Generating Low Cost and High Throughput Candidate Routes for Evaluation in Route Selection for Hybrid Peptide Synthesis─A Mathematical Optimization Approach

Route selection is an important first step in hybrid peptide synthesis. Route selection is based on multiple criteria and typically involves assessing cost and throughput after the fact for promising routes to further narrow alternatives. We discuss a mathematical optimization approach to generate low cost and high throughput route candidates apriori to augment the list of routes that are evaluated in a route selection workflow for hybrid peptide synthesis. Specifically, we show how a Dynamic Programming approach can be used to efficiently screen route alternatives for cost and throughput. We also discuss how the uncertainty and lack of good information at this stage can be addressed by screening route candidates based on a range of assumptions. This approach is easy to implement and has the potential to enhance the current route selection workflow for hybrid peptide synthesis.