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Artificial intelligence and machine learning in smart vaginal formulation development
Deborah A Ogundemuren1, Vivek Agrahari2, Andrew P Wong2
1Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, University of Lagos, Lagos, Nigeria; MEDAFRICA GMP Laboratory, Faculty of Pharmacy, University of Lagos, Lagos, Nigeria.
Advanced Drug Delivery Reviews
|April 29, 2026
Summary
Artificial intelligence (AI) and machine learning (ML) can overcome challenges in vaginal drug delivery by accounting for biological variability. These technologies promise more effective and personalized women
Area of Science:
- Pharmacology and Pharmaceutics
- Biotechnology
- Women's Health
Background:
- Vaginal drug delivery is complex due to the dynamic vaginal microenvironment (pH, hormones, microbiota).
- Biological variability leads to inconsistent therapeutic outcomes and poor patient adherence.
- Current vaginal formulations often fail to address individual patient differences.
Purpose of the Study:
- To review the emerging role of AI and ML in vaginal drug delivery.
- To explore AI/ML applications in designing advanced vaginal formulations.
- To discuss challenges and future potential of AI/ML in women's health therapeutics.
Main Methods:
- Literature review of AI/ML applications in vaginal drug delivery.
- Analysis of factors influencing vaginal formulation performance (e.g., microbiota).
- Consideration of ethical, regulatory, and technical challenges.
Main Results:
- AI/ML enables data-driven formulation development considering biological variability.
- AI/ML integration can improve predictability, efficiency, and reproducibility in formulation development.
- Early research indicates AI/ML's potential to enhance vaginal drug delivery systems.
Conclusions:
- AI/ML offers a promising approach to address limitations in current vaginal drug delivery.
- Integration of AI/ML with digital health can lead to personalized vaginal medicines.
- AI/ML has the potential to transform women's health outcomes through advanced drug delivery.
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