stdClass Object
(
    [id] => 17794
    [paper_index] => 202510-02-024362
    [title] => REVIEW ON AI IN THE FIELD OF PHARMACOGENOMICS
    [description] => 
    [author] => Shreyam Dubey, Vishwanath Dubey
    [googlescholar] => 
    [doi] => 
    [year] => 2025
    [month] => October
    [volume] => 10
    [issue] => 10
    [file] => fm/jpanel/upload/2025/October/202510-02-024362.pdf
    [abstract] => Pharmacogenomics has seen a dramatic change as a result of artificial intelligence (AI), which has made it possible to create customized treatment models based on a patient's genetic composition. Thus, many facets of genetic data might be analyzed by machine and deep learning algorithms of artificial intelligence to precisely predict how patients will react to specific drugs and prescriptions. The synergy also contributes to better drug efficacy, reduced adverse drug effects, and enhanced efficiency in drug development. This is not yet the case, though, as AI in pharmacogenomics has certain drawbacks, such as ethical and data privacy issues and the requirement for sufficient framework validation before it can be used in reality.
    [keywords] => Artificial Intelligence (AI), Pharmacogenomics, Personalized therapeutic models, Genetic makeup, Machine learning, Deep learning algorithms
    [doj] => 2025-10-10
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 20
    [journal_id] => 2
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Research & Development (IJRD)
    [short_code] => IJSR
    [eissn] =>  2455-7838 (Online)
    [pissn] => - -
    [home_page_wrapper] => images/products_image/2-n.png
)
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