestructura que facilite la evolución de los procedimientos médicos actuales hacia la medicina personalizada. Una de las tareas enmarcadas en el proyecto P-medicine que tiene asignado el grupo consiste en elaborar herramientas que ayuden a usuarios en el proceso de integración de datos contenidos en fuentes de información heterogéneas. Algunas de estas fuentes de información son bases de datos públicas de ámbito biomédico contenidas en la plataforma NCBI [3] (National Center for Biotechnology Information). Una de las herramientas que el grupo desarrolla para integrar fuentes de datos es Ontology Annotator. En una de sus fases, la labor del usuario consiste en recuperar información de una base de datos pública y seleccionar de forma manual los resultados relevantes. Para automatizar el proceso de búsqueda y selección de resultados relevantes, por un lado existe un gran interés en conseguir generar consultas que guíen hacia resultados lo más precisos y exactos como sea posible, por otro lado, existe un gran interés en extraer información relevante de elevadas cantidades de documentos, lo cual requiere de sistemas que analicen y ponderen los datos que caracterizan a los mismos. En el campo informático de la inteligencia artificial, dentro de la rama de la recuperación de la información, existen diversos estudios acerca de la expansión de consultas a partir de retroalimentación relevante que podrían ser de gran utilidad para dar solución a la cuestión. Estos estudios se centran en técnicas para reformular o expandir la consulta inicial utilizando como realimentación los resultados que en una primera instancia fueron relevantes para el usuario, de forma que el nuevo conjunto de resultados tenga mayor proximidad con los que el usuario realmente desea. El objetivo de este trabajo de fin de grado consiste en el estudio, implementación y experimentación de métodos que automaticen el proceso de extracción de información trascendente de documentos, utilizándola para expandir o reformular consultas. De esta forma se pretende mejorar la precisión y el ranking de los resultados asociados. Dichos métodos serán integrados en la herramienta Ontology Annotator y enfocados a la fuente de datos de PubMed [4].---ABSTRACT---Part of the current biomedical research is focused on the analysis of heterogeneous data. These data may have different origin, structure and semantics. A big quantity of interesting data is contained in public databases which gather information from different sources and make it open and free to be used by the community. In order to homogenize thise sources of public data with others which origin is private, there are some tools and techniques that allow automating the processes of integration heterogeneous data. The biomedical informatics group of the Universidad Politécnica de Madrid cooperates with the European project P-medicine which main purpose is to create an infrastructure and models to facilitate the transition from current medical practice to personalized medicine. One of the tasks of the project that the group is in charge of consists on the development of tools that will help users in the process of integrating data from diverse sources. Some of the sources are biomedical public data bases from the NCBI platform (National Center for Biotechnology Information). One of the tools in which the group is currently working on for the integration of data sources is called the Ontology Annotator. In this tool there is a phase in which the user has to retrieve information from a public data base and select the relevant data contained in it manually. For automating the process of searching and selecting data on the one hand, there is an interest in automatically generating queries that guide towards the more precise results as possible. On the other hand, there is an interest on retrieve relevant information from large quantities of documents. The solution requires systems that analyze and weigh the data allowing the localization of the relevant items. In the computer science field of the artificial intelligence, in the branch of information retrieval there are diverse studies about the query expansion from relevance feedback that could be used to solve the problem. The main purpose of this studies is to obtain a set of results that is the closer as possible to the information that the user really wants to retrieve. In order to reach this purpose different techniques are used to reformulate or expand the initial query using a feedback the results that where relevant for the user, with this method, the new set of results will have more proximity with the ones that the user really desires. The goal of this final dissertation project consists on the study, implementation and experimentation of methods that automate the process of extraction of relevant information from documents using this information to expand queries. This way, the precision and the ranking of the results associated will be improved. These methods will be integrated in the Ontology Annotator tool and will focus on the PubMed data source.
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Introdução: A identificação de variantes genéticas que predispõem a maior susceptibilidade à dependência à nicotina pode ser importante para a prevenção e o tratamento do tabagismo. No contexto de medicina personalizada, os principais objetivos do presente estudo foram avaliar se polimorfismos nos genes CHRNA2, CHRNA3, CHRNA5 e CHRNB3 estão associados com o nível de dependência em indivíduos fumantes e com o resultado do tratamento antitabágico. Métodos: Estudo de coorte com 1049 pacientes fumantes que receberam tratamento farmacológico (vareniclina, vareniclina e bupropiona, bupropiona e/ou terapia de reposição nicotínica). O sucesso na cessação tabágica foi considerado para os pacientes que completaram 6 meses de abstinência contínua. O teste de Fagerström para a dependência à nicotina (FTND) e o escore de consumo situacional Issa foram utilizados para avaliar a dependência à nicotina. A escala de conforto PAF foi utilizada para avaliar o conforto do paciente durante o tratamento. Os polimorfismos CHRNA2 rs2472553, CHRNA3 rs1051730, CHRNA5 rs16969968, CHRNA5 rs2036527 e CHRNB3 rs6474413 foram genotipados pela análise da curva de melting. Resultados: As mulheres portadoras dos genótipos GA e AA para os polimorfismos CHRNA5 rs16969968 e rs2036527 obtiveram maior taxa de sucesso no tratamento antitabagismo: 44,0% e 56,3% (rs16969968), 41,5% e 56,5% (rs2036527), respectivamente; em comparação com as mulheres portadoras do genótipo GG: 35,7% (rs16969968) e 34,8% (rs2036527), (P=0,03; n=389; P=0,01; n=391). Os genótipos GA ou AA para os rs16969968 e rs2036527 foram associados com maior OR para o sucesso em mulheres (OR=1,63; IC 95%=1,04-2,54; P=0,03 e OR=1,59; IC 95%=1,02-2,48; P=0,04; respectivamente), em um modelo multivariado. Não foi encontrada associação dos polimorfismos no gene CHRNA5 com o escore de FTND. Para os polimorfismos CHRNA2 rs2472553, CHRNA3 rs1051730 e CHRNB3 rs6474413 não foram encontradas associações significativas com os fenótipos estudados. Conclusão: Os polimorfismos rs16969968 e rs2036527 no gene CHRNA5 foram associados com maior taxa de sucesso no tratamento antitabagismo em mulheres. Estes resultados podem contribuir com avanços na terapêutica baseada em medicina personalizada
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