Artificial Intelligence and Innovations in Onco-Reproductive Pharmaceutics
Abstract
The impact of artificial intelligence in onco-reproductive pharmaceutics is perhaps the most dramatic technological advancement in the field since the genomics revolution, ranging from the early detection of ovarian cancer using AI panels for liquid biopsy, to AI-accelerated drug discovery pipelines designing novel therapeutics against resistant reproductive cancer targets, to real-time treatment response monitoring with ctDNA-trained ML algorithms. AI in reproductive medicine is enhancing IVF success rates through objective embryo selection, personalizing fertility preservation for cancer patients, and predicting gonadotoxicity risk with unprecedented accuracy. The innovations such as digital twins, federated learning platforms, AI-guided CRISPR systems, and quantum machine learning are poised to expand these capabilities in the next 10 years. Realizing the potential of AI in this sensitive domain responsibly will require attention to algorithmic fairness, explainability, data privacy, and regulatory compliance, with the most effective AI applications developed in true multidisciplinary collaboration, including computational scientists, reproductive oncologists, pharmacologists, patient advocates, and ethicists, who ensure that AI works for the broad diversity of patients facing the intersection of cancer and reproductive health challenges.
Author Affiliations
- 1 Principal and Professor, Department of Pharmacology, Trinity Educational Institute, Ramgarh, Jharkhand, India.