AccScience Publishing / TD / Online First / DOI: 10.36922/TD025520129
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ORIGINAL RESEARCH ARTICLE

The one-of-a-kind PGA technology harnesses patient’s gene signature to predict drug efficacy: A reality check with the real-world treatment trend

Shu-Ti Lin1 ,  Hung-Chih Lai2 ,  Peter Schill1 ,  Chen Yeh1*
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1 OncoDxRx, Los Angeles, CA, United States of America
2 Division of Hematology and Oncology, Department of Internal Medicine, Shin Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan
Tumor Discovery, 025520129 https://doi.org/10.36922/TD025520129
Received: 22 December 2025 | Revised: 16 February 2026 | Accepted: 24 March 2026 | Published online: 5 May 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

In 1937, President Roosevelt launched the National Cancer Act. Eighty-nine years later, challenges remain despite progress, with 50–80% of patients being unresponsive to treatment and over 600,000 cases of mortality annually in the United States (U.S.) Biomarker tests enable precision medicine but exclude most patients. A disruptive technology is needed to expand precision treatments and benefit every cancer patient. The revolutionary drug-finding technology, PGA (patient-derived gene expression-informed anticancer drug efficacy), has been developed and validated previously, which integrates a patient’s own gene signature to identify the top-ranking drugs that individual patients are most likely to respond to. In this study, we further conducted a benchmarking reality check to evaluate the clinical utility of PGA in real-world settings. To validate PGA LUNG testing results, the framework incorporates three publicly accessible drug utilization datasets for NSCLC: TCGA, MEDLINE, and NCCN guidelines. To enable a comprehensive assessment of PGA LUNG clinical utility, we defined evaluation metrics by capturing drug usage trends in the best clinical practice. Aligned with TCGA treatment landscapes and real-world NSCLC treatment trends in the U.S., the PGA LUNG test could significantly help oncologists by providing them with reliable predictions to choose the most suitable drugs for their patients. PGA LUNG also highlights the potential for off-label cancer drugs to overcome the challenges of ongoing therapy exhaustion and drug resistance. PGA LUNG’s ability to predict drug efficacies/responses for treatment-unresponsive cancer patients with high accuracy provides a critical clinical advantage.

Keywords
Drug efficacy/response prediction
PGA
Gene-drug mapping
Gene expression signature
Non-small cell lung cancer
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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Tumor Discovery, Electronic ISSN: 2810-9775 Print ISSN: 3060-8597, Published by AccScience Publishing
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