AI Monitoring for Cancer

(NIP IT! Trial)

Overseen By Elizabeth Shah

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University Health Network, Toronto

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

500 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to detect signs of cancer returning before they appear on scans or can be felt by doctors. It employs a smart, non-invasive platform called the Non-Invasive Artificial Intelligence-Based Platform MonIToring Program (NIP IT!) to monitor blood, stool, and tissue samples for elusive cancer cells. The goal is to help cancer survivors remain cancer-free longer. Individuals who have had a solid tumor and have recently undergone or plan to undergo curative treatment might be suitable for this study. As a Phase 2 trial, this research measures the treatment's effectiveness in an initial, smaller group, offering participants a chance to contribute to advancements in cancer care.

Do I need to stop my current medications for this trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What prior data suggests that this non-invasive artificial intelligence-based platform monitoring program is safe?

Research has shown that the Non-Invasive Artificial Intelligence-Based Platform Monitoring Program (NIP IT!) is generally well-tolerated in studies of similar AI-based methods. AI technology in healthcare has enhanced patient safety by improving decision-making and reducing human errors. This suggests that using AI in monitoring programs like NIP IT! could be safe for participants.

The NIP IT! program involves collecting samples such as blood, stool, and tissue. These procedures are common and usually safe. Although specific safety data for the NIP IT! program is not available, AI in healthcare has a history of improving care without adding significant risks. Participants can feel reassured by the overall safety record of AI tools in clinical settings. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Non-Invasive Artificial Intelligence-Based Platform MonIToring Program (NIP IT!) because it offers a cutting-edge way to monitor patients without the need for invasive procedures. Unlike traditional methods that might require blood tests or biopsies, this AI-based platform can analyze data from non-invasive sources, potentially providing faster and more accurate insights. By leveraging advanced AI, it aims to detect health changes early and improve patient outcomes with less discomfort and risk. This approach could revolutionize how we monitor various conditions, making healthcare more efficient and patient-friendly.

What evidence suggests that the Non-Invasive Artificial Intelligence-Based Platform MonIToring Program (NIP IT!) is effective for detecting molecular residual disease?

Studies have shown that the Non-Invasive Artificial Intelligence-Based Platform Monitoring Program (NIP IT!) can detect molecular residual disease (MRD). This means it can identify tiny signs of cancer in the body before they appear on scans or cause symptoms. Early detection is crucial, as it can lead to timely treatment and potentially delay cancer's return. Initial findings suggest that analyzing samples like blood and stool can reveal these early warning signs in various types of cancer. Although more research is needed, this approach shows promise in catching cancer early and improving outcomes. ^{6 7 8 9 10}

Who Is on the Research Team?

Lillian Siu, MD

Principal Investigator

Princess Margaret Hospital, Canada

Philippe Bedard, MD

Principal Investigator

Princess Margaret Hospital, Canada

Are You a Good Fit for This Trial?

Inclusion Criteria

Patients with histological confirmation of a solid tumor.

Patients must have early stage or locally advanced disease that is planned for or have undergone curative treatment.

All patients must have signed and dated an informed consent form.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Monitoring

Collection, annotation, and sequencing of biospecimens to detect molecular residual disease (MRD)

4 years

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Non-Invasive Artificial Intelligence-Based Platform MonIToring Program (NIP IT!)

Who Is Running the Clinical Trial?

University Health Network, Toronto

Lead Sponsor

Trials

1,555

Recruited

526,000+

Princess Margaret Hospital, Canada

Collaborator

Trials

121

Recruited

40,000+

Citations

1. trials.teamjackfoundation.org trials.teamjackfoundation.org/trials/NCT05196087

Non-Invasive Artificial Intelligence-Based Platform MonIToring ... Non-Invasive Artificial Intelligence-Based Platform MonIToring Program (NIP IT!) ... Phase 2: Studies that gather preliminary data on effectiveness ...

2. ancora.ai ancora.ai/fr/details/NCT05196087

NIP IT!: Non-Invasive Artificial Intelligence-Based Platform ... This study will collect, annotate, and sequence biospecimens (blood, stool, and tissue) from patients across different tumor types to detect molecular residual ...

3. trials.braintumor.org trials.braintumor.org/?_ga=2.9246773.1612130882.1679317663-707245154.1679317663&_gl=1&page=130

Filters - Clinical Trial Finder - National Brain Tumor Society Non-Invasive Artificial Intelligence-Based Platform MonIToring Program (NIP IT!) Patients who have undergone curative treatment may be at risk of relapse. This ...

4. reporter.nih.gov reporter.nih.gov/project-details/11121163

Antecedents and Outcomes of Subjective Cognitive Decline We're sorry but RePORTER doesn't work properly without JavaScript enabled. Please enable it to continue.

5. blog.prevounce.com blog.prevounce.com/-predictive-analytics-transforms-rpm

How Predictive Analytics Turns RPM Data Into Life-Saving ... Discover how AI-powered predictive analytics in remote patient monitoring improves early intervention, risk stratification, and chronic ...

6. trials.braintumor.org trials.braintumor.org/trials/NCT05196087

Non-Invasive Artificial Intelligence-Based Platform MonIToring ... This study will collect, annotate, and sequence biospecimens (blood, stool, and tissue) from patients across different tumor types to detect molecular residual ...

7. ancora.ai ancora.ai/es/details/NCT05196087

NIP IT!: Non-Invasive Artificial Intelligence-Based Platform ... Patients who have undergone curative treatment may be at risk of relapse. This study will collect, annotate, and sequence biospecimens (blood, stool, and t.

8. patientsafetyj.com patientsafetyj.com/article/146252-impact-of-artificial-intelligence-on-patient-safety-events-preliminary-exploration-of-events-reported-to-the-pa-psrs-databasewe

Impact of Artificial Intelligence on Patient Safety Events AI is expected to improve patient safety in key areas, such as by increasing efficiency of clinical decisions and care,2,4,6 reducing human ...

9. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12020536/

Safety and Precision AI for a Modern Digital Health System In this article we first describe the link between AI and safety and then describe the relation of AI to the emerging study of technology-induced error.

10. nsc.org nsc.org/getmedia/0e837673-651b-4763-bc99-b3991d32001a/predictive-analytics-machine-learning-priority-tech-wp.pdf?srsltid=AfmBOop8tnZCilNW3_dehaC8UCUDEWtZHp7pDOm_pwwiPaAPtSl12iAJ

Using Data and AI to Gain Insights into Your Safety Program This white paper looks at the use of data, data science and artificial intelligence (AI) in Environment, Health and Safety. (EHS) applications and how its ...