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<Article>
<Journal>
				<PublisherName>AmitisGen TECH Dev Group</PublisherName>
				<JournalTitle>Personalized and Precision Medicine Journal</JournalTitle>
				<Issn>3115-7874</Issn>
				<Volume>10</Volume>
				<Issue>38</Issue>
				<PubDate PubStatus="epublish">
					<Year>2025</Year>
					<Month>09</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Personalized Medicine Approaches in the Management of Chronic Pain: From Genomics to Targeted Therapy</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>48</FirstPage>
			<LastPage>58</LastPage>
			<ELocationID EIdType="pii">728443</ELocationID>
			
<ELocationID EIdType="doi">10.22034/pmj.2025.2063912.1063</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Hossein</FirstName>
					<LastName>Fazli</LastName>
<Affiliation>Department of Anasthesiology, School of Medicine, Alborz University of Medical Science, Karaj, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Mehdi</FirstName>
					<LastName>Rezaee</LastName>
<Affiliation>Assistant professor of anesthesiology, school of Medicine, Alborz University of Medical Science, Karaj, Iran.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>04</Month>
					<Day>19</Day>
				</PubDate>
			</History>
		<Abstract>A common and incapacitating condition, chronic pain offers a difficult field of work because of its variability and response to conventional treatments. Genomic and proteomic-based personalized medicine including epigenetic and biomarker information could help to lower treatment variability, so improving diagnosis, phenotypic classification, and individualized approaches to treatment. Recent developments in genetics and pharmacogenetics of pain, pain phenotyping techniques, and the development of focused therapies including epigenetic modulators, peptides, biologics and nanomedicine are underlined in this review. Personalized medicine seeks to match every patient&#039;s individual genetic makeup to their course of treatment. It is increasingly accepted that pain chronology involves epigenetic processes, including DNA methylation and histone modifications. Furthermore discussed are the value of biomarkers in evaluating therapy response and prognosis as well as ethical, financial, and data availability-related issues. Finally, future directions involve the use of artificial intelligence mixed with multi-omics data for tailored optimal pain management. Adopting these changes can help patients to have less chronic pain and improve the therapeutic outcomes.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Chronic Pain</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Pain phenotyping</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Targeted therapy</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Biomarkers</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Precision pain management</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.pmjournal.ir/article_728443_179ba8436cb3160eb0a11fed91f7a03c.pdf</ArchiveCopySource>
</Article>
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