Colorectal CancerMuSTARDNCT07189312
Multi-scale Spatio-Temporal Analysis of Research Data
An observational study of Colorectal Cancer, run by Universidad de Granada at 1 site in Spain.
Trial summary
MuSTARD is a singular project in the sense that investigators will develop a computational framework that is conceived as a common solution for disparate applications. This framework responds to a common need: the derivation of multi-scale spatio-temporal (ST) models equipped with statistical inference capabilities. Read more about this study
- Who is it for?
- Ages 18 to 90 years
- Conditions the study is for
- Colorectal Cancer
- How many people
- 15 participants
- Where
- 1 siteSpain
- Study dates
- 2 Feb 2025to 2 Dec 2026
- How long will I take part?
- 3 Months
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 90 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with a diagnosis of colorectal cancer that are going to have a cancer planned surgery
Who may be able to join
- Diagnosis for colorectal cancer
- Patients with cancer planned surgery
- Absence of instability microsatellites
- Absence of any other associated disease that can affect the cancer pathology
Who cannot join
- Patients who need an urgent surgery
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Spain1 site, 1 recruiting
- Recruiting
Virgen de las Nieves Hospital
Granada, Granada
Raquel Conde, MD
Carolina Gomez-Llorente, PhD
About this study
MuSTARD is a singular project in the sense that investigators will develop a computational framework that is conceived as a common solution for disparate applications. This framework responds to a common need: the derivation of multi-scale spatio-temporal (ST) models equipped with statistical inference capabilities. Since the sequencing of the human genome, a significant portion of clinical research has shifted to the study of precision medicine (PM), resulting in numerous breakthroughs in both non-communicable and infectious diseases. PM refers to disease treatment and prevention that considers variability in genes, environment, and lifestyle for each person. Main drivers of PM are the omics technologies . Omics data is obtained from new high-throughput instruments that generate massive volumes of data. It is also notoriously complex data to analyze. In the last years, new separation technology has allowed us to measure omics data at single-cell resolution, creating a new (and even more complex) type of data generally referred to as single-cell omics. This allow us to study the spatial distribution of omics in a sample. Spatial and single cell omics represents one of the most powerful approaches today to understand cancer propagation in both time and space. Spatial omics. Unfortunately, there are no computational tools that can readily combine the nature of this new type of data with powerful statistical inference. Furthermore, spatially resolved omics experiments with repeated measures is another form of complex ST data. MuSTARD will provide a new computational framework that can handle ST omics to understand colorectal cancer propagation in both time and space, and leverage it in a new clinical study of reduced sample size (15 patients). The MuSTARD computational framework applied to ST omics will be made available for the general community in the form of open software.
- Conditions
- Colorectal Cancer
- Medical subject headings
- Colorectal Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Patients with a diagnoses of colorectal cancer | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
To develop a framework of computational tools and services capable of handling multi-scale spatio-temporal structures in massive scientific data and providing interpretable models and visualizations with sound statistical support.
Sample Collection A total of 15 patients with a diagnosis of colorectal cancer, that undergoes surgery, will be recruited. Blood and fecal samples will be collected at two time points (baseline and endpoint). In addition, three spatially distinct tissue samples will be obtained at a single time point (during cancer surgery).
Measurements
- Variation of the intestinal microbiota composition before and after surgery. Intestinal microbiota composition willbe determined by shot-gun sequencing techniques.
- Variation of the plasma metabolite before and after surgery, by untargeted metabolimics.
- Variation in specific metabolites and gene expression in the colorectal cancer's tissue samples. Next-generation sequencing and untargeted metabolomic techniques will be used.
The multi-omics data will be processed and integrated using Artificial Intelligence (AI) techniques, allowing the development
Measured: three years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Sep 2025
- Study start2 Feb 2025
- Primary completion28 Feb 2026
- Study completion2 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Other
- Enrolment
- 15 participants (estimated)
- Target duration
- 3 Months
Sponsor and investigators
- Lead sponsor
- Universidad de Granada
- Sponsor type
- University, hospital or other
- Collaborators
- University Hospital Virgen de las Nieves
- Responsible party
- Principal investigator, Carolina Gómez Llorente, Universidad de Granada
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07189312
- Sponsor's protocol ID
- PID2023-152301OB-IOO
- Acronym
- MuSTARD
- Status last verified
- Apr 2026
- First submitted
- 9 Sep 2025
- Last updated
- 28 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 28 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multi-scale Spatio-Temporal Analysis of Research Data
- ClinicalTrials.gov ID
- NCT07189312
- Acronym / sponsor ID
- MuSTARD / PID2023-152301OB-IOO
- Conditions
- Colorectal Cancer
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 15 participants (estimated)
- Lead sponsor
- Universidad de GranadaUniversity, hospital or other
- Collaborators
- University Hospital Virgen de las Nieves
- Study start
- 2 Feb 2025 (actual)
- Primary completion
- 28 Feb 2026 (actual)
- Study completion
- 2 Dec 2026 (estimated)
- First posted
- 23 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
MuSTARD is a singular project in the sense that investigators will develop a computational framework that is conceived as a common solution for disparate applications. This framework responds to a common need: the derivation of multi-scale spatio-temporal (ST) models equipped with statistical inference capabilities. Since the sequencing of the human genome, a significant portion of clinical research has shifted to the study of precision medicine (PM), resulting in numerous breakthroughs in both non-communicable and infectious diseases. PM refers to disease treatment and prevention that considers variability in genes, environment, and lifestyle for each person. Main drivers of PM are the omics technologies . Omics data is obtained from new high-throughput instruments that generate massive volumes of data. It is also notoriously complex data to analyze. In the last years, new separation technology has allowed us to measure omics data at single-cell resolution, creating a new (and even more complex) type of data generally referred to as single-cell omics. This allow us to study the spatial distribution of omics in a sample. Spatial and single cell omics represents one of the most powerful approaches today to understand cancer propagation in both time and space. Spatial omics. Unfortunately, there are no computational tools that can readily combine the nature of this new type of data with powerful statistical inference. Furthermore, spatially resolved omics experiments with repeated measures is another form of complex ST data. MuSTARD will provide a new computational framework that can handle ST omics to understand colorectal cancer propagation in both time and space, and leverage it in a new clinical study of reduced sample size (15 patients). The MuSTARD computational framework applied to ST omics will be made available for the general community in the form of open software.
Study design
- Observational model
- Case only
- Time perspective
- Other
- Target follow-up
- 3 Months
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients with a diagnoses of colorectal cancer | – | – |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with a diagnosis of colorectal cancer that are going to have a cancer planned surgery
Key inclusion criteria (4 listed)
- Diagnosis for colorectal cancer
- Patients with cancer planned surgery
- Absence of instability microsatellites
- Absence of any other associated disease that can affect the cancer pathology
Key exclusion criteria (1 listed)
- Patients who need an urgent surgery
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
To develop a framework of computational tools and services capable of handling multi-scale spatio-temporal structures in massive scientific data and providing interpretable models and visualizations with sound statistical support.
Time frame: three years
Sample Collection A total of 15 patients with a diagnosis of colorectal cancer, that undergoes surgery, will be recruited. Blood and fecal samples will be collected at two time points (baseline and endpoint). In addition, three spatially distinct tissue samples will be obtained at a single time point (during cancer surgery). Measurements * Variation of the intestinal microbiota composition before and after surgery. Intestinal microbiota composition willbe determined by shot-gun sequencing techniques. * Variation of the plasma metabolite before and after surgery, by untargeted metabolimics. * Variation in specific metabolites and gene expression in the colorectal cancer's tissue samples. Next-generation sequencing and untargeted metabolomic techniques will be used. The multi-omics data will be processed and integrated using Artificial Intelligence (AI) techniques, allowing the development
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Apr 2026.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Colorectal Cancer, run by Universidad de Granada at 1 site in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 28 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Jose Camacho, PhD (+34 958248898, jcamacho@ugr.es), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To develop a framework of computational tools and services capable of handling multi-scale spatio-temporal structures in massive scientific data and providing interpretable models and visualizations with sound statistical support. (time frame: three years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Apr 2026.