Artificial intelligence and machine learning are used in medical trials to boost human productivity rather than replace humans with digital technologies.
Fremont, CA: Artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) were becoming a cornerstone of successful modern clinical trials and got integrated into most of the technologies allowing clinical development transformation.
In recent years, the health and life sciences business has made a major leap into the digital era, with innovations and scientific advances boosting patient outcomes and public health. As a result, adopting digital transformation is no longer a choice but rather an industry norm. Let's take a look at what that entails for clinical development.
· A look into compliance and privacy
When considering the usage of patient data, companies must view privacy and compliance adherence. The stakes are enormous for any technology used in clinical trial execution.
Good Clinical Practice (GCP) and validation procedures must get followed to guarantee that an outcome is legitimate by being predictable and reproducible. Furthermore, there must be openness and explainability surrounding how any AI system makes judgments to demonstrate accuracy and eliminate potential bias. This is more important than ever from a compliance standpoint since regulators consider algorithms as part of what they base their approvals on.
