<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>Baqiyatallah University of Medical Sciences</PublisherName>
				<JournalTitle>Journal of Applied Biotechnology Reports</JournalTitle>
				<Issn>2322-1186</Issn>
				<Volume>13</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>03</Month>
					<Day>30</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Role of Artificial Intelligence in Modern Biotechnology: A Comprehensive Review</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>1899</FirstPage>
			<LastPage>1921</LastPage>
			<ELocationID EIdType="pii">242574</ELocationID>
			
<ELocationID EIdType="doi">10.30491/jabr.2025.523309.1873</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Akash</FirstName>
					<LastName>Phillip</LastName>
<Affiliation>Department of Biotechnology, IIMT University, Meerut, Uttar Pradesh, India</Affiliation>
<Identifier Source="ORCID">0009-0004-6067-512X</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>05</Month>
					<Day>14</Day>
				</PubDate>
			</History>
		<Abstract>&lt;span class=&quot;fontstyle0&quot;&gt;Artificial Intelligence (AI) is rapidly transforming biotechnology, unlocking unprecedented opportunities for innovation across the life sciences. As the complexity and volume of biological data continue to grow, AI-powered tools are revolutionizing how we understand, design, and manipulate biological systems. This review provides a comprehensive examination of how AI is reshaping core biotechnological domains, from drug discovery, protein structure prediction, and multi-omics integration to synthetic biology, genome editing, bioprocess optimization, and personalized medicine. Advances such as AlphaFold, generative models for molecular design, and digital twins underscore AI’s pivotal role in accelerating research, improving precision, and enabling real-time decision-making. The integration of AI with robotics, microfluidics, and lab automation further enhances high-throughput experimentation and reproducibility. In addition to technical advancements, this review addresses ethical, legal, and regulatory challenges, including data bias, algorithmic transparency, and biosecurity concerns. This review also highlights future frontiers such as AI-enabled organoid modeling, foundation models for biology, and sustainable applications in biomanufacturing and environmental biotechnology.&lt;/span&gt; </Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Artificial intelligence</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Biological Sciences</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Deep Learning</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Machine Learning</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">digital transformation</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.biotechrep.ir/article_242574_3afe6528ab176e66728fbae8aebfdce0.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
