Gene and cell therapy is entering a new phase, one where artificial intelligence is bringing precision and predictability to editing systems that were once largely trial-and-error. From CRISPR-Cas genome editing to emerging techniques like epigenome modulation and mitochondrial genome correction, machine learning and deep learning are increasingly guiding how these tools are designed and scaled. AI is helping minimize off-target effects, improve manufacturing predictability, and build in the kind of explainability and bias mitigation that safety and regulatory approval demand. As these technologies move closer to widespread clinical use, the field needs a framework that ties computational innovation directly to therapeutic application, rather than treating AI and biomedicine as separate conversations. This convergence of computational innovation and biological engineering marks one of the most consequential shifts in modern therapeutic science. AI-Driven Innovations in Genome, Epigenome, and Mitochondrial Therapies provides state-of-the-art, data-driven methodologies for designing, optimizing, and validating safer, more precise, and scalable gene and cell therapies. By connecting concrete biomedical applications with benchmarked computational pipelines and structured frameworks for transparent, accountable AI governance, this book equips researchers and practitioners to navigate discovery, preclinical validation, clinical translation, and lifecycle risk management. Covering topics such as genome-enabled precision wound care, mitochondrial mutation detection, and mitochondrial editing, this book is an excellent academic resource for graduate and doctoral students, biomedical researchers, AI and machine learning specialists, bioinformaticians, regulatory affairs professionals, policymakers, and more.
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Divya Andy is a pharmaceutical scientist and medicinal chemist whose work spans Large and small-molecule design, analytical method development, and evolving models of pharmacy practice. She earned her Bachelor of Pharmacy from Shri Vishnu College of Pharmacy, a Master’s in Pharmaceutical Chemistry from Andhra University, and a Ph.D. in Medicinal and Biological Chemistry from the University of Toledo, where her doctoral research focused on identifying binding proteins for the calcium-mobilizing second messengers NAADP and cADPR. She subsequently served as a postdoctoral fellow in medicinal chemistry and drug development at the University of Toledo College of Medicine and Life Sciences. Dr. Andy’s research portfolio includes highly cited work on UHPLC–MS/MS bioanalytical methods, photo-clickable adenosine and cyclic ADP-ribose analogs, and PPARδ agonists that promote osteogenesis, alongside collaborative studies in osteoporosis models. More recently, she has coauthored publications on the role of pharmacists in over-the-counter medicine stewardship, test-and-treat programs, digital pharmacy ecosystems, and pharmacist-led weight-management strategies, reflecting an expanding focus on patient-centered pharmacy services and public health. An ORCID-registered researcher, she combines deep laboratory expertise with a growing body of practice-oriented scholarship to advance safe, effective, and accessible medication use.
Anmol Budhewar serves as an Assistant Professor in Computer Engineering, with research interests spanning artificial intelligence, machine learning, blockchain-enabled systems, and secure computing architectures. In the previous academic year, he published one Scopus-indexed research article and one IEEE international conference paper, demonstrating his commitment to high-quality scholarly dissemination. He contributes extensively to the academic peer-review ecosystem, serving as a reviewer for multiple international journals and edited books, and earning several Certificates of Excellence for review quality. Notably, he reviewed four research articles for SN Computer Science (Springer Nature) on topics including blockchain security, medical image analysis, fraud detection, and authentication systems. His academic work emphasizes integrating intelligent computational models with real-world applications in healthcare, cybersecurity, and data-driven decision systems. Through research, reviewing, and teaching, he strengthens methodological rigor and interdisciplinary innovation in computer science.
Dr. Adinarayana Andy is a licensed pharmacist and research scientist with over sixteen years of experience bridging clinical pharmacy practice, pharmaceutical innovation, and operations management. A multidisciplinary expert, Dr. Andy holds a unique combination of credentials: a PhD in Biotechnology, an MBA in Project Management, and active licensure as a pharmacist. Currently works as a Inpatient pharmacist at Mass general Brigham in Massachusetts , served as Pharmacist-in-Charge at Weatherwax Family Pharmacy in Michigan, Dr. Andy directs clinical operations with a focus on medication therapy management (MTM), immunization initiatives, and public health outreach. His leadership is grounded in extensive industry experience with global pharmaceutical organizations, including Bristol-Myers Squibb-Biocon, Cadila Pharmaceuticals, and Dr. Reddy’s Laboratories. In these roles, he contributed significantly to drug development, regulatory affairs, and quality assurance frameworks. Andy earned his PhD in Biotechnology from Acharya Nagarjuna University and an MBA from the University of the Cumberlands, USA. He also holds a Master of Pharmacy in Pharmaceutical Analysis and Quality Assurance from Biju Patnaik University of Technology and a Bachelors of Pharmacy from Andhra University. An active contributor to the scientific community, Dr. Andy serves as a peer reviewer for international journals, championing evidence-based strategies to improve patient outcomes and healthcare delivery.
Aman Suresh Tharayil is an Assistant Professor in Pharmacy Practice, currently serving at the Faculty of Pharmacy, Dr. M.G.R. Educational and Research Institute, Chennai. With a Pharm.D and ongoing PhD in Pharmacy Practice from SIMATS, he brings academic depth and clinical insight to his teaching and research. His teaching repertoire includes subjects such as pharmacotherapeutics, biostatistics, and pharmacoepidemiology for undergraduate and doctoral pharmacy programs. Dr. Aman is an active contributor to scholarly literature with multiple publications in Scopus and Web of Science-indexed journals, including research on diabetes, nephrology, and pharmacovigilance. His work has earned recognition such as subject-wise ranks at RGUHS and a prestigious ASCPT LMIC Travel Grant. Beyond academia, Dr. Aman has reviewed over 200 manuscripts and serves on editorial boards of reputed journals like Acta Scientific Pharmaceutical Sciences, PLOS ONE, and Cureus. He is also a frequent workshop resource person and guest lecturer on clinical pharmacy and regulatory topics. With strong skills in academic mentorship, interdisciplinary collaboration, and public health education, he actively bridges classroom instruction with real-world clinical practice.
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Paperback. Etat : new. Paperback. Gene and cell therapy is entering a new phase, one where artificial intelligence is bringing precision and predictability to editing systems that were once largely trial-and-error. From CRISPR-Cas genome editing to emerging techniques like epigenome modulation and mitochondrial genome correction, machine learning and deep learning are increasingly guiding how these tools are designed and scaled. AI is helping minimize off-target effects, improve manufacturing predictability, and build in the kind of explainability and bias mitigation that safety and regulatory approval demand. As these technologies move closer to widespread clinical use, the field needs a framework that ties computational innovation directly to therapeutic application, rather than treating AI and biomedicine as separate conversations. This convergence of computational innovation and biological engineering marks one of the most consequential shifts in modern therapeutic science. AI-Driven Innovations in Genome, Epigenome, and Mitochondrial Therapies provides state-of-the-art, data-driven methodologies for designing, optimizing, and validating safer, more precise, and scalable gene and cell therapies. By connecting concrete biomedical applications with benchmarked computational pipelines and structured frameworks for transparent, accountable AI governance, this book equips researchers and practitioners to navigate discovery, preclinical validation, clinical translation, and lifecycle risk management. Covering topics such as genome-enabled precision wound care, mitochondrial mutation detection, and mitochondrial editing, this book is an excellent academic resource for graduate and doctoral students, biomedical researchers, AI and machine learning specialists, bioinformaticians, regulatory affairs professionals, policymakers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798260001622
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Paperback. Etat : new. Paperback. Gene and cell therapy is entering a new phase, one where artificial intelligence is bringing precision and predictability to editing systems that were once largely trial-and-error. From CRISPR-Cas genome editing to emerging techniques like epigenome modulation and mitochondrial genome correction, machine learning and deep learning are increasingly guiding how these tools are designed and scaled. AI is helping minimize off-target effects, improve manufacturing predictability, and build in the kind of explainability and bias mitigation that safety and regulatory approval demand. As these technologies move closer to widespread clinical use, the field needs a framework that ties computational innovation directly to therapeutic application, rather than treating AI and biomedicine as separate conversations. This convergence of computational innovation and biological engineering marks one of the most consequential shifts in modern therapeutic science. AI-Driven Innovations in Genome, Epigenome, and Mitochondrial Therapies provides state-of-the-art, data-driven methodologies for designing, optimizing, and validating safer, more precise, and scalable gene and cell therapies. By connecting concrete biomedical applications with benchmarked computational pipelines and structured frameworks for transparent, accountable AI governance, this book equips researchers and practitioners to navigate discovery, preclinical validation, clinical translation, and lifecycle risk management. Covering topics such as genome-enabled precision wound care, mitochondrial mutation detection, and mitochondrial editing, this book is an excellent academic resource for graduate and doctoral students, biomedical researchers, AI and machine learning specialists, bioinformaticians, regulatory affairs professionals, policymakers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798260001622
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Paperback. Etat : new. Paperback. Gene and cell therapy is entering a new phase, one where artificial intelligence is bringing precision and predictability to editing systems that were once largely trial-and-error. From CRISPR-Cas genome editing to emerging techniques like epigenome modulation and mitochondrial genome correction, machine learning and deep learning are increasingly guiding how these tools are designed and scaled. AI is helping minimize off-target effects, improve manufacturing predictability, and build in the kind of explainability and bias mitigation that safety and regulatory approval demand. As these technologies move closer to widespread clinical use, the field needs a framework that ties computational innovation directly to therapeutic application, rather than treating AI and biomedicine as separate conversations. This convergence of computational innovation and biological engineering marks one of the most consequential shifts in modern therapeutic science. AI-Driven Innovations in Genome, Epigenome, and Mitochondrial Therapies provides state-of-the-art, data-driven methodologies for designing, optimizing, and validating safer, more precise, and scalable gene and cell therapies. By connecting concrete biomedical applications with benchmarked computational pipelines and structured frameworks for transparent, accountable AI governance, this book equips researchers and practitioners to navigate discovery, preclinical validation, clinical translation, and lifecycle risk management. Covering topics such as genome-enabled precision wound care, mitochondrial mutation detection, and mitochondrial editing, this book is an excellent academic resource for graduate and doctoral students, biomedical researchers, AI and machine learning specialists, bioinformaticians, regulatory affairs professionals, policymakers, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9798260001622
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Taschenbuch. Etat : Neu. AI-Driven Innovations in Genome, Epigenome, and Mitochondrial Therapies | Divya Andy (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798260001622 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 136460168
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