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Artificial Intelligence in Pharmaceutical Innovation: Accelerating Drug Discovery and Development

Students & Supervisors

Student Authors
Asif Aman Jihad
Bachelor of Science in Computer Science & Engineering, FACULTY OF SCIENCE & TECHNOLOGY
Sifur Taher Sarar
Bachelor of Science in Computer Science & Engineering, FACULTY OF SCIENCE & TECHNOLOGY
Md Nazmul Alam Shanto
Bachelor of Science in Computer Science & Engineering, FACULTY OF SCIENCE & TECHNOLOGY
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FACULTY OF SCIENCE & TECHNOLOGY

Abstract

Background: Pharmaceutical industry faces with high costs, development time-delays and the complexity of designing effective drugs. As traditional drug discovery depends on high failure rates in clinical trials. Artificial Intelligence (AI), with its ability to process vast amounts of data quickly offers a solution by improving efficiency, reducing costs, reducing development time-delays and enhancing drug design. This study shows how AI technologies can transform the drug discovery process. Methods: This study showcases the combination of reviews of existing AI applications in drug discovery with case studies from pharmaceutical companies that have integrated AI into their works. The research examines how AI analyze biological and chemical data. Machine learning algorithms and deep learning models are assessed for their ability to stimulate clinical trials, predict toxicity and streamline drug development. Results: The findings shows that AI can significantly accelerate drug discovery, particularly in early-stage drug design and toxicity prediction. AI tools have demonstrated effectiveness in identifying potential drug candidates and predicting clinical outcomes more efficiently than traditional methods. However, challenges remain, such as the need for high-quality data for training AI models, the complexity of regulatory approval, and a shortage of skilled professionals in the field. Conclusion: AI is significantly cheaper, more accurate and faster than traditional process. Though there are many challenges such as data privacy, regulatory barriers and workforce development exist the integration of AI in pharmaceutical research is promising path forward.

Keywords

Artificial Intelligence AI in Pharmaceutical Drug Discovery

Publication Details

  • Type of Publication: Conference 
  • Conference Name: 3rd International Conference on Life Sciences 2025 (ICALS 2025)
  • Date of Conference: 11/01/2025 - 12/01/2025
  • Venue: Mawlana Bhashani Science and Technology University, Santosh, Tangail-1902
  • Organizer: Mawlana Bhashani Science and Technology University, Santosh, Tangail-1902
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