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Advanced Technologies in Clinical Research and Drug Development
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Author(s): N. L. Swathi (Jawaharlal Nehru Technological University, Anantapur, India)and Achukutla Kumar (Indian Council of Medical Research, India)
Copyright: 2024
Pages: 17
Source title:
The Ethical Frontier of AI and Data Analysis
Source Author(s)/Editor(s): Rajeev Kumar (Moradabad Institute of Technology, India), Ankush Joshi (COER University, Roorkee, India), Hari Om Sharan (Rama University, Kanpur, India), Sheng-Lung Peng (College of Innovative Design and Management, National Taipei University of Business, Taiwan)and Chetan R. Dudhagara (Anand Agricultural University, India)
DOI: 10.4018/979-8-3693-2964-1.ch001
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Abstract
This chapter explores the synergistic potential of decentralized trials, gene editing (e.g., CRISPR-Cas9), and the integration of artificial intelligence (AI) and machine learning (ML) in clinical trials and drug development. Decentralized trials enhance diversity and expedite timelines, while gene editing ensures precision in treating genetic diseases, necessitating robust ethical guidelines. AI and ML streamline processes, improving efficiency from patient recruitment to data analysis. Digital biomarkers and real-time monitoring systems provide rich data streams. This confluence marks a transformative era, promoting patient-centric research, accelerating innovation, and optimizing trial design. Ethical and regulatory challenges require careful navigation. Integrating digital biomarkers and continuous monitoring will enhance data quality. This synergy holds promise for personalized medicine and improved outcomes, emphasizing the need for stakeholders to balance innovation with ethical responsibility for optimal healthcare advancement.
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