Determination of ultra-trace metal-protein interactions in co-formulated monoclonal antibody drug product by SEC-ICP-MS.

Transition metals can be introduced in therapeutic protein drugs at various steps of the manufacturing process (e.g. manufacturing raw materials, formulation, storage), and can cause a variety of modifications on the protein. These modifications can potentially influence the efficacy, safety, and stability of the therapeutic protein, especially if critical quality attributes (CQAs) are affected. Therefore, it is meaningful to understand the interactions between proteins and metals that can occur during the manufacturing process, formulation, and storage of biotherapeutics. Here, we describe a novel strategy to differentiate between ultra-trace levels of transition metals (cobalt, chromium, copper, iron, and nickel) interacting with therapeutic proteins and free metal in solution in the drug formulation using size exclusion chromatography coupled to inductively coupled plasma mass spectrometry (SEC-ICP-MS). Two monoclonal antibodies (mAbs) were coformulated and stored up to nine days in a scaled down model to mimic metal exposure from manufacturing tanks. The samples containing the mAbs were first analyzed by ICP-MS for bulk metal analysis, then studied using SEC-ICP-MS to measure the extent of metal-protein interactions. The SEC separation was used to differentiate metal associated with the mAbs from free metal in solution. Relative quantitation of metal-protein interaction was then calculated using the relative peak areas of protein-associated metal to free metal in solution and weighting it to the total metal concentration in the mixture as measured by bulk metal analysis by ICP-MS. The SEC-ICP-MS method offers an informative means of measuring metal-protein interactions during drug development.

Electronic health record risk score provides earlier prognostication of clinical outcomes in patients admitted to the cardiac intensive care unit.

In this observational study, we compared the prognostic ability of an electronic health record (EHR)-derived risk score, the Rothman Index (RI), automatically derived on admission, to the first 24-hour Sequential Organ Failure Assessment (SOFA) score for outcome prediction in the modern cardiac intensive care unit (CICU). We found that while the 24-hour SOFA score provided modestly superior discrimination for both in-hospital and CICU mortality, the RI upon CICU admission had better calibration for both outcomes. Given the ubiquitous nature of EHR utilization in the United States, the RI may become an important tool to rapidly risk stratify CICU patients within the ICU and improve resource allocation.

Transition From an Open to Closed Staffing Model in the Cardiac Intensive Care Unit Improves Clinical Outcomes.

Background Several studies have shown improved outcomes in closed compared with open medical and surgical intensive care units. However, very little is known about the ideal organizational structure in the modern cardiac intensive care unit (CICU). Methods and Results We retrospectively reviewed consecutive unique admissions (n=3996) to our tertiary care CICU from September 2013 to October 2017. The aim of our study was to assess for differences in clinical outcomes between an open compared with a closed CICU. We used multivariable logistic regression adjusting for demographics, comorbidities, and severity of illness. The primary outcome was in-hospital mortality. We identified 2226 patients in the open unit and 1770 in the closed CICU. The unadjusted in-hospital mortality in the open compared with closed unit was 9.6% and 8.9%, respectively (P=0.42). After multivariable adjustment, admission to the closed unit was associated with a lower in-hospital mortality (odds ratio [OR], 0.69; 95% CI: 0.53-0.90, P=0.007) and CICU mortality (OR, 0.70; 95% CI, 0.52-0.94, P=0.02). In subgroup analysis, admissions for cardiac arrest (OR, 0.42; 95% CI, 0.20-0.88, P=0.02) and respiratory insufficiency (OR, 0.43; 95% CI, 0.22-0.82, P=0.01) were also associated with a lower in-hospital mortality in the closed unit. We did not find a difference in CICU length of stay or total hospital charges (P>0.05). Conclusions We found an association between lower in-hospital and CICU mortality after the transition to a closed CICU. These results may help guide the ongoing redesign in other tertiary care CICUs.