Personalized Diabetes Management in Europe
In the year 2018 Profil joined the team creating the iPDM-GO (integrated Personalized Diabetes Management Goes Europe) consortium for implementing integrated Personalized Diabetes Management in Europe. Following a thorough and competitive evaluation the iPDM-GO project at the beginning of 2019 became part of the Innovation portfolio curated by EIT Health. EIT Health is a public-private knowledge and innovation community (KIC) of best-in-class health innovators backed by the European Union. The KICs Innovation ecosystem enables a collaborative multi-stakeholder approach to implementing a more effective diabetes management in Europe.
What is iPDM-GO about exactly?
While the costs of chronic diseases continue to rise, many people with diabetes still do not achieve their treatment goals. It is thus key to provide cost-eﬀective health services tailored to each person's unique needs and requirements by considering individual treatment-effect-modifiers. Integrated Personalized Diabetes Management (iPDM) is a six-step iterative process  that was shown to improve outcomes, treatment satisfaction and patient adherence in the PDM-ProValue study program .
Encouraged through the ProValue outcomes iPDM-GO is going to implement iPDM, along with an outcomes-based payment model, in a Danish community setting. The goal is to lay groundwork for expanding these concepts to additional European countries and to other disease indications. iPDM-GO will explore new opportunities for leveraging Big Data resources and developing effective educational programs for health care professionals.
To support the transformation of healthcare from volume-based to value-based, iPDM-GO will develop a healthcare transformation toolkit that guides the implementation of outcomes-based care in European countries. Further information on the iPDM-GO project, the consortium behind and EIT Health is available here.
What role has Profil in iPDM-GO?
Profil is the coordinator of the iPDM-GO Work Package on Research into iPDM Enhancement, Implementation and Scalability. This research endeavour is driven by a collaboration between the German Center for Diabetes Research (Helmholtz Center Munich: Institute of Epidemiology, Institute of Health Economics & Healthcare Management), Aberystwyth University (Institute of Biological, Environmental and Rural Sciences) and Profil.
By applying a machine learning approach to big data sources we are going to enable an accurate assessment of each patent’s unique health and disease signatures. This information will be used to predict the individual responsiveness to available treatment options and to model the corresponding disease course and cost scenarios.
At a more general level we will pursue a further enhancement of iPDM. During the EIT Health-funded project phase we will secure a maximum and multi-dimensional scalability of iPDM along the lines of drugs & technologies, treatment guidelines, data policies, geography, cost-effectiveness and reimbursement rules, to name a few. Research outcomes will be disseminated to the different audiences.
What is Profils ambition here?
Profil aims at making a signiﬁcant impact on the real-world effectiveness of diabetes treatments. One approach is to explore synergies from convergent trends in controlled clinical research and real-world clinical care. Indeed diverse but complementary innovation consortia like iPDM-GO which integrate health industries, regional healthcare provision, data sciences and health economy create an excellent ecosystem for advancing the real-world effectiveness of diabetes management in a socially responsible manner.
Based on Profil's experience with initiatives on the implementation of artificial pancreas (AP) systems in diabetes care, i.e. AP@home, CLOSE and D4Kids, we see a high value in integrating the acquisition of person-generated real-world data already in early phase clinical trials. An early integration of real-world experience as accessible through collaborations such as iPDM-GO could strengthen the external validity of outcomes from controlled clinical trials. This again could add evidence to the sponsor’s decision making on the (dis)continuation of clinical development programs.
Accordingly clinical contract research organisations (CROs) are increasingly going to expand their data management & statistic offers by creating a full portfolio of real-world data acquisition and exploitation services. Such services cover the whole spectrum from a rational trial design and the selection of appropriate sensor systems up to the calculation and consolidated interpretation of digital biomarker signatures and reporting of the clinical trial to different audiences. It goes without saying that CROs like Profil have the capabilities to delivering services around real-world data in full compliance with the requirements imposed by law (e.g. the General Data Protection Regulation in Europe and the Health Insurance Portability and Accountability Act in the United States) and by regulatory authorities like FDA and EMA.
Vice versa, real-world clinical care can get inspiration from the collaboration with clinical contract research. The application of sensor-based technologies for the continuous acquisition and algorithm-based exploitation of person-generated data in the framework of professional clinical trial conduct may provide an ethical and operational blueprint for the exploitation of patient-generated data in chronic care. Clinical contract research lives particularly high standards in data management and statistical analysis as well as data reporting and interpretation. By performing independent trials clinical CROs contribute to the social acceptance of digital health solutions for clinical care, sharpen their competitive edge and prove their eligibility for reimbursement. Last but not least elements of the pay-for-performance culture widely established in clinical contract research could serve as a model for corresponding remuneration schemes in clinical care.