OncoPDSS: an evidence-based clinical decision support system for oncology pharmacotherapy at the individual level

Autor: Jin-Cheng Zhai, Zhang Zhi, Xi-Ling Zeng, Chang Yujun, Yang Li, Wan-Ling Zhang, Sheng-Nan Zhang, Fang Yang, Chuang Shen, Fan-Lin Meng, Huo Caiqin, Quan Xu, Xue-Jiao Dong, Zhou Yiming, Dongfang Li, Ru-Dan Huang
Rok vydání: 2019
Předmět:
0301 basic medicine
Oncology
Cancer Research
Decision support system
medicine.medical_specialty
Evidence-based practice
Databases
Factual
Oncology pharmacotherapy
Clinical support tool
Antineoplastic Agents
Web Browser
Clinical decision support system
lcsh:RC254-282
03 medical and health sciences
User-Computer Interface
0302 clinical medicine
Pharmacotherapy
Clinical trials
Internal medicine
Neoplasms
Health care
Genetics
medicine
Alterations
Humans
Implications
Precision Medicine
Clinical Trials as Topic
business.industry
Molecular Sequence Annotation
Drug indications
Precision medicine
lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Decision Support Systems
Clinical
Knowledgebase
Clinical trial
030104 developmental biology
Knowledge base
030220 oncology & carcinogenesis
business
Software
Zdroj: BMC Cancer
BMC Cancer, Vol 20, Iss 1, Pp 1-10 (2020)
ISSN: 1471-2407
Popis: Background Precision oncology pharmacotherapy relies on precise patient-specific alterations that impact drug responses. Due to rapid advances in clinical tumor sequencing, an urgent need exists for a clinical support tool that automatically interprets sequencing results based on a structured knowledge base of alteration events associated with clinical implications. Results Here, we introduced the Oncology Pharmacotherapy Decision Support System (OncoPDSS), a web server that systematically annotates the effects of alterations on drug responses. The platform integrates actionable evidence from several well-known resources, distills drug indications from anti-cancer drug labels, and extracts cancer clinical trial data from the ClinicalTrials.gov database. A therapy-centric classification strategy was used to identify potentially effective and non-effective pharmacotherapies from user-uploaded alterations of multi-omics based on integrative evidence. For each potentially effective therapy, clinical trials with faculty information were listed to help patients and their health care providers find the most suitable one. Conclusions OncoPDSS can serve as both an integrative knowledge base on cancer precision medicine, as well as a clinical decision support system for cancer researchers and clinical oncologists. It receives multi-omics alterations as input and interprets them into pharmacotherapy-centered information, thus helping clinicians to make clinical pharmacotherapy decisions. The OncoPDSS web server is freely accessible at https://oncopdss.capitalbiobigdata.com.
Databáze: OpenAIRE
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