Citeline BioBytes: Machine Learning Could Improve Clinical Trial Diversity

Emerging technologies are making waves in biopharma research. A recent article in Citeline In Vivo discusses how machine learning (ML) is being used to improve clinical trial diversity. By analyzing data related to social determinants of health, ML tools can help recruit from historically marginalized communities.

Increasing trial diversity is now a significant focus, especially with FDORA provisions requiring diversity action plans for specific late-stage trials. However, historically marginalized populations have been logistically challenging to access, and there remains a reluctance due to past injustices. Innovative tools, like Lokavant's platform, are making strides in optimizing recruitment.

For a detailed dive into how AI and ML are transforming clinical trial inclusivity, check out the full article at Citeline In Vivo.