AI’s integration into clinical trials promises significant advancements, but it also introduces ethical considerations that must be addressed in practice. One key concern is the potential for algorithmic bias, which can skew patient selection processes. To mitigate this risk, trial designers should implement transparency and fairness checks in AI algorithms, ensuring they are trained on diverse datasets that reflect a broad patient population. Regular audits of AI-driven decisions can also help identify and correct biases early in the trial process.
Another ethical consideration is informed consent. AI systems that personalize trial protocols or modify treatment pathways must ensure that patients are fully informed about how AI will be used in their care. This requires clear communication strategies and possibly new consent forms that explain AI’s role in non-technical language.
Additionally, the use of AI in monitoring and decision-making must maintain patient autonomy. For instance, while AI might suggest optimal dosing or treatment modifications, clinicians should retain the final decision-making authority, incorporating AI recommendations as one of many factors in their judgment. This balance between AI-driven innovation and patient safety is crucial for the ethical deployment of AI in clinical trials.
