Detlef Beckers

The full version of this counterfeiting feature can be read in the July issue of our digital magazine: http://www.pharmtech.com/ptedigital0710

X-ray powder diffraction (XRPD) is a versatile, non-destructive technique that reveals detailed information about the chemical composition and crystallographic structure of pharmaceuticals. As such, it can clearly distinguish between tablets on the basis of type and amount of API (

), crystal structure of the API and/or composition of excipients. Importantly, because the technique uses X-rays, measurements can be made with the tablets in their original and intact packaging (

The recent introduction of the world's first 3D detector for use in an XRPD system (by PANalytical) brings further insight. Now, computed tomography (CT) images of the tablet under test can be generated in the same instrument as the diffraction data is collected. This allows the non-invasive analysis of size, shape and inner microstructure of tablets giving additional information about the production processes involved (

Although XRPD is already a standard tool for analysing illicit drugs and is used extensively in criminal investigations, it is not yet embedded in the pharmaceutical industry as a standard analytical technique for detecting counterfeit medicines. However, there are many inherent qualities of the method for this application. XRPD allows a fast analysis of the complete composition of the tablet, including the excipient mixture, polymorphic form and crystallinity of the API. The technique can also non-destructively analyse intact pharmaceutical tablets, without requiring removal from the original blister packaging. This allows a batch of samples to be released for sale if appropriate, or to be retained in the original form for use as an exhibit in a court of law. Furthermore, tablets can be used in subsequent analysis by other methods.  

XRPD offers several advantages over other tablet analysis techniques. For instance, traditional wet chemistry methods, such as gas chromatography–mass spectrometry, are time consuming because of the need for sample preparation, and also destroy the physical properties of the tablets. More advanced analytical techniques also have disadvantages. Infrared techniques often have problems with hydrate mixtures because of moisture content and while NIR is often promoted as being easy to use (particularly in the case of portable instruments), a proper evaluation of the resulting spectra requires advanced spectroscopy knowledge. This is particularly the case where NIR tests are conducted through packaging. In this case, so called 'multiplicative scattering' from the packaging may lead to false positives or false negatives. Additionally, an appropriate test set for NIR needs to be built up from dozens of samples and validated on the instrument. These samples also need to be monitored for small changes, which can occur due to variations in humidity, temperature, or differences in particle size, and may impact results.  

As with NIR, fourier transform spectroscopy Raman also offers the benefit of being available as a portable instrument — and in my opinion is perhaps the most appropriate of this group of techniques. However, it also suffers from problems with interference and issues with high moisture content samples.  

XRPD can easily be transferred from one instrument to another without the need for complex calibrations. It also provides rapid unequivocal analysis where both organic and inorganic materials, and/or components with similar molecular weights, polarities, boiling points and structures, are present.  

XRPD is widely used in the pharmaceutical industry; it has moved from being a technology that simply enables pharmaceutical companies to 'tick a box' (by providing the crystal pattern of a drug needed for patent and regulatory approval) to one that meets valuable applications across discovery, development and production control. New-generation XRD instruments that include ultra-fast detectors, and pre-aligned stages and optical components for fast method set up and switching, have made the technique accessible to all. The development of control and analysis software that uses a familiar user interface and supports standard operating procedures has helped to 'demystify' the technique too. Despite its advantages, however, XRPD is not yet widely used for detecting counterfeit medicines, but the pharma industry has a history of broadening the use of any technique that is already established in the laboratory — an XRPD is certainly an available tool in all pharma companies. Additionally, a recent trial in Germany (data not yet published) has already been investigating the use of XRD for the rapid analysis of counterfeit medicines 

Many governments and institutions are constantly reviewing new anti-counterfeiting methods and technologies. The European Commission launched a public consultation in 2008 in preparation for a legal proposal to combat counterfeit medicines. Other initiatives are in place around the world, including a major FDA task force that is exploring the use of modern technologies and other measures that will make it more difficult for counterfeit drugs to become integrated into the supply chain. In addition, the WHO established the first global initiative against counterfeit drugs — the International Medical Products Anti-Counterfeiting Taskforce (IMPACT) — in February 2006. IMPACT aims to build coordinated networks to halt the production, trading and selling of fake medicines around the globe. The taskforce comprises a wide variety of international bodies, including non-governmental organisations, enforcement agencies, pharmaceutical manufacturers' associations and drug and regulatory authorities. IMPACT's vision is that all counterfeit drugs will be eradicated from the supply chain by 2015. To accomplish this goal, they are focused on five key areas, including assessing technologies that prevent, deter or detect counterfeit medicinal products.  

Industry practice often runs ahead of 'official' recommendations and this may be the case with XRD in counterfeit analysis. However, with so much work going on, I believe it is simply a matter of time before firm technology recommendations emerge. 

Product Manager Scientific XRPD at PANalytical. 

Articles

X-ray powder diffraction (XRPD) is a versatile, non-destructive technique that reveals detailed information about pharmaceuticals.

The Power Of X-Ray Analysis

Some of the procedures used to process pharmaceutical solids, such as milling, spray drying or lyophilization, can disrupt the crystalline structure and lead to the formation of amorphous regions. As the physicochemical properties of pharmaceuticals are influenced by the form of their solid state, such phase transformations can profoundly impact both processing behaviour

  and the bioavailability of the active ingredient in the finished product (Figure 1).

  Changes in dissolution rate and chemical stability, for example, influence bioavailability, while changes in compressability, compactability and hygroscopicity influence processability. 

The influence of phase transformations on product performance is by no means limited to APIs; changes in the excipients in a dosage form during processing also have to be considered. 

Figure 1: The amorphous state: properties and significance. 

To establish the integrity of the finished product it is important, therefore, to determine the existence and amount of amorphous material within a crystalline matrix. A number of different methods are available, but they are best divided into four groups: gravimetric, calorimetric, spectroscopic and density methods.  

Gravimetric methods are based on differences in the absorption of water between the crystalline and amorphous states

. Although such methods can determine the amorphous content quite accurately, they are time-consuming and can destroy the sample (e.g., dynamic vapour sorption). Consequently, they are unsuitable for on-line measurements. The same is true of calorimetric methods

,  which measure the enthalpy changes during crystallization. Density measurements, although nondestructive, tend to be time-consuming and not very accurate.  

This leaves spectroscopic methods, where differences in the spectra generated by amorphous and crystalline materials are evaluated. Fourier transform Raman spectroscopy (FT-RS)

  and Fourier transform Raman near infrared spectroscopy (FT-NIRS)

,  are particularly fast, accurate and nondestructive and, therefore, well-suited to on-line analysis. 

X-ray powder diffraction (XRPD) is another potentially useful nondestructive spectroscopic method. Previously, it has been unable to compete with FT-RS and FT-NIRS in terms of measurement time and accuracy. Detection limits (DLs) cited in the literature have shown considerable variation. Recent refinements in hardware and software, however, have significantly increased the technique's speed, accuracy and versatility.  

 This is a versatile, nondestructive technique. By measuring the angular positions and intensities of the diffracted radiation a wealth of structural, physical and chemical information can be obtained about the material investigated. 

 This is a nondestructive, spectroscopic method utilizing the NIR region of the electromagnetic spectrum (wavelength from 800–2500 nm). This spectral region is particularly suitable for the excitation of the vibration of functional groups in organic compounds, such as OH-, NH- and CH. 

Alpha-lactose monohydrate was used as a model substance. In the pharmaceutical industry, this material is widely employed as a filler and diluent in tablets and capsules, as a carrier substance in dry powder inhalers and as a lyoprotectant during the lyophilization of proteins. 

To ensure complete recrystallization of any amorphous regions present, samples of 100% crystalline alpha-lactose monohydrate were stored at a relative humidity of 65% at 30 °C for 1 week before use. Samples of amorphous lactose were prepared by lyophilization of a saturated lactose solution. 

 Spectra were obtained of the pure crystalline and amorphous form and the binary mixtures at intervals of 10% (10–90%) and 1% (1–9% and 90–100%). 

XRPD patterns were obtained using an X'Pert PRO MPD system (PANalytical B.V., The Netherlands) with nickel-filtered copper Kα radiation (40 kV, 40 mA), Bragg-Brentano focusing optics and the X'Celerator detector (PANalytical B.V.) Measurement conditions were as follows:  

Mixture 0–100% crystallinity: 0.008° 2θ step size; 3 min/measurement; scan range 4–40° 2θ. 

Mixture 1–9% amorphous content: 0.016° 2θ step size; 2 min/measurement, scan range 7–45° 2θ.

Mixture 0–10% crystallinity: 0.008° 2θ step size, 6 min/measurement, scan range 12–13° 2θ. 

Data were evaluated using PANalytical's X'Pert HighScore software for phase identification. For low amorphous content samples (Figure 2), the relative intensity between reflections and background (I

) was used for the evaluation. All scans were also evaluated by partial least squares regression (PLSR) using either baseline data or the baseline and reflections in the region of 10–35° 2θ using Unscrambler software (Camo ASA, Norway). For low crystalline content samples data were evaluated using the peak area of the 12.4° 2θ reflection and by PLSR of the recorded scan. 

Figure 2: XRPD patterns of crystalline lactose with varying amounts of amorphous lactose. 

NIRS data were acquired using a Bruker Optics Vector 22/N FT NIR spectrometer (Bruker Optik GmbH, Germany)

with fibre optics. The mean spectrum of 32 scans for each sample over a wave number region of 3800–12000 cm

  was recorded (taking 30 s for each measurement). The regression model for the samples was calculated by PLSR after data preprocessing by multiplicative scatter correction and first derivative. Low amorphous content samples were evaluated over wavelengths of 5342–4865 cm

,  and low crystalline samples were evaluated over wavelengths of 5992–5693 cm

For an increasing crystalline content (0–100%) at 10% intervals, calibration curves for both methods showed excellent linearity with a correlation coefficient of better than 0.99. 

Figure 3: Results of the cross validation for samples with low amorphous content (1â9%). (a) NIRS data after PLS regression;  (b) XRPD data with classical evaluation of Inet / Iobs; and (c) XRPD data after PLS regression on the background of the XRPD scans. 

Results for low amorphous content (1–9% amorphous) samples are shown in Figure 3 and Table 1. The classical linear regression gave a good correlation of 0.994 for both NIRS and XRPD. NIRS gave a root mean square error of prediction (RMSEP) value of 0.36 and a limit of detection (LOD) of 0.22%. With the standard I

 method of analysis for XRPD the RMSEP was 0.52% and the DL 0.99%. With a multivariant evaluation (PLSR method) of the whole XRPD diffraction pattern in the 10–35° 2θ range, the RMSEP could be reduced to 0.38% and the DL to 0.63. Where the background only was used for the multivariant evaluation, the model simplified to two principal components and RMSEP and LOD could be further improved to 0.33 and 0.30%, respectively. 

Table 1:  Comparison of reliability parameters for NIRS and XRPD measurements on the samples with low amorphous content. 

Results for low crystalline content (0–10%) samples are shown in Figure 4 and Table 2. In contrast to the results for low amorphous content, those for NIRS were not as impressive as those for XRPD. With NIRS, linear regression had a correlation of 0.990, a RMSEP value of 0.540 and a DL of 0.82%. Using the peak area of the 12.4° 2θ reflection, XRPD had a correlation of 0.999, a RMSEP value of 0.30 and a DL of 0. 50%. Further evaluation using PLSR reduced the RMSEP to 0.14 and the DL of crystalline material to 0.30%.  

Figure 4: Results of the cross validation for samples with low crystalline content (0â10%). (a) NIRS data after PLS regression; (b) XRPD data using the peak area under the reflection at 12.4Â° 2Theta; and (c) XRPD data after PLS regression using the scan between 12Â° and 13Â° 2Theta. 

Both XRPD and NIRS proved accurate and precise, with DLs below 1%.  

Table 2: Comparison of reliability parameters for NIRS and XRPD measurements on the samples with low crystalline content. 

For samples with a low amorphous content (1–9%), XRPD gave data of a similar quality to NIRS. XRPD showed a slightly smaller method error (RMSEP), especially when the background information was used, but it also showed a higher variation within the data sets. 

For samples with a low crystalline content, XRPD was more accurate and precise, and had lower DLs than NIRS. This can be explained by the lower sensitivity of XRPD to the presence of water. XRPD also has the advantage of offering a simple means of determining whether or not a sample has recrystallized and, if it has, which phase is involved. Taking all this into account, XRPD appears both qualitatively and quantitatively superior to NIR for monitoring crystallization and recrystallization processes. 

XRPD and NIRS are powerful analytical techniques capable of correlating the physicochemical structure of pharmaceutical solids to observed stability and drug release profiles. Both techniques are characterized by high precision and accuracy, low DLs, nondestructive analysis, and rapid production of results. Despite slight differences in accuracy between the analysis of partially amorphous and partially crystalline samples of lactose, both methods were considered sufficiently accurate for the purposes of process control. With the use of PLSR for data analysis, XRPD appears both qualitatively and quantitatively superior to NIRS for samples with a low crystalline content and is, therefore, best suited to the monitoring of crystallization and recrystallization processes.

is market segment manager pharmaceuticals, food and life science at PANalytical B.V. He has responsibilities for applications and business development and the co-ordination of the pharmaceutical, food and life sciences market activities within the company. 

gained her PhD at the University of Bonn (Germany) in 2004. She now works at research-based pharmaceutical company Grünenthal GmbH in Aachen (Germany). 

is professor of pharmaceutical technology at the University of Bonn. Following studies, PhD and habilitation at Marburg University (Germany), he was appointed as professor of pharmaceutical technology — first at Braunschweig University (Germany) and now in Bonn.  

4. A. Saleki-Gerhardt, C. Ahlneck and G. Zografi, 

The crystalline structure of pharmaceutical solids can sometimes be altered during processing. X-ray powder diffraction and near infrared spectroscopy can be used to determine the amorphous and crystalline content of a model substance. The two techniques' precision, accuracy, detection limit and the speed of analysis are compared.