The FDA Enhancing Quality Using the Inspection Program (EQUIP) Breast Imaging Quality Initiative. 5-Year Clinical Experience.

OBJECTIVES: To evaluate the effects of the Enhancing Quality Using the Inspection Program (EQUIP) on quality control (QC) and quality assurance (QA) at an academic medical center. METHODS: EQUIP audit logs for technologist image quality review as well as mammography unit QA and QC formed the basis for study data. One randomly selected screening mammogram was evaluated by the lead interpreting physician (LIP) using EQUIP criteria for each technologist for each imaging site worked, initially semiannually and then monthly. One randomly selected screening mammogram interpreted by each interpreting physician (IP) for each imaging site was evaluated on a semiannual basis. Quarterly, the LIP reviewed QA and QC logs for each mammography unit with deficiencies further investigated. RESULTS: Of 214 965 eligible screening mammograms performed, 5955 (2.8%) underwent EQUIP image quality review. Five were found to be technically inadequate (0.08%, 5955/214 965). The LIP identified 20 significant interpretive differences compared with the clinical interpretation resulting in 10 biopsies and 7 previously undetected malignancies, with supplemental cancer detection rate of 1.2/1000 cases reviewed. Two hundred ninety mammography unit QA/QC reviews identified 31 potential deficiencies, 29 of which were due to human documentation error (93.4%). CONCLUSION: EQUIP review of both IP and technologists' quality and mammography unit QA/QC logs as performed identified few deficiencies. EQUIP policies should be evaluated at each institution and modified to best utilize resources and provide opportunities for meaningful quality improvement. Although not an EQUIP focus, supplemental cancer detection was observed as might be expected with double reading.

Enzyme-Mediated Exponential Glucose Release: A Model-Based Strategy for Continuous Defined Fed-Batch in Small-Scale Cultivations.

Miniaturized cultivation systems offer the potential to enhance experimental throughput in bioprocess development. However, they usually lack the miniaturized pumps necessary for fed-batch mode, which is commonly employed in industrial bioprocesses. An alternative are enzyme-mediated glucose release systems from starch-derived polymers, facilitating continuous glucose supply. Nevertheless, while the glucose release, and thus the feed rate, is controlled by the enzyme concentration, it also strongly depends on the type of starch derivative, and the culture conditions as well as pH and temperature. So far it was not possible to implement controlled feeding strategies (e.g., exponential feeding). In this context, we propose a model-based approach to achieve precise control over enzyme-mediated glucose release in cultivations. To this aim, an existing mathematical model was integrated into a computational framework to calculate setpoints for enzyme additions. We demonstrate the ability of the tool to maintain different pre-defined exponential growth rates during Escherichia coli cultivations in parallel mini-bioreactors integrated into a robotic facility. Although in this case study, the intermittent additions of enzyme and dextrin were performed by a liquid handler, the approach is adaptable to manual applications. Thus, we present a straightforward and robust approach for implementing defined continuous fed-batch processes in small-scale systems, where continuous feeding was only possible with low accuracy or high technical efforts until now.

Nonlinear state estimation as tool for online monitoring and adaptive feed in high throughput cultivations.

Robotic facilities that can perform advanced cultivations (e.g., fed-batch or continuous) in high throughput have drastically increased the speed and reliability of the bioprocess development pipeline. Still, developing reliable analytical technologies, that can cope with the throughput of the cultivation system, has proven to be very challenging. On the one hand, the analytical accuracy suffers from the low sampling volumes, and on the other hand, the number of samples that must be treated rapidly is very large. These issues have been a major limitation for the implementation of feedback control methods in miniaturized bioreactor systems, where observations of the process states are typically obtained after the experiment has finished. In this work, we implement a Sigma-Point Kalman Filter in a high throughput platform with 24 parallel experiments at the mL-scale to demonstrate its viability and added value in high throughput experiments. The filter exploits the information generated by the ammonia-based pH control to enable the continuous estimation of the biomass concentration, a critical state to monitor the specific rates of production and consumption in the process. The objective in the selected case study is to ensure that the selected specific substrate consumption rate is tightly controlled throughout the complete Escherichia coli cultivations for recombinant production of an antibody fragment.

High-Throughput Expression of Inclusion Bodies on an Automated Platform.

In bioprocesses, which target the production of recombinant proteins as inclusion bodies, the upstream process has a decisive influence on the downstream operations, especially regarding cell disruption, inclusion body purity and composition, and refolding yield. Therefore, optimization of the processes in fed-batch mode is a major issue, and screening for strains and process conditions are performed in highly labor, time and cost intensive shake flasks or multiwell plates. Thus, high-throughput experiments performed similar to the industrial operating conditions offer a possibility to develop efficient and robust upstream processes. We present here an automated platform for Escherichia coli fed-batch cultivations in parallelized minibioreactors. The platform allows execution of experiments under multiple conditions while allowing for real-time monitoring of critical process parameters and a controlled fermentation environment. By this, the main factors that affect yields and quality of inclusion bodies can be investigated, speeding up the development process significantly.

The dynamics of E1A in regulating networks and canonical pathways in quiescent cells.

BACKGROUND: Adenoviruses force quiescent cells to re-enter the cell cycle to replicate their DNA, and for the most part, this is accomplished after they express the E1A protein immediately after infection. In this context, E1A is believed to inactivate cellular proteins (e.g., p130) that are known to be involved in the silencing of E2F-dependent genes that are required for cell cycle entry. However, the potential perturbation of these types of genes by E1A relative to their functions in regulatory networks and canonical pathways remains poorly understood. FINDINGS: We have used DNA microarrays analyzed with Bayesian ANOVA for microarray (BAM) to assess changes in gene expression after E1A alone was introduced into quiescent cells from a regulated promoter. Approximately 2,401 genes were significantly modulated by E1A, and of these, 385 and 1033 met the criteria for generating networks and functional and canonical pathway analysis respectively, as determined by using Ingenuity Pathway Analysis software. After focusing on the highest-ranking cellular processes and regulatory networks that were responsive to E1A in quiescent cells, we observed that many of the up-regulated genes were associated with DNA replication, the cell cycle and cellular compromise. We also identified a cadre of up regulated genes with no previous connection to E1A; including genes that encode components of global DNA repair systems and DNA damage checkpoints. Among the down-regulated genes, we found that many were involved in cell signalling, cell movement, and cellular proliferation. Remarkably, a subset of these was also associated with p53-independent apoptosis, and the putative suppression of this pathway may be necessary in the viral life cycle until sufficient progeny have been produced. CONCLUSIONS: These studies have identified for the first time a large number of genes that are relevant to E1A's activities in promoting quiescent cells to re-enter the cell cycle in order to create an optimum environment for adenoviral replication.