Systems medicine approaches for the definition of complex phenotypes in chronic diseases and ageing. From concept to implementation and policies.

Chronic diseases are diseases of long duration and slow progression. Major NCDs (cardiovascular diseases, cancer, chronic respiratory diseases, diabetes, rheumatologic diseases and mental health) represent the predominant health problem of the Century. The prevention and control of NCDs are the priority of the World Health Organization 2008 Action Plan, the United Nations 2010 Resolution and the European Union 2010 Council. The novel trend for the management of NCDs is evolving towards integrative, holistic approaches. NCDs are intertwined with ageing. The European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) has prioritised NCDs. To tackle them in their totality in order to reduce their burden and societal impact, it is proposed that NCDs should be considered as a single expression of disease with different risk factors and entities. An innovative integrated health system built around systems medicine and strategic partnerships is proposed to combat NCDs. It includes (i) understanding the social, economic, environmental, genetic determinants, as well as the molecular and cellular mechanisms underlying NCDs; (ii) primary care and practice-based interprofessional collaboration; (iii) carefully phenotyped patients; (iv) development of unbiased and accurate biomarkers for comorbidities, severity and follow up of patients; (v) socio-economic science; (vi) development of guidelines; (vii) training; and (viii) policy decisions. The results could be applicable to all countries and adapted to local needs, economy and health systems. This paper reviews the complexity of NCDs intertwined with ageing. It gives an overview of the problem and proposes two practical examples of systems medicine (MeDALL) applied to allergy and to NCD co-morbidities (MACVIA-LR, Reference Site of the European Innovation Partnership on Active and Healthy Ageing).

Adaptation of the application of good clinical practice depending on the features of specific research projects.

The conduct of clinical trials falls within a strict regulatory framework. The objective of the round table was to develop reasonable recommendations for the implementation of GCP according to the type of research and taking in account the risks and challenges related to this research. Two types of risks have been identified: those related to the characteristics of the research and those related to the impact of the study results. The group designed an evaluation table of these risks. The round table focused its investigations on 3 main themes: monitoring, the investigational medicinal product and undesirable effects. Three methods of monitoring adaptation were analysed in terms of advantages and disadvantages: the gradual approach, the central monitoring, monitoring on the basis of sampling. Examination of the investigational medicinal product focused on the medicinal product circuit. The group recommends using the following 'basic' decision-making tree, which takes three elements into account: 1) is it an investigational medicinal product?, 2) do the trial objectives and design require packaging specific to the research?, 3) is the risk of use higher than that in standard practice? Finally, adaptation of the implementation of GCP in terms of pharmacovigilance appeared very limited and could possibly be considered for the medicinal product, the subject of the research, which already holds a marketing authorisation, and for which the safety profile is well known; in this case, only simplified collection of non-serious adverse events may be envisaged, which may be implemented by designing and using a standard collection listing. The adaptation of the implementation of GCP is possible. This firstly takes into account the characteristics of the research: which objectives/which risks/which challenges. The options in terms of adaptation must be pre-defined, documented and justified; if necessary, they will also be re-assessed in the course of analysis.