Dr Michael Caves, Business Development Manager, Malvern Instruments, gives an insight on how particle size measurements, using a Mastersizer 3000, and rheological measurements, using a Malvern Kinexus rotational rheometer, can be used to fully characterise pharma formulations
To Successfully develop pharmaceutical formulations it is essential to understand particle size and microstructure parameters that have a major impact on the efficacy and stability of a formulation.
Hyaluronic acid (HA) is a naturally occurring polysaccharide frequently used as a functional ingredient in many topical and subcutaneous anti-ageing treatments such as dermal fillers, which exploit the polymer’s unique viscoelastic properties for effective soft tissue augmentation. When administered subcutaneously, HA builds an elastic network within wrinkles and rhytides to give the skin a plumper and fuller look. Naturally occurring HA has a half-life of less than three days so increasing the durability of the polymer is essential to developing products with greater clinical persistence and an acceptable shelf life. Increasing both the molecular weight (MW) and degree of cross-linking of the polymer is a proven strategy for improving mechanical strength and extending degradation times. However, these characteristics also impact other properties of the HA such as viscosity and viscoelasticity. Clearly, comprehensive characterisation of these formulations is essential to an understanding of their efficacy, applicability and stability.
Results and discussion
Oscillation testing
There are many factors that affect the viscoelastic properties of HA dermal fillers including HA concentration, molecular weight and crosslinking degree. By changing these characteristics the viscoelastic properties, especially the elastic modulus G’, can be engineered for a specific application. Gels with high G’ give higher resistance to deformation and should be more effective as fillers but could be harder to inject and may give more pain. Therefore, strong gels with high G’ may be more suitable to use for deeper or more serious winkles. On the other hand, weaker gels with low G’ may be better for fine or light wrinkles found in lips or tear troughs, which are more sensitive, because they would give less pain when injected. The lower modulus may also better match the properties of the local tissue. Of the three HA samples tested it can be said that sample A is the weakest and softest gel and sample C is the stiffest and strongest gel based on results presented in Figures 1 and 2.
Figure 1. Amplitude sweep data showing elastic modulus (G’) as a function of shear strain
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Figure 2. Frequency sweep data showing elastic modulus (G’) and phase angle (d) as a function of frequency
Steady shear testing and yield stress determination
The results of the steady state shear measurement – shear viscosity measured as a function of shear rate are shown in Figure 3. The viscosity decreases significantly with increasing shear rate indicating that the materials are highly shear thinning. Also, the structure of the fillers is so strong that at a low shear rate the viscosity is very high and continues to rise with decreasing shear rate suggesting yield stress or solid like behaviour at rest. This corresponds with observations from oscillation testing which showed a highly elastic gel-like structure. A yield stress indicates that the material will behave like a solid below critical stress but will flow like a liquid above this critical stress. The magnitude of the yield stress should be related to the structural strength and hence degree of cross-linking and concentration of the gel particles, which should be reflected in G’.
Figure 3. Flow curves showing steady state shear viscosity (h) as a function of shear rate
Yield stress can be determined using a number of different tests, however, a stress ramp is one of the quickest and easiest ways, where the instantaneous viscosity (not steady state) is measured continuously with increasing shear stress. Stress ramp data for the three HA samples are shown in Figure 4. The peak in viscosity represents the point of yield and the stress value at which this occurs is the yield stress. Sample A has the lowest yield stress (42Pa) and Sample C the highest (55Pa) with Sample B slightly lower than C (53Pa). This is the same order observed in oscillation testing with Sample C the strongest and Sample A the weakest of the three gels. As these gels tend to exists as a collection of covalently cross-linked gel particles (as opposed to a continuous gel network) then the yield stress is associated with the stress required to ‘un-jam’ the particles and allow them to move past one another.
Figure 4. Stress ramp data showing instantaneous shear viscosity (h) as a function of shear stress
Tack testing
The normal force profiles as a function of time as the plate-plate gap is increased, which is shown in Figure 5. The normal force value is negative because the sample is pulling down on the upper plate due to adhesive/ cohesive forces and decays towards zero at failure; the residual force at long times is due to the weight of the retained samples on the upper plate. The peak normal force for samples A, B, and C are 0.35 N, 0.46 N, and 0.54N respectively, which again correlate with the order of G’ and yield stress measurements for the three samples. Hence, Sample C has the highest degree of tack or cohesivity and Sample A the least.
Figure 5. Tack tests data showing normal force profiles as a function of time during a pull-away test
Particle size
Particle size of the gel particles needs to be controlled in order to reduce the extrusion force and associated side effects like pain and bleeding when gels are injected. Therefore, the gels need to be engineered to pass through needles at the appropriate rate with the desired extrusion force. In Figure 6, particle size distribution of gels is shown as a cumulative volume percent. The median size (Dv50) of samples A, B, and C is 480µm, 425µm, and 203µm. Strong gels with high G’ and yield stress values, need to be sized to small particles to be easily injected through the needles. Sample C has the smallest particle size because it has the highest G’ value in the samples. On the other hand, the sample A has the largest particle size as it is the weakest gels in the samples (it can be easily passed through the needles). The resulting size will also be related to the extent of cross-linking and molecular weight since highly cross-linked polymers associated with higher values of G’ will be denser and more compact.
Figure 6. Particle size distribution (Cumulative volume) for gel particles in dermal fillers
Conclusion
Rheological properties and particle size of three commercial HA- based dermal fillers were characterised and compared. The elastic modulus G’ was determined from oscillation testing and those values correlated with gel stiffness and strength (e.g. weak gels or strong gels). Steady state shear measurements were made to check the viscosity dependence on the shear rate and stress ramp tests were performed to determine the force required to break down the gel structure i.e. the yield stress. The tackiness of the fillers was determined by measuring normal force profile when the plate-plate gap was increasing and correlated with oscillation, and yield stress data. Furthermore, the particle size of gels was measured because the size affects extrusion, and this was found to correlate with rheological data also.
In conclusion, the rheological properties and particle size of HA based dermal fillers are essential parameters to determine the performance (e.g. easy delivery, extrusion force, injection, resistance to deformation, pain reduction) and application (e.g. fine or deep wrinkle, facial contouring) of these products.
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