Sustained Delivery of GLP-1 Receptor Agonists from Injectable Biomimetic Hydrogels Improves Treatment of Diabetes
Notice bibliographique
Résumé
Glucagon-like peptide-1 (GLP-1) is an incretin hormone and neurotransmitter secreted from intestinal L-cells in response to nutrients to stimulate insulin and block glucagon secretion in a glucose-dependent manner. GLP-1 in itself is rapidly degraded, but long-acting GLP-1 receptor agonists (GLP-1 RAs) have become central in the treatment of T2D because of the beneficial effects extending also beyond glucose control. Currently, these therapeutics must be injected either daily or weekly or taken daily orally, leaving room for technological innovations that enable less frequent administrations, which will reduce patient burden and increase patient compliance. An ideal GLP-1 RA drug product would provide continuous therapy for upwards of four months from a single administration to match the cadence with which T2D patients typically visit their physician. In this work, we leveraged an injectable hydrogel depot technology to develop a long-acting GLP-1 RA drug product. By modulating the hydrogel properties to tune GLP-1 RA retention within the hydrogel depot, we engineered formulations capable of months-long GLP-1 RA delivery. Using a rat model of T2D, we confirmed that a single injection of hydrogel-based therapies exhibits sustained exposure of GLP-1 RA over 42 days, corresponding to a once-every four month therapy in humans. Moreover, these hydrogel therapies maintained optimal management of blood glucose and weight comparable to daily injections of a leading GLP-1 RA drug molecule. The pharmacokinetics and pharmacodynamics of these hydrogel-based long-acting GLP-1 RA treatments are promising for development of novel therapies reducing treatment burden for more effective management of T2D. Progress and Potential: While insufficient access to quality healthcare is problematic for consistent management of Type II diabetes (T2D), poor adherence to burdensome treatment regimens is one of the greatest challenges for disease management. Glucagon-like peptide 1 (GLP1) drugs have become central to the treatment of T2D due to their many beneficial effects beyond improving glucose control. Unfortunately, while optimization of GLP1 drugs has reduced treatment frequency from daily to weekly, significant patient burden still leads to poor patience compliance. In this work we developed an injectable hydrogel technology to enable GLP1 drugs only requiring administration once every four months. We showed in a rat model of T2D that one injection of a hydrogel-based therapy improves management of blood glucose and weight when compared with daily injections of the leading drug used clinically. These hydrogel-based GLP1 treatments are promising for reducing treatment burden and more effectively managing T2D. Future Impact: A GLP-1-based drug product providing four months of continuous therapy per administration could be transformational for the management of Type II diabetes (T2D). One of the most challenging aspects of diabetes management with GLP-1 mimics is maintenance of consistent levels of the drugs in the body, which is complicated by poor patient compliance on account of the high frequency of dosing required for current treatments. By leveraging a unique sustained release hydrogel depot technology we develop a months-long GLP-1 drug product candidate that has the potential to reduce patient burden and improving diabetes management. Overall, the hydrogel technology we describe here can dramatically reduce the frequency of therapeutic interventions, significantly increasing patient quality of life and reducing complications of diabetes management.Our next steps will focus on optimization of the drug formulations in a swine model of T2D, which is the most advanced and translationally-relevant animal model for these types of therapeutics. The long-term vision for this work is to translate lead candidate drug products towards clinical evaluation, which will also require comprehensive safety evaluation in multiple species and manufacturing our these materials according to Good Manufacturing Practices. The months-long-acting GLP-1 drug product that will come from this work has the potential to afford thus far unrealized therapeutic impact for the hundreds of millions of people with diabetes worldwide.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».