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April 3, 2026Journal of Exploratory Research in PharmacologyOpen Access

Cage-to-Code: From Animal Experimentation to AI-driven Drug Discovery

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Authors

PCPratip K. ChaskarSBSneha BaglePSPiyusha S. Shete-Patil

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Overview

This review examines AI's role in drug discovery, highlighting ethical advancements and scientific challenges.

Key Points

  • The aim is to explore how AI-driven polypharmacology can bridge the gap between animal experimentation and human drug development.
  • Critically reviewing literature on AI applications in drug discovery.
  • Assessing regulatory and ethical drivers for non-animal methodologies.
  • Examining gaps in science and education due to reduced animal model dependence.
  • Analyzing AI and deep learning roles in biological complexity and toxicity modeling.
  • AI-driven approaches may enhance ethical standards in drug development.
  • Reduction of animal models is challenged by gaps in scientific understanding.
  • AI platforms offer potential for scalable and precise pharmacological research.

Cite This Study

Chaskar et al. (2026) studied this question.

synapsesocial.com/papers/69cf5dc55a333a821460bc02https://doi.org/10.14218/jerp.2025.00058
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