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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | University of Strathclyde |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Sep 29, 2028 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2925304 |
Background
Peptide drug candidates (PDCs) and their lipidated forms represent a growth area in delivering new therapeutic modalities for addressing unmet clinical need. Unmodified PDCs generally suffer from low circulation half-lives, requiring multiple dosing, chemical modifications to prolong circulation half-life, or incorporation into controlled release delivery systems.
Lipidated PDCs have emerged as a promising strategy to prolong systemic exposure to PDCs. However, their propensity to self-associate under formulation conditions has hampered their clinical translation. An underpinning gap in our knowledge base regarding PDC development is understanding the molecular determinants which define PDC self-association.
Project Objective
Undesirable developability attributes pose a major drawback to the clinical and commercial translation of chemically-modified (e.g., lipidated) PDCs. The commercial translation of these drug products is often hampered by a lack of fundamental knowledge of their solution-phase behaviour and the interactions that drive self-association. The term aggregation encompasses many types of interactions promoting self-association, ranging from dimerization to fibrillation.
Aggregates can pose severe developability risks, including reduced therapeutic efficacy, immunogenicity, and adverse events. A key challenge and research question in the development of biotherapeutics is defining the sequence and structural determinants that influence undesirable developability attributes. Through developing a computational and analytical framework a number of critical research questions concerning lipidated PDC developability will be addressed.
The objective of this studentship is to develop an integrated computational and analytical framework for understanding the mechanisms driving PDC aggregation. This information will then be used to guide chemical and formulation-based strategies to mitigate self-association. The desired outcome will be a framework to design next-generation PDCs with enhanced physicochemical properties for downstream therapeutic development.
University of Strathclyde
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