Visuelles Studienmanagement mit dem Trial Outline Builder in ObTiMA

Die heutige klinische Landschaft ist ein Spannungsfeld aus Kosteneffizienz, umfangreichen Dokumentationspflichten, Personalmangel und vieler weiterer Herausforderungen in der Behandlung von Patienten. Mithilfe der heutigen Computertechnologie und ihren Möglichkeiten wird trotz des eingeschränkten Zeitpensums der behandelnden Ärzte versucht, eine möglichst auf den einzelnen Patienten abgestimmte Behandlung zu ermöglichen. Damit in der personalisierten Medizin auf die für den jeweiligen Patienten am besten passende Therapie zur Bekämpfung seiner Erkrankung zurückgegriffen werden kann, sind im Vorfeld klinische Studien über neue Medikamente und Therapieformen notwendig. Diese klinischen Studien benötigen viel Vorbereitungszeit, da zunächst ein Studienprotokoll inklusive eines Behandlungsplans mit entsprechenden Fragestellungen entwickelt werden muss. In größeren Studien erfordert dies den Austausch zwischen Medizinern aus verschiedenen Fachbereichen. Um diesen Planungsmitgliedern schon zu Beginn eine gemeinsame Diskussionsgrundlage auf Basis eines grafischen Behandlungsplans zu ermöglichen, kann der in dieser Arbeit vorgestellte Trial Outline Builder (TOB) dienen. Damit die Anwendbar- und Nützlichkeit dieser Technologie nicht schon in der Anfangsphase einer Studie endet, wurde sie auf das Studienmanagementsystem Ontology-based Trial Management Application (ObTiMA) angepasst und in diese integriert. Für die vorliegende Arbeit wurde im ersten Schritt ObTiMA und der Trial Outline Builder auf den gleichen technischen Stand gebracht. Somit wurde die in ObTiMA vorhandene Struktur von Study Events und ihren Case Report Form (CRF) Fragebögen im TOB nutzbar gemacht. Dies war notwendig geworden, da sich die beiden Anwendungen über die Jahre auseinanderentwickelt hatten. Im zweiten Schritt wurden Kommunikationsschnittstellen zwischen ObTiMA und dem TOB geschaffen, um erstellte Behandlungspläne speichern und erneut laden zu können. Dafür wurde die Patientenansicht des TOBs mit der Möglichkeit erweitert, medizinische Events über einen Representational State Transfer (REST) Service in ObTiMA zu aktivieren. Dies hatte weitreichende Änderungen am ObTiMA Quellcode zur Folge, da dieser bislang ausschließlich für Benutzersessions ausgelegt war und nun auch über das statuslose REST ausführbar sein musste. Während dieser Entwicklung war es immer wieder erforderlich neu entdeckte Bugs im TOB zu korrigieren, die zu einer nicht geladenen TOB Seite oder zu defekten Behandlungsplänen nach der Speicherung in der Datenbank führte. Im letzten Arbeitsteil wurde eine durch Anwender leicht ausführbare Randomisierung von Patienten nach der Minimisationsmethode realisiert, die die jeweiligen Stärken der beiden Anwendungen nutzt. Mit dem Ergebnis dieser Arbeit können nun die in der Studiendesignphase in ObTiMA erstellten Study Events mit einzelnen medizinischen Events zu einem zeitbasierten Behandlungsplan verknüpft werden. Nach Studienstart werden für die Patienten zusätzlich neben der geplanten Behandlung auch eine persönliche Timeline mit allen medizinischen Events angezeigt. Dadurch erhält das Studienpersonal auf einen Blick eine grafische Übersicht über den realen Behandlungsverlauf des jeweiligen Patienten inklusive unerwünschter Ereignisse wie Serious Adverse Events (SAEs), Suspected Unexpected Serious Adverse Reactions (SUSARs), Notoperationen, etc. Im klinischen Alltag kann der behandelnde Arzt damit leichter und effizienter die erfasste Studiendaten auffinden. Diese Verbesserungen dürften in der zukünftigen Anwendung des Trial Outline Builders sowohl dem medizinischen Personal als auch den Patienten zu Gute kommen.Today's clinical landscape is an area of conflict between cost efficiency, extensive documentation requirements, lack of personnel and many other challenges in the treatment of patients. With the help of today's computer technology and its possibilities, an attempt is being made to enable treatment to be tailored as closely as possible to the individual patient, especially, in times when time is very limited for the physicians. Clinical studies on new drugs and forms of therapy have to be performed in advance so that personalised medicine can use the therapy best suited to the patient's illness. These clinical studies require a lot of preparation time, since a Trial Master Protocol must first be developed, including the corresponding research questions and a treatment plan. In larger studies this requires the exchange of information between many physicians from different departments. In order to provide these planning members with a common basis for discussion based on a visual treatment plan right from the start, the Trial Outline Builder presented in this thesis can be used. To ensure that the applicability and usefulness of this technology does not end in the initial phase of a study, it was adapted to and integrated into the Ontology-based Trial Management Application (ObTiMA). In the first step, ObTiMA and the Trial Outline Builder (TOB) were brought to the same level by unifying the structure of study events and Case Report Form (CRF) questionnaires. This had become necessary since the two applications developed into kind of different direction over the past years. In the second step, communication interfaces between ObTiMA and the Trial Outline Builder were implemented for saving and loading treatment plans. Later, the pa-tient view of the TOB was extended with the possibility to activate medical events via a Rep-resentational State Transfer (REST) service in ObTiMA. This resulted in extensive changes in the ObTiMA source code, since it previously was only supposed to work with user sessions. Now this code works with stateless REST services as well. During this whole transformation process, it was often necessary to correct several breaking bugs in the original TOB code, which led to unloaded pages or broken treatment plans after saving. In the last step of this work, an easy user-executable randomization of patients (minimization method) was implemented, which combined the strengths of both applications. With the result of this work, the CRF questionnaires created in the study design phase in ObTiMA can now be linked with individual medical events to form a time-based treatment plan. After the start of the study, patients have a personal timeline with all medical events in addi-tion to the planned treatment. This provides the study staff with a visual overview of the actual treatment process of the respective patient at a glance, including unwanted events such as Serious Adverse Events (SAEs), Suspected Unexpected Serious Adverse Reactions (SUSARs), emergency operations, etc. This allows physicians in charge to find the recorded study data easier and more efficiently in the clinical routine. These improvements should benefit both, clinicians and patients, in the future use of the Trial Outline Builder

Disease state index and disease state fingerprint: supervised learning applied to clinical decision support in Alzheimer’s disease

Due to scientific and technological advancements, investigations in modern medicine are producing more measurement data than ever before. Since a large amount of information exists, and it is also being produced at ever-increasing rates, no single person can digest all current knowledge of diseases. Data collected from large patient cohorts may contain valuable knowledge of diseases, which could be useful to clinicians when making diagnoses or choosing treatments. Making use of the large volumes of data in clinical decision-making requires ancillary help from information technologies, but such systems have not yet become widely available. This thesis addresses the challenge by proposing a computer-based decision support method that is suited to clinical use.This thesis presents the Disease State Index (DSI), a supervised machine learning method intended for the analysis of patient data. The DSI comprehensively compares patient data with previously diagnosed cases with or without a disease. Based on this comparison, the method provides an estimate of the state of disease progression in the patient. Interpreting the DSI is made possible by its visual counterpart, the Disease State Fingerprint (DSF), which allows domain experts to gain a comprehensive view of patient data and the state of the disease at a quick glance. In the design and development of these methods, both performance and applicability in clinical use were taken into account equally.Alzheimer’s disease (AD) is a slowly progressing neurodegenerative disease and one of the largest social and economic burdens in the world today, and it will continue to be so in the future. Studies with large patient cohorts have significantly improved our knowledge of AD during the last decade. This information should be made extensively available at memory clinics to maximize the benefits for diagnostics and treatment of the disease. The DSI and DSF methods proposed in this thesis were studied in the early diagnosis of AD and as a measure of disease progression in six original publications. The methods themselves and their implementation within a clinical decision support system, the PredictAD tool, were quantitatively evaluated with regard to their performance and potential benefits in clinical use. The results show that the methods and clinical decision support tool based on these methods can be used to follow disease progression objectively and provide earlier diagnoses of AD. These, in turn, could improve treatment efficacy due to earlier interventions and make drug trials more efficient by allowing better patient selection

Une approche logicielle du traitement de la dyslexie : étude de modèles et applications

Neuropsychological disorders are widespread and generate real public health problems. In particular in our modern society, where written communication is ubiquitous, dyslexia can be extremely disabling. Nevertheless we can note that the diagnosis and remediation of this pathology are fastidious and lack of standardization. Unfortunately it seems inherent to the clinical characterization of dyslexia by exclusion, to the multitude of different practitioners involved in such treatment and to the lack of objectivity of some existing methods. In this respect, we decided to investigate the possibilities offered by modern computing to overcome these barriers. Indeed we have assumed that the democratization of computer systems and their computing power could make of them a perfect tool to alleviate the difficulties encountered in the treatment of dyslexia. This research has led us to study the techniques software as well as hardware, which can conduct to the development of an inexpensive and scalable system able to attend a beneficial and progressive changing of practices in this pathology field. With this project we put ourselves definitely in an innovative stream serving quality of care and aid provided to people with disabilities. Our work has been identifying different improvement areas that the use of computers enables. Then each of these areas could then be the subject of extensive research, modeling and prototype developments. We also considered the methodology for designing this kind of system as a whole. In particular our thoughts and these accomplishments have allowed us to define a software framework suitable for implementing a software platform that we called the PAMMA. This platform should theoretically have access to all the tools required for the flexible and efficient development of medical applications integrating business processes. In this way it is expected that this system allows the development of applications for caring dyslexic patients thus leading to a faster and more accurate diagnosis and a more appropriate and effective remediation. Of our innovation efforts emerge encouraging perspectives. However such initiatives can only be achieved within multidisciplinary collaborations with many functional, technical and financial means. Creating such a consortium seems to be the next required step to get a funding necessary for realizing a first functional prototype of the PAMMA, as well as its first applications. Some clinical studies may be conducted to prove undoubtedly the effectiveness of such an approach for treating dyslexia and eventually other neuropsychological disorders.Les troubles neuropsychologiques sont très répandus et posent de réels problèmes de santé publique. En particulier, dans notre société moderne où la communication écrite est omniprésente, la dyslexie peut s’avérer excessivement handicapante. On remarque néanmoins que le diagnostic et la remédiation de cette pathologie restent délicats et manquent d’uniformisation. Ceci semble malheureusement inhérent à la caractérisation clinique par exclusion de la dyslexie, à la multitude de praticiens différents impliqués dans une telle prise en charge ainsi qu’au manque d’objectivité de certaines méthodes existantes. A ce titre, nous avons décidé d’investiguer les possibilités offertes par l’informatique actuelle pour surmonter ces barrières. Effectivement, nous avons supposé que la démocratisation des systèmes informatiques et leur puissance de calcul pourraient en faire un outil de choix pour pallier les difficultés rencontrées lors de la prise en charge de la dyslexie. Cette recherche nous a ainsi mené à étudier les techniques, aussi bien logicielles que matérielles, pouvant conduire au développement d’un système bon marché et évolutif qui serait capable d’assister un changement bénéfique et progressif des pratiques qui entourent cette pathologie. Avec ce projet, nous nous plaçons définitivement dans un courant innovant au service de la qualité des soins et des aides apportées aux personnes souffrant d’un handicap. Notre travail a ainsi consisté à identifier différents axes d’amélioration que l’utilisation de l’outil informatique rend possible. Chacun de ces axes a alors pu faire l’objet de recherches exhaustives, de modélisations et de développements de prototypes. Nous avons également réfléchi à la méthodologie à mettre en œuvre pour concevoir un tel système dans sa globalité. En particulier, nos réflexions et ces différents accomplissements nous ont permis de définir un framework logiciel propice à l’implémentation d’une plate-forme logicielle que nous avons appelée la PAMMA. Cette plate-forme devrait théoriquement pouvoir disposer de tous les outils permettant le développement souple et efficace d’applications médicales intégrant des processus métiers. Il est ainsi attendu de ce système qu’il permette le développement d’applications, pour la prise en charges des patients dyslexiques, conduisant à un diagnostic plus rapide et plus précis ainsi qu’à une remédiation plus adaptée et plus efficace. De notre effort d’innovation ressortent des perspectives encourageantes. Cependant, ce type d’initiative ne peut se concrétiser qu’autour de collaborations pluridisciplinaires disposant de nombreux moyens fonctionnels, techniques et financiers. La constitution d’un tel consortium semble donc être la prochaine étape nécessaire à l’obtention des financements pour réaliser un premier prototype fonctionnel de la PAMMA, ainsi que de premières applications. Des études cliniques pourront être alors menées pour prouver indubitablement l’efficacité d’une telle approche dans le cadre de la prise en charge de la dyslexie, ainsi qu’éventuellement d’autres troubles neuropsychologiques