ABSTRACT
MeDALL (Mechanisms of the Development of ALLergy; EU FP7-CP-IP; Project No: 261357; 2010-2015) has proposed an innovative approach to develop early indicators for the prediction, diagnosis, prevention and targets for therapy. MeDALL has linked epidemiological, clinical and basic research using a stepwise, large-scale and integrative approach: MeDALL data of precisely phenotyped children followed in 14 birth cohorts spread across Europe were combined with systems biology (omics, IgE measurement using microarrays) and environmental data. Multimorbidity in the same child is more common than expected by chance alone, suggesting that these diseases share causal mechanisms irrespective of IgE sensitization. IgE sensitization should be considered differently in monosensitized and polysensitized individuals. Allergic multimorbidities and IgE polysensitization are often associated with the persistence or severity of allergic diseases. Environmental exposures are relevant for the development of allergy-related diseases. To complement the population-based studies in children, MeDALL included mechanistic experimental animal studies and in vitro studies in humans. The integration of multimorbidities and polysensitization has resulted in a new classification framework of allergic diseases that could help to improve the understanding of genetic and epigenetic mechanisms of allergy as well as to better manage allergic diseases. Ethics and gender were considered. MeDALL has deployed translational activities within the EU agenda.
Subject(s)
Hypersensitivity/diagnosis , Hypersensitivity/therapy , Precision Medicine/methods , Systems Biology/methods , Disease Management , European Union , Health Policy , Humans , Hypersensitivity/etiology , Hypersensitivity/prevention & control , Immunization , Immunoglobulin E/immunology , Inventions , Prognosis , World Health OrganizationABSTRACT
Information and Communication Technologies (ICT) are expected to support Healthcare Professionals in reducing medical errors, making the most relevant decisions and finding the most appropriate procedure for each patient. In particular, Knowledge Management and Decision Support Systems provide access to high quality information and to appropriate protocols. The present paper aims at comparing the approaches used in three ongoing R&D projects in order to support risk reduction and clinical governance. This comparison will lead to the presentation of a generic model of Decision Support Tools that transform shared and documented "Good Practices" into software entities that can pro-actively advice users in their daily work or when they encounter difficult situations.
