Material-Efficient Optimization of Peptide Bioconjugation via Sub-Micromole Automated Flow and Bayesian Optimization

Added on:
26 Oct, 2026

We report a miniaturized, low-consumption optimization workflow for peptide bioconjugation by integrating automated continuous-flow experimentation with Bayesian optimization. Peptide substrates are often available only in limited quantities and exhibit substantial structural diversity, necessitating extensive condition screening and rendering conventional approaches inefficient. In this study, Trp-selective bioconjugation of leuprorelin was employed as a model reaction. The flow platform enabled precise control of reaction parameters and automated screening using minimal sample quantities (<1 μmol per trial). Bayesian optimization efficiently identified optimal conditions while significantly reducing experimental burden. The developed strategy achieved up to 82 % yield with high reproducibility and minimized by-product formation, demonstrating a practical approach for data-driven optimization of substrate-dependent peptide reactions involving limited and valuable materials.

Equipment used in this paper: R-Series Flow Chemistry System 

  • Fujii Y1
  • Doi T1
  • Ueda Y2
  • Yada A3
  • Oisaki K3,4
  • Nozawa‐Kumada K3,5
  •   1Graduate School of Pharmaceutical Sciences, Tohoku University (Ringgold ID: RIN13101), Sendai, Miyagi Prefecture, Japan
  • 2Research Institute for Chemical Process Technology, National Institute of Advanced Industrial Science and Technology (AIST) (Ringgold ID: RIN73461), Tsukuba, Ibaraki, Japan
  • 3Catalytic Chemistry Research Institute (CCRI), National Institute of Advanced Industrial Science and Technology Tsukuba Center Tsukuba Central (Ringgold ID: RIN73461), Tsukuba, Ibaraki Prefecture, Japan
  • 4Open Innovation Laboratory for Food and Medicinal Resource Engineering (FoodMed-OIL), National Institute of Advanced Industrial Science and Technology Tsukuba Center Tsukuba Central (Ringgold ID: RIN73461), Tsukuba, Ibaraki Prefecture, Japan
  • 5PRESTO, Japan Science and Technology Agency (Ringgold ID: RIN13501), Kawaguchi, Saitama Prefecture, Japan
Material-Efficient Optimization of Peptide Bioconjugation via Sub-Micromole Automated Flow and Bayesian Optimization
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