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Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research.

Parveen Kumar1, Benu Chaudhary2, Preeti Arya2

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Artificial intelligence (AI) offers significant benefits and drawbacks in healthcare and pharmaceutical research. This review explores AI applications from drug discovery to disease diagnosis and outbreak prediction.

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Area of Science:

  • Artificial Intelligence (AI)
  • Machine Learning
  • Computational Science

Background:

  • AI aims to create intelligent computer programs mimicking human cognitive processes.
  • AI applications are rapidly expanding in medical services and pharmaceutical research.
  • Understanding the pros and cons of AI in healthcare is crucial.

Purpose of the Study:

  • To provide a comprehensive overview of AI applications in healthcare and pharmaceutical research.
  • To review the benefits and limitations of AI in these industries.
  • To highlight AI's role in disease diagnosis, treatment, drug discovery, and outbreak prediction.

Main Methods:

  • Systematic review of research and review articles from PubMed, Google Scholar, and Science Direct.
  • Search terms included 'artificial intelligence', 'drug discovery', 'pharmacy research', and 'clinical trial'.
  • Analysis focused on AI's impact on diagnosis, digital treatment, drug development, and pandemic prediction.

Main Results:

  • AI, particularly neural networks and deep learning, is used for disease diagnosis and digital treatment.
  • AI aids in drug discovery and predicting outbreaks like COVID-19, Ebola, and Zika.
  • Tools like Bayesian non-parametric approaches, smartphones, and natural language processing are employed in clinical research and patient monitoring.

Conclusions:

  • AI has the potential to revolutionize medical and pharmaceutical investigations, making them more efficient and cost-effective.
  • AI promises improved public health services through advanced diagnostics and predictive capabilities.
  • Continued development in AI is expected to enhance healthcare outcomes and research efficiency.