Pharmaceutical materials science and disorder: The next steps

Posted: 16 February 2011 | | No comments yet

Over the past decade, the pursuit of materials science within the pharmaceutical industry has largely focused on determining the crystal structure of our drug molecules and ensuring that the most stable polymorphic form is carried forward and maintained through development, as the manufacturing issues and regulatory impact arising from the appearance of an unexpected solid form during development are well documented. Recent advances in this field have begun to make progress towards the prediction of crystal structures for small organic molecules ab initio, a feat considered at the edges of possibility barely a decade ago.

Over the past decade, the pursuit of materials science within the pharmaceutical industry has largely focused on determining the crystal structure of our drug molecules and ensuring that the most stable polymorphic form is carried forward and maintained through development, as the manufacturing issues and regulatory impact arising from the appearance of an unexpected solid form during development are well documented. Recent advances in this field have begun to make progress towards the prediction of crystal structures for small organic molecules ab initio, a feat considered at the edges of possibility barely a decade ago.

Over the past decade, the pursuit of materials science within the pharmaceutical industry has largely focused on determining the crystal structure of our drug molecules and ensuring that the most stable polymorphic form is carried forward and maintained through development, as the manufacturing issues and regulatory impact arising from the appearance of an unexpected solid form during development are well documented1. Recent advances in this field have begun to make progress towards the prediction of crystal structures for small organic molecules ab initio2, a feat considered at the edges of possibility barely a decade ago3.

Whilst the study of the dynamics and behaviour of amorphous systems in the pharmaceutical industry, common methods of which are briefly outlined below, has emerged over the course of the last 15 years to guide pharmaceutical scientists through both the benefits and pitfalls of amorphous systems4-6, we have often found ourselves urged down the path towards quantification of our disordered materials in order to meet regulatory expectation and agree with established scientific consensus. Whilst models of the glassy state exist to mathematically represent how the molecules in these systems relax, and hence how the physical properties observed across the glass transition relax, varying from simple equations relating the empirical properties of the system7,8 through free-volume theories modelling the molecular motions possible given certain degrees of space constraints in the system9, to highly complex entropy models related to describing the behaviour of a lattice model of flexible polymer chains10, our fundamental understanding of the behaviour of our API molecules in the disordered state has not always kept pace with our advancing fundamental understanding of the behaviour of these same molecules in the ordered state.

A completely amorphous system can be considered as having the molecular arrangement of a liquid but with a viscosity high enough to render detection of molecular motion impossible on the timescale of the measurement. As energy is introduced into this theoretically ‘classical’ amorphous state, different modes of molecular motion become possible until the material undergoes a ‘glass transition’ and the viscosity of the system measurably decreases by several orders of magnitude. Once the freedom for molecules to move in this rubbery state, capable of flow in real time, is achieved, subsequent physical transformations such as recrystallisation to a more stable crystalline state can occur. Our most frequently employed analytical tools for the detection of amorphous material arise from either the observation and measurement of these characteristic behaviours directly, or the measurement of physical properties related to phenomena arising from them, such as the implication of amorphous material being present by the observation of a recrystallisation peak in a differential scanning calorimetry trace.

Well established thermal methods such as Differential Scanning Calorimetry (DSC) and associated operating modes (Modulated Temperature DSC and Hyper-DSC) have been frequently employed to detect the presence of amorphous material by observing the deviation from baseline of the heat flow signal as the sample passes through the glass transition11,12. The use of differential scanning calorimetry to determine quantitative measurements has, however, been largely superseded by more accurate bulk measurement techniques.

Solution calorimetry13 allows for accurate measurement of the enthalpy of solution (comprising both the lattice and solvation enthalpies of a material as it dissolves). Where the magnitude of the solvation enthalpy is sufficient to not overly mask the contribution from the lattice enthalpy, enthalpy of solution measurements can be used to not only infer the presence of amorphous material by noting the reduction in lattice enthalpy expected from a system with no long range order, but by use of careful calibration plots based on the measurement of physical mixtures of a known ratio of amorphous and crystalline material, quantification of the amount of amorphous material in an unknown sample can be achieved.

Vapour sorption techniques can also be used to probe the bulk properties of amorphous materials by observing the incorporation of a solvent into the porous amorphous material and lowering the energy barrier for the material to undergo a glass transition. The most commonly discussed variation of this approach uses Dynamic Vapour Sorption (DVS) to measure the weight change as the amorphous sample, immersed in a solvent-rich environment, takes on the solvent (usually water)14. With enough solvent incorporated within the sample for the local ambient temperature to be sufficient for the material to pass through its glass transition, the now mobile amorphous material can reorganise into a more stable crystalline configuration and expel the solvent in doing so. The manifestation of a notable ‘spike’ of weight loss associated with this forced removal of solvent as the sample crystallises can be used again, not only for detection methods, but for quantification of the amorphous material present. For lactose, this method has the advantage of not requiring the construction of a calibration plot based on the measurements made from known physical mixtures of amorphous and crystalline samples, but relying on the knowledge that amorphous lactose crystallises to α-lactose monohydrate with five per cent water of crystallisation. It is therefore possible to determine the amount of newly recrystallised α-lactose monohydrate present in a partially amorphous sample post-recrystallisation and therefore determine how much of that sample was amorphous prior to recrystallisation.

As described above, the material properties, behaviours and phenomena that these most commonly used, and importantly for the pharmaceutical material scientist scientifically well established sufficiently for regulatory bodies to be conversant in, analytical methods arise firmly from the classical definitions of a theoretically ‘perfect’ amorphous state. In day to day experience, however, the materials that we see passing through our laboratory are far from either perfect crystals or perfectly amorphous. These real world samples could consist of a fully homogenous material with its molecules ordered somewhere on a continuum from a perfect defect-free crystal to a complete lack of order; a multi phase sample consisting of regions of high crystallinity alongside distinct regions of entirely amorphous character, crystalline materials with a high number of mechanically induced defects, or some combination of all of the above. In this context it is easy to see that a bulk detection method based on the measurement of lattice enthalpy, for example, could give very similar results for a mostly crystalline material containing some lattice defects and a material consisting of particles with a crystalline core but a mostly disordered surface layer, although the real world performance of these samples in formulation and stability could be vastly different. In this case, a purely quantitative approach doesn’t entirely help us. Recent work towards the fundamental understanding of these partially ordered systems15 begins to address the need for a framework in which to rationalise all of the observed transitions of these materials.

The development of scanning thermal microscopy16 and its application to pharma – ceutical systems17-19 along with the emerging use of scanning probe microscopy as an analytical tool in the pharmaceutical sciences20,21 has given pharmaceutical material scientists the tools to identify and characterise regions of varying physical character at the surfaces of our materials and by using these techniques to add context to our bulk measurements a multi dimensional approach to characterising and understanding the behaviour of the real-world regions of disorder present in our samples can be employed.

Conventional Atomic Force Microscopy (AFM)22 allows for very accurate measurements of the surface of a sample by utilising a probe (usually silicon) attached to a piezoelectrically controlled scan head. The piezoelectric actuators control the movement of the scan head, and therefore the probe, in three dimensions. A laser beam is reflected off the back of the probe tip and into a four zone photodetector, the displacement of the reflected beam in the Z-axis is monitored, and via a force-feedback mechanism, the probe tip can apply a constant force to the sample surface by variation of the current applied to the Z-axis piezoelectric actuator. Motion of the probe tip across the surface is controlled by the X- and Yaxis piezoelectric actuators.

Thermal analysis is made possible by the replacement of the conventional atomic force microscopy probe with a specially designed thermal probe. The design of these probes relies on the ability to pass a current along a conductive strip which reaches a point at the probe tip. When the current is flowing, the point of the probe tip acts as a resistive heater, and when brought into contact with the sample surface highly localised thermal analysis measurements can be made to help physically identify the components present at the surface of the sample. The major drawback of using this technique in isolation, however, is that the heat transfer conditions are not as fully characterised as in conventional bulk thermal analysis techniques, such as differential scanning calorimetry, due to the uncontrolled heat losses and gains from the regions of the surface surrounding the area being directly heated.

Tapping Mode Atomic Force Microscopy (TM-AFM) allows for the determination of the local physical properties of a sample surface alongside the surface’s topographical features23. An atomic force microscopy probe, subject to a driving oscillation at its resonant frequency, is brought into intermittent contact with a sample surface and the responding oscillation is measured. The ‘phase lag’ between the sinusoidal driving oscillation and the tip’s responding oscillation is a measure of the damping properties of the surface and hence its local apparent stiffness and adhesion. By observing and comparing regions with different apparent stiffness and adhesion on the sample surface, a measure of the heterogeneity of the surface can be obtained and expressed as the percentage coverage of one component over the total surface area examined. This application and processing of tapping mode atomic force microscopy phase data has only recently been developed to provide surface area coverage estimations and work is currently ongoing around the statistical and mathematical validity of the analysis process. The phase data obtained is initially corrected in order to remove the effects of topographical and local charging artefacts, then analysed to identify locations of material exhibiting different phase lag values. A histogram of the individual phase lag values measured at each pixel in the image can then be constructed from the corrected and analysed images allowing for the percentage distribution of the minority component over the majority component of a multi-component sample surface to be expressed. The resulting data therefore relates to the percentage of material seen with different stiffness and adhesion properties to the underlying sample over the total examined surface area, or the ‘percentage of heterogeneity’ seen on the sample surface.

By combining this spatially resolved information with bulk quantification information obtained from the most suitable of a variety of thermal or vapour sorption methods, as outlined above, the likely behaviour of the material under investigation could be predicted and engineered removal or ‘conditioning’ of disordered regions by careful manipulation of the local environment the material is stored or processed in, or the employment of a more radical solution involving the re-examination of the crystallisation behaviour and solid form landscape of the material could be considered.

In this way we hope to be able to take the first steps towards our challenge for the next decade of materials science in the pharmaceutical industry – to use and combine a multitude of techniques and methods to understand the behaviour of our API molecules not only through their ordered configurations, in crystallisation and polymorph selection, but also through their possible disordered configurations to help speed their journey through processing and formulation into a commercially available drug product, a possibility that might seem as fanciful now as ab initio prediction of crystal polymorphs did a decade ago.

The author gratefully acknowledges the debate and discussion provided by Dr. Andrew Hills of Pfizer Worldwide R&D during the preparation of this article.


  1. Chemburkar, S.R., Bauer, J., Deming, K., Spiwek, H., Patel, K., Morris, J., Henry, R., Spanton, S., Dziki, W., Porter, W., Quick, J., Bauer, P., Donaubauer, J., Narayanan, B.A., Soldani, M., Riley, D., McFarland, K. (2000). Dealing with the Impact of Ritonavir Polymorphs on the Late Stages of Drug Process Development. Organic Process Res. Dev., 4, 413-417
  2. Day, G.M., Cooper, T.G., Cruz-Cabeza, A.J., Hejczyk, K.E., Ammon, H.L., Boerrigter, S.X.M., Tan, J.S., Della Valle, R.G., Venuti, E., Jose, J., Gadre, S.R., Desiraju, G.R., Thakur, T.S., van Eijck, B.P. Facelli, J.C. Bazterra, V.E., Ferraro, M.B., Hofmann, D.W.M., Neumann, M.A., Leusen, F.J.J., Kendrick, J., Price, S.L., Misquitta, A.J., Karamertzanis, P.G., Welch, G.W.A., Scheraga, H.A., Arnautova, Y.A., Schmidt, M.U., van de Streek, J., Wolf, A.K., Schweizer, B. (2009). Significant progress in predicting the crystal structures of small organic molecules – a report on the fourth blind test. Acta Cryst.,B 65, 107-125
  3. Craig, D. Q. M., Royall, P. G., Kett, V. L., Hopton, M. L. (1999) “The relevance of the amorphous state to pharmaceutical dosage forms: glassy drugs and freeze dried systems.” Int. J. Pharm., 179, 179-207
  4. Kerc, J. & Srcic, S. (1995) “Thermal Analysis of Glassy Pharmaceuticals.” Therm. Acta, 248, 81-95
  5. Hancock, B. C., Zografi, G. (1997) “Characteristics and Significance of the Amorphous State in Pharmaceutical Systems.” J. Pharm. Sci. 86: 1-12
  6. Gavezotti, A. (2002). Ten years of experience in polymorph prediction: what next? Cryst. Eng. Comm., 4, 1-5
  7. Vogel (1921). Das Temperaturabhangigkeitsgesetz der Viskositat von Flussigkeiten. Phys. Z, 22, 645
  8. Fulcher, G.S. (1925). Analysis of Recent Measurements of the Viscosity of Glasses. J. Am. Chem. Soc. 8, 339
  9. Doolittle, A. K. (1951). Studies in Newtonian Flow. II. The Dependance of the viscosity of liquids on free space. J. App. Phys., 22, 1471-1475
  10. Gibbs, J. H. (1956). Nature of the Glass Transition in Polymers. J. Chem. Phys. 25: 185-196
  11. Saklatvala, R.; Royall, P. G.; Craig, D. Q. M. (1999). The detection of amorphous material in a nominally crystalline drug using modulated temperature DSC. A case study. International Journal of Pharmaceutics, 192(1), 55-62
  12. Saunders, M; Podluii, K; Shergill, S; Buckton, G.; Royall, P. (2004). The potential of high speed DSC ( hyper – DSC ) for the detection and quantification of small amounts of amorphous content in predominantly crystalline samples. International Journal of Pharmaceutics, 274(1-2), 35-40
  13. Hogan, Sarah E.; Buckton, Graham. (2000) The quantification of small degrees of disorder in lactose using solution calorimetry. International Journal of Pharmaceutics (2000), 207(1-2), 57-64
  14. Buckton, G.; Darcy, P. (1995). The use of gravimetric studies to assess the degree of crystallinity of predominantly crystalline powders. World Meeting on Pharmaceutics, Biopharmaceutics and Pharmaceutical Technology, 1st, Budapest, May 9-11, 1995, 203-4
  15. Descamps, Marc; Willart, Jean Francois; Dudognon, Emeline; Legort, Ronan; Desprez, Sylvain; Caron, Vincent. (2007). Phase transformations induced by grinding: what is revealed by molecular materials. Materials Research Society Symposium Proceedings, Volume Date 2006, 979E(Thermodynamics and Kinetics of Phase Transformations in Inorganic Materials), No pp. given
  16. Hassler, R.; zur Muhlen, E. (2000). An introduction to μTA and its application to the study of interfaces. Therm. Acta, 361, 113-120
  17. Royall, P.G., Kett, V.L., Andrews, C.S., Craig, D.Q.M. (2001). Identification of Crystalline and Amorphous regions in low molecular weight materials using Microthermal Analysis. J. Phys. Chem. B, 105, 7021-7026
  18. Murphy, J.R., Andrews, C.S., Craig, D.Q.M. (2003). Characterization of the thermal properties of powder particles using Microthermal Analysis. Pharm. Res., 20(3), 500-507
  19. Harding, L.; Qi, S.; Hill, G.; Reading, M.; Craig, D. Q. M. (2008) The development of microthermal analysis and photothermal microspectroscopy as novel approaches to drug-excipient compatibility studies. International Journal of Pharmaceutics (2008), 354(1-2), 149-157
  20. Young, Paul M.; Tobyn, Michael J.; Price, Robert; Buttrum, Mark; Dey, Fiona. (2006). The use of colloid probe microscopy to predict aerosolization performance in dry powder inhalers: AFM and in vitro correlation. J. Pharm. Sci. 95(8), 1800-1809
  21. Perkins, M. C.; Bunker, M.; James, J.; Rigby-Singleton, S.; Ledru, J.; Madden-Smith, C.; Luk, S.; Patel, N.; Roberts, C. J. (2009). Towards the understanding and prediction of material changes during micronization using atomic force microscopy. European Journal of Pharmaceutical Sciences (2009), 38(1), 1-8
  22. Binnig, G.; Quate, C.F.; Gerber, C. (1986). Atomic force microscope. Phys. Rev. Lett., 56, 930-933
  23. Begat, P.; Young, P.M.; Edge, S.; Kaerger, J.S.; Price, R. (2002). The effect of mechanical processing on surface stability of pharmaceutical powders: Visualisation by Atomic Force Microscopy. J. Pharm. Sci., 92(3). 611-620

About the Author

John Murphy completed his PhD at Queen’s University Belfast in 2002 before undertaking an EPSRC sponsored post-doc project at the University of East Anglia. After a post-doc project in Medway Sciences at the University of Greenwich, John took a position as a Senior Scientist in Materials Science within Pfizer Worldwide R&D in 2007.