Personalized Drug Selection for Pancreatic Cancer

Overseen By Robert C. Grant, MD

Age: 18+

Sex: Any

Trial Phase: Phase 2

Sponsor: University Health Network, Toronto

Must not be taking: Anticancer therapies

Disqualifiers: Concurrent malignancy, Brain metastases, Cardiac conditions, others

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

Prior Safety Data This treatment has passed at least one previous human trial

Compensation: Varies

Number of Visits: Unknown

Duration: 8-12 weeks

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine if a personalized approach to drug selection can improve treatment outcomes for people with pancreatic cancer. Researchers will use small models of each patient’s tumor, called Patient Derived Organoids, to select the best treatment. Participants will join one of two groups: those with worsening disease or those with stable disease needing maintenance therapy. The trial seeks individuals with advanced pancreatic cancer who have either stable or worsening disease after standard treatments. As a Phase 2 trial, this research measures the treatment's effectiveness in an initial, smaller group, offering participants a chance to benefit from potentially effective personalized therapies.

Will I have to stop taking my current medications?

The trial protocol does not specify if you need to stop taking your current medications. However, you cannot be on any other anti-cancer therapy, except for certain supportive care medications that were started at least one month before joining the study.

Is there any evidence suggesting that this trial's treatments are likely to be safe?

Research has shown that models like Patient Derived Organoids (PDO) can help select the best treatment for each pancreatic cancer patient. These models can predict how well a tumor might respond to various drugs.

Previous patients using similar methods have demonstrated that these personalized approaches are generally well-tolerated, with most people not experiencing severe side effects. Since this trial is in Phase 2, earlier studies have already shown some safety. However, researchers continue to monitor for any side effects to ensure safety.

In summary, while personalized treatments using PDOs are still under study, early findings suggest they are generally safe and could offer a promising way to treat pancreatic cancer. ^{1 2 3 4 5}

Why are researchers excited about this trial's treatment?

Researchers are excited about using tumor models to guide personalized drug selection for pancreatic cancer because this method tailors treatment to the individual patient. Unlike standard chemotherapy options like FOLFIRINOX and Gemcitabine, which are administered based on general efficacy, this approach uses models of a patient's own tumor to predict which drug will work best for their specific cancer. By focusing on personalized treatment, the goal is to increase effectiveness and reduce unnecessary side effects, potentially improving outcomes for patients with both progressive and stable disease.

What evidence suggests that using tumor models to determine treatments might be effective for pancreatic cancer?

Research has shown that using patient-derived organoids (PDOs) to select treatments for pancreatic cancer appears promising. These organoids are tiny versions of tumors grown in the lab from a patient's own cancer cells. In this trial, participants in Cohort A will receive treatment for progressive disease, while those in Cohort B will receive maintenance therapy for stable disease. Studies have demonstrated that PDOs can help predict which drugs might work best for each person. This personalized approach aims to attack the cancer more effectively, potentially leading to better outcomes. Although more research is needed to confirm these findings, early results suggest this method could be a valuable tool in fighting pancreatic cancer. ^{5 6 7 8 9}

Who Is on the Research Team?

Robert C. Grant, MD

Principal Investigator

Princess Margaret Cancer Centre

Are You a Good Fit for This Trial?

This trial is for individuals with pancreatic cancer. It's exploring if using Patient Derived Organoids (PDO) to select a personalized drug treatment can be effective. Participants must have a type of pancreatic cancer that qualifies and should meet other specific health criteria not detailed here.

Inclusion Criteria

Life Expectancy of greater than 12 weeks

I am able to get out of my bed or chair and move around.

Ability to understand and willing to sign a written informed consent form in accordance with applicable local and regulatory requirements. Each patient must sign a consent form prior to screening to document their willingness to participate.

Exclusion Criteria

Lactating and nursing women

I do not have severe numbness or pain in my hands or feet.

Patients with a history of a severe allergic reaction attributed to compounds of similar or biologic composition to the PDO matched drug may be excluded if assessed by the investigator and determined to be unsafe to proceed

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive a drug selected based on their Patient Derived Organoids (PDO) results for either progressive disease or maintenance therapy

8-12 weeks

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Using Tumor Models to Determine Treatments

Trial Overview The study tests the effectiveness of various drugs (Colchicine, Selinexor, Abemaciclib, Ponatinib, Cobimetinib, Brigatinib, Neratinib, Doxorubicin, Etoposide, Ceritinib) chosen based on PDO models for treating pancreatic cancer. The main focus is on how many patients respond positively to their tailored treatment.

How Is the Trial Designed?

Group I: Cohort B Experimental Treatment 10 Interventions

Patients in this cohort will be entering the study for maintenance therapy with stable disease.

Group II: Cohort A Experimental Treatment 10 Interventions

Patients in this cohort will be entering the study for treatment for progressive disease.

Who Is Running the Clinical Trial?

University Health Network, Toronto

Lead Sponsor

Trials

1,555

Recruited

526,000+

Published Research Related to This Trial

The ADEStrata framework, previously used for breast cancer, was successfully applied to ovarian cancer patients treated with cisplatin, demonstrating its versatility in predicting adverse drug events (ADEs) and patient outcomes.

By analyzing 156 ovarian cancer patients, the study showed that understanding the molecular mechanisms of cisplatin-related ADEs can help identify tumor subtypes with varying clinical outcomes, potentially guiding personalized treatment strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Adverse Drug Events-based Tumor Stratification for Ovarian Cancer Patients Receiving Platinum Therapy. Wang, C., Zimmermann, MT., Chute, CG., et al.[2020]

A study involving 14 patients with pancreatic ductal adenocarcinoma (PDAC) used next-generation sequencing (NGS) to identify mutations and pharmacogenomic biomarkers, confirming known driver mutations like KRAS and TP53.

The analysis revealed that while no changes in therapy were made, the software could predict treatment efficacy and toxicity, suggesting that integrating NGS with evidence-based software could enhance precision medicine approaches for PDAC.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Bioinformatory-assisted analysis of next-generation sequencing data for precision medicine in pancreatic cancer. Malgerud, L., Lindberg, J., Wirta, V., et al.[2018]

The ADEStrata approach, developed in this study, allows for the stratification of tumor mutations based on adverse drug events (ADEs), specifically focusing on musculoskeletal adverse events in breast cancer patients treated with aromatase inhibitors, using data from 212 patients.

By prioritizing somatic variants linked to ADEs, the study found that this method can identify high-risk patients who may experience poor outcomes, suggesting that it could help tailor cancer therapies to improve patient safety and efficacy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Adverse Drug Event-based Stratification of Tumor Mutations: A Case Study of Breast Cancer Patients Receiving Aromatase Inhibitors. Wang, C., Zimmermann, MT., Prodduturi, N., et al.[2018]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12352895/

Experimental models of pancreas cancer: what has been ... Pancreatic cancer has a 5-year survival rate of approximately 13% and is projected to become the second-leading cause of cancer-related ...

2. sciencedirect.com sciencedirect.com/science/article/pii/S0305737225000957

Medical management of pancreatic cancer This figure illustrates a multiscale model integrating six levels of information used to personalize treatment in pancreatic cancer: patient-level clinical and ...

3. jenci.springeropen.com jenci.springeropen.com/articles/10.1186/s43046-025-00323-w

Pancreatic cancer in the era of precision medicine: challenges ... These advancements highlight the critical role of personalized medicine in optimizing pancreatic cancer treatment. However, further research is ...

4. nature.com nature.com/articles/s12276-024-01378-w

Advancing pancreatic cancer research and therapeutics This review highlights the critical advancements facilitated by pancreatic organoid models in understanding disease progression, evaluating therapeutic ...

5. cell.com cell.com/cell-reports-medicine/fulltext/S2666-3791(24)00413-0

CTC-derived pancreatic cancer models serve as research ... CTCs hold the potential to advance our ability to diagnose patients with cancer more accurately and earlier, predict their outcomes, monitor ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC5968824/

Genomics-Driven Precision Medicine for Advanced ... LCM dramatically increased tumor cellularity (median: 79%; range 37–93%), and enabled high-resolution genomic analysis in all cases. Performance targets for ...

7. letswinpc.org letswinpc.org/research/pass-01-trial-personalized-medicine/

PASS-01 Personalized Medicine Results The PASS-01 trial results provide data to help clarify how the subtypes of pancreatic cancer respond to the two main treatment protocols.

8. sciencedirect.com sciencedirect.com/science/article/pii/S0169409X25001279

Pancreatic organoids as cancer avatars for true ... This review presents how PDO models can revolutionize precision oncology in pancreatic cancer by prognosticating tumor response and thereby, assist clinical ...

9. aacrjournals.org aacrjournals.org/clincancerres/article/31/2/278/751097/A-Phase-III-Randomized-Trial-of-Integrated

A Phase III Randomized Trial of Integrated Genomics and ... In a large retrospective analysis of the Know Your Tumor registry trial (19), 26% of patients with pancreatic cancer were found to have actionable molecular ...