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Artificial intelligence and anti-cancer drugs' response

Xinrui Long1,2,3,4,5,6, Kai Sun1,3,4,5,6, Sicen Lai1,2,3,4,5,6

  • 1Department of Dermatology, Xiangya Hospital, Central South University, Changsha 410028, China.

Acta Pharmaceutica Sinica. B
|July 23, 2025
PubMed

Insights

Artificial intelligence (AI) can predict cancer drug resistance by analyzing multi-omics data. Early prediction using AI aids in developing personalized treatment plans, improving patient outcomes and quality of life.

Area of Science:

  • Oncology
  • Bioinformatics
  • Artificial Intelligence

Background:

  • Drug resistance significantly impacts cancer treatment efficacy (chemotherapy, radiotherapy, immunotherapy).
  • Factors like mRNA expression and methylation influence drug resistance.
  • Early identification of drug resistance is crucial for effective treatment planning and improving patient survival rates.

Purpose of the Study:

  • To comprehensively review AI-driven approaches for predicting cancer drug resistance.
  • To summarize the analysis of multi-omics data for resistance prediction.
  • To highlight challenges and future directions in AI for precision oncology.

Main Methods:

  • Utilizing artificial intelligence (AI) algorithms.
  • Analyzing diverse multi-omics data: genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology.
  • Detailed exposition of data processing and AI model construction for drug resistance prediction.

Main Results:

  • AI demonstrates promising application prospects in predicting cancer drug resistance.
  • Multi-omics data analysis via AI can guide individualized and precise cancer medication.
  • This approach has the potential to significantly improve clinical treatment strategies.

Conclusions:

  • AI-powered analysis of multi-omics data is a key area for advancing cancer drug resistance prediction.
  • Addressing current challenges and exploring future directions will further enhance AI's role in precision medicine.
  • AI holds significant potential for improving cancer patient survival and quality of life through personalized treatments.
Keywords:
Anti-cancer drugsArtificial intelligenceDrug resistanceMulti-omicsPrecision medication

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