The evolving global landscape of first-in-class oncology drug innovation

First-in-class (FIC) oncology drugs-defined by their novel mechanisms of action or targeting of previously unaddressed molecular targets-have emerged as a leading force in cancer therapeutic innovation. In this Review, we delineate the global landscape of FIC oncology drug approvals between 2009 and 2024 and analyze the evolving characteristics of both approved FIC therapies and potential FIC (PFIC) candidates in clinical development. To clarify the underlying dynamics of this evolution, we construct an analytic framework encompassing four distinct archetypes of FIC development: new targets, new mutation subtypes, new modalities, and new multi-target strategies. This typology enables a systematic dissection of divergent translational trajectories and bottlenecks across the evolving FIC landscape. While most approved FIC drugs are driven by target novelty, PFIC candidates increasingly capitalize on technological breakthroughs, particularly in modalities such as cell and gene therapies, antibody-drug conjugates, proteolysis-targeting chimeras, cancer vaccines and bispecific antibodies. These advances not only expand the boundaries of druggability but also redefine how therapeutic interventions are conceived, delivered and translated into patient outcomes. Despite this momentum, critical bottlenecks-including the identification and validation of tractable targets, high clinical attrition rates, and persistent disparities in global access-continue to limit the real-world impact of oncology innovation. Looking forward, the convergence of artificial intelligence, next-generation modalities, and translational collaboration may serve as powerful engines for translating scientific breakthroughs into widely accessible therapies and for driving sustainable, mechanism-based innovations in oncology.

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Publication Details

Journal
Signal Transduction and Targeted Therapy
Published
2026-05-11
DOI
https://doi.org/10.1038/s41392-026-02606-7
Primary Topic
Economic and Financial Impacts of Cancer
Type
article
Field-Weighted Citation Impact
0.00

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article

The evolving global landscape of first-in-class oncology drug innovation

Shu Kong, Zhaoqing Wang, Xiangyun Mao, Yue Yang et al.
Signal Transduction and Targeted Therapy
Economic and Financial Impacts of Cancer
article

The evolving global landscape of first-in-class oncology drug innovation

Shu Kong, Zhaoqing Wang, Xiangyun Mao, Yue Yang, Nancy A. Dreyer, Guanqiao Li, Qimin Zhan, Michael T. Lotze, Yi Ba
article en

Abstract

First-in-class (FIC) oncology drugs-defined by their novel mechanisms of action or targeting of previously unaddressed molecular targets-have emerged as a leading force in cancer therapeutic innovation. In this Review, we delineate the global landscape of FIC oncology drug approvals between 2009 and 2024 and analyze the evolving characteristics of both approved FIC therapies and potential FIC (PFIC) candidates in clinical development. To clarify the underlying dynamics of this evolution, we construct an analytic framework encompassing four distinct archetypes of FIC development: new targets, new mutation subtypes, new modalities, and new multi-target strategies. This typology enables a systematic dissection of divergent translational trajectories and bottlenecks across the evolving FIC landscape. While most approved FIC drugs are driven by target novelty, PFIC candidates increasingly capitalize on technological breakthroughs, particularly in modalities such as cell and gene therapies, antibody-drug conjugates, proteolysis-targeting chimeras, cancer vaccines and bispecific antibodies. These advances not only expand the boundaries of druggability but also redefine how therapeutic interventions are conceived, delivered and translated into patient outcomes. Despite this momentum, critical bottlenecks-including the identification and validation of tractable targets, high clinical attrition rates, and persistent disparities in global access-continue to limit the real-world impact of oncology innovation. Looking forward, the convergence of artificial intelligence, next-generation modalities, and translational collaboration may serve as powerful engines for translating scientific breakthroughs into widely accessible therapies and for driving sustainable, mechanism-based innovations in oncology.

Signal Transduction and Targeted TherapyVol. 11(1)
University of North Carolina at Chapel Hill (US), University of Pittsburgh (US), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking University (CN), National Medical Products Administration (CN), Peking Union Medical College Hospital (CN), Vanke (China) (CN), Peking University International Hospital (CN), Ministry of Education (ET), Tsinghua University (CN)
National Natural Science Foundation of China, Beijing Nova Program
Industry, innovation and infrastructure
Openalex Percentile: Top 3%
Economic and Financial Impacts of Cancer
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