Page 11 - GTM-4-2

Global Translational Medicine

REVIEW ARTICLE
Revolutionizing drug response prediction: An

unmet requirement for patients unresponsive to
precision medicine

Chen Yeh* , Shu-Ti Lin, Andre Baranski, and Sharon Yeh

OncoDxRx, Los Angeles, California, United States of America

Abstract

Precision cancer therapies frequently fail due to tumors’ evolving clonal diversity
rather than drug efficacy. Even when initial treatment succeeds, resistance often
emerges, leading to relapse. Clinicians then find themselves in the same cycle of
repeating the process of testing a new drug until therapeutic exhaustion. The cycle
escalates with each new treatment until no further options are available. The real-life
experience of precision therapy will undeniably lead to an upgrade – from biomarker
testing to drug response prediction – accordingly to favor more effective treatment
options, more clinical benefit, and more patient coverage to include non-responders.
While biomarker tests (or companion diagnostics) advance precision medicine by
identifying only a fraction of patients as responders, drug response prediction
aims to expand treatment options – particularly for non-responders – by tailoring
personalized therapies to optimize outcomes while minimizing side effects. Artificial
*Corresponding author: intelligence-driven approaches (e.g., deep learning and predictive modeling)
Chen Yeh leverage large datasets to generate these predictions. However, such systems
(cyeh.oncodxrx@gmail.com) remain experimental, not yet ready for clinical use. Patient-derived gene expression-
Citation: Yeh C, Lin S, Baranski A, informed anticancer drug efficacy (PGA) is the ultimate answer to the unmet clinical
Yeh S. Revolutionizing drug need for a quick turnaround and cost-efficient drug response prediction technology.
response prediction: An unmet
requirement for patients With PGA, therapeutic non-responders now are able to benefit from more drug
unresponsive to precision medicine. options than ever before. Since the technology is fitted with patient testing, gene
Global Transl Med. 2025;4(2):3-11. activity detection, data mapping, drug matching, and efficacy ranking capabilities,
doi: 10.36922/gtm.5091
clinicians can be quickly notified of potentially effective drugs, winning the decisive
Received: October 8, 2024 time for decision-making.
Revised: January 18, 2025
Accepted: February 24, 2025 Keywords: Drug response prediction; Precision medicine; Biomarker testing;
Patient-derived gene expression-informed anticancer drug efficacy; Non-responders
Published online: March 7, 2025
Copyright: © 2025 Author(s).
This is an Open-Access article
distributed under the terms of the
Creative Commons Attribution 1. Introduction
License, permitting distribution,
and reproduction in any medium, Cancer remains one of the most life-threatening diseases globally, with an estimated
provided the original work is 20 million new cases and 10 million deaths annually. The World Health Organization
1
properly cited. projects a 60% increase in the global cancer burden by 2040, with substantial health,
1
Publisher’s Note: AccScience social, and financial impacts. The economic burden alone is expected to reach
Publishing remains neutral with $25.2 trillion between 2020 and 2050. Traditional treatments such as surgery, radiation
1
regard to jurisdictional claims in
published maps and institutional therapy, chemotherapy, and immunotherapy are currently available but often fall short
affiliations. in addressing intrinsic genetic abnormalities unique to each patient. This has led to
Volume 4 Issue 2 (2025) 3 doi: 10.36922/gtm.5091