NCT06019208

Brief Summary

GenoMed4All 'Genomics and Personalized Medicine for all though Artificial Intelligence in Haematological Diseases' aims to advance on individual SCD patients' disease characterisation and to improve the monitoring of patients' health status, optimise clinical therapy guidance and ultimately improved health outcomes by the identification of biomarkers and the development of individual (risk) models in SCD. Genomed4All supports the pooling of genomic, clinical data and other "-omics" health through a secure and privacy respectful data sharing platform based on the novel Federated Learning scheme, to advance research in personalised medicine in haematological diseases thanks to advanced Artificial Intelligence (AI) models and standardised interoperable sharing of cross-border data, without needing to directly share any sensitive clinical patients' data. The SCD Use case will gather multi-modal clinical and -OMICs data from 1,000 SCD patients in 4 EU-MS: France, Italy, Spain and The Netherlands. In close collaboration with the European Reference Network on Rare Hematological Diseases (ERN-EuroBloodNet, GA101157011), GENOMED4ALL involves multiple clinical partners from the network, while leveraging on healthcare information and repositories that will be gathered incorporating interoperability standards as promoted by ERN-EuroBloodNet central registry, the European Rare Blood Disorders Platform.

Trial Health

47
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
1,000

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jan 2021

Longer than P75 for all trials

Geographic Reach
4 countries

5 active sites

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

January 1, 2021

Completed
2.5 years until next milestone

First Submitted

Initial submission to the registry

June 15, 2023

Completed
3 months until next milestone

First Posted

Study publicly available on registry

August 31, 2023

Completed
1 month until next milestone

Primary Completion

Last participant's last visit for primary outcome

September 30, 2023

Completed
1.3 years until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2024

Completed
Last Updated

April 12, 2024

Status Verified

June 1, 2023

Enrollment Period

2.7 years

First QC Date

June 15, 2023

Last Update Submit

April 11, 2024

Conditions

Sickle Cell Disorders

Keywords

Artificial IntelligenceHematological diseasesGWASPersonalized medicinePrognosisDisease classificationSickle cell diseaseRadiomicsMetabolomicsClinical unmet needs

Outcome Measures

Primary Outcomes (2)

  • Improving SCD classification

    To improve classification of SCD by integrating clinical and hematological information with genomic features. To address this issue, different methods of statistical learning (Dirichlet processes (DP), Bayesian networks (BN)) and machine learning (deep learning physics informed neural network, constrained regression and deep models) will be compared in order to define specific genotype-phenotype correlations and to develop a new disease classification.

    through study completion, an average of 2 years

  • Improve diagnosis of cerebrovascular complications.

    Develop an artificial intelligence algorithm for early diagnosis of silent infarcts by analyzing brain magnetic resonance imaging (Radiomics).

    through study completion, an average of 2 years

Study Arms (1)

GENOMED4ALL - SCD patients

Non transplanted SCD patients aged over 1 year.

Eligibility Criteria

Age1 Year+
Sexall
Healthy VolunteersNo
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Patients affected by SCD

You may qualify if:

  • Patients older than 1 year, diagnosed with SCD, all genotypes.

You may not qualify if:

  • Patients treated with stem cell transplant or gene therapy.
  • Patients younger than 1 year old.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (5)

APHP Henri Mondor

Créteil, 94000, France

Location

APHP Necker

Paris, 75015, France

Location

Azienda Ospedale Università Padova

Padua, 35121, Italy

Location

UMC Utrecht

Utrecht, 3584, Netherlands

Location

Hospital Universitari Vall d'Hebron Research Institute

Barcelona, 08035, Spain

Location

Related Publications (11)

  • Aguilar Martinez P, Angastiniotis M, Eleftheriou A, Gulbis B, Manu Pereira Mdel M, Petrova-Benedict R, Corrons JL. Haemoglobinopathies in Europe: health & migration policy perspectives. Orphanet J Rare Dis. 2014 Jul 1;9:97. doi: 10.1186/1750-1172-9-97.

    PMID: 24980780BACKGROUND

  • INGRAM VM. Abnormal human haemoglobins. III. The chemical difference between normal and sickle cell haemoglobins. Biochim Biophys Acta. 1959 Dec;36:402-11. doi: 10.1016/0006-3002(59)90183-0. No abstract available.

    PMID: 13852872BACKGROUND

  • Bunn HF. Pathogenesis and treatment of sickle cell disease. N Engl J Med. 1997 Sep 11;337(11):762-9. doi: 10.1056/NEJM199709113371107. No abstract available.

    PMID: 9287233BACKGROUND

  • Kato GJ, Piel FB, Reid CD, Gaston MH, Ohene-Frempong K, Krishnamurti L, Smith WR, Panepinto JA, Weatherall DJ, Costa FF, Vichinsky EP. Sickle cell disease. Nat Rev Dis Primers. 2018 Mar 15;4:18010. doi: 10.1038/nrdp.2018.10.

    PMID: 29542687BACKGROUND

  • Steinberg MH, Sebastiani P. Genetic modifiers of sickle cell disease. Am J Hematol. 2012 Aug;87(8):795-803. doi: 10.1002/ajh.23232. Epub 2012 May 28.

    PMID: 22641398BACKGROUND

  • Alapan Y, Fraiwan A, Kucukal E, Hasan MN, Ung R, Kim M, Odame I, Little JA, Gurkan UA. Emerging point-of-care technologies for sickle cell disease screening and monitoring. Expert Rev Med Devices. 2016 Dec;13(12):1073-1093. doi: 10.1080/17434440.2016.1254038. Epub 2016 Nov 22.

    PMID: 27785945BACKGROUND

  • Bao EL, Lareau CA, Brugnara C, Fulcher IR, Barau C, Moutereau S, Habibi A, Badaoui B, Berkenou J, Bartolucci P, Galacteros F, Platt OS, Mahaney M, Sankaran VG. Heritability of fetal hemoglobin, white cell count, and other clinical traits from a sickle cell disease family cohort. Am J Hematol. 2019 May;94(5):522-527. doi: 10.1002/ajh.25421. Epub 2019 Feb 6.

    PMID: 30680775BACKGROUND

  • Thein SL, Menzel S, Peng X, Best S, Jiang J, Close J, Silver N, Gerovasilli A, Ping C, Yamaguchi M, Wahlberg K, Ulug P, Spector TD, Garner C, Matsuda F, Farrall M, Lathrop M. Intergenic variants of HBS1L-MYB are responsible for a major quantitative trait locus on chromosome 6q23 influencing fetal hemoglobin levels in adults. Proc Natl Acad Sci U S A. 2007 Jul 3;104(27):11346-51. doi: 10.1073/pnas.0611393104. Epub 2007 Jun 25.

    PMID: 17592125BACKGROUND

  • Thein SL. Genetic modifiers of the beta-haemoglobinopathies. Br J Haematol. 2008 May;141(3):357-66. doi: 10.1111/j.1365-2141.2008.07084.x.

    PMID: 18410570BACKGROUND

  • Rab MAE, van Oirschot BA, Bos J, Merkx TH, van Wesel ACW, Abdulmalik O, Safo MK, Versluijs BA, Houwing ME, Cnossen MH, Riedl J, Schutgens REG, Pasterkamp G, Bartels M, van Beers EJ, van Wijk R. Rapid and reproducible characterization of sickling during automated deoxygenation in sickle cell disease patients. Am J Hematol. 2019 May;94(5):575-584. doi: 10.1002/ajh.25443. Epub 2019 Mar 8.

    PMID: 30784099BACKGROUND

  • Collado A, Boaro MP, van der Veen S, Idrizovic A, Biemond BJ, Beneitez Pastor D, Ortuno A, Cela E, Ruiz-Llobet A, Bartolucci P, de Montalembert M, Castellani G, Biondi R, Manara R, Sanavia T, Fariselli P, Kountouris P, Kleanthous M, Alvarez F, Zazo S, Colombatti R, van Beers EJ, Manu-Pereira MDM. Challenges and Opportunities of Precision Medicine in Sickle Cell Disease: Novel European Approach by GenoMed4All Consortium and ERN-EuroBloodNet. Hemasphere. 2023 Feb 22;7(3):e844. doi: 10.1097/HS9.0000000000000844. eCollection 2023 Mar. No abstract available.

    PMID: 36844183BACKGROUND

MeSH Terms

Conditions

Anemia, Sickle CellHematologic Diseases

Condition Hierarchy (Ancestors)

Anemia, Hemolytic, CongenitalAnemia, HemolyticAnemiaHemic and Lymphatic DiseasesHemoglobinopathiesGenetic Diseases, InbornCongenital, Hereditary, and Neonatal Diseases and Abnormalities

Study Officials

  • Federico Alvarez

    Universidad Politecnica de Madrid

    PRINCIPAL INVESTIGATOR

  • Gastone Castellani

    University of Bologna

    PRINCIPAL INVESTIGATOR

  • Raffaella Colombatti

    University of Padova

    PRINCIPAL INVESTIGATOR

  • Eduard van Beers

    UMC Utrecht

    PRINCIPAL INVESTIGATOR

  • Marianne de Montalembert

    APHP Necker

    PRINCIPAL INVESTIGATOR

  • Pablo Bartolucci

    APHP Henri Mondor

    PRINCIPAL INVESTIGATOR

  • Tiziana Sanavia

    University of Torino

    PRINCIPAL INVESTIGATOR

  • Petros Kountouris

    Cyprus Institute of Neurology and Genetics

    PRINCIPAL INVESTIGATOR

  • Matteo Della Porta

    Istituto Clinico Humanitas

    PRINCIPAL INVESTIGATOR

  • Maria del Mar Mañú Pereira

    Hospital Universitari Vall d'Hebron Research Institute

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
CROSS SECTIONAL
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

June 15, 2023

First Posted

August 31, 2023

Study Start

January 1, 2021

Primary Completion

September 30, 2023

Study Completion

December 31, 2024

Last Updated

April 12, 2024

Record last verified: 2023-06

Locations

FR(2)NL(1)IT(1)ES(1)