Breast Cancer

“We tried to look into artificial intelligence models that could use synthetic and real-world data to create, a twin data set that matches the same statistical patterns.”

Eddy Saad, MD, a postdoctoral research fellow at Dana-Farber Cancer Institute, discussed how the growing need for timely, high-quality evidence in metastatic breast cancer informed the rationale for exploring AI-generated synthetic cohorts as a complementary tool for clinical trial design and multi-stakeholder collaboration.

The oncology field is experiencing a rapid increase in accelerated FDA approvals, creating substantial pressure to generate robust data to guide therapeutic decision-making. Although traditional clinical trials remain essential, Saad noted that they require significant time, financial investment, and operational resources. Real-world data (RWD) has emerged as an alternative source of evidence; however, its utility is often limited by privacy protections, regulatory constraints, and restricted data-sharing agreements across institutions.

To address these barriers, Saad and colleagues evaluated the use of artificial intelligence models capable of generating synthetic datasets derived from a large RWD repository of approximately 19,000 patients with metastatic breast cancer. These models create statistically representative “twin” datasets that reflect the distributions and clinical relationships present in real-world populations without containing identifiable patient information. This approach enables privacy-preserving data sharing while maintaining the analytical value of the underlying data.

Based on these capabilities, synthetic cohorts may support more efficient trial development, Saad explained. Investigators can simulate eligibility criteria, event rates, and control arms, allowing refinement of study design before trial activation. These datasets may also be shared among academic groups, industry sponsors, and regulatory collaborators without the constraints typically associated with protected health information, facilitating alignment on feasibility assumptions and methodological planning.

Saad emphasized that although synthetic datasets cannot replace prospective studies, they offer a practical and scalable solution to support early-phase trial design and accelerate cross-institutional collaboration. Importantly, the breadth of the underlying metastatic breast cancer dataset allows these synthetic models to capture clinically relevant heterogeneity, improving simulation accuracy for diverse subpopulations.

Thus, the development of synthetic cohorts aims to streamline evidence generation, enhance collaborative trial planning, and help investigators more efficiently evaluate emerging therapeutic strategies in metastatic breast cancer.

Videos

Eddy Saad, MD, discusses how AI-generated synthetic cohorts derived from real-world data may accelerate trial design and collaboration in metastatic breast cancer.

Dr Saad on the Rationale for AI-Generated Synthetic Cohorts in Metastatic Breast Cancer Research

Eddy Saad, MD, MSc, the potential predictive value of IL-7 SNPs to inform treatment decisions for select patients with renal cell carcinoma.

Dr Saad on the Potential Predictive Value of IL7 SNPs in RCC

Eddy Saad, MD, MSc, postdoctoral research fellow, Dana-Farber Cancer Institute, discusses results from a study characterizing the association between a germline single nucleotide polymorphism (SNP) in the interleukin-7 (IL-7) gene and immune-related adverse effects (AEs), highlighting how this may inform treatment decision-making for select patients with renal cell carcinoma (RCC) who have received treatment with immune checkpoint inhibitors (ICIs).

Results revealed that the presence of an IL-7 single nucleotide polymorphism (SNP) is associated with an increased risk of immune-related adverse effects (irAEs) in patients receiving PD-1 inhibitors, such as nivolumab (Opdivo) and pembrolizumab (Keytruda). Saad explained that this association was not observed in patients treated with non-ICI therapies, like everolimus (Afinitor). Moreover, the presence of the IL-7 SNP did not correlate with differences in treatment outcomes or survival among patients treated with checkpoint inhibitors in either of the trials. These findings are significant as they suggest a potential genetic biomarker for predicting irAEs in patients undergoing ICI therapy, which could help clinicians better manage and personalize treatments.

Currently, there are no clinically available biomarkers to identify patients at risk for irAEs, making this discovery potentially transformative for cancer care, Saad begins. If validated in further studies, the IL-7 SNP may guide clinical decision-making by identifying patients who have the potential to benefit from preemptive strategies to mitigate irAEs, Saad states. For instance, patients identified as SNP carriers may receive an immunosuppressive regimen alongside their ICI therapy or have their treatment regimen adjusted to minimize the risk of irAEs, he explains.

The next steps involve advancing this research into a phase 3 clinical trial to confirm these findings and explore the clinical utility of using the IL-7 SNP as a predictive biomarker, Saad continues. Additionally, ongoing research aims to elucidate the biological mechanisms by which this germline variant contributes to irAEs, he says. However, understanding these mechanisms has proven challenging, partly because replicating these findings in model organisms such as mice has been difficult, Saad notes. Researchers are currently focused on identifying the specific immune cells involved in this association, which could provide insights into the underlying pathways and reveal new therapeutic targets, he details.

By uncovering the mechanisms at play and potentially identifying new therapeutic targets, this research could lead to more tailored and safer cancer immunotherapy options, improving outcomes for patients who are at higher risk for irAEs, Saad continues.

Dr Saad on the Association Between IL-7 SNPs and Immune-Related AEs in RCC

Eddy Saad, MD, MSc, postdoctoral research fellow, Dana-Farber Cancer Institute, discusses findings from a study characterizing and validating the association between a germline single nucleotide polymorphism (SNP) in the interleukin-7 (IL-7) gene and immune-related adverse effects (AEs) in 2 prospective, randomized, phase 3 trials of patients with cancer, including renal cell carcinoma (RCC), who received immune checkpoint inhibitors (ICIs).

This study included data from the phase 3 CheckMate 025 trial (NCT01668784) investigating nivolumab (Opdivo) vs the mTOR inhibitor everolimus (Afinitor) in patients with advanced RCC. Investigators also analyzed data from the phase 3 INTR@PID LUNG 037 trial (NCT03631706), which evaluated bintrafusp alfa vs pembrolizumab (Keytruda) in patients with advanced non–small cell lung cancer.

Across both studies, investigators found that the presence of an IL-7 SNP was associated with immune-related AEs in patients who received the PD-1 inhibitors nivolumab and pembrolizumab, Saad says. However, the presence of this SNP was not associated with immune-related AEs in the patients who received non-ICI agents, such as everolimus, Saad explains. This finding indicates that the relationship between the presence of SNPs and the incidence of immune-related AEs is limited to SNP carriers who receive ICIs, he notes. The IL-7 SNP was also associated with recurrent immune-related AEs in the ICI arms of the CheckMate 025 trial.

Moreover, the presence of an IL-7 SNP was not associated with treatment or survival outcomes with checkpoint inhibitors in either trial, Saad emphasizes. In CheckMate 025, the differences in PFS and OS outcomes with nivolumab between the IL-7 SNP carriers and SNP wild-type patients were not statistically significant (PFS, log-rank 

 = .74). Therefore, this SNP may be used as a biomarker to predict which patients may develop immune-related AEs from ICIs, Saad reports. Patients who are at higher risk of developing these AEs may then be considered for other types of treatment, Saad concludes.

Eddy Saad, MD, MSc, discusses the association between an IL-7 SNP and immune-related AEs in patients with RCC who received immune checkpoint inhibitors.

Eddy Saad, MD, MSc

Articles

Dr Saad on the Rationale for AI-Generated Synthetic Cohorts in Metastatic Breast Cancer Research

Dr Saad on the Potential Predictive Value of IL7 SNPs in RCC

Dr Saad on the Association Between IL-7 SNPs and Immune-Related AEs in RCC