Combining AI and stem cells to combat age-related ovarian decline

Ovarian aging, marked by decreasing egg quality and reserves, poses a significant barrier to fertility. Traditional fertility treatments such as hormone replacement therapy (HRT) or assisted reproductive technologies (ART) often fall short due to their general, non-targeted nature. 

A recent study by researchers from Peking University Third Hospital introduces a new strategy using artificial intelligence and genetically modified stem cells to counteract ovarian decline. The dual system combines OvaRePred, an AI-based diagnostic platform, with OvaResCells, customized stem cells generated via CRISPR/Cas9 editing. 

OvaRePred applies machine learning to analyze biomarkers such as: 

• Anti-Müllerian hormone (AMH) 

• Follicle-stimulating hormone (FSH) 

The system predicts critical fertility thresholds and personalizes treatment timelines. This data guides the application of OvaResCells, reprogrammed from somatic cells into induced pluripotent stem cells (iPSCs), then genetically optimized to enhance antioxidant functions or mitochondrial repair. 

Quality control is ensured by AI algorithms, including convolutional neural networks (CNNs), which identify unwanted cell traits with over 99% accuracy. 

• Targeted Gene Editing: Single-cell transcriptomics uncovered genes such as FOXP1 that play a role in ovarian aging. These findings inform specific gene edits in iPSCs. 

• Therapeutic Delivery: Preclinical models suggest that direct injection into the ovaries could help increase follicle counts and normalize hormone levels. 

• Scalability and Standardization: AI supports automated, high-throughput production of consistent stem cell batches. 

MEDICA-tradefair.com; Source: Peking University