Translation And Cultural Adaptation Of Clinical Outcome Assessments (COAs): Is Machine Translation A Viable Option?

In the dynamic landscape of advancing technology and the escalating demand for accelerated drug development, the utilization of Machine Translation (MT) and Artificial Intelligence (AI) in translation processes emerges as a compelling avenue. This exploration becomes crucial to meet the exigencies of contemporary drug development timelines. The poster below delves into the applications of iterative learning and feedback mechanisms as tools in the translation domain, recognizing their potential to enhance efficiency. However, it is imperative to acknowledge and navigate the limitations inherent in these technologies.

Specifically, the poster conducts a comparative analysis between human translation (HT) and machine translation (MT) during the back translation phase. This comparative assessment extends to both Clinical Outcome Assessments (COAs) and supplementary study materials. By scrutinizing the strengths and constraints of each approach, the poster aims to contribute insights that can inform strategic decisions in leveraging translation technologies for Clinical Outcome Assessments and associated study materials, thereby paving the way for optimized processes in drug development endeavors.