Optimizing the Formulation of Poorly Water-Soluble Drugs
2.2 Solid-State Characterization
2.2.3 X-Ray Diffraction
XRD is the measurement of the intensity of X-rays scattered by electrons bound to atoms and the corresponding phase shifts that occur as a result of the position of the atom. For a detailed explanation of XRD theory, the reader is referred to Dinnebier and Billinge ( 2008 ) . XRD is typically a nondestructive test (i.e., the analyzed mate-rial can be recovered) and, as will be discussed, is highly useful for determining
differences in crystal structure (i.e., polymorphs), drug–excipient interactions, and identifying amorphous systems.
Prior to analysis, it is necessary to calibrate and optimize the device to be used for testing. This can be done by use of various reference standards such as those offered by the National Institute of Standards and Technology (NIST). Standard Reference Material 674b consists of four oxide powders to be used as internal stan-dards or calibrators for an XRD unit: ZnO, TiO 2 , Cr 2 O 3 , and CeO 2 . Alternatively, standards of materials with well-understood diffraction patterns can be used such as alumina, mica, or silicon pellets.
2.2.3.1 Parameter Selection
During sample analysis, the operator will be required to input a number of param-eters for each scan, including the scan range in degrees on a 2 Q scale, the step size (degrees per step), and the count time for each step (often referred to as dwell time).
Assigning the proper parameters is crucial to ensure that adequate peak shape is obtained while minimizing processing time. For the fi rst scan of a new API, it is necessary to analyze a very broad range, such as 5–120° on the 2 Q scale. This will allow for identifi cation of the characteristic crystalline peaks and subsequent analyses should be shortened to include only the footprint region.
Twenty data points per peak are desired to ensure adequate peak shape. In order to obtain this value, the researcher must alter the step size of each scan. For highly crystalline materials, a step size of 0.02° is adequate to meet this requirement. For materials exhibiting broad peaks, this value can be increased to shorten the run time while still maintaining the 20 data points per peak. In order to optimize the step size, the powder should be analyzed over a very narrow range, such as 2–5° 2 Q , in a region containing a characteristic crystalline peak(s) over a range of step sizes.
Cameron and Armstrong analyzed quartz from 67 to 69° 2 Q and varied the step size from 0.1 to 0.01° 2 Q in order to fi nd the optimum step. Identifi cation of the step size in which the diffractogram decays to baseline following the peak was selected as optimum (Cameron and Armstrong 1988 ) . If upon return to baseline the inception of a new peak is immediate, a shorter step size should be selected to increase resolution.
Oftentimes, the step size and dwell time are considered together as a scan rate.
For example, analysis of tenofovir disoproxil fumarate (TDF) was reported as being conducted from 4 to 40° at a rate of 4°/min (Lee et al. 2010 ) . Prevalent rates in the literature are between 0.5 and 4°/min.
The fi nal parameter that must be determined is the dwell time. While a longer dwell time will increase the signal-to-noise ratio and improve counting statistics, it will also drastically increase the duration of a run. This is especially true for methods utilizing small step sizes. Therefore, in order to ensure timely analysis, the shortest dwell time, which provides a strong signal of all characteristic peaks without signifi cant interference from the baseline, should be selected. This parameter will be most infl uential for systems lacking strong crystallinity, such
as pharmaceutical systems containing a polymer, in which case longer dwell times will aid peak structure. Dwell times of 1–5 s can be employed, with times of 1–3 s being most prevalent in practice.
2.2.3.2 Polymorph Screening
As mentioned earlier, XRD analysis reveals phase shifts that occur as a result of atomic position within a material. Therefore, alterations in crystal structure that arise as a physical result of polymorphism can often be detected by XRD. This can be observed as a shift in a major characteristic peak, or the appearance or disappear-ance of peaks in the diffraction pattern. XRD analysis of the three polymorphs of TDF reveals that the diffraction patterns for forms B and I are similar, making their defi nite distinction diffi cult. However, form A contains multiple peaks not present in the diffraction patterns of the other polymorphs as well as the absence of one characteristic peak near 30°, making its identifi cation absolute (Fig. 2.6 ). Kirk et al . demonstrated that three of four generated lactose polymorphs crystallize with mon-oclinic unit cells by XRD employing a range of 5–40° and a step size of 0.014767°
and a 2 second dwell time (Kirk and Blatchford 2007 ) . In another work, a variable
Fig. 2.6 XRD patterns of three polymorphic forms of TDF. Forms B and I are similar while Form A is unique. Reproduced with permission from American Chemical Society
temperature cell was utilized and the XRD pattern of mebendazole was analyzed as a function of temperature to assess polymorphic transformations that occur due to temperature variation (de Villiers et al. 2005 ) . Indeed, it was seen that at tempera-tures above 180°C a transformation to the more thermodynamically stable poly-morph occurred.
Olanzapine can crystallize into 25 different crystalline structures of which seven are active pharmaceutically. Identifi cation and quantifi cation of each polymorph are necessary throughout the development cycle of a formulation containing such a compound to ensure that the fi nal product is of acceptable quality. Tiwari et al . examined two polymorphs of the compound by XRD. Prior to analysis, the unit was calibrated with a silicon pellet. The scan was then optimized by varying the dwell time and step size such that the maximum number of identifi able peaks were obtained. As can be seen in Table 2.2 , a dwell time of 5 s with a step size of 0.05°
produced the greatest number of identifi able peaks in the shortest amount of time.
In order to accurately quantify the amount of a given polymorph present in a mix-ture, each form must be analyzed as a pure sample. The highest-intensity peak is then selected and the intensity of the pure polymorph is set to 100%. The ratio of intensities for the selected peak in the mixture compared to the pure polymorph provides the percent present in the mixture. This, however, cannot be employed in the case of olanzapine, as the highest-intensity peaks overlap for multiple forms (Tiwari et al. 2007 ) . However, screening of mannitol demonstrated that even with similar polymorphic forms coupling sample rotation with particle-size reduction increases the ability to differentiate the forms present. In the case of mannitol, it allowed identifi cation of the individual components down to approximately the 1%
level (Campbell Roberts et al., 2002 ) .
2.2.3.3 Excipient Interactions
Changes in the XRD pattern may occur as a result of drug–excipient interactions.
Such alterations include the conversion to a unique polymorphic form, or amor-phous to crystalline transitions. For example, a sample of pure b -form carbam-azepine displays a characteristic peak at 13°, while the a -form displays this peak as well as an additional peak at 8.8° 2 Q . In a study of physical mixtures of pure b -form
Table 2.2 Optimization of scan parameters for XRD analysis. Reproduced with permission from Elsevier
Combination Step time (s) Step size (º)
Scan rate (º 2 q /min)
Recording time (min)
No. of identifi able peaks
A 0.5 0.025 3 12.33 1
B 0.5 0.0125 1.5 24.67 1
C 1 0.0125 0.75 49.33 2
D 5 0.05 0.6 61.66 4
E 5 0.0125 0.15 246.66 4
carbamazepine in combination with various tableting excipients, it was seen that the characteristic peak at 13° was present in all samples. However, following storage at 55°C for 3 weeks, a combination of carbamazepine and stearic acid displayed the additional peak at 8.8°, indicating a conversion to the a -form. This was attributed to partial solubilization of carbamazepine in steric acid at elevated temperatures fol-lowed by recrystallization upon cooling (Joshi et al. 2002 ) . Indeed, stability studies, to be discussed later, often rely on alterations in XRD patterns as an indication of formulation stability.
An amorphous material will yield an XRD pattern termed a “halo” which is a gradual rise and fall of the baseline with no distinct peaks. As many processing techniques focus on rendering the drug amorphous, XRD can be utilized to identify whether or not a drug or formulation is amorphous. This can be complicated when polymeric systems are used, as most polymers used in pharmaceutical applications are amorphous in nature. At low drug loadings, the amorphous signal from the poly-mer may overshadow or mask the crystalline pattern of the drug. As such, physical mixtures identical in drug:polymer ratio to that used in processing must be analyzed to ensure that the pattern is validated. Tobyn et al . analyzed an experimental com-pound as a solid dispersion with PVP at various drug-to-polymer ratios. As can be seen in Fig. 2.7 , the bulk drug product is highly crystalline with many characteristic peaks (parameters: 2–60° 2 Q , 2°/min scan rate, calibration with mica and alumina reference standards). At a 50:50 ratio of drug-to-PVP the formulation produced an amorphous halo, indicating amorphization of the drug. This was confi rmed using a
Fig. 2.7 XRD patterns of experimental compound BMS-488043 bulk material, physical blend with PVP and solid dispersions thereof. Reproduced with permission from John Wiley and Sons
dry blend of the materials at the same ratio. While a decrease in peak intensity can be observed for the 50:50 physical mixture, the peaks are still present, indicating that processing indeed rendered the drug amorphous. Additionally, it can be seen that at higher drug loading levels the process did not generate or stabilize the drug in the amorphous form (Tobyn et al. 2009 ) .