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Record W7019843825

Incorporation of Lipid Nanoparticles into Pullulan Based Oral Thin Films for the Delivery of Vaccines

2022· dissertation· en· W7019843825 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsnot available
Fundersnot available
KeywordsBuccal administrationActive ingredientSyringeDosage formHypodermic needleOral administrationDrugVaccinationImmune system
DOInot available

Abstract

fetched live from OpenAlex

Infectious diseases are most effectively controlled by vaccines that can elicit an immune response and create antibodies. As it stands, most vaccines are administered using subcutaneous or intramuscular injections. Injections via needle and syringe often invoke anxiety for individuals, which can result in low vaccination rates. The cost associated with administering vaccines is also high due to the requirement of trained health care professionals for administration. Additionally, administration via injection produces significant amounts of biohazardous waste. Administration of a vaccine by the swallowing of a pill or capsule also presents challenges. The active ingredient must be able to withstand passage through the gastrointestinal tract where enzymatic or acid related degradation is possible. Two promising sites for vaccine delivery are the sublingual region which is located on the floor of the mouth and the underside of the tongue, and the buccal region located on the gums, cheeks, and inner lip. These regions, present in the oral cavity, allow for an active ingredient to be rapidly absorbed into the bloodstream without having to undergo first pass metabolism. One drug delivery method that has recently gained interest is the oral thin film. Upon placing an oral thin film on the buccal or sublingual region of the mouth, the film will rapidly dissolve and release the active ingredient to be absorbed into the bloodstream. Rapid Dose Therapeutics, a company in Burlington, Ontario, has developed the QuickStrip, an oral thin film that can deliver caffeine, vitamin B12, melatonin, and tetrahydrocannabinol (THC) through the buccal and sublingual route. Rapid Dose Therapeutics is interested in expanding the applications of the QuickStrip into vaccine delivery. Incorporating vaccines into oral thin films would allow for a pain-free, self-administrable inoculation process. This would result in a decrease in costs associated with vaccine distribution, making vaccines more accessible, while also eliminating associated biohazardous waste. Vaccines are traditionally classified as live and non-live. Live vaccines contain a live, weakened strain of the pathogenic organism whereas non-live vaccines contain an inactivated whole pathogenic organism or a subunit of the pathogen. Over the course of the COVID-19 pandemic, a new vaccine type, messenger RNA (mRNA) -based vaccines, emerged. The mRNA within these vaccines encodes for the target antigen and employs the ribosomes within the host cell to transcribe the mRNA into the target antigen. The mRNA is encapsulated within lipid nanoparticles (LNP) which assist in delivering and protecting the RNA. mRNA based vaccines are beneficial over traditional vaccine types as they are safe and faster to manufacture. This thesis was performed in conjunction with Rapid Dose Therapeutics and worked toward being able to use the QuickStrip as a vaccine delivery method. In this work, lipid polymer hybrid nanoparticles were prepared using a probe sonication technique. The effect of sonication amplitude and temperature on particle size was studied. Next, ibuprofen loaded lipid polymer hybrid nanoparticles were synthesized using a nanoprecipitation technique. A fluorescent dye, fluorescein isothiocyanate, was then loaded into the hybrid nanoparticles. This allowed the acquisition of super resolution optical microscopy images of the particles, both prior to and after being incorporated into an oral thin film. Commercially produced lipid nanoparticles were then acquired from Acuitas Therapeutics, the company that produces the lipid nanoparticles for the Pfizer-BioNTech vaccine. These lipid nanoparticles contain a model mRNA strand as well as the fluorescent dye 1,1’-dioctadecyl-3,3,3’,3’-tetramethylindocarbocyanine. Super resolution optical microscopy was employed to visualize the Acuitas Therapeutics lipid nanoparticles on a glass coverslip and in oral thin films. The images acquired suggested that the lipid nanoparticles were unharmed during the film casting process. The integrity of the mRNA within the lipid nanoparticles was then assessed and confirmed using gel electrophoresis. To ensure the mRNA was remaining encapsulated within the particles, the Quant-iT RiboGreen RNA assay was used. Initial studies indicated that the RNA was becoming unencapsulated from the nanoparticles once the film mixture had been cast. This resulted in several modifications to the preparation and formulation of the oral thin films. Ultimately, a film formulation containing a lipid-PEG molecule was used to stabilize the lipid nanoparticles within the oral thin film.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0390.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.331
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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