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EU project IntReALL 2020 started
Coordinated by PD Dr. med. Arend von Stackelberg, Pädiatrie m. S. Onkologie/Hämatologie - CHARITE - Universitätsmedizin Berlin (DE), project management by tp21.
Duration: 5 years - Start: 01 May 2023 - 25 Partners - Total funding: approximately € 6 million.
Relapse of acute lymphoblastic leukemia (ALL) remains a leading cause of mortality in childhood cancer. IntReALL 2020 will conduct
randomized and historically controlled trials in children with relapsed B-cell precursor (BCP) ALL with the aim to replace toxic
chemotherapy with better tolerated and more efficacious immunotherapeutic drugs. In standard risk (SR) patients, the CD22 directed
antibody-drug conjugate inotuzumab ozogamicin (InO) will be randomly compared with standard of care (SOC) ALL-R3 induction. All
patients will receive one SOC consolidation- and one Blina course, compared to historical controls. SR patients with MRD good response
will receive 2 additional Blina courses replacing chemotherapy randomly compared with SOC. Patients with high-risk relapse will
receive induction investigating InO versus ALL-R3 in an industry-sponsored trial, followed by IntReALL consolidation and allogeneic
HSCT. Patients with isolated extramedullary (IEM) relapse are treated based on ALL-REZ BFM 2002 backbone. IntReALL 2020 will
establish a federated relapsed/refractory leukaemia board generating personalized recommendations based on clinical, molecular-genetic
and drug response profiling data. Patients with very-high risk disease will receive experimental/personalized therapies, including a trial
investigating CD19-directed chimeric receptor antigen (CAR) T-cells produced in academic institutions. Other CAR T-cells trials as well
as an induction trial for T-ALL relapse will be developed. Documentation and monitoring of the trials and the individualized treatment
will be realized using the MARVIN database. Comprehensive statistical and data management activities will warrant the accuracy and
interpretability of the data. IntReALL 2020 involves representatives from participating pharmaceutical companies and EMA as well as
patient/parent advocates to discuss strategies for developing new drugs within academic trials warranting a benefit for all patients on the
results. “This action is part of the Cancer Mission cluster of projects on ‘Diagnosis and treatment’.
EU project Microb-AI-ome started
Coordinated by Prof. Jan Baumbach, Institute for Computational Systems Biology, Universität Hamburg (DE), project management by tp21.
Duration: 5 years - Start: 01 April 2023 - Total funding: approximately € 6 million.
In the EU, 1 in 35 women and 1 in 23 men will be diagnosed with colorectal cancer (CRC) in their life span (ca. 340,000
cases and 156,000 deaths in 2020) causing an annual economic burden of ca. 20 billion EUR. Identifying CRC early
enables better treatment options. Screening usually entails a quantitative faecal immunological test (FIT) to predict the
need of colonoscopy for the detection of colorectal lesions, an expensive and invasive procedure. We aim to predict
this need with specificity increased by >20 percentage points by using metagenomic microbiomes. We hypothesise
that computational microbiome profiles extracted using artificial intelligence (Al) technology will allow for optimised
personal therapy stratification. However, clinicians do not have access to broad microbiome data. With Microb-AIome,
we will develop a novel kind of computational stratification technology to enable microbiome-enhanced precision
medicine of CRC. Metagenomic microbiome data to date is distributed over many national registries, and privacy
regulations are hindering its effective integration. With Microb-AI-ome, we will overcome this barrier by establishing the
first privacy-preserving federated big data network in CRC research. We will integrate isolated, national databases into
one international federated database network - rather than a cloud - covering metagenomes for over 5,000 individuals
screened for CRC, and an expected total of 100,000 by 2026. Microb-AI-ome ensures that no sensitive patient data will
leave the safe harbours of the local databases while still allowing for the classification of clinical CRC phenotypes, which
we will demonstrate in clinical practice allowing regulatory bodies to adopt evidence-based guidelines. Our consortium
combines expertise in CRC and its treatment, microbiomics, artificial intelligence, software development, and privacy
protection to close the gap between privacy and big data in international medical research.
EU project AISN started
Integrating AI in Stroke Neurorehabilitation
Coordinated by Prof. Paul Verschure, STICHTING RADBOUD UNIVERSITEIT (NL), project management by tp21.
Duration: 4 years - Start: 01 December 2022 - Total funding: approximately € 7.8 million.
Health services are increasingly moving towards a treatment continuum aligned with the patient journey. This transition will critically depend on the successful deployment of trustworthy AI-enhanced technologies that are accurate, secure, and trusted. The AISN project will develop and validate operating procedures and guidelines for integrating AI in a healthcare continuum, focussing on post-stroke rehabilitation. AISN delivers a representative AI health platform built from integrating validated platforms for data acquisition and access, clinical interpretation, whole-brain simulation, clinically validated intervention delivery and optimization and model-based prediction. The AISN integrated platform will be validated in the clinical context of rehabilitation in the outpatient and at-home phase and facilitate a concrete assessment of the fundamental ways in which AI-enhanced clinical decision-support will change the care pathway and the formulation of novel AI compatible treatment guidelines. AISN ensures an ethical approach by developing legal and ethical guidelines for the robust, fair, and trustworthy deployment of AI in health and validating acceptance and transparency of its solutions. Building on the AISN platform, the project will test current standard operating procedures for integrating AI in health care and formulate and validate new ones where needed. The AISN guidelines and procedures will emphasize the evidence base and safety of clinical interventions, transparency, prognostics at varying time-scales, personalization of interventions, access to disease-specific information by clinicians, patients and their careers, and assure that the potential of AI is fully developed in the service of value-based medicine satisfying standards of security and safety. We will go beyond currently available guidelines and frameworks by emphasizing explainability, AI tools with evolving performance, and the dynamic interaction between users and algorithms.