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CompletedNCT03409692MMpredictUpdated Jun 29, 2023

Validation of a Personalised Medicine Tool for Multiple Myeloma That Predicts Treatment Effectiveness in Patients

An observational study in Multiple Myeloma, sponsored by Mario Boccadoro. Completed at 1 site in Italy. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2023-06-29.

Sponsored by Mario Boccadoro · Observational

Study type
Observational
Model
Case-only
Time perspective
Retrospective
Enrollment
278
Ages
18 Years and older
Sex
All
01

Study summary

The consortium aims to commercialise the MMpredictor as a personalised medicine tool that predicts the most effective treatment strategy for individual Multiple Myeloma (MM) patients. MM is the second most common form of blood cancer contributing to 15% of all blood cancers and \~1,5% and 2% of all cancer deaths annually in the EU and US, respectively.

Patients show a large variability in treatment response and side effects due to tumour heterogeneity and the patient's intrinsic characteristics. Therefore, not every treatment will be suitable for each patient, and treatment strategies are often based on trial-and-error. The availability of multiple (>20) treatment options complicates treatment decision-making even more. With the current development of many more promising treatments, there is an urgent unmet clinical need for a diagnostic assay that supports personalised cancer treatment in order to improve patient health outcomes, prevent side effects and reduce healthcare costs.

SkylineDx has previously developed the MMprofiler, a microarray-based diagnostic test that can subtype MM patients and reliably predict MM patient survival (prognosis). In this project, the test's clinical value will be expanded to include the prediction of treatment effectiveness in individual patients based on Gene Expression Profiling. An addendum for new intended use will be filed to the current in vitro diagnostic (IVD) registration, while renaming the test to MMpredictor. The project will also focus on positioning the test as a cost-effective IVD test for personalised medicine, that will increase health outcome and quality of life of patients and reduce healthcare costs.

The consortium consists of a life science SME specialised in molecular diagnostics, clinical centres with world renowned KOLs, a leading health economic institute, and a European MM patient advocacy organisation combining all the required complementary expertise to successfully bring the MMpredictor to market.

02

Conditions studied

03

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

MM patients enrolled in clinical trials that have been conducted over the past 5 years.

Inclusion criteria

  • The bio-banked MM patient samples and clinical data will be obtained from previous European clinical trials that have been conducted over the past 5 years within the participating clinical centres and other clinical centers. The samples were not collected for the purposes of this project. The subjects from which the data was initially taken cannot be identified from the data/records. However, the patients from the above mentioned trial have explicitly consented for the use of their samples for other (future) clinical research purposes.

Exclusion criteria

Exclusion Criteria:

-

04

Study design

Observational model
Case-only
Time perspective
Retrospective
Enrollment
278 participants (actual)
Patient registry
No

Interventions

  • Diagnostic testGene Expression Profiling

    SkylineDx has previously developed the MMprofiler, a microarray-based diagnostic test that can subtype MM patients and reliably predict MM patient survival (prognosis). In this project, the test's clinical value will be expanded to include the prediction of treatment effectiveness in individual patients based on Gene Expression Profiling.

05

What researchers measure

Primary outcomes

  1. MMpredictor as a personalised medicine tool

    The main objective of the MMpredict project is to commercialise the MMpredictor as a personalised medicine tool that predicts the most effective treatment strategy for individual Multiple Myeloma (MM) patients.

    Time frame: 1 year

Secondary outcomes

  1. - Genetic subtyping with the MMprofiler of 800 bio-banked MM patient samples

    Time frame: 2 years

  2. - Clinical validation of genetic subtypes correlating with specific treatment effect

    Time frame: 2 years

  3. - Establish a treatment decision matrix that will guide physicians in treatment decision-making

    Time frame: 2 years

  4. - Perform a Medical Technology Assessment (MTA) to evaluate health economic benefits

    Time frame: 2 years

  5. - File addendum to current CE-IVD registration, while also renaming the test to "MMpredictor"

    Time frame: 2 years

  6. - Develop and execute commercialisation and marketing plan for the MMpredictor

    Time frame: 2 years

06

Study locations

1 site
  • University of Turin
    Turin, 10125, Italy
07

References and documents

Individual participant data

Plan to share: No

No publications or documents are linked to this record.

08

Registry details

Key details

Study ID
NCT03409692
Lead sponsor
Mario Boccadoro
Responsible party
Mario Boccadoro (Director of Department of Molecular Biotechnology and Health Sciences, University of Turin, Italy) — Sponsor-investigator
First posted
Jan 24, 2018
Start date
Jun 14, 2017
Primary completion
Nov 30, 2017
Completion
Jul 25, 2022
Last update
Jun 29, 2023

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Jun 2023. You cannot join it, but the record below documents what was studied.

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