Despite growing interest in ADC biotransformation, its characterization has not become a routine practice in the industry, primarily due to challenges with data analysis. There is no streamlined software tool for high-throughput data annotation. In contrast, for small molecule biotransformation or metabolism, there are a number of commercial and academic software options available for metabolite prediction and identification. To bridge the gap, we developed a data analysis workflow that can automatically annotate peaks for ADC biotransformation, by integrating a traditionally small molecule metabolite prediction tool with large molecule intact MS data analysis software. The general approach of the new workflow has 2 main steps: 1) build linker-payload biotransformation library by considering truncations and potential modifications, 2) import this delta mass library to automated intact data processing software. This approach was tested on two historical datasets as proof of concept. With this new approach, the timeframe of data analysis shortens from a week (manual search) to just a few hours.