High throughput chromatography strategies for potential use in the formal process characterization of a monoclonal antibody.

High throughput experimental strategies are central to the rapid optimization of biologics purification processes. In this work, we extend common high throughput technologies towards the characterization of a multi-column chromatography process for a monoclonal antibody (mAb). Scale-down strategies were first evaluated by comparing breakthrough, retention, and performance (yields and clearance of aggregates and host cell protein) across miniature and lab scale columns. The process operating space was then evaluated using several integrated formats, with batch experimentation to define process testing ranges, miniature columns to evaluate the operating space, and comparison to traditional scale columns to establish scale-up correlations and verify the determined operating space. When compared to an independent characterization study at traditional lab column scale, the high throughput approach identified the same control parameters and similar process sensitivity. Importantly, the high throughput approach significantly decreased time and material needs while improving prediction robustness. Miniature columns and manufacturing scale centerpoint data comparisons support the validity of this approach, making the high throughput strategy an attractive and appropriate scale-down tool for the formal characterization of biotherapeutic processes in the future if regulatory acceptance of the miniature column data can be achieved. Biotechnol. Bioeng. 2016;113: 1273-1283. © 2015 Wiley Periodicals, Inc.

A cost-consequence model of using the 21-gene assay to identify patients with early-stage node-positive breast cancer who benefit from adjuvant chemotherapy in the Netherlands.

BACKGROUND: Patients with early-stage hormone receptor positive, human epidermal growth factor receptor-2 (HER2) negative invasive breast cancer with 1-3 positive lymph nodes (N1) often undergo surgical excisions followed by adjuvant chemotherapy (ACT). Many patients have no benefit from ACT and receive unnecessary, costly treatment often associated with short- and long-term adverse events (AEs). Gene expression profiling (GEP) assays, such as the 21-gene assay (i.e. the Oncotype DX assay), can identify patients at higher risk for recurrence who may benefit from ACT. However, the budgetary consequence of using the Oncotype DX assay versus no GEP testing in the Netherlands is unknown. Our study therefore assessed it using a cost-consequence model. METHODS: A validated model was used to create the N1 model. The model compared the costs and consequences of using the Oncotype DX assay versus no GEP testing and MammaPrint, and subsequent ACT use with corresponding costs for chemotherapy, treatment of AEs, productivity losses, GEP testing, and treatment of recurrences, according to the Oncotype DX results. The model time horizon was 5 years. RESULTS: Costs for the total population amounted to €8.0 million (M), €16.2 M, and €9.5 M, and cost per patient amounted to €13,540, €27,455, and €16,154 for using the Oncotype DX assay, no GEP testing, and MammaPrint, respectively. Total cost savings of using the Oncotype DX assay amounted to €8.2 M versus no GEP testing and €1.5 M versus MammaPrint. Using the Oncotype DX assay would result in fewer patients receiving ACT and thus fewer AEs, sick days, and hospitalizations, leading to overall cost savings compared with no GEP testing and MammaPrint. CONCLUSIONS: Implementing Oncotype DX testing in this population can prevent unnecessary overtreatment, reducing clinical and economic burden on the patient and Dutch healthcare system.

Early-stage invasive breast cancer patients often undergo surgery followed by adjuvant chemotherapy. However, many of these patients have no benefit from adjuvant chemotherapy and thus receive unnecessary and costly treatment often associated with side-effects. Patients who may benefit from adjuvant chemotherapy can be identified by analyzing the genomic profile of the patients' tumors using a molecular diagnostic test called the 21-gene assay (also known as Oncotype DX assay). However, the budgetary consequences of using Oncotype DX for this purpose in the Netherlands are currently unknown and, therefore, assessed using a health-economic model. The model compared the costs and consequences of using the Oncotype DX assay versus no molecular diagnostic testing and an alternative molecular diagnostic test called MammaPrint. The three diagnostic testing strategies resulted in different costs in terms of several different costing categories and were compared with one another. The total costs were lowest for the diagnostic strategy using the Oncotype DX assay, as it would result in fewer patients receiving adjuvant chemotherapy compared with no molecular diagnostic testing and MammaPrint. Implementing the Oncotype DX assay as a molecular diagnostic test can identify the right patient who benefits from chemotherapy (prevent over- and undertreatment) and lead to cost-savings, reducing the clinical and economic burden on the patient and Dutch healthcare system.