Bioanalytical Drug Tolerance Limit Prediction and Optimization Model Developed Through Machine Learning With TensorFlow

Award winning poster presented at the 14th WRIB

“The selection is based on novelty of the concept, utility of the approach and the presentation style. It was a difficult decision for us to select 1 winner from total of 11 posters since the posters are generally with high quality and have addressed common challenges in the field with solid data. The winning poster stands out for its novelty, applying machine learning to predict drug tolerance of ADA method. Drug tolerance is a critical parameter for ADA method performance and is often the most resource-intensive component of ADA assay development. Although more data may be needed to further evaluate the prediction accuracy prior to broad implementation, the machine learning approach has the potential to streamline ADA method development and significantly improve the efficiency of immunogenicity assessment.”