This paper describes Optum’s submission to the Biomedical Translation task of the seventh conference on Machine Translation (WMT22). The task aims at promoting the development and evaluation of machine translation systems in their ability to handle challenging domain-specific biomedical data. We made submissions to two sub-tracks of ClinSpEn 2022, namely, ClinSpEn-CC (clinical cases) and ClinSpEn-OC (ontology concepts). These sub-tasks aim to test translation from English to Spanish. Our approach involves fine-tuning a pre-trained transformer model using in-house clinical domain data and the biomedical data provided by WMT. The fine-tuned model results in a test BLEU score of 38.12 in the ClinSpEn-CC (clinical cases) subtask, which is a gain of 1.23 BLEU compared to the pre-trained model.