Taking Particle Tracking into Practice by Novel Software and Screening Approach: Case-Study of Oral Lipid Nanocarriers
Abstract
:1. Introduction
- Underestimation of the fraction of the nanocarrier retained in the mucus layer.
- Overestimation of the potential therapeutic effect of the nanocarrier after their oral administration.
- Difficulties in stablishing a clear relationship between the physicochemical properties of the nanocarrier and its capacity to overcome the intestinal mucus.
- Amplified in vitro–in vivo divergence.
- Misuse of test animals in the subsequent in vivo assays.
2. Materials and Methods
2.1. Polystyrene Nanoparticles
2.2. Formulation of Lipid Nanocarriers (Case-Study)
2.3. Intestinal Mucus Extraction
2.4. PT Videos Recording and Data Collection
2.5. PT Data Processing
2.6. Analysis of the Trajectories
2.6.1. Software Implementation
2.6.2. Modular Implementation
- : Although some authors use raw D in mucus (Dm), derived from MSD analysis, for the evaluation of the mobility of particles, others tend to compare Dm of the sample with a reference (Dr). More concretely, it is common to express Dm compared to D measured in a simple reference media, such as saline (Dsaline) or water (Dw). In this way, Dm/Dw is calculated and particles are considered diffusive at Dm/Dw ~ 1 [10,13]. As an alternative, Dm might also be compared to Dm of a mucodiffusive control (Dm control), obtaining Dm/Dm control value. The Dm/Dm control ratio gains relevance when different samples of intestinal mucus are used to perform a PT experiment, since it enables to correct the variability occuring due to the intra- and inter-heterogeneity of the mucus porcine samples, e.g., different viscosity [3,38,39].
- : An interesting option to determine whether the particles are able or not to diffuse across the mucus is to determine the diffusivity factor for each individual particle () [3,14,40]. As for Dm/Dr, it is possible to calculate D for the same trajectory at two different temporal scales, namely the lag time threshold and an additional shorter lag time (e.g., 1 and 0.2 s); referring to D. Free diffusing particles may display a similar diffusion pattern at long (1 s) and short (0.2 s) lag times, i.e., DF ≥ 0.9. However, those particles that interact with the mucus display an MSD vs. τ curve which slopes decrease with the time, that is DF < 0.9 [11,14,25].
- α: As commented above, while free-diffusing particles display an α ≈ 1, mucus-retained particles present α < 1. Depending on the mucins-particle strength of interaction, the transport mode of each individual particle can be sorted as follows: (i) immobile (α < 0.2); (ii) hindered (0.2 < α < 0.4); (iii) subdiffusive (0.4 < α < 0.9); and (iv) diffusive (0.9 < α) [3,11,13,37,41]. On the other hand, α > 1 is usually associated with super-diffusive particles. This may occur in case the sample is not properly sealed, which may lead to flow channels through which particles rapidly diffuse. Thus, α values > 1.1 are normally discarded from the results. Similarly, the fitting of equations Equation (1) or Equation (3) may result on an estimation of . In these cases, is considered to be equal to 0.
2.6.3. Mean and Median Paradigm in Real Samples
3. Results and Discussion
3.1. Video Recording and Data Processing Parameters
3.2. Analysis of the Trajectories
3.3. Case Study: Analysis of the Mucodiffusion of Oral Lipid Nanocarriers
3.4. PT Software Implementation
- (I).
- Select an appropriate lag time threshold.
- (II).
- Accurately screen the goodness-of-fit of the experimental data to the mathematical model.
- (III).
- Perform an individual analysis of each trajectory.
- (IV).
- Group similar trajectories into subpopulations.
- (V).
- Express results in an easy-comprehensive fashion, including D and α, as well as other parameters that can help to understand the interaction of the nanocarrier with the intestinal mucus.
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Screening Approach | α | Dm/Dw | NPs | NPs (%) |
---|---|---|---|---|
R2 ≥ 0.0 | 0.37 | 0.064 | 6965 | 100.0 |
R2 ≥ 0.1 | 0.47 | 0.083 | 5259 | 75.5 |
R2 ≥ 0.2 | 0.52 | 0.094 | 4532 | 65.1 |
R2 ≥ 0.3 | 0.57 | 0.108 | 3883 | 55.8 |
R2 ≥ 0.4 | 0.62 | 0.126 | 3236 | 46.5 |
R2 ≥ 0.5 | 0.66 | 0.148 | 2646 | 38.0 |
R2 ≥ 0.6 | 0.71 | 0.181 | 2090 | 30.0 |
R2 ≥ 0.7 | 0.76 | 0.225 | 1591 | 22.8 |
R2 ≥ 0.8 | 0.83 | 0.299 | 1102 | 15.8 |
R2 ≥ 0.9 | 0.92 | 0.443 | 627 | 9.0 |
R2 + RSS | 0.32 | 0.064 | 6681 | 95.9 |
Screening Approach | α | Dm/Dw | NPs | NPs (%) |
---|---|---|---|---|
R2 ≥ 0.0 | 0.22 | 0.009 | 1167 | 100.0 |
R2 ≥ 0.1 | 0.35 | 0.014 | 741 | 63.5 |
R2 ≥ 0.2 | 0.41 | 0.017 | 605 | 51.8 |
R2 ≥ 0.3 | 0.46 | 0.020 | 517 | 44.3 |
R2 ≥ 0.4 | 0.50 | 0.023 | 449 | 38.5 |
R2 ≥ 0.5 | 0.53 | 0.025 | 396 | 33.9 |
R2 ≥ 0.6 | 0.56 | 0.029 | 342 | 29.3 |
R2 ≥ 0.7 | 0.59 | 0.035 | 282 | 24.2 |
R2 ≥ 0.8 | 0.66 | 0.044 | 211 | 18.1 |
R2 ≥ 0.9 | 0.78 | 0.072 | 122 | 10.5 |
R2 + RSS | 0.22 | 0.009 | 1113 | 95.4 |
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Plaza-Oliver, M.; Cano, E.L.; Arroyo-Jimenez, M.M.; Gámez, M.; Lozano-López, M.V.; Santander-Ortega, M.J. Taking Particle Tracking into Practice by Novel Software and Screening Approach: Case-Study of Oral Lipid Nanocarriers. Pharmaceutics 2021, 13, 370. https://doi.org/10.3390/pharmaceutics13030370
Plaza-Oliver M, Cano EL, Arroyo-Jimenez MM, Gámez M, Lozano-López MV, Santander-Ortega MJ. Taking Particle Tracking into Practice by Novel Software and Screening Approach: Case-Study of Oral Lipid Nanocarriers. Pharmaceutics. 2021; 13(3):370. https://doi.org/10.3390/pharmaceutics13030370
Chicago/Turabian StylePlaza-Oliver, María, Emilio L. Cano, María Mar Arroyo-Jimenez, Matías Gámez, María Victoria Lozano-López, and Manuel J. Santander-Ortega. 2021. "Taking Particle Tracking into Practice by Novel Software and Screening Approach: Case-Study of Oral Lipid Nanocarriers" Pharmaceutics 13, no. 3: 370. https://doi.org/10.3390/pharmaceutics13030370
APA StylePlaza-Oliver, M., Cano, E. L., Arroyo-Jimenez, M. M., Gámez, M., Lozano-López, M. V., & Santander-Ortega, M. J. (2021). Taking Particle Tracking into Practice by Novel Software and Screening Approach: Case-Study of Oral Lipid Nanocarriers. Pharmaceutics, 13(3), 370. https://doi.org/10.3390/pharmaceutics13030370