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March 01, 2017

Quantifying Stability for Biologics

ΔG Help Researchers Make Biologic Stability and Aggregation Assessments Quantitatively

  • Biologics characterization is a complex problem due to storage requirements, dosing concentrations, and molecule complexity. Bispecific antibodies are an even greater challenge, with higher variation compared to monoclonals. Many techniques are used to identify biologics and formulations that are stable and do not aggregate, thereby improving manufacturability, storage, and efficacy.

    Forced degradation methods are often used to rapidly assess biologic stability and aggregation propensity. Thermal melting (Tm) measurements are a favorite, because they do not require a lot of sample or time. While Tm can usually distinguish good actors from bad, it is not perfectly predictive of what will occur at 4°C or 25°C. Also, many engineered antibodies and good formulations will have similar or identical Tm measurements, and optimization will require something that can distinguish among what may appear to be many acceptable conditions.

    A complementary and under-utilized measurement is ΔG, the Gibbs free energy. While recalling college thermodynamics lessons may normally be a cause for nightmares, it’s pretty useful in this instance. A ΔG measurement can be extrapolated back to ambient equilibrium concentrations; it’s a quantifiable measure of the ratio of folded: unfolded protein in a given formulation. In practical terms, the higher the ΔG, the higher the quantity of folded protein, and the more stable the biologic.

    Knowing the amount of folded protein is critical for stability and aggregation. Small quantities of unfolded protein can lead to big aggregation problems. Considering that biologics are manufactured and dosed at high concentrations—understanding early if a protein will aggregate is important for choosing the right candidate and formulation. Monitoring ΔG changes over increasing biologic concentrations provides information on biologic aggregation propensity and aggregation pathway.

    ΔG usually takes a back seat to Tm for stability determinations because it requires more time, more sample, and was a tedious process to obtain it. The two measurements can be used effectively together, with Tm as a first pass, and ΔG for quantifying stability on the better conditions. There are newer instruments, such as the HUNK from Unchained Labs, which automates the tedious parts of ΔG measurements. Eliminating the barriers to measuring ΔG provides researchers the early data to help make biologic stability and aggregation assessments quantitatively.

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