The two-step screening strategy outlined herein provides a framework for efficient screening of anti-IDs and identification of the most robust PK assay format. Using fixed plate maps in this approach allowed for the use of automation and development of the WAND scoring tool, which together provide an additional layer of uniformity and eliminates potential operational variability. The scoring system that was developed was also designed to allow for changing of the weighting of the individual scores as needed. This could occur if there is additional knowledge on the mAb or program indicating that a parameter has potentially more impact on the necessary PK results. The scoring system for each parameter additionally can be expanded if there is a need to further differentiate the anti-IDs. Combining fixed plate formats with easily interchangeable elements in this strategy allows for use of these tools in future anti-ID screenings and PK assay development. Future work on the scoring system aims to leverage an automated data science driven approach. This includes development of the data-dependent scoring metric based on the distribution of assay parameters and interference data across different formats for generic and PK screens. In addition, a predictive machine learning algorithm will be developed to facilitate the generation of screening conditions to further expedite the selection and discovery of the optimal anti-IDs with minimum number of experiments. These methodological frameworks will facilitate the development of automated ligand-based assays to enhance the discovery process without human bias.