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Review
. 2024 Oct 18:16:17588359241287658.
doi: 10.1177/17588359241287658. eCollection 2024.

Pharmacogenomics and Big Data in medical oncology: developments and challenges

Loredana G Marcu  1   2 , David C Marcu  3
Affiliations
Review

Pharmacogenomics and Big Data in medical oncology: developments and challenges

Loredana G Marcu et al. Ther Adv Med Oncol. .

Abstract

Medical oncology, through conventional chemotherapy as well as targeted drugs, remains an important component of cancer patient management, particularly for systemic disease. Despite advances in all areas of medical oncology, certain challenges persist in the form of drug resistance and severe normal tissue toxicity. These unwanted effects can be counteracted through a patient-tailored treatment approach, which in chemotherapy is translated as pharmacogenomics. This research field investigates the way genetic makeup influences a patient's response to various drugs with the aim to minimize trial-and-error associated with drug administration. The paper introduces the role, advances and challenges of pharmacogenomics, highlighting the importance of Big Data mining to reveal the mechanisms behind drug-gene pair interaction for better patient outcomes. International consortiums have prioritized their focus on the clinical implementation of pharmacogenomics while tackling the challenges ahead: data standardization, ethical aspects and the education of physicians and patients alike to comprehend the power of pharmacogenomics to transform medical oncology.

Keywords: big data; chemotherapy; drug–gene interaction; normal tissue effects; personalized therapy.

Plain language summary

Drug-gene interaction and implications for medical oncology Pharmacogenomics is a research field that investigates the way the genetic makeup influences a patient’s response to various drugs with the aim to minimise trial-and-error associated with drug administration. This overview of state-of-the-art research introduces the role, advances, and challenges of pharmacogenomics, highlighting the importance of Big Data mining to reveal the mechanisms behind drug-gene pair interaction for better patient outcome.

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Conflict of interest statement

The authors declare that there is no conflict of interest.

Figures

Figure 1.
Figure 1.
Treatment personalization using big data mining and pharmacogenomics.
Figure 2.
Figure 2.
Challenges posed by chemotherapy and their effect on patients’ outcomes.
Figure 3.
Figure 3.
The original three V-s of big data: volume, variety and velocity.
See this image and copyright information in PMC

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