Abstract 7115: PredicineDIRECT: a one-stop “from sample to result” workflow for improved sample management in oncology clinical trials
Abstract Background: Liquid biopsy is now a standard in clinical trials, improving therapy selection, prognosis, and biomarker discovery. However, reliance on CROs for sample collection, processing, and storage often leads to delays and inefficiencies. PredicineDIRECT, a genomics-based biorepository system, addresses these challenges by centralizing sample management, enabling rapid and accurate support for clinical trials. Methods: Using ISO13485-certified GMP kits, Predicine collects and processes blood, urine, and tissue samples globally and manage samples using BioLIMS. Patient-specific SNP barcodes and bioinformatics analyses detect errors like mislabeling or sample swaps. Tumor Fraction (TF) is measured via low-pass whole-genome sequencing to assess tumor burden efficiently. This workflow enables real-time quality control, longitudinal tumor burden evaluation, and optimized sample selection for downstream analysis. Sponsors access data through a client portal, while securely stored samples remain ready for immediate in-house genomic testing. Results: In a trial cohort, SNP barcoding identified sample mismatches, including one between plasma and buffy coat samples and another at a longitudinal time point. Predicine promptly resolved these discrepancies, communicating actionable solutions to the sponsor before long-term storage. TF analysis of plasma samples revealed molecular progression, guiding selection of key time points for deep sequencing. A case study also demonstrated SNP inconsistencies between plasma and buffy coat samples, highlighting the robustness of PredicineDIRECT’s error-detection system. Conclusion: PredicineDIRECT provides a streamlined, cost-effective solution for clinical trial sample management by centralizing processes in a single laboratory. With integrated SNP barcoding and TF analysis, the system ensures error-free handling, accelerates downstream sequencing, and delivers actionable insights into tumor burden, supporting efficient and informed decisions in oncology trials. Citation Format: Yong Huang, Ao Zhou, Pan Du, Shidong Jia, Qin Luo, Alexander Kuklin, Myles Walsh. PredicineDIRECT: a one-stop “from sample to result” workflow for improved sample management in oncology clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7115.
Authors
- Shidong Jia (ORCID: https://orcid.org/0009-0006-3823-8227)
- A. I. Kuklin (ORCID: https://orcid.org/0000-0002-4530-2980)
- Ao Zhou
- Pan Du (ORCID: https://orcid.org/0000-0002-4561-6883)
- Huang Yong
- Myles Walsh
- Qin Luo
Institutions
- Shanghai Medical Information Center (CN)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-7115
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00