OncoAID - an open access targeted anti-cancer drugs database

Posted: Wednesday, August 13, 2025

August 13, 2025
Frontiers in Pharmacology
DATA REPORT article: Sec. Pharmacology of Anti-Cancer Drugs
Volume 16 - 2025 | https://doi.org/10.3389/fphar.2025.1588191

INTRODUCTION

The rapid evolution of targeted therapies in oncology has revolutionized cancer
treatment, offering new hope to patients through precision medicine. These therapies are designed to specifically inhibit molecular targets that drive tumor growth and progression. By focusing on the unique genetic and molecular characteristics of individual tumors, targeted therapies enable more effective and personalized treatment strategies, thereby improving patient outcomes and minimizing adverse effects (Choi and Chang, 2023).

In recent years, the U.S. Food and Drug Administration (FDA) has approved a growing number of targeted therapies, reflecting the increasing understanding of the molecular underpinnings of various cancers. As of 2024, over 150 targeted agents have received FDA approval (Zhong et al., 2021), each associated with specific molecular targets and indications. These therapies encompass a range of mechanisms, including small molecule inhibitors that disrupt intracellular signaling pathways and monoclonal antibodies that block the interaction between cancer cells and their environment (Zhong et al., 2021; FDA Approved Targeted Drug List, 2024). For instance, agents targeting the epidermal growth factor receptor (EGFR), such as erlotinib and gefitinib, have demonstrated significant efficacy in non-small cell lung cancer (NSCLC) (Maemondo et al., 2010; Toschi et al., 2017), while BRAF inhibitors have transformed the treatment landscape for melanoma (Ribas and Flaherty, 2011; Patel et al., 2020).

To effectively track the landscape of these targeted therapies, comprehensive databases serve as invaluable resources for clinicians and researchers alike. Amid the ongoing artificial intelligent (AI) revolution, such databases hold immense significance for precision oncology algorithms and clinical pharmacology applications, enabling clinicians and researchers to leverage accessible knowledge and tools to make personalized, evidence-based decisions in cancer treatment (Alowais et al., 2023). Comprehensive databases, like PHARMGKB (Whirl-Carrillo et al., 2021), DrugBank (Knox et al., 2024) and Therapeutic Target Database (TTD) (Zhou et al., 2024; Liu et al., 2020; Yang et al., 2024), offer detailed molecular characterization of drugs, pharmacogenomic insights and clinical annotations across numerous therapeutic areas. Clinicians and researchers can use such databases to delve into treatment responses and explore repurposing possibilities. Recently, datasets specifically focusing on anti-cancer drugs (Pantziarka et al., 2021) have been introduced, offering enhanced data availability for machine learning applications and drug repurposing in precision oncology. These resources, though extensive, merely scratch the surface of potential oncology data. The vast possibilities and the comprehensiveness of such databases also introduce challenges, particularly for clinicians who often face time constraints, specifically, when patients fail to respond to guideline-recommended treatments. In such cases oncologists must consider alternative therapeutic approaches by integrating clinical guidelines with available data (Otte et al., 2017; Glatzer et al., 2020).

This report presents the OncoAID database, a specialized and dynamic resource meticulously developed by integration of existing datasets as well as newly curated, up-to-date information. The database is comprehensive, practical, relevant and features an interactive, user-friendly interface that enables clinicians and researchers to quickly and effectively search, filter, and explore information of interest, whether within the database or through navigation to linked external resources.

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