Citations

5 Background: Penile cancer (PC) is often diagnosed late, which leads to advanced disease. Studies have reported that less than 18% of individuals with metastatic PC receive any kind of palliative therapy. Place of Death (PoD) is a crucial determinant of patient and caregiver preferences and the cost of caregiving at the end of life (EOL). We aimed to evaluate the trends in PoD for patients with PC in the U.S. from 2003 to 2023 based on the CDC WONDER (Wide-ranging Online Data for Epidemiologic Research) database. Methods: We analyzed data from January 01, 2003, to December 31, 2023. The data for deaths due to PC were pooled using the International Classification of Diseases-10th Revision code as C60 for malignant neoplasm of the penis. The inclusion criteria included patients aged > 25 years. PoD is defined as deaths at home and hospice (H&H) versus medical facilities. Average annual percentage change (AAPC) was calculated using the Joinpoint Regression Program, version 5.0.2. Results: The analysis demonstrated a total of n = 6,074 deaths from PC. A total of 52.1% of deaths, n = 3,167, were reported at H&H. The trend analysis demonstrates an exponential rise in H&H utilization from 34.4% in 2003 to 57.5% in 2023, AAPC [5.4284, CI (4.7-6.10, p < 0.000001]. A significant increase in the utilization of H&H is notable in both African Americans (AA), AAPC [2.8514, CI (1.0-4.7), p = 0.004], and the White population, AAPC [5.3497, CI (4.6-6.0); p < 0.000001]. However, a racial disparity is also noted, with 45.4% in AA, while the White population is at 52.5% deaths in H&H-based care. PC mortality in medical facilities has a 29.7% decline from 2003 to 2023. On age stratification, there was a significant increase in utilizing H&H as PoD for the 45-64 years cohort AAPC [4.29, CI (3.2, 5.2), p < 0.000001], similarly, with the older age group 65+ cohorts AAPC [6.26, CI (5.4, 7.0), p < 0.000001]. In contrast, the younger cohort deduced no significant trend AAPC [2.92, CI (-1.5, 7.6), p = 0.14]. Conclusions: This is the first study to our knowledge providing valuable insights into the evolving PoD preferences among PC patients in the U.S.The age-related trends underscore the importance of tailoring end-of-life care strategies to specific age cohorts. The findings emphasize the importance of policies promoting and supporting H&H care for PC patients. Targeted efforts are warranted to address notable disparities in PoD preferences among racial and age groups.

TPS283 Background: Emerging evidence suggests that metastasis-directed therapy (MDT) with stereotactic body radiotherapy (SBRT) can delay systemic therapy in oligometastatic castration-sensitive prostate cancer (omCSPC). However, the optimal timing of androgen deprivation therapy (ADT) and androgen receptor pathway inhibitor (ARPI) initiation in this setting remains undefined. While deferred ADT following MDT may preserve quality of life, early short-course ADT/ARPI may eradicate micrometastatic disease and extend progression-free survival. Extracellular vesicles (EVs) carrying PSMA-positive prostate cancer (PC) signals and circulating tumor DNA (ctDNA) may serve as real-time biomarkers of MRD and treatment response. Methods: DIVINE [NCT06378866] is an open-label, phase II, randomized trial enrolling men with omCSPC defined by 1–5 metastases (≥1 extrapelvic) on conventional imaging (CT/MRI and bone scan) and testosterone >100 ng/dL. PSMA PET may be obtained for correlative purposes but does not determine eligibility. Participants (N = 220) are randomized 1:1 to: Arm A (Early systemic): SBRT plus 6 months of ADT + ARPI. Arm B (Deferred systemic): SBRT alone with observation, reserving systemic therapy until radiographic progression not amenable to further SBRT (mrPD). SBRT is delivered per institutional standard; repeat SBRT is allowed until lesions become non-addressable. The primary endpoint, modified radiographic progression-free survival (mrPFS), is the time from randomization to death or radiographic progression not amenable to further MDT, defined by PCWG3 (bone) and modified RECIST 1.1 (soft tissue) criteria on conventional imaging. Soft-tissue progression requires ≥ 20% increase in measurable disease or a new lesion; bone progression requires ≥ 2 new confirmed lesions. Secondary endpoints include OS, biochemical PFS, time to local and distant progression, and grade 3–5 adverse events during systemic therapy. Exploratory endpoints evaluate EV and ctDNA kinetics as MRD markers, correlation of PSMA-positive EV burden with outcomes, and duration of response after short-course ADT/ARPI. Correlative analyses will longitudinally quantify PSMA-positive EVs and ctDNA at baseline, on treatment, and at progression to define MRD dynamics and resistance patterns. The trial uses Pocock–Simon dynamic allocation by EV strata and metastatic burden to ensure balance across arms. The trial is open and actively enrolling across all Mayo Clinic sites; as of October 2025, 35 of the planned 220 patients have been accrued. Clinical trial information: NCT06378866 .

Abstract Hereditary hemorrhagic telangiectasia (HHT) results in recurrent severe epistaxis, chronic gastrointestinal bleeding, and other morbid manifestations. Pomalidomide was recently demonstrated to be efficacious for bleeding in HHT in the landmark PATH-HHT trial. Given that the vascular remodeling that results in bleeding improvement may require several months, characteristics associated with treatment response would be invaluable to plan treatment. Using data from PATH-HHT (NCT03910244), we identified characteristics associated with change from baseline in Epistaxis Severity Score (ESS; a well-validated 10-point HHT bleeding scale and the trial’s primary end point) using multivariable-adjusted repeated-measures models. Characteristics associated with a better response to pomalidomide at weeks 16 to 24 of the trial included a higher (more severe) baseline ESS (change from baseline, −0.76 [95% confidence interval (CI), −0.99 to −0.54] points per 1-point higher baseline score, P&lt; .001) and concomitant antifibrinolytic therapy (−0.73 [95% CI, −1.48 to 0.01] vs no therapy, P = .05). Characteristics associated with a less robust response were older age (0.29 [95% CI, 0.05-0.53] per 10 years older, P = .02) and underlying ACVRL1 germ line mutation (0.62 [95% CI, −0.04 to 1.27] vs ENG, SMAD4, or mutation not known, P = .06]. Characteristics notably associated with placebo response (placebo effect) were patient-reported outcome measures, such that those experiencing more severe disease at baseline had less placebo effect. In conclusion, several baseline patient and disease characteristics were associated with pomalidomide response, findings that may help guide patient selection for the use of pomalidomide in HHT. This trial was registered at www.Clinicaltrials.gov as NCT03910244.

Abstract Introduction: Accurate detection and prioritization of tumor-specific somatic variants is foundational to the development of personalized immunotherapies. Traditional pipelines for neoepitope identification rely heavily on short-read next-generation sequencing (NGS) and DNA-based variant calling, followed by RNA expression filtering and HLA-binding prediction. However, this approach is limited by time-intensive workflows, potential false positives from DNA-only calls, and poor capture of complex isoforms or RNA-level editing. Moreover, the accuracy of neoepitope prediction is constrained by conventional sequence-based HLA binding algorithms that do not account for structural and biophysical features of peptide-MHC interactions, particularly across underrepresented HLA alleles. Methods: To overcome these limitations, we developed a streamlined, sequencing-to-vaccine framework that leverages long-read RNA sequencing for direct detection of expressed somatic variants, including fusions, indels, and single nucleotide variants. Using Oxford Nanopore Technologies’ cDNA-PCR approach, we enable comprehensive, full-length transcript characterization from both fresh and frozen breast tumor samples. Our bioinformatic pipeline, NeoTarget, integrates alignment, variant calling, and neoepitope inference from tumor RNA in a single, modular workflow. A core innovation of this pipeline is HLA-Inception, a deep convolutional neural network trained to predict peptide-MHC class I binding using features derived from molecular dynamics-based modeling of electrostatic potential at the peptide-HLA interface, enhancing generalizability across diverse HLA subtypes. Results: Expanding on previous results, the current NeoTarget pipeline identifies, evaluates, and prioritizes single nucleotide variants, indels, and fusions. To validate this system, we used a set of 9 human breast cancer tumors benchmarked with short read sequencing. Identified neoantigens included most variants shown by clinical short read sequencing and also novel structural variants (i.e., fusions) only revealed with long read sequencing with high confidence. Conclusion: Here, we describe the design and performance of the NeoTarget pipeline, and show proof-of-concept feasibility of applying this fast and cost-effective workflow for HLA-restricted epitope discovery in breast tumors using long-read RNA sequencing. Overall, these methods can be applied to rapidly identify and prioritize neoantigens for personalized neoantigen-based immune therapies. Citation Format: F. Batalini, S. Henry, Y. Zhang, R. Foster, J. M. Gayton, A. Hostal, E. A. Wilson, A. Singharoy, M. Gustafson, B. Pockaj, J. Park, K. S. Anderson. Somatic variant detection using long read RNA sequencing reveals HLA-restricted targets for immunotherapy [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-06-08.

Abstract Background: Triple-negative breast cancer (TNBC) is an aggressive yet immunogenic subtype of breast cancer (BC) and the only one with FDA-approved immune checkpoint inhibitor (ICI) - pembrolizumab. Currently, PD-L1 (22C3) is the companion biomarker for predicting pembrolizumab benefit, but its utility is limited by spatial/temporal heterogeneity, assay variability, and modest correlation with treatment response. Chemokines such as CXCL9, CXCL10, and CCL5 recruit CD8+ T cells into the tumor microenvironment and have been associated with improved response to ICI, but their predictive value alongside PD-L1 remains unclear. Here, we examined the relationship between these chemokines, PD-L1, and pembrolizumab efficacy in TNBC. Methods: We analyzed 3662 TNBC tumors profiled by NGS (592, NextSeq; WES/WTS, NovaSeq; Caris Life Sciences). Immune cells were estimated using WTS deconvolution (Quantiseq). PD-L1 positivity was defined as &gt;10% CPS (PharmDx 22C3). CXCL9/CXCL10/CCL5-high (H) and -low (L) TNBC were classified by RNA expression above or below 50th percentile. Real-world median overall survival (mOS) was derived from insurance claims and calculated from start of pembrolizumab to last contact using Kaplan-Meier. Statistical significance was assessed by chi-square and Mann-Whitney U with multiple comparison adjustments (q&lt;0.05). Results: TNBC expressed higher levels of CXCL9, CXCL10, and CCL5 (N = 3662, median TPM: 5.3, 14.8, and 15.1) compared to HER2+ (N = 1344; 4.8, 10.1, 10.6) and HR+HER2- BC (N = 6097; 2.7, 6.6, 9.4), all q&lt;0.05. Moderate correlations were observed between PD-L1 CPS and each chemokine (r = 0.41, p&lt;.01). PD-L1-positive tumors had better mOS (24.3 months (m) vs 18.6 m, HR 0.75, 95% CI 0.6-0.92, p=0.007) compared to PD-L1-negative TNBC post-pembrolizumab. Among PD-L1-negative tumors, those with CXCL9-H had better mOS (26.9 m vs 15.8 m for CXCL9-L, HR 0.61, 95% CI 0.45-0.82, p=0.001) post-pembrolizumab. Among PD-L1-positive tumors, CXCL10-H and CCL5-H was associated with improved mOS (CXCL10-H: 25.7 m vs. 20.7 m for CXC10-L, p = 0.03; CCL5-H: 26.7 vs. 18.5 m for CCL5-L, p = 0.03) post-pembrolizumab. PD-L1 negative CXCL9-H, PD-L1 positive CXCL10-H and PD-L1 positive CCL5-H groups showed higher infiltration of CD8+ T cell, B cells, M1/M2 macrophages, Tregs. They also exhibited higher T cell inflamed score, IFNy score and MAPK activation score vs. CXCL9-L, CXCL10-L and CCL5-L groups (Table). Conclusions: In TNBC, a chemokine signature comprising CXCL9, CXCL10 and CCL5 refines PD-L1 based prediction of pembrolizumab benefit. Specifically, high CXCL10 or CCL5 expression in PD-L1-positive tumors, and high CXCL9 expression in PD-L1-negative tumors, were associated with improved survival post pembrolizumab and immune-rich microenvironment. These findings support the use of chemokine profiling to complement PD-L1 and enhance patient selection for ICI therapy in TNBC. Citation Format: S. Gandhi, S. Deshmukh, S. Wu, J. Xiu, G. Sledge Jr., D. Trapani, J. Leone, S. Chumsri, M. Lustberg, C. Hong, S. Yao, K. Takabe, M. Ernstoff, M. Opyrchal, P. Chalasani, C. Paulos, G. Lesinski, A. Madabhushi, S. Badve, K. Kalinsky, P. Kalinski. Chemokine signatures improve PD-L1-based prediction of pembrolizumab response in triple-negative breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-08-14.

Abstract Background: In MBC, CTC enumeration is highly prognostic for both progression free survival (PFS) and overall survival (OS). Multiparametric technologies enable for expanded phenotypic profiling of CTCs, including ER and HER2 assessment. Limited information is available on the concordance of CTC ER and HER2 levels compared to synchronously obtained tissue. We assessed the prognostic performance of CTC enumeration and phenotypic profiling of ER and HER2 on CTCs. Methods: The prospective, multi-institutional Aurora study enrolled pts with MBC of any subtype either at diagnosis of metastatic disease or at time of progression on any line of systemic therapy. Pts underwent a metastatic site biopsy, consented to archival primary tissue collection and donated blood samples serially every 3-4 months until progression. CTCs, from blood collected at study entry, were identified as nucleated, EpCAM+/ cytokeratin+/ CD45- cells using an automated imaging system (RareCyte, Seattle). ER and HER2 expression levels were measured by mean fluorescence intensity (MFI), with thresholds above 80 (ER) and 160 (HER2) considered positive. Comparisons were made to total RNAseq from paired metastatic tissue biopsies. PFS and OS were calculated from the time of study entry to last follow up or death. Results: Baseline CTC enumeration was performed in 154 pts. The most common clinical subtype was HR+/HER2- (59.7%), followed by HER2-positive (16.8%) and TNBC (15.5%). The median lines of prior therapy were 1 (range 0-10). At least 1 CTC was identified in 68/154 pts (44%), 30 (19%) had ≥ 5 CTCs, and 15 (9.7%) had CTC clusters. The median CTC value was 0 (0-877). The presence of CTCs (≥1 or ≥5) and CTC clusters was adversely associated with PFS and OS (Table 1 Table 1. CTC survival analyses Number Median PFS PFS HR (95% CI) Median OS OS HR (95% CI) Presence of CTC 0 CTC 86 7.37 (0.03 - 43.1) reference 20.72 (0.03 - 50.6) reference ≥ 1 CTC 68 4.7 (0.43 - 19.5) 1.65 (1.16-2.36) 12.04. (0.43-44.1) 2.13 (1.44-3.16) Presence of ≥ 5 CTC &lt;5 CTC 124 7.7 (0.03 - 43.1) reference 19.31 (0.03 - 50.6) reference ≥ 5 CTC 30 2.88 (0.43 - 18.7) 1.77 (1.15 - 2.71) 5.74 (0.43 - 29.3) 3.59 (2.26-5.70) Presence of clusters 0 clusters 139 7.37 (0.03 - 43.1) reference 18.06 (0.03 - 50.6) reference ≥ 1 cluster 15 1.91 (0.43 - 18.7) 2.06 (1.16 - 3.68) 3.42 (0.43 - 18.7) 5.44 (2.94-10.09) ). Across all subtypes, the median CTC ER-MFI across was 36.2 (range 4.2-10,016.6) and the median HER2-MFI was 139.6 (range 4.2-2480.5). We observed high intra-patient heterogeneity of ER-MFI (CV: 0.65 [0.34-1.25]) and HER2-MFI (CV: 0.79 [0.42-1.54]). Clinical metastatic subtype from metastasis at study entry was available in 54/68 pts with CTCs. Pts with clinical ER+ MBC had a higher median ER-MFI compared to clinical TNBC (111.9 vs 68.6, p = 0.02). However, 11 pts (26.8%) with clinical ER+ MBC had all CTCs with an ER-MFI &lt;80. Lower ER expression was observed in CTCs collected after prior exposure to a SERD (median ER-MFI: post-SERD [n=8] 27 vs post-aromatase inhibitor [n=4] 252, p&lt;2.22e-16). No correlations were observed between the median CTC ER-MFI or HER2-MFI and paired tissue ESR1 or ERBB2 RNA expression (n=66). Conclusions: CTCs are strongly predictive of PFS and OS. CTC ER- and HER2-MFI were highly heterogeneous without clear correlation with bulk tissue RNA expression. The clinical impact of discordant clinical receptor status and CTC receptor status warrants further exploration. Citation Format: K. V. Giridhar, W. C. Nenad, H. Ye, G. L. Wheeler, T. Hinoue, A. R. Michmerhuizen, B. M. Felsheim, U. R. Chandran, B. J. Kelly, E. R. Mardis, P. W. Laird, J. M. Balko, A. C. Garrido-Castro, S. Coppens, J. Bowen, R. Nanda, N. U. Lin, C. K. Anders, C. Isaacs, J. J. Tao, J. D. Anampa, N. Jahan, L. Huppert, A. DeMichele, B. H. Park, S. Vinayak, A. L. Delson, M. M. Magbanua, M. Balic, H. A. Parsons, A. V. Lee, L. A. Carey, L. Norton, A. C. Wolff, N. E. Davidson, I. Krop, T. A. King, C. M. Perou, K. A. Hoadley, Aurora US Metastases Network. Characterizing circulating tumor cell (CTC) enumeration and phenotypic profiling in blood with synchronously obtained tissue in metastatic breast cancer (MBC) in TBCRC /AURORA US [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-07-17.

Abstract Allogeneic hematopoietic cell transplantation (allo-HCT) is a potentially curative treatment for many hematological malignancies, but graft-versus-host disease (GVHD) is a common complication. Low gut microbiome diversity is associated with higher GVHD risk and shorter survival in multiple studies. Recently, the BMT CTN 1703 clinical trial demonstrated superiority of a GVHD-prophylaxis regimen including post-transplant cyclophosphamide (PTCy) compared to the standard prophylaxis (tacrolimus and methotrexate, Tac/MTX) in terms of GVHD-free, relapse-free survival at one year among reduced intensity conditioning allo-HCT recipients. However, the effect of PTCy on the gut microbiome and its association with clinical outcome have not been described. Here, we report on a companion randomized clinical controlled trial (BMT CTN 1801), which collected 2575 longitudinal stool samples from 304 study participants. Samples were obtained up to weekly up to day 84 post allo-HCT and at less frequent intervals thereafter, up to 2 years. Microbiome diversity and absolute microbial load were lower in the PTCy group compared to the Tac/MTX group on days 14–28 post-HCT. However, diversity at the timepoint closest to neutrophil engraftment was not significantly associated with non-relapse mortality after one year or other clinical outcomes, contrary to expectations from previous studies. Microbial domination events, when a single species exceeds 30% relative abundance, were comparable across treatment arms and reflected both pathogen blooms as well as less severe disruptions of the microbial community. Clostridium scindens and secondary bile acid metabolism pathways were less prevalent in the PTCy arm than in the Tac/MTX arm post-HCT, yet presence of secondary bile acid metabolism pathways was associated with a lower risk of chronic GVHD. Given that PTCy was associated with a greater disruption of the microbiome as measured by diversity, absolute microbial abundance, and bile acid metabolism capability, but better clinical outcomes overall, these data suggest that the importance of the microbiome in modulating the host immune systems after allo-HCT is specific to different types of GVHD prophylaxis.

Abstract Background: Clear cell renal cell carcinoma (ccRCC), metastatic castration-resistant prostate cancer (mCRPC), and glioblastoma (GBM) are highly treatment-refractory tumors characterized by elevated TGF-β1, a key suppressor of antitumor immunity and antigen presentation. Because CAR-T cells infiltrating these tumors experience persistent physiologic TGF-β exposure, assessing CAR-T functional resilience across increasing TGF-β concentrations is critical for determining therapeutic feasibility. Methylseleninic acid (MSA), a pharmacologic selenium compound, potently inhibits TGF-β1, PD-L1, and VEGF with minimal off-target toxicity. FN14, the TWEAK receptor and a metastasis driver, is selectively overexpressed in these malignancies, making it a high-specificity CAR target. Methods: We developed second-generation anti-FN14 CARs containing CD28 or 4-1BB costimulatory domains and a CD3ζ signaling motif, then lentivirally transduced into primary human CD4+ and CD8+ T cells. Cytotoxicity against FN14+ ccRCC, mCRPC, GBM lines and patient-derived cells was assessed using LDH release and xCELLigence assays. Effector function was evaluated through intracellular cytokine profiling, multiplex analysis, and phenotypic characterization by flow cytometry. CAR-T persistence in TGF-β-rich conditions was measured using CCK-8 proliferation assays, and Ki-67 and activation/exhaustion markers (PD-1, CXCR3) in the presence of 0-10 ng/mL TGF-β. MSA’s immunomodulatory and synergistic effects were tested at physiologically concentrations to measure impacts on CAR-T viability, metabolic activity, cytokine secretion, and tumor cell susceptibility. Results: Anti-FN14 CAR-T cells mediated rapid, antigen-specific lysis across all tumor types, achieving &gt;50% specific killing at a 1:1 E:T ratio. MSA (2.5-5 µM) reduced tumor PD-L1 and TGF-β expression by &gt;40% and enhanced CAR-T metabolic activity, IL-2, and IFN-γ secretion. CAR-T cells maintained comparable proliferation and activation in 0-5 ng/mL TGF-β, indicating that antigen-driven signaling counteracted low-to-moderate TGF-β-mediated suppression. Ex vivo CAR-T manufacturing with MSA (2.5 µM) improved cytotoxicity and persistence versus untreated CAR-T cells (p &lt; 0.01). MSA’s effects were dose- and schedule-dependent and remained within human-relevant exposure ranges without detectable toxicity. Conclusion: MSA enhances anti-FN14 CAR-T cytotoxicity, metabolic fitness, and sustained effector activity by suppressing tumor-derived TGF-β1 and PD-L1 and by directly improving CAR-T functional capacity. Consistent with this mechanism, physiological TGF-β levels (0-5 ng/mL) did not significantly impair CAR-T proliferation or activation, demonstrating intrinsic resilience of FN14 CAR-T cells in TGF-β-rich environments. As a clinically relevant TGF-β1 inhibitor and active metabolite of seleno-L-methionine, MSA represents a readily translatable strategy to reduce CAR-T exhaustion and enhance efficacy in TGF-β-rich solid tumors including ccRCC, mCRPC, and GBM. Citation Format: Obed B. Amissah, Casey Ager, Yousef Zakharia, Youcef M. Rustum, Gloria B. Kim. Anti-FN14 CAR-T cells overcome TGF-β-mediated suppression, and their synergy with methylseleninic acid enhances cytotoxicity and effector function in kidney, prostate, and brain tumors [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr C010.

Abstract The adoption of electronic health records (EHRs) has transformed health care, improving efficiency and chart accessibility. However, the widespread reliance on unstructured data entry and the lack of standardized documentation frameworks have resulted in significant data fragmentation across health care systems. The prevalence of unstructured data in EHRs limits their potential for clinical decision support, trial matching, real‐world evidence (RWE) generation, and quality measurement. Data fragmentation in health care triggers a cascade of challenges that ultimately compromise patient care. Clinicians face an excessive documentation burden and struggle to locate critical information buried in unstructured notes. Researchers encounter difficulties in extracting reliable clinical data. EHR vendors grapple with standardizing unstructured information for interoperability, and payers are unable to process unstructured clinical data efficiently to support value‐based care models. These challenges are particularly acute in oncology, where complex clinical elements like cancer staging, disease status, and treatment changes require precise, structured documentation. Emerging artificial intelligence (AI) technologies, such as large language models (LLMs) and ambient listening, offer a path to automate structured data generation while reducing the workload on providers. Here, the authors propose LLM‐based workflows that balance automation with clinician verification, streamlining data entry without compromising accuracy. Realizing these benefits requires coordinated efforts among clinicians, researchers, EHR vendors, payers, and policymakers to align regulatory frameworks with AI‐driven innovations. This article outlines a strategy to enhance structured data capture within EHRs, ultimately improving patient care, research, and health care efficiency.