Assessment of a novel silicone hydrogel daily disposable lens among physically active subjects

Reindel, William; Steffen, Robert; Mosehauer, Gary; Schäfer, Jeffery; Rah, Marjorie J.

doi:10.1016/j.clae.2022.101611

Cited by 2 publications

(2 citation statements)

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“…Statistical tests, such as t-tests [78] or chi-square tests [79], are used to test hypotheses and determine whether observed differences between groups are statistically significant.…”

Section: Statistical Data Analysismentioning

confidence: 99%

Exploring the Potential of Artificial Intelligence for Hydrogel Development—A Short Review

Negut,

Bita

2023

Gels

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AI and ML have emerged as transformative tools in various scientific domains, including hydrogel design. This work explores the integration of AI and ML techniques in the realm of hydrogel development, highlighting their significance in enhancing the design, characterisation, and optimisation of hydrogels for diverse applications. We introduced the concept of AI train hydrogel design, underscoring its potential to decode intricate relationships between hydrogel compositions, structures, and properties from complex data sets. In this work, we outlined classical physical and chemical techniques in hydrogel design, setting the stage for AI/ML advancements. These methods provide a foundational understanding for the subsequent AI-driven innovations. Numerical and analytical methods empowered by AI/ML were also included. These computational tools enable predictive simulations of hydrogel behaviour under varying conditions, aiding in property customisation. We also emphasised AI’s impact, elucidating its role in rapid material discovery, precise property predictions, and optimal design. ML techniques like neural networks and support vector machines that expedite pattern recognition and predictive modelling using vast datasets, advancing hydrogel formulation discovery are also presented. AI and ML’s have a transformative influence on hydrogel design. AI and ML have revolutionised hydrogel design by expediting material discovery, optimising properties, reducing costs, and enabling precise customisation. These technologies have the potential to address pressing healthcare and biomedical challenges, offering innovative solutions for drug delivery, tissue engineering, wound healing, and more. By harmonising computational insights with classical techniques, researchers can unlock unprecedented hydrogel potentials, tailoring solutions for diverse applications.

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“…Statistical tests, such as t-tests [78] or chi-square tests [79], are used to test hypotheses and determine whether observed differences between groups are statistically significant.…”

Section: Statistical Data Analysismentioning

confidence: 99%

Exploring the Potential of Artificial Intelligence for Hydrogel Development—A Short Review

Negut,

Bita

2023

Gels

View full text Add to dashboard Cite

show abstract

“…Its packaging solution includes moisturizing components (poloxamine and poloxamer) and osmoprotectants (erythritol and glycerin). Reindel et al 11 conducted in-vivo performance evaluations of Kalifilcon A CLs, focusing on habitual planned-replacement SiHy CL wearers involved in regular physical activity (PA) and those who were not (NPA). The study aimed to explore the impact of physical exercise on both body hydration status and eye blink rate, factors that could lead to hyperosmotic tears.…”

Section: Introductionmentioning

confidence: 99%

In-vitro dehydration kinetics coefficient of Kalifilcon A and other contact lens materials

Ponzini,

Maspero,

Galli

et al. 2024

Sci Rep

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In contact lens (CL) wear, dehydration needs to be tailored to avoid dryness and related symptoms. In this view, this work aims to assess and compare the in-vitro dehydration kinetics of five CL materials, including the newly developed Kalifilcon A CL. At 36 °C and 60% relative humidity, the in-vitro dehydration kinetics of the different CLs were compared using a gravimetric method. CLs were analyzed either after a rinse of a few seconds in preservative-free saline solution or after a 24-h incubation in the same solution. A model based on the Fick diffusion equation was employed to deduce a water kinetics coefficient, providing insights into water diffusion within the polymeric matrix. The study reveals that all materials exhibit a non-Fickian dehydration behavior, with significant differences in dehydration kinetics coefficients and dehydration rate slopes. Etafilcon A and Omafilcon A, both hydrogel CLs, exhibit a similar behavior, different compared to the pattern shown by Senofilcon A and Delefilcon A, silicone-hydrogel CLs. Notably, Kalifilcon A, despite being a silicone-hydrogel, displays a hydration behavior reminiscent of hydrogel CLs.

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Assessment of a novel silicone hydrogel daily disposable lens among physically active subjects

Cited by 2 publications

References 0 publications

Exploring the Potential of Artificial Intelligence for Hydrogel Development—A Short Review

Exploring the Potential of Artificial Intelligence for Hydrogel Development—A Short Review

In-vitro dehydration kinetics coefficient of Kalifilcon A and other contact lens materials

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