Pharmacogenomics with Genomics & Informatics Lab
Pharmacogenomics is the study of how a person's genes affect their response to drugs. By combining knowledge of pharmacology (the study of drugs) and genomics (the study of genes), it helps healthcare providers select the right medication and dosage for each individual, improving drug effectiveness and reducing adverse reactions. This personalized approach to medicine aims to tailor treatment based on a person's unique genetic makeup to achieve better health outcomes.
Pharmacogenomics Services
Our Pharmacogenomics Services Encompass:
Biomarker Identification Associated with Disease:
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Utilize bioinformatics tools to identify genetic variants or expression patterns associated with disease susceptibility or progression.
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Analyze genomic data to discover potential biomarkers that can predict disease outcomes or response to treatment.
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Genetic Variation Analysis:
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Perform variant calling and annotation to identify genetic variations relevant to pharmacogenomics.
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Analyze the functional significance of genetic variants and their potential impact on drug response phenotypes.
Protein Modeling and Drug Screening:
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Utilize computational modeling techniques to predict protein structures and understand their interactions with drugs.
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Screen potential drug candidates using molecular docking simulations and virtual screening approaches to identify molecules with high binding affinity and specificity.
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Potential Drug Identification:
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Employ bioinformatics methods to analyze drug-target interactions and predict potential drug candidates based on genomic and proteomic data.
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Utilize pathway analysis and functional enrichment to prioritize drug candidates targeting specific molecular pathways or biological processes.
Drug ADMET Analysis:
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Assess the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of candidate drugs using computational methods.
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Predict drug pharmacokinetics and pharmacodynamics to optimize drug efficacy and safety profiles.
Drug Receptor Interaction Analysis:
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Analyze protein-receptor interactions using molecular modeling techniques to predict drug binding modes and affinities.
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Investigate the molecular mechanisms underlying drug-target interactions to optimize drug design and development.
Integration and Interpretation of Results:
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Integrate findings from biomarker identification, genetic variation analysis, protein modeling, drug screening, ADMET analysis, and drug receptor interaction analysis.
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Interpret the integrated results to provide comprehensive insights into pharmacogenomic relationships and facilitate personalized medicine approaches.
