Determining gradient conditions for peptide purification in RPLC with machine-learning-based retention time predictions.

•Machine learning is used to predict retention times based on amino acid sequences.•Suitable preparative gradient settings are determined from these data.•The amount experimental work needed to find a purification method is reduced.•The method is verified experimentally and its limitations are explored.•The approach targets pharmaceutical discovery where peptide properties varies much.