Lipid nanoparticles (LNPs) are vesicles composed of ionizable lipids, helper lipids, cholesterol, and polyethylene glycol (PEG). As drug delivery vehicles, LNPs encapsulate nucleic acids (NA) and aid in their effective delivery to cells. LNPs are widely recognized for their use in the COVID-19 vaccines produced by Pfizer/BioNTech and Moderna. Both ionizable lipids, C12-200 and MC3 were used throughout this study, and were tested with and without a cDNA payload. With limited information regarding thermodynamic properties, this work highlights two methods to further characterize LNPs including differential scanning calorimetry (DSC) and TNS fluorescence assay. Understanding the physical properties, thermal behavior, and pH responsiveness of LNPs enables the rational design and optimization of LNPs. This work utilizes DSC to assess thermal properties such as transition peaks, activation energy, and pre-exponential factors. Apparent pKa analysis was also conducted to characterize LNPs with and without a payload. A relevant molecular difference between C12-200 and MC3 is that C12-200 contains five amine groups, while MC3 contains one amine group. By using differential scanning calorimetry (DSC), the results suggest that peak transition time is not significantly different between samples. Samples displayed an overall average transition time of 55.25 ± 2.716 minutes. Working with pKa analysis, the data suggests that samples without a payload displayed a higher apparent pKa: C12-200 being 7.12 and MC3 being 6.85. Various data analysis methods suggest that although the thermodynamic properties are not significantly different, working with pKa highlights the differences between molecules as well as between loaded and unloaded molecules.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Deichert, Abigail
• Dowd, Julia
• Swartz, Caitlyn

Subject

• Well-Being
• Health
• Innovation
• Project-Based Learning
• Computing

Publisher

• Worcester Polytechnic Institute

Identifier

• 121566
• E-project-042424-163921

Parola chiave

• differential scanning calorimetry
• drug delivery
• chemistry
• thermodynamics
• lipid nanoparticles
• chemical engineering

Advisor

• Grimm, Ronald
• Bailey, Christina M.

Year

• 2024

UN Sustainable Development Goals

• 3 - Good Health and Well-being

Date created

• 2024-04-24

Resource type

• Major Qualifying Project

Major

• Chemical Engineering

Source

• E-project-042424-163921

Rights statement

• In Copyright

Ultima modifica

• 2024-05-23