Multiple myeloma: who works on it

One card per institution. Filter by target, by country, or show only institutions in EU-13 (Horizon Europe widening) countries.

• All targets
• BCMA 132
• CD38 22
• GPRC5D 35
• CD19 31
• TP53 0
• STAT3 0
• CXCR4 4
• MYC 0
• BCL-2 2
• PI3K 1
• mTOR 0
• IL-6 0
• STING 0
• BRAF 2
• CD47 1
• HDAC 0
• AKT 0
• PD-1 1
• PD-L1 1
• CD20 3
• GLP-1 0
• JAK 0
• PTEN 0
• SGLT2 0
• AMPK 0
• B7-H3 0
• NRAS 1
• TIGIT 0
• CTLA-4 1
• ERK 0
• EZH2 0
• FTO 0
• IL-15 3
• JNK 0
• KRAS 1
• MAPK 0
• RAS 0
• CD22 2
• CD33 1
• CTNNB1 0
• EGFR 0
• FGFR 0
• LAG-3 0
• MDM2 0
• METTL3 0
• NRF2 0
• BRCA1 0
• BRD4 0
• BTK 1
• CD123 1
• CD30 0
• CDK4/6 0
• GPX4 0
• HER2 0
• HIF-1 0
• HSP90 0
• MEK 0
• MET 0
• MUC1 0
• NTRK 0

EU-13 is a filter, not a ranking: it only narrows the list.

3 of 3+ institutions, ordered by recent publications and open trials. This is not a ranking of quality.

Trials whose registry record says individual participant data (IPD) will be shared.

No trial in this view states that it shares participant data.

Find publications on this disease by a MeSH method term, for example a sequencing or imaging method.

• Single-Cell Analysis 23
• Organoids 3
• Mendelian Randomization Analysis 10
• CRISPR-Cas Systems 8
• Gene Expression Profiling 44
• Sequence Analysis, RNA 7
• Whole Genome Sequencing 4
• Exome Sequencing 3
• Proteomics 15
• Metabolomics 10
• Mass Spectrometry 7
• Flow Cytometry 48
• Immunohistochemistry 11
• Liquid Biopsy 2
• Circulating Tumor DNA 2
• Xenograft Model Antitumor Assays 78
• Positron-Emission Tomography 14
• Magnetic Resonance Imaging 26
• Machine Learning 16
• Deep Learning 6
• Cohort Studies 32
• Genome-Wide Association Study 7

• Machine-Learning-Guided Identification of CCT245737 as a Functional Pan-G-Quadruplex Ligand for the Treatment of Multiple Myeloma.

  J Phys Chem B, Nov 2026

• Machine Learning and Molecular Modeling Reveal HDAC6 as a Key Target of Tanshinone IIA in Multiple Myeloma.

  J Phys Chem B, Sept 2026

• Development and temporal validation of a machine learning-based model for predicting renal impairment in multiple myeloma: a single-center retrospective cohort study.

  BMC Med Inform Decis Mak, Jul 2026

• Machine Learning for Prediction of High-Risk Infections in Patients With Cancer.

  Cancer Med, Jul 2026

• Identification of Bone Marrow and Peripheral Blood Plasma Extracellular Vesicle Protein Biomarker Signatures for Multiple Myeloma Diagnosis and Staging.

  Int J Nanomedicine, Jun 2026

• Machine Learning Model Predicts Monoclonal Gammopathy Using Routine Laboratory Values.

  JCO Clin Cancer Inform, May 2026

• Machine learning triumphs in differentiating fungal and bacterial infections.

  BMC Infect Dis, Apr 2026

• FTO-CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification.

  Ann Hematol, Mar 2026

• Dynamic biomarker-based machine learning model predicts short-term treatment response in multiple myeloma.

  J Transl Med, Mar 2026

• A Multi-Omics and machine learning platelet-related prognostic signature in multiple myeloma.

  Ann Hematol, Feb 2026

See which targets of this disease your abstract mentions, and go to the people working on them.