A target map of clinical combination therapies in oncology: an analysis of clinicaltrials.gov

• Published in: Discover. Oncology Vol. 14; no. 1; p. 151
• Main Authors: Yang, Jing, Kang, Heming, Lyu, Liyang, Xiong, Wei, Hu, Yuanjia
• Format: Journal Article
• Language: English
• Published: New York Springer US 21.08.2023; Springer Nature B.V; Springer
• Subjects: Adenosine; Apoptosis; Bispecific antibodies; Cancer Research; Cancer therapies; Chemokines; Clinical trials; Combination therapy; Cyclin-dependent kinases; Data processing; Drugs; Endocrine therapy; FDA approval; Growth factors; Immuno-oncology therapy; Internal Medicine; Kinase inhibitors; Kinases; Medicine; Medicine & Public Health; Molecular Medicine; Oncology; PD-1/PD-L1 inhibitors; Pharmaceutical industry; Radiotherapy; Steroids; Surgical Oncology; Targeted therapy; Tumors; Immuno-oncology therapy; PD-1/PD-L1 inhibitors; Combination therapy; Kinase inhibitors; Targeted therapy; Bispecific antibodies
• DOI: 10.1007/s12672-023-00758-4
• ISSN: 2730-6011

Combination therapies have taken center stage for cancer treatment, however, there is a lack of a comprehensive portrait to quantitatively map the current clinical combination progress. This study aims to capture clinical combination therapies of the validated FDA-approved new oncology drugs by a macro data analysis and to summarize combination mechanisms and strategies in the context of the existing literature. A total of 72 new molecular entities or new therapeutic biological products for cancer treatment approved by the FDA from 2017 to 2021 were identified, and the data on their related 3334 trials were retrieved from the database of ClinicalTrials.gov. Moreover, these sampled clinical trials were refined by activity status and combination relevance and labeled with the relevant clinical arms and drug combinations, as well as drug targets and target pairs. Combination therapies are increasingly prevalent in clinical trials of new oncology drugs. From retrospective work, existing clinical combination therapies in oncology are driven by different patterns (i.e., rational design and industry trends). The former can be represented by mechanism-based or structure-based combinations, such as targeting different domains of HER2 protein or in-series co-targeting in RAF plus MEK inhibitors. The latter is an empirically driven strategy, including redundant combinations in hot targets, such as PD-1/PD-L1, PI3K, CDK4/6, and PARP. Because of an explosion in the number of clinical trials and the resultant shortage of available patients, it is essential to rationally design drug combinations.