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2000
Volume 1, Issue 1
  • ISSN: 2772-6215
  • E-ISSN: 2772-6223

Abstract

Cancer is a fatal disease with different hallmarks and pathogenesis pathways. Personalized oncology (PO) or precision medicine (PM) serves as a platform for maximizing therapeutic efficacy by enabling rapid drug selection and combination based on the analysis of oncogenic hallmarks and pathogenesis in the clinical setting.

In a long developing history (six-decades similar and unique pharmacology and medical framework), personalized therapies have been broadening into various platforms and disciplines. The advantages and limitations of these methodologies are addressed. The next generation of PO will integrate information on pharmacology (drug sensitivity or drug combination) and oncology (sequencing, multi-omics profiling, computation, and drug response score analysis) and avoid undesired side effects (suitable organ delivery, dose-ranging prediction, and drug optimization).

Unlimited technical advances can drive the overall cancer treatment progress of different platforms and disciplines in medical knowledge. Greater therapeutic benefits are anticipated from the widespread development of drug selection and combination approaches using cutting-edge technologies, such as artificial intelligence and computational algorithms.

A combination of different techniques and disciplines takes a leading role in advancing cancer treatments and clinical pharmacology through the development of the next generation of PO strategies. Useful, cost-effective, and integrative algorithms and platforms will be innovated by the promotion of biomedical, mathematical, and clinical cancer treatment studies.

Routines and techniques of various PO are formalized according to specific cancer targets, mechanisms, and high-throughput drug sensitivity selection from a greater number of anticancer drugs.

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2025-10-09

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Personalized Oncology: Scientific and Technical Approaches
Curr Cell Sci 1, E27726215350799 (2025); https://doi.org/10.2174/0127726215350799250401214735
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  • Article Type:     Review Article
Keyword(s): cancer metastasis; cancer research; computational network; diagnostic platforms; drug selection; medical history; Personalized oncology; precision medicine
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