Acute Lymphoblastic Leukaemia (ALL) is the most frequent leukaemia entity in children and adolescents. Despite continued progress and refinement of therapeutic approaches, disease relapse due to insufficient extinction of leukaemic blasts still remains the number one cause of treatment failure. About 15-20% of paediatric patients with the disease still suffer from relapse. Hence, in all advanced treatment schemes world-wide, assessment of the response to poly-chemotherapy via quantification of Minimal Residual Disease (MRD) at certain time-points of treatment has become a fundamental diagnostic procedure for tailoring therapy intensity and duration upon individual patients’ needs. Flow Cytometry (FCM) is one of the methodologies most useful in this respect, because it is widely available and applicable to most patients.

Currently, children and adolescents with ALL from multiple European countries are treated according to closely related “BFM-style” treatment protocols. The involved national FCM reference laboratories for paediatric leukaemia diagnostics have joined in the international-BFM FCM-network where Michael Dworzak (Labdia) is the co-ordinator. Our network AutoFLOW will be dedicated to the standardisation of high-quality FCM-based MRD-assessment.

While sample preparation, antibody panels, staining procedures, and FCM acquisition can be harmonized straightforwardly, data analysis and interpretation rely largely on operator skills and experience. These assessments are time-consuming and costly to be attained via staff-training, online support between twinning laboratories (instructor and apprentice; internet-based data reviewing), and continued quality control. Hence, these requirements represent the current bottleneck of safely applying the FCM-MRD methodology in a growing community of diagnostic laboratories to the benefit of an increasing number of patients with leukaemia.

Solving the Bottleneck with AutoFLOW

To address this bottleneck, AutoFLOW aims at developing an objective and automated tool for multi-parameter FCM data analysis with specifically reliable MRD quantification. To achieve this goal FCM-experts will closely co-operate with Information Communication Technology (ICT) specialists, who will adopt methods from (multi-variate) statistics, data mining, and machine learning.

Knowledge transfer between the medical and the ICT sector will facilitate to explicitly incorporate medical expert knowledge specific to FCM-data into inferred automated procedures.

Eventually, the AutoFLOW project will deliver a valid solution for automated Flow Cytometric analysis for clinical follow-up assessment of Acute Lymphoblastic Leukaemia.

Additionally, this consortium aims at engaging professionals from the medical and ICTfields in a network where the exchange of knowledge will culminate in better career perspectives for the involved personnel and increase the competitiveness of the participating SMEs.

The AutoFLOW team will be composed on one side by clinicians and basic researchers that expose the clinical problem and associated challenges, and on the other side specialists for ICT and software programmers that will develop the technical solutions to address the clinical problem. Traditionally, in this type of venture, a major obstacle for people from different fields to overcome is the lack of deep understanding for each other’s technical language and points of view.

To overcome the challenge of semantics AutoFLOW will give to clinicians and ICT specialists the rare opportunity to work together and share common physical space. Additionally, the SMEs involved expect to establish tighter collaborations with the medical research institutions improve the know-how of their staff and achieve a better market position, whereas the clinicians and basic researchers expect to improve their experience within the private sector and developed a broader technical knowledge.

Automation of Flow Cytometric Analysis for Quality-Assured Follow-up Assessment to Guide Curative Therapy for Acute Lymphoblastic Leukaemia in Children