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Sep 1, 2012 (Vol. 32, No. 15)

Expediting Early Preformulation Studies

High-Throughput Characterization Systems and Empirical Phase Diagrams Can Speed Process

  • The stability of macromolecule-based drugs and vaccines is a key issue in the development of biopharmaceuticals. In addition to the intrinsic instability of the molecules themselves, biopharmaceuticals may be affected by parameters such as temperature, pH, and excipient incompatibility. Since this can have a significant impact on the therapeutic effects of a drug and its long-term storage ability, these characterization parameters must be thoroughly investigated and understood as part of routine preformulation and formulation processes.

    Design of experiments is a common approach to obtaining this data. Due to time and cost constraints, however, this technique often relies on collecting the bare minimum of multivariable data from which conclusions can be drawn. An alternative, faster and more comprehensive approach, developed at the Laboratory for Macromolecule and Vaccine Stabilization at the University of Kansas and already adopted by several large pharmaceutical companies, depends on the measurement of all potential variables. The results are then processed mathematically using specially developed software and are represented visually using empirical phase diagrams.

    Factors such as protein concentration, ionic strength, shear forces, and freeze-thaw cycling can all influence the biological function of macromolecules, and representing these criteria in the form of empirical phase diagrams is a particularly effective way to compare similar sets of data from a molecule under different states, or even from different molecules.

    The targets of interest—peptides, proteins, virus-like particles, nucleic acids, viruses, and even bacterial and mammalian cells—are represented as vectors in a highly dimensional space, where the components of the vector are the experimental parameters being measured, most frequently as a function of temperature and pH.

    The diagram is constructed by assigning a color based on the magnitude of each component of the characterization data, and the final result is a two-dimensional diagram, where one dimension is temperature and the other pH. Interpretation of the phase diagram relies on the fact that molecules in a similar state will produce regions of a similar color with color differences indicating molecules that are in different physical states under the particular conditions studied.

  • Generating Data

    Click Image To Enlarge +
    Figure. Examples of empirical phase diagrams produced from the Avacta Optim 1000. Data was obtained from intrinsic fluorescence intensity and peak position as well as light scattering.

    In the ideal situation, a replicate series of results for each parameter is acquired to create a phase diagram. Although a variety of instruments can be used to measure each parameter individually, this type of equipment tends to rely on relatively time-consuming processes and can generally handle only low throughputs. Sample volume is also an issue since many conventional analytical techniques require large amounts of the target molecule when, in the early stages of development, they are expensive to produce and not generally available in significant quantities. Instrument developers have taken these considerations into account and there are now systems available that are significantly faster, capable of measuring multiple parameters simultaneously and at higher throughputs, and require far smaller sample volumes.

    One example, the Optim® 1000 micro-volume protein analysis and characterization system (Avacta Analytical), was developed specifically to reduce the time and cost of therapeutic protein preformulation studies, stability testing, and formulation development, and has proved well suited to rapidly generating data for phase diagrams.

    Two laser sources allow simultaneous measurement of intrinsic protein fluorescence, static light scattering, and extrinsic fluorescence from a range of probe dyes, providing complementary information and a greater insight into protein behavior than single measurements.

    A range of stability parameters, including protein unfolding transition temperature (Tm) and aggregation onset temperature (Tagg), can be determined concurrently. In addition, the system’s high sensitivity permits good quality data to be obtained from small volume, low protein concentration samples; minimal amounts of sample as low as 1 µL are required for a full spectrum of measurements.

    The main advantage of the Optim, however, is speed. It is microplate-based and faster than other instruments in the field; increases in throughput by a factor of between 10 and 20 have been observed. The data obtained is then entered into the analytical software developed by the team at Kansas, and the resulting phase diagram shows the behavior of the target. An illustration of EPDs generated from Avacta Analytical data for four proteins is shown in the Figure.

    Conventional analytical methods used for preformulation, stability, and formulation studies have previously relied on methods that extrapolate partial data on slow and labor-intensive instrumentation that is incompatible with high-throughput measurements and tight development timelines.

    The Optim 1000 microvolume protein analysis and characterization system offers rapid, multimodal analysis of ultra-low sample volumes at high throughputs.



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