Leveraging Drug-Gene Interaction Information for Personalized Hypertension Drug Molecule Discovery

Aims: To examine whether novel lead hypertension molecules can be used in the personalized treatment of hypertension. Background/Introduction: Hypertension is a modifiable condition that affects over 1 billion adults worldwide. Maintaining a healthy blood pressure is vital for overall health, especially given that hypertension is a primary risk factor for developing cardiovascular conditions. However, some individuals have resistant hypertension, which may be due to variations in genetic expression, making standard hypertension treatments ineffective. Objective: The integration of genetic data into the personalized optimization of novel hypertension drugs is demonstrated. Method: This research created coding criteria for drug-gene recommendations based on the genomic profiles of ten pseudo-patients. The genomic data of these patients was created using chromosome and hypertension-implicated gene sequences from the NCBI National Library of Medicine database. Results and Discussion: This study uses the proposed drug recommendation criteria to recommend novel hypertension lead molecules to each patient based on their gene expression profiles. Conclusion: This study’s patient-centric drug prescription approach integrates patient gene expression data with drug-gene interaction data and recommends novel hypertension drugs most suitable for each patient. Variations in patient gene expression explain the diverse treatment responses inherent across hypertensive patients, thus necessitating a personalized approach to their drug prescription. Future studies can investigate the challenges of ethical, technological, and technical expertise that may affect the clinical implementation of personalized drug prescription recommendation systems.

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Journal
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Published
2024-12-16
DOI
https://doi.org/10.2174/0118756921355914241203054023
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Leveraging Drug-Gene Interaction Information for Personalized Hypertension Drug Molecule Discovery

Odifentse Mapula-e Lehasa, Uche A. K. Chude‐Okonkwo
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Computational Drug Discovery Methods
article

Leveraging Drug-Gene Interaction Information for Personalized Hypertension Drug Molecule Discovery

Odifentse Mapula-e Lehasa, Uche A. K. Chude‐Okonkwo
article en

Abstract

Aims: To examine whether novel lead hypertension molecules can be used in the personalized treatment of hypertension. Background/Introduction: Hypertension is a modifiable condition that affects over 1 billion adults worldwide. Maintaining a healthy blood pressure is vital for overall health, especially given that hypertension is a primary risk factor for developing cardiovascular conditions. However, some individuals have resistant hypertension, which may be due to variations in genetic expression, making standard hypertension treatments ineffective. Objective: The integration of genetic data into the personalized optimization of novel hypertension drugs is demonstrated. Method: This research created coding criteria for drug-gene recommendations based on the genomic profiles of ten pseudo-patients. The genomic data of these patients was created using chromosome and hypertension-implicated gene sequences from the NCBI National Library of Medicine database. Results and Discussion: This study uses the proposed drug recommendation criteria to recommend novel hypertension lead molecules to each patient based on their gene expression profiles. Conclusion: This study’s patient-centric drug prescription approach integrates patient gene expression data with drug-gene interaction data and recommends novel hypertension drugs most suitable for each patient. Variations in patient gene expression explain the diverse treatment responses inherent across hypertensive patients, thus necessitating a personalized approach to their drug prescription. Future studies can investigate the challenges of ethical, technological, and technical expertise that may affect the clinical implementation of personalized drug prescription recommendation systems.

Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicineVol. 22
University of Johannesburg (ZA)
Good health and well-being
Openalex Percentile: Top 72%
Computational Drug Discovery Methods
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Leveraging Drug-Gene Interaction Information for Personalized Hypertension Drug Molecule Discovery — Odifentse Mapula-e Lehasa, Uche A. K. Chude‐Okonkwo · Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine (2024) | TGRS Research Map | TGRS