Ana L. Gomes Dos Santos

Therapeutic peptides combine high target specificity with potent biological activity. ¹ However, treatment success is often limited by rapid clearance and the need for frequent injections. ^{2, 3} This challenge is particularly acute for therapeutic peptides used in obesity, where clinical benefit must be balanced against dose-dependent adverse effects. In nature, these constraints are overcome by storing hormones as reversible fibrils, ⁴ but pharmacokinetic control is essential for widespread adoption of bio-inspired self-assembled depots for therapeutic peptides. Here, we show that tuneable pharmacokinetics can be achieved and modelled by mapping the fundamental chemical parameters of reversibly self-assembly in vitro . We demonstrate this approach for the amylin analogue pramlintide. Amylin analogues are under development for the next generation of diabetes and obesity treatments, with improved mechanism of action e.g. preserving lean body mass. ^5–8 Pramlintide is an approved drug with a well-established safety profile, however, it has a comparable half-life to native amylin. ^8–12 In a pilot study, we achieve in vitro – in vivo correlation, increasing the half-life of pramlintide 20–82-fold in rats, while controlling burst release. These findings demonstrate that the optimisation of pharmacokinetics can be decoupled from peptide engineering, establishing a generalisable framework for generating long-acting peptide formulations by emulating native storage mechanisms.

Introduction: Oxyntomodulin (Oxm) hormone peptide has a number of beneficial effects on nutrition and metabolism including increased energy expenditure and reduced body weight gain. Despite its many advantages as a potential therapeutic agent, Oxm is subjected to rapid renal clearance and protease degradation limiting its clinical application. Previously, we have shown that subcutaneous administration of a fibrillar Oxm formulation can significantly prolong its bioactivity in vivo from a few hours to a few days.Methods: We used a protease resistant analogue of Oxm, Aib2-Oxm, to form nanfibrils depot and improve serum stability of released peptide. The nanofibrils and monomeric peptide in solution were characterized by spectroscopic, microscopic techniques, potency assay, QCM-D and in vivo studies.Results: We show that in comparison to Oxm, Aib2-Oxm fibrils display a slower elongation rate requiring higher ionic strength solutions, and a higher propensity to dissociate. Upon subcutaneous administration of fibrillar Aib2-Oxm in rodents, a 5-fold increase in bioactivity relative to fibrillar Oxm and a significantly longer bioactivity than free Aib2-Oxm were characterized. Importantly, a decrease in food intake was observed up to 72-hour post-administration, which was not seen for free Aib2-Oxm.Conclusion: Our findings provides compelling evidence for the development of long-lasting peptide fibrillar formulations that yield extended plasma exposure and enhanced in vivo pharmacological response.

3D printing is an emerging technology aiming towards personalized drug delivery, among many other applications. Microneedles (MN) are a viable method for transdermal drug delivery that is becoming more popular for delivery through the skin. However, there is a need for a faster fabrication process with potential for easily exploring different geometries of MNs. In the current study, a digital light processing (DLP) method of 3D printing for fabrication of hollow MN arrays using commercial UV curable resin was proposed. Print quality was optimised by assessing the effect of print angle on needle geometries. Mechanical testing of MN arrays was conducted using a texture analyser. Angled prints were found to produce prints with geometries closer to the CAD designs. Curing times were found to affect the mechanical strength of MNs, with arrays not breaking when subjected to 300 N of force but were bent. Overall, DLP process produced hollow MNs with good mechanical strength and depicts a viable, quick, and efficient method for the fabrication of hollow MN arrays.