ReviewESMO real world data and digital oncology2025
Collaborating across sectors in service of open science, precision oncology, and patients: an overview of the AACR Project GENIE (Genomics Evidence Neoplasia Information Exchange) Biopharma Collaborative (BPC).
Review in ESMO real world data and digital oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Clinical and genomic determinants of early treatment discontinuation in non-small-cell lung cancer: an analysis of the AACR Project GENIE Biopharma Collaborative NSCLC dataset.ESMO real world data and digital oncology · 2026Article
- From fusion partner to clinical practice: A treatment-oriented framework for transcription factor E3 (Cancer pathogenesis and therapy · 2026Review
- Impact of somatic PIK3CA mutations on clinical outcomes in HER2-positive breast cancer.Breast cancer research : BCR · 2026Article
- Convergence of machine learning and genomics for precision oncology.Nature reviews. Cancer · 2026Review
- Learning Patient Similarity from Genomics for Precision Oncology.medRxiv : the preprint server for health sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
35 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The American Association for Cancer Research (AACR) Project GENIE (Genomics Evidence Neoplasia Information Exchange) Biopharma Collaborative (BPC) is a multi-phase, pre-competitive collaboration between 10 biopharmaceutical companies and select GENIE-participating academic institutions, focused on detailed clinical annotations of a subset of patients within the GENIE Registry. The cohorts focus on 10 solid tumors, and each integrates demographic, diagnosis, genomic, and treatment data with longitudinal, real-world patient outcomes. Data are collected following a structured framework to ensure interoperability and forward compatibility with other data models. Each cohort undergoes a series of rigorous quality control and assurance protocols which ensures consistency, accuracy, and reliability of the data across multiple institutions before public release of the data. Initial analyses of the BPC data have yielded valuable insights, including the validation of treatment-induced resistance mutations and genomic drivers associated with anatomic sites of metastasis. Additionally, the real-world response endpoints compare favorably to published trial results. Central management and a shared knowledgebase help integrate diverse functional teams in the execution of a complex, multi-institutional data collection effort. Future directions aim to automate significant portions of the clinical annotation process to collect clinical data at scale. These efforts will increase the depth and granularity of the BPC data, as well as expand the overall cohort size and range of cancer types represented.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.