Prof Dr Freimut Schliess, explores how artificial pancreas systems are revolutionising healthcare for Type 2 diabetes patients
In the last ten years, tremendous progress has been made in the clinical validation of automated insulin delivery by means of artificial pancreas (AP) systems for people with Type 1 diabetes (T1D). In Europe, both the MiniMed 670G and the Diabeloop DBLG1 hybrid AP systems were granted marketing authorisation for treating adults with T1D. Clinical trials in people with Type 2 diabetes (T2D) indicated the feasibility and safety of AP systems also in this patient population.
Objectives and scope of AP usage in T2D may vary according to the diversity of people with T2D and their needs and requirements. Introduction of the AP early after diagnosis might facilitate the transition to insulin therapy thereby helping to delay the decline of beta cell function and the onset of clinically overt diabetes complications. People with T2D already on insulin pump therapy might have a particularly positive attitude towards AP usage. For them, the AP could be perceived as a logical and consistent enhancement of insulin pump functionalities. Probably some people on insulin pump therapy will show additional benefit from the transition to an AP system in terms of glycaemic control.
In the management of people with advanced T2D and elderly people with T2D AP usage could be expected to relieve users and caregivers from the burden associated with insulin administration. Here the AP usage might protect people from frailty, disability, and disease aggravation related to unrecognised episodes of massive dysglycaemia. This could translate into lower rates of avoidable hospitalisations for actually ambulatory care-sensitive conditions – a well-recognised cost driver with a high impact on life quality for people with diabetes and their loved ones.
The pan-European CLOSE consortium(1) is aiming to develop integrated AP solutions (APplus) for people with T2D. APplus means a comprehensive product and service package, adding education and training, outcome predictors and performance indicators as well as telemedical services to the AP device. When developing APplus CLOSE follows a co-creative approach in the specific framework of French homecare service provision. French homecare service provider operate fully integrated chronic care platforms at the crossroads between patients, health professionals, payers, and prescribers.
French homecare service provision seems to be a real-world environment particularly suitable as a learning lab for co-creating an APplus solution meeting the needs and requirements of patients, payers and caregiver teams. Here learnings about the different stakeholders’ perceptions of diabetes, their attitudes towards diabetes management, and their understanding of treatment success can immediately inform the customisation of APplus packages.
For a wider distribution of AP usage, it seems reasonable to assume that APplus should be highly adaptable to the requirements of different T2D patient sub-groups and their specific care situations. This calls for an APplus portfolio containing an array of AP systems e.g. with and without carbohydrate counting and realising different intensities of insulin therapy and degrees of automation.
Indeed, APplus has a high potential for massive and multidimensional scalability. Using homecare as a starting point APplus could be expanded to operate in assisted living facilities, nursing homes, and hospitals. Also, APplus solutions for people having T2D without overt comorbid conditions or T1D are under consideration. Geographical upscaling should seek benefit from collaboration with regions and municipalities in a careful consideration of existing local/national competencies, healthcare structures and payment models. An obligatory delivery of train-the-trainer programs would grow a network of certified caregivers guaranteeing a safe and cost-effective implementation of AP solutions around Europe and globally. Beyond technical adaptations, the design of highly targeted training modules is predicted to be the main differentiator of APplus solutions tailored to the needs and requirements of different patient groups and care environments.
Adding capabilities for the exploitation of patient-generated health and behavioural data will functionally enhance the AP in the medium term. The utilisation of self-learning algorithms and an increased interconnectedness with health and social service providers will close the loop between the users’ state of health and customised care provision in a more comprehensive meaning. Converging with other strands of health innovations in chronic care enhanced AP systems will contribute to a fully integrated personalised diabetes management.
From the previous CLOSE investigations into stakeholder attitudes, it became clear that physicians and patients see a high need for a continuous further development of the AP. An AP system focusing on the closed-loop control of blood glucose levels is considered a transition technology towards a much more comprehensive predictive decision support based on further advanced control algorithms. This scenario matches the outcome of the CDTM Trend Seminar on “Digital Innovation in Diabetes Care” co-organised by CLOSE (2). Here AP operation is predicted to become gradually integrated as part of an interconnected ecosystem of digital health and social care.
A comprehensive monitoring of metabolic signatures and parameters reflecting patterns of everyday behaviour would produce a huge amount of real-world data which could be processed by self-learning control algorithms using artificial intelligence tools. The outcome should trigger an adjustment of therapies, treatments and behavioural patterns which again would feedback to the captured parameters.
Closing control loops and gradually optimising disease management in a personalised way is going to realise the twin objective of optimising everyday metabolic control and re-adapting behavioural habits to prolong the patient’s independence and prevent the development of frailty & disability and comorbid conditions.
1 Schliess, F. et al. J. Diabetes Sci. Technol. 2018
Prof Dr Freimut Schliess
*Please note: this is a commercial profile
Editor's Recommended Articles
Must Read >> A smart mirror for cardio-metabolic risk prevention
Must Read >> Artificial Intelligence to improve cancer diagnosis
Must Read >> Type 2 Diabetes now affects 7,000 under 25s