TY - JOUR
T1 - A scalable natural language processing framework for drug repurposing in chemotherapy-induced adverse events from clinical narrative records
AU - Tsuchiya, Masami
AU - Inoue, Mari
AU - Kawazoe, Yoshimasa
AU - Shimamoto, Kiminori
AU - Seki, Tomohisa
AU - Imai, Shungo
AU - Kizaki, Hayato
AU - Shinohara, Emiko
AU - Yada, Shuntaro
AU - Wakamiya, Shoko
AU - Aramaki, Eiji
AU - Hori, Satoko
N1 - Publisher Copyright:
© 2025 The Authors.
PY - 2026/1
Y1 - 2026/1
N2 - Background Preventing chemotherapy-related adverse events (AEs) remains an unmet clinical challenge. Preclinical studies have suggested protective effects of several existing agents, but translation into human evidence has been limited. We aimed to establish proof of concept (PoC) for drug repurposing by applying a natural language processing (NLP)-based framework to electronic health record (EHR) narratives, thereby bridging preclinical findings with clinical validation. Methods We retrospectively analyzed 56,326 patients with cancer treated at the University of Tokyo Hospital (2004–2023). A transformer-based NLP model extracted symptomatic AEs from clinical notes. Candidate preventive drugs identified from preclinical evidence were assessed using propensity score matching and Cox proportional hazards models. We evaluated angiotensin II receptor blockers (ARBs) for fluoropyrimidine-induced oral mucositis and ramelteon for platinum-induced peripheral neuropathy, with laxatives serving as a negative control. Results NLP demonstrated high accuracy (precision 0.81–0.83; recall 0.95–0.97). After matching, ARB co-administration was significantly associated with reduced mucositis incidence (hazard ratio [HR] 0.58, 95 % confidence interval [CI] 0.44–0.77; P < 0.001), representing a clinical PoC consistent with mechanistic preclinical data. Ramelteon showed an exploratory protective signal against neuropathy (HR 0.60, 95 % CI:0.38–0.93; P = 0.024). No preventive association was observed for laxatives. Conclusions This study introduces a scalable NLP-epidemiology framework for non-invasive, real-world validation of drug repurposing candidates. The ARB finding provides human-level PoC evidence supporting prospective clinical testing, while the ramelteon signal warrants further exploration. Our approach demonstrates how EHR narratives can operationalize translational research, prioritizing safe, accessible agents for improving the tolerability of cancer treatment.
AB - Background Preventing chemotherapy-related adverse events (AEs) remains an unmet clinical challenge. Preclinical studies have suggested protective effects of several existing agents, but translation into human evidence has been limited. We aimed to establish proof of concept (PoC) for drug repurposing by applying a natural language processing (NLP)-based framework to electronic health record (EHR) narratives, thereby bridging preclinical findings with clinical validation. Methods We retrospectively analyzed 56,326 patients with cancer treated at the University of Tokyo Hospital (2004–2023). A transformer-based NLP model extracted symptomatic AEs from clinical notes. Candidate preventive drugs identified from preclinical evidence were assessed using propensity score matching and Cox proportional hazards models. We evaluated angiotensin II receptor blockers (ARBs) for fluoropyrimidine-induced oral mucositis and ramelteon for platinum-induced peripheral neuropathy, with laxatives serving as a negative control. Results NLP demonstrated high accuracy (precision 0.81–0.83; recall 0.95–0.97). After matching, ARB co-administration was significantly associated with reduced mucositis incidence (hazard ratio [HR] 0.58, 95 % confidence interval [CI] 0.44–0.77; P < 0.001), representing a clinical PoC consistent with mechanistic preclinical data. Ramelteon showed an exploratory protective signal against neuropathy (HR 0.60, 95 % CI:0.38–0.93; P = 0.024). No preventive association was observed for laxatives. Conclusions This study introduces a scalable NLP-epidemiology framework for non-invasive, real-world validation of drug repurposing candidates. The ARB finding provides human-level PoC evidence supporting prospective clinical testing, while the ramelteon signal warrants further exploration. Our approach demonstrates how EHR narratives can operationalize translational research, prioritizing safe, accessible agents for improving the tolerability of cancer treatment.
KW - Adverse events
KW - Drug repurposing
KW - Electronic health records
KW - Natural language processing
UR - https://www.scopus.com/pages/publications/105023861167
UR - https://www.scopus.com/pages/publications/105023861167#tab=citedBy
U2 - 10.1016/j.ejca.2025.116157
DO - 10.1016/j.ejca.2025.116157
M3 - Article
C2 - 41349154
AN - SCOPUS:105023861167
SN - 0959-8049
VL - 232
JO - European Journal of Cancer
JF - European Journal of Cancer
M1 - 116157
ER -