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Impact Factor : 8.14

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Paper Title: AI-Driven Prediction of Drug Adverse Effects Using Genomic DNA Profiling
Authors Name: Prasad Alai , Sanket Gadekar , Pranjal Vedpathak , Vighnesh Narawade
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IJRTI_212868
Published Paper Id: IJRTI2605156
Published In: Volume 11 Issue 5, May-2026
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Abstract: Adverse drug reactions (ADRs) remain one of the leading preventable causes of hospitalization worldwide. Conventional prescribing practices do not account for individual genetic variability, leading to suboptimal drug responses and preventable toxicities. This paper presents an end-to-end AI-driven pipeline that predicts potential drug side effects for an individual by combining their raw genomic data with curated pharmacogenomics and drug-side-effect databases. Raw Variant Call Format (VCF) files from the 1000 Genomes Project are processed to extract single nucleotide polymorphisms (SNPs), which are filtered for variability, mapped to genes using GENCODE annotation, and aggregated into per-gene genetic scores. Gene-to-drug relationships from PharmGKB are then used to derive drug-level genetic scores, and side-effect associations are retrieved from SIDER. A binary ADR risk label is assigned per individual per drug by applying a 75th-percentile threshold on the population-level genetic-score distribution, producing a labelled, machine-learning-ready dataset. The framework demonstrates that population-scale genomic data can be transformed into personalized pharmacogenomic features suitable for supervised classification. The work is positioned relative to six reference studies on ADR prediction using genomic data and machine learning, highlighting its unique contribution of an uninterrupted VCF-to-label pipeline built entirely from publicly available resources.
Keywords: Adverse Drug Reactions (ADRs), DNA Profiles, Pharmacogenomics, Single Nucleotide Polymorphisms (SNPs), 1000 Genomes Project, PharmGKB, SIDER, Genetic Score, Machine Learning, Personalized Medicine.
Cite Article: "AI-Driven Prediction of Drug Adverse Effects Using Genomic DNA Profiling", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.b465-b472, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605156.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2605156
Registration ID:212868
Published In: Volume 11 Issue 5, May-2026
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Page No: b465-b472
Country: pune, Maharashtra, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605156
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605156
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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