Creating peptide drugs that enhance analgesia and suppress the development of tolerance @oistedu

Uploaded June 2025 | Updated September 2026, 2 weeks ago

As part of the OIST Proof of Concept (POC) Program, Dr. Peng Zhou, a recipient and recent alumnus of a Technology Pioneer Fellowship has made an essential contributions to the field of clinical pain management by creating peptide drugs that enhance analgesia and suppress the development of tolerance in long-term opioid treatment. After having proved the peptides' function in vitro and in vivo, Dr. Zhou will evaluate their toxicity, stability and blood-brain barrier permeability in preclinical tests, hoping to offer a new generation of chronic pain management.

The development of these new peptide drugs is an important step toward more effective and safer pain management with existing opioids such as morphine and fentanyl, especially for patients in long-term opioid therapy.

Speaker: Dr. Peng Zhou, OIST Innovation, linkedin.com/in/peng-zhou-a577222b8
More information in English: oist.jp/sites/default/files/2025-02/61.%20Peng_TPF.pdf
More information in Japanese: oist.jp/sites/default/files/2025-03/61.%20Peng_Zhou_TPF_JP.pdf

The OIST Proof of Concept (POC) Program is a competitive funding initiative designed to bridge the gap between laboratory discoveries and commercialization. Learn more about POC projects: oist.jp/innovation/technology-development

Creating peptide drugs that enhance analgesia and suppress the development of tolerance

$Sylvester Eriksson-Bique: Embeddings as a Problem Solving Technique (TSVP Talk at OIST) Sylvester Eriksson-Bique is visiting OIST from 2024-01-08 until 2024-03-28 through the Theoretical Sciences Visiting Program (TSVP). Find out more about the TSVP on the program website: https://www.oist.jp/visiting-program. Abstract: Whether the graph of roads in Okinawa, or connections in social media, data often comes to as a network. We may wish to study optimization problems in such networks: such as shortest path or decompositions of the space. It turns out, that embedding the network into a linear space is a powerful way of simplifying these problems. We will first see some examples of this. Given the remarkable implications of such embeddings, we then wish to study when and how to construct such embeddings. This turns out to be a rich mathematical question, and I will be giving a mini course at OIST on this as well. In the talk, I will explain some ways embeddings can help you in your problems. I will also show you, with some pictures, some situations where an embedding can be very difficult to construct. Profile: I am primarily interested in geometric problems which arise in the context of rough spaces: embedding problems of metric spaces, the structure of boundaries of hyperbolic groups, the geometry of fractal spaces arising from dynamics, or fractal properties of sub-Riemannian geometries. Since many of these concepts are related to quasisymmetric mappings, I would describe these questions as being part of the quasiworld. Especially embedding questions are not only of theoretical interest. They arise naturally in data analysis and the analysis of certain relaxation methods to solve optimization problems. Further, these questions have profound connections to the analysis on such rough spaces and concepts that come from first order analysis of metric spaces. Indeed, these notions can obstruct embeddings, prevent certain geometries from existing, or reveal subtle geometric facts about dynamical systems. Their study also leads to natural invariants that can be used to classify and distinguish spaces from each other. Especially recently, I have come to see that the study of Analysis on Metric spaces can lead to answering some difficult open problems related to geometric group theory. However, an obstacle to making progress in this direction is that many fundamental notions in Analysis on metric spaces remain poorly understood. It is there, that I strive to develop new techniques, concepts and results, that help us answer these open problems. #OIST #OIST_TSVP #Mathematics #Embeddings #MetricSpaces #Theoretical #Science #VisitingProgram #Okinawa #TSVP$

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