Using artificial intelligence to improve peptide drug development.

Artificial intelligence based platform for peptide lead optimization.

NIH-funded research Koliber Biosciences, INC. · NIH-11006711

This study is working on making better peptide-based medicines by using artificial intelligence to help researchers create drugs that last longer and are easier to take, all while providing a simple tool to predict how well these new treatments will work.

Quick facts

Grant typeSbir 1 grant
Study typeNIH-funded research
Funding institutionKoliber Biosciences, INC. NIH-funded
Lab location1 site (San Diego, United States)
Project IDNIH-11006711 on NIH RePORTER

What this research studies

This research focuses on enhancing the development of peptide-based drugs by utilizing artificial intelligence (AI) to optimize their properties. It aims to address common challenges such as short half-life and poor oral bioavailability of peptides by developing innovative methods for encoding non-canonical amino acids and cyclic peptides. The project will create a user-friendly software platform that allows researchers to train models predicting the potency, solubility, stability, and permeability of peptide drugs, ultimately streamlining the drug discovery process. By leveraging machine learning, the research seeks to provide valuable insights from limited datasets, making it easier for scientists to develop effective and safe peptide therapies.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals with conditions that could be treated with peptide-based therapies, such as certain cancers or metabolic disorders like diabetes.

Not a fit: Patients who do not have conditions that can be addressed by peptide therapies may not receive any benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to the development of novel peptide treatments that are safer, more effective, and more affordable for patients.

How similar studies have performed: Previous research has shown promise in using machine learning for drug development, indicating that this approach could lead to significant advancements in peptide therapy.

Where this research is happening

San Diego, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Conditions Cancers
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.