https://orcid.org/0000-0002-1399-8944
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ABSTRACT
Introduction
Subcutaneous physiology is distinct from other parenteral routes that benefit the administration of prolonged-release formulations. A prolonged-release effect is particularly convenient for treating chronic diseases because it is associated with complex and often prolonged posologies. Therefore, drug-delivery systems focused on nanotechnology are proposed as alternatives that can overcome the limitations of current therapeutic regimens and improve therapeutic efficacy.
Areas covered
This review presents an updated systematization of nanosystems, focusing on their applications in highly prevalent chronic diseases. Subcutaneous-delivered nanosystem-based therapies comprehensively summarize nanosystems, drugs, and diseases and their advantages, limitations, and strategies to increase their translation into clinical applications. An outline of the potential contribution of quality-by-design (QbD) and artificial intelligence (AI) to the pharmaceutical development of nanosystems is presented.
Expert opinion
Although recent academic research and development (R&D) advances in the subcutaneous delivery of nanosystems have exhibited promising results, pharmaceutical industries and regulatory agencies need to catch up. The lack of standardized methodologies for analyzing in vitro data from nanosystems for subcutaneous administration and subsequent in vivo correlation limits their access to clinical trials. There is an urgent need for regulatory agencies to develop methods that faithfully mimic subcutaneous administration and specific guidelines for evaluating nanosystems.
Article highlights
The subcutaneous self-injection of drugs is more convenient and cost-effective than the intravenous route for chronic diseases.
Nanosystems delivered via the subcutaneous route have a prolonged release and low incidence of adverse systemic effects.
The prolonged-release effect of microparticle-associated and hydrogel-associated nanosystems is due to their higher targeting efficacy and lower nonspecific biodistribution.
Missing subcutaneous specificity in the Quality Target Product Profile (QTPP) makes it challenging to establish nanosystems for this route.
AI potential in subcutaneous prolonged-release nanosystems developed using QbD approaches.
The lack of standardized methodologies mimicking in vitro subcutaneous administration limits data interpretation.
Investing in nanosystems for subcutaneous administration may revitalize the pharmaceutical market owing to their intellectual property value.
List of abbreviations
| AB | = | antibody |
| AI | = | artificial intelligence |
| ANN | = | artificial neural networks |
| APC | = | antigen-presenting cell |
| BGL | = | blood glucose level |
| BMP-2 | = | bone morphogenetic protein 2 |
| Cmax | = | maximum concentration |
| CINV | = | chemotherapy-induced nausea and vomiting |
| CKD | = | chronic kidney disease |
| CQA | = | critical quality attribute |
| ds-siRNA | = | double-stranded small interfering RNA |
| EMA | = | European Medicines Agency |
| ECM | = | extracellular matrix |
| EPR | = | enhanced permeability and retention |
| EX | = | exenatide |
| FBR | = | foreign body response |
| FDA | = | Food and Drug Administration |
| FPP | = | folate-polyethyleneimine conjugated poly (organophosphazene) |
| GLP-1 | = | glucagon-like peptide-1 |
| HIV | = | human immunodeficiency virus |
| ICH | = | International Committee on Harmonization |
| IFN | = | interferon |
| IL | = | interleukin |
| IL-4 Rα | = | α subunit of interleukin 4 receptor |
| IL-5 Rα | = | α subunit of interleukin 5 receptor |
| IL-13 Rα | = | α subunit of interleukin 15 receptor |
| IL-17 Rα | = | α subunit of interleukin 17 receptor |
| IM | = | intramuscular |
| IV | = | intravenous |
| ML | = | machine learning |
| MPS | = | mononuclear phagocytic system |
| mRNA | = | messenger RNA |
| NS1 | = | nonstructural protein 1 |
| PAEU | = | poly(β-amino urethane) |
| PCL | = | polycaprolactone |
| PCLA | = | poly(ε-caprolactone-co-lactide) |
| PDI | = | polydispersity index |
| PEG | = | polyethylene glycol |
| PHBV | = | poly(3-hydroxybutyrate-co-3-hydroxyvalerate) |
| PLGA | = | poly(lactic-co-glycolic acid) |
| PS | = | particle size |
| PTX | = | paclitaxel |
| QbD | = | quality by design |
| QTPP | = | quality target product profile |
| R&D | = | research and development |
| rHuPH20 | = | recombinant human hyaluronidase PH20 |
| SCT | = | salmon calcitonin |
| SC | = | subcutaneous |
| T1D | = | type 1 diabetes |
| T2D | = | type 2 diabetes |
| tmax | = | time it takes for a drug to reach the maximum concentration after administration |
Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.