Clinical text embedding refers to the process of learning representations (i.e., features or embeddings) of clinical trial data that capture its underlying structure and patterns. The goal of TRL is to get an accurate latent space of data from clinical trials that can be used for downstream tasks like clinical trial outcome prediction.