Impact of AI on drug delivery and pharmacokinetics: The present scenario and future prospects

Prajapati, Jigna B.; Paliwal, Himanshu; Saikia, Surovi; Prajapati, Bhupendra G.; Prajapati, Bhupendra G.; Philip, Anil K.; Faiyazuddin, Md.

doi:10.1016/b978-0-323-89925-3.00016-2

Cited by 3 publications

(1 citation statement)

References 108 publications

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“…Digitalization and Data Analytics. Leveraging digital technologies, such as artificial intelligence (AI), machine learning, and data analytics [148,149], can identify novel and sustainable reaction pathways and thus directly or indirectly optimize processes, improve energy efficiency, and identify opportunities for emission reduction. Advanced modeling and simulation tools [150] can also aid in designing more sustainable and environmentally friendly pharmaceutical manufacturing processes [151,152].…”

Section: Pharmaceutical Industrymentioning

confidence: 99%

Transitioning towards Net-Zero Emissions in Chemical and Process Industries: A Holistic Perspective

Glavič,

Pintarič,

Levičnik

et al. 2023

Processes

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Given the urgency to combat climate change and ensure environmental sustainability, this review examines the transition to net-zero emissions in chemical and process industries. It addresses the core areas of carbon emissions reduction, efficient energy use, and sustainable practices. What is new, however, is that it focuses on cutting-edge technologies such as biomass utilization, biotechnology applications, and waste management strategies that are key drivers of this transition. In particular, the study addresses the unique challenges faced by industries such as cement manufacturing and highlights the need for innovative solutions to effectively reduce their carbon footprint. In particular, the role of hydrogen as a clean fuel is at the heart of revolutionizing the chemical and process sectors, pointing the way to cleaner and greener operations. In addition, the manuscript explores the immense importance of the European Green Deal and the Sustainable Development Goals (SDGs) for the chemical industry. These initiatives provide a clear roadmap and framework for advancing sustainability, driving innovation, and reducing the industry’s environmental impact, and are a notable contribution to the existing body of knowledge. Ultimately, alignment with the European Green Deal and the SDGs can bring numerous benefits to the chemical industry, increasing its competitiveness, promoting societal well-being, and supporting cross-sector collaboration to achieve shared sustainability goals. By highlighting the novelty of integrating cutting-edge technologies, addressing unique industrial challenges, and positioning global initiatives, this report offers valuable insights to guide the chemical and process industries on their transformative path to a sustainable future.

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Section: Pharmaceutical Industrymentioning

confidence: 99%

Transitioning towards Net-Zero Emissions in Chemical and Process Industries: A Holistic Perspective

Glavič,

Pintarič,

Levičnik

et al. 2023

Processes

View full text Add to dashboard Cite

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Transformative trends: A comprehensive review on role of artificial intelligence in healthcare and pharmaceutical research

Bhabad,

Lamkhade,

Koyate

et al. 2023

IJCAAP

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Artificial intelligence (AI) represents a specialized field within computer science, empowering machines to efficiently process and analyze intricate data. The surge in AI-focused research has notably accelerated, particularly in its growing role within healthcare services and research. This review delves into the manifold opportunities and challenges that AI presents in the realms of healthcare and pharmaceutical research. To compile relevant literature, a comprehensive search was conducted across databases such as PubMed, Science Direct, and Google Scholar. The article extensively explores the application of AI in diverse healthcare aspects such as disease diagnosis, digital therapy, personalized treatment, drug discovery, and the anticipation of epidemics or pandemics. The predominant AI technologies employed include deep learning and neural networks. The review emphasizes the pivotal role of advancing AI technologies in fostering rapid and cost-effective healthcare and pharmaceutical research. The anticipated outcome is an improved delivery of services to the general public, reflecting the transformative impact of AI on scientific endeavors.

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Artificial Intelligence-Enhanced Nanomedicine Design and Deep Reinforcement Learning in Pharmacokinetics

Padmini,

Amaran,

Sreekumar

et al. 2024

Advances in Medical Technologies and Clinical Practice

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This chapter explores the potential of Artificial Intelligence (AI) in nanomedicine design, focusing on Deep Reinforcement Learning (DRL) for optimizing pharmacokinetics. Nanomedicine uses nanoscale materials for disease diagnosis, treatment, and monitoring, presenting unique challenges and opportunities due to biological system complexity. Deep Learning (DRL) principles are used to design nanoparticles with optimal properties for targeted drug delivery and controlled release. AI is practically applied in nanomedicine design, including AI-driven platforms for predicting biodistribution, metabolism, and clearance. The chapter also discusses the integration of DRL with other AI techniques and ethical considerations, emphasizing transparency, reproducibility, and collaboration between AI experts, clinicians, and regulatory bodies.

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Impact of AI on drug delivery and pharmacokinetics: The present scenario and future prospects

Cited by 3 publications

References 108 publications

Transitioning towards Net-Zero Emissions in Chemical and Process Industries: A Holistic Perspective

Transitioning towards Net-Zero Emissions in Chemical and Process Industries: A Holistic Perspective

Transformative trends: A comprehensive review on role of artificial intelligence in healthcare and pharmaceutical research

Artificial Intelligence-Enhanced Nanomedicine Design and Deep Reinforcement Learning in Pharmacokinetics

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