Apparent protein cloud point temperature determination using a low volume high-throughput cryogenic device in combination with automated imaging

Application of ultraviolet, visible, and infrared light imaging in protein-based biopharmaceutical formulation characterization and development studies

Imaging is increasingly more utilized as analytical technology in biopharmaceutical formulation research, with applications ranging from subvisible particle characterization to thermal stability screening and residual moisture analysis. This review offers a comprehensive overview of analytical imaging for scientists active in biopharmaceutical formulation research and development, where it presents the unique information provided by the ultraviolet (UV), visible (Vis), and infrared (IR) sections in the electromagnetic spectrum. The main body of this review consists of an outline of UV, Vis, and IR imaging techniques for several (bio)physical properties that are commonly determined during protein-based biopharmaceutical formulation characterization and development studies. The review concludes with a future perspective of applied imaging within the field of biopharmaceutical formulation research.

Influence of image analysis strategy, cooling rate, and sample volume on apparent protein cloud-point temperature determination

The protein cloud-point temperature (TCloud) is a known representative of protein-protein interaction strength and provides valuable information during the development and characterization of protein-based products, such as biopharmaceutics. A high-throughput low volume TCloud detection method was introduced in preceding work, where it was concluded that the extracted value is an apparent TCloud (TCloud,app). As an understanding of the apparent nature is imperative to facilitate inter-study data comparability, the current work was performed to systematically evaluate the influence of 3 image analysis strategies and 2 experimental parameters (sample volume and cooling rate) on TCloud,app detection of lysozyme. Different image analysis strategies showed that TCloud,app is detectable by means of total pixel intensity difference and the total number of white pixels, but the latter is also able to extract the ice nucleation temperature. Experimental parameter variation showed a TCloud,app depression for increasing cooling rates (0.1-0.5 °C/min), and larger sample volumes (5-24 μL). Exploratory thermographic data indicated this resulted from a temperature discrepancy between the measured temperature by the cryogenic device and the actual sample temperature. Literature validation confirmed that the discrepancy does not affect the relative inter-study comparability of the samples, regardless of the image analysis strategy or experimental parameters. Additionally, high measurement precision was demonstrated, as TCloud,app changes were detectable down to a sample volume of only 5 μL and for 0.1 °C/min cooling rate increments. This work explains the apparent nature of the TCloud detection method, showcases its detection precision, and broadens the applicability of the experimental setup.

Investigation of the reversibility of freeze/thaw stress-induced protein instability using heat cycling as a function of different cryoprotectants

Formulation conditions have a significant influence on the degree of freeze/thaw (FT) stress-induced protein instabilities. Adding cryoprotectants might stabilize the induced FT stress instabilities. However, a simple preservation of protein stability might be insufficient and further methods are necessary. This study aims to evaluate the addition of a heat cycle following FT application as a function of different cryoprotectants with lysozyme as exemplary protein. Sucrose and glycerol were shown to be the most effective cryoprotectants when compared to PEG200 and Tween20. In terms of heat-induced reversibility of aggregates, glycerol showed the best performance followed by sucrose, NaCl and Tween20 systems. The analysis was performed using a novel approach to visualize complex interplays by a clustering and data reduction scheme. In addition, solubility and structural integrity were measured and confirmed the obtained results.