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- All Subjects: Biomaterials
- Creators: Harrington Bioengineering Program
- Creators: Stabenfeldt, Sarah
- Status: Published
The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.
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Lab-grown food products of animal cell origin, now becoming popularly coined as, ‘Cellular Agriculture’ is a revolutionary breakthrough technology that has the potential to penetrate the lives of every American or citizen of the world. It is important to recognize that the impetus for developing this technology is fueled by environmental concerns with climate change, rising geopolitical instability, and population growth projections, where farm-grown food has now become a growing national security issue. Notwithstanding its potential, in addition to the necessary technological innovation and economic scalability, the market success of cellular agriculture will depend greatly on regulatory oversight by multiple government agencies without which it can cause undue harm to individuals, populations, and the environment. Thus, it is critical for those appropriate United States governing bodies to ensure that the technology being developed is both safe and of an acceptable quality for human consumption and has no adverse environmental impact. As such, animal foods, derived from farms, previously regulated almost exclusively by the United States Department of Agriculture (USDA) are now being regulated under a joint formal agreement between the US Food and Drug Administration (US FDA) and the USDA if derived from the lab, i.e., lab-grown animal foods. The main reason for joint oversight between the FDA and the USDA is that the FDA has developed the in-house expertise to oversee primary cell harvesting and cell storage, as well as, cell growth and differentiation for the development of 3D-engineered tissues intended for tissue and organ replacement for the emerging field of regenerative medicine. As such, the FDA has been given the authority to oversee the ‘front end’ of lab-grown food processes which relies on the very same processes utilized in engineered human tissues to produce food-grade engineered tissues. Oversight then transitions to the USDA-FSIS (Food Safety and Inspection Service) during the harvesting stage of the cell culture process. The USDA-FSIS then oversees the further production and labeling of these products. Included in the agreement is the understanding that both bodies are responsible for communicating necessary information to each other and collaboratively developing new regulatory actions as needed. However, there currently lacks clarity on some topics regarding certain legal, ethical, and scientific issues. Lab-grown meat products require more extensive regulation than farm-grown animal food products to ensure that they are safe and nutritious for consumption. To do this, CFSAN can create new classes of lab-grown foods, such as ‘lab-grown USDA foods,’ ‘lab-grown non-USDA foods,’ ‘lab-grown extinct foods,’ ‘lab-grown human food tissues,’ and ‘medically activated lab-grown foods.’
Polymeric nanoparticles (NP) consisting of Poly Lactic-co-lactic acid - methyl polyethylene glycol (PLLA-mPEG) or Poly Lactic-co-Glycolic Acid (PLGA) are an emerging field of study for therapeutic and diagnostic applications. NPs have a variety of tunable physical characteristics like size, morphology, and surface topography. They can be loaded with therapeutic and/or diagnostic agents, either on the surface or within the core. NP size is an important characteristic as it directly impacts clearance and where the particles can travel and bind in the body. To that end, the typical target size for NPs is 30-200 nm for the majority of applications. Fabricating NPs using the typical techniques such as drop emulsion, microfluidics, or traditional nanoprecipitation can be expensive and may not yield the appropriate particle size. Therefore, a need has emerged for low-cost fabrication methods that allow customization of NP physical characteristics with high reproducibility. In this study we manufactured a low-cost (<$210), open-source syringe pump that can be used in nanoprecipitation. A design of experiments was utilized to find the relationship between the independent variables: polymer concentration (mg/mL), agitation rate of aqueous solution (rpm), and injection rate of the polymer solution (mL/min) and the dependent variables: size (nm), zeta potential, and polydispersity index (PDI). The quarter factorial design consisted of 4 experiments, each of which was manufactured in batches of three. Each sample of each batch was measured three times via dynamic light scattering. The particles were made with PLLA-mPEG dissolved in a 50% dichloromethane and 50% acetone solution. The polymer solution was dispensed into the aqueous solution containing 0.3% polyvinyl alcohol (PVA). Data suggests that none of the factors had a statistically significant effect on NP size. However, all interactions and relationships showed that there was a negative correlation between the above defined input parameters and the NP size. The NP sizes ranged from 276.144 ± 14.710 nm at the largest to 185.611 ± 15.634 nm at the smallest. In conclusion, the low-cost syringe pump nanoprecipitation method can achieve small sizes like the ones reported with drop emulsion or microfluidics. While there are trends suggesting predictable tuning of physical characteristics, significant control over the customization has not yet been achieved.