Multi-attribute Raman spectroscopy (MARS) for monitoring product quality attributes in formulated monoclonal antibody therapeutics.

Rapid release of biopharmaceutical products enables a more efficient drug manufacturing process. Multi-attribute methods that target several product quality attributes (PQAs) at one time are an essential pillar of the rapid-release strategy. The novel, high-throughput, and nondestructive multi-attribute Raman spectroscopy (MARS) method combines Raman spectroscopy, design of experiments, and multivariate data analysis (MVDA). MARS allows the measurement of multiple PQAs for formulated protein therapeutics without sample preparation from a single spectroscopic scan. Variable importance in projection analysis is used to associate the chemical and spectral basis of targeted PQAs, which assists in model interpretation and selection. This study shows the feasibility of MARS for the measurement of both protein purity-related and formulation-related PQAs; measurements of protein concentration, osmolality, and some formulation additives were achieved by a generic multiproduct model for various protein products containing the same formulation components. MARS demonstrates the potential to be a powerful methodology to improve the efficiency of biopharmaceutical development and manufacturing, as it features fast turnaround time, good robustness, less human intervention, and potential for automation.

A cross-sectional study of prevalence, distribution, cause, and impact of blood product recalls in the United States.

Defective blood products that are recalled because of safety or potency deviations can trigger adverse health events and constrict the nation's blood supply chain. However, the underlying characteristics and impact of blood product recalls are not fully understood. In this study, we identified 4700 recall events, 7 reasons for recall, and 144 346 units affected by recalls. Using geospatial mapping of the newly defined county-level recall event density, we discovered hot spots with high prevalence and likelihood of blood product recall events. Distribution patterns and distribution distances of recalled blood products vary significantly between product types. Blood plasma is the most recalled product (87 980 units), and leukocyte-reduced products (34 230 units) are recalled in larger numbers than non-leukocyte-reduced products (8076 units). Donor-related reasons (92 382 units) and sterility deviations (22 408 units) are the major cause of blood product recalls. Monetary loss resulting from blood product recalls is estimated to be $17.9 million, and economic sensitivity tests show that donor-related reasons and sterility deviations contribute most to the overall monetary burden. A total of 2.8 million days was required to resolve recall events, and probabilistic survival time analysis shows that sterility deviations and contamination took longer to resolve because of their systemic effect on blood collection and processing. Our studies demonstrate that better donor screening procedures, rigorous sterility requirements, improved containment methods, and mitigation of recall events in high-prevalence regions will enable a more robust blood supply chain.

The Expanding Toolbox of In Vivo Bioluminescent Imaging.

In vivo bioluminescent imaging (BLI) permits the visualization of engineered bioluminescence from living cells and tissues to provide a unique perspective toward the understanding of biological processes as they occur within the framework of an authentic in vivo environment. The toolbox of in vivo BLI includes an inventory of luciferase compounds capable of generating bioluminescent light signals along with sophisticated and powerful instrumentation designed to detect and quantify these light signals non-invasively as they emit from the living subject. The information acquired reveals the dynamics of a wide range of biological functions that play key roles in the physiological and pathological control of disease and its therapeutic management. This mini review provides an overview of the tools and applications central to the evolution of in vivo BLI as a core technology in the preclinical imaging disciplines.

Quantifying Limits on Replication, Death, and Quiescence of Mycobacterium tuberculosis in Mice.

When an individual is exposed to Mycobacterium tuberculosis (Mtb) three outcomes are possible: bacterial clearance, active disease, or latent infection. It is generally believed that most individuals exposed to Mtb become latently infected and carry the mycobacteria for life. How Mtb is maintained during this latent infection remains largely unknown. During an Mtb infection in mice, there is a phase of rapid increase in bacterial numbers in the murine lungs within the first 3 weeks, and then bacterial numbers either stabilize or increase slowly over the period of many months. It has been debated whether the relatively constant numbers of bacteria in the chronic infection result from latent (dormant, quiescent), non-replicating bacteria, or whether the observed Mtb cell numbers are due to balance between rapid replication and death. A recent study of mice, infected with a Mtb strain carrying an unstable plasmid, showed that during the chronic phase, Mtb was replicating at significant rates. Using experimental data from this study and mathematical modeling we investigated the limits of the rates of bacterial replication, death, and quiescence during Mtb infection of mice. First, we found that to explain the data the rates of bacterial replication and death could not be constant and had to decrease with time since infection unless there were large changes in plasmid segregation probability over time. While a decrease in the rate of Mtb replication with time since infection was expected due to depletion of host's resources, a decrease in the Mtb death rate was counterintuitive since Mtb-specific immune response, appearing in the lungs 3-4 weeks after infection, should increase removal of bacteria. Interestingly, we found no significant correlation between estimated rates of Mtb replication and death suggesting the decline in these rates was driven by independent mechanisms. Second, we found that the data could not be explained by assuming that bacteria do not die, suggesting that some removal of bacteria from lungs of these mice had to occur even though the total bacterial counts in these mice always increased over time. Third and finally, we showed that to explain the data the majority of bacterial cells (at least ~60%) must be replicating in the chronic phase of infection further challenging widespread belief of nonreplicating Mtb in latency. Our predictions were robust to some changes in the structure of the model, for example, when the loss of plasmid-bearing cells was mainly due to high fitness cost of the plasmid. Further studies should determine if more mechanistic models for Mtb dynamics are also able to accurately explain these data.