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Background <p>Artificial Intelligence (AI) is becoming a game-changer in pharmaceutical sciences, especially in drug formulation. Traditional methods of formulation often face challenges such as long timelines, high costs, and repeated trial-and-error processes.</p> Insights <p>AI offers solutions by using smart algorithms to speed up development, reduce failures, and improve precision.&#xa0;Machine learning techniques, including neural networks, support vector machines, and reinforcement learning, are being used to predict the best excipients, check drug–drug interactions, improve stability, and even suggest personalized dosages. These tools help researchers make better decisions and cut down on unnecessary experiments.&#xa0;Several AI-driven platforms like IBM Watson, Atomwise, and Schrödinger are already supporting drug discovery and formulation. They combine with existing processes to make workflows more reliable and efficient. Still, challenges remain. Issues with the quality and availability of data, limited computing resources, and regulatory concerns can slow down wider adoption. In addition, questions around ethics and the need for AI systems to be transparent and interpretable are important for building trust. Looking ahead, AI has the potential to transform formulation by integrating omics data, monitoring patients in real time, and creating adaptive formulations that respond to individual needs. Collaboration between pharmacists, AI specialists, and regulators will be essential to make this vision a reality.</p> Conclusion <p>AI is paving the way toward faster, cheaper, and more tailored drug development. With continued innovation, it is set to play an indispensable role in pharmaceutical formulation and the advancement of personalized medicine.</p>

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AI-Driven Drug Formulation Development: Transforming the Future of Pharmaceutical Drug Development from Discovery to Regulatory Aspects

  • 期刊论文

  • 发表日期：

    2025年12月3日

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  • Ali Sartaj,
  • Anjali Rajora,
  • Juveria Usmani,
  • Sweeti Bana,
  • Annu,
  • Javed Ali

摘要

Background

Artificial Intelligence (AI) is becoming a game-changer in pharmaceutical sciences, especially in drug formulation. Traditional methods of formulation often face challenges such as long timelines, high costs, and repeated trial-and-error processes.

Insights

AI offers solutions by using smart algorithms to speed up development, reduce failures, and improve precision. Machine learning techniques, including neural networks, support vector machines, and reinforcement learning, are being used to predict the best excipients, check drug–drug interactions, improve stability, and even suggest personalized dosages. These tools help researchers make better decisions and cut down on unnecessary experiments. Several AI-driven platforms like IBM Watson, Atomwise, and Schrödinger are already supporting drug discovery and formulation. They combine with existing processes to make workflows more reliable and efficient. Still, challenges remain. Issues with the quality and availability of data, limited computing resources, and regulatory concerns can slow down wider adoption. In addition, questions around ethics and the need for AI systems to be transparent and interpretable are important for building trust. Looking ahead, AI has the potential to transform formulation by integrating omics data, monitoring patients in real time, and creating adaptive formulations that respond to individual needs. Collaboration between pharmacists, AI specialists, and regulators will be essential to make this vision a reality.

Conclusion

AI is paving the way toward faster, cheaper, and more tailored drug development. With continued innovation, it is set to play an indispensable role in pharmaceutical formulation and the advancement of personalized medicine.