The introduction of new technology often means a significant step forward in the performance of one subprocess, but only an incremental improvement in the full product development process. In the case of Next Generation Genomics (NGG) Technologies, a series of incremental technology advancements has brought about the ability to radically change the way bioprocesses are developed and optimized. Bioprocessing in pharmaceuticals and in industrial biotech have significantly different economic drivers, but both can realize significant economic benefit from the application of these new technologies. Pharmaceutical applications are driven foremost by the cost of development, regulatory approval, and compliance, and only secondarily by process productivity. In contrast, the primary market driver of industrial bioprocesses is productivity, particularly in commodity and biofuel applications. In this paper, we focus on the practical application to biopharmaceuticals, which need to increase emphasis on productivity of manufacturing due to the continual rise in health care costs, and the expansion of access to pharmaceuticals in developing countries. In addition, there is the potential for significant impact of NGG in the emerging FDA initiative, known as quality by design (QbD).
For new biologics to be profitable, they must be developed in a cost-effective manner and optimized to produce the highest possible titers. For existing biologics to remain profitable, especially with the emergence of biosimilars, they must be efficiently optimized in order to improve productivity and scales, with the resultant lowering of cost–of–goods. Remarkably, most of the research currently conducted uses outdated tools and is performed generally on model cell lines that have been subjected to numerous population doubling events that, over time, induce extensive genetic polymorphisms, ultimately decreasing product quality and process stability (1). When it comes to production of these newly developed biologics, total economic pressure is a key driver of success. Aside from the inherent complexity (structural, glycosylation, folding, stability, etc.) of the biopharmaceutical products themselves, bioprocess engineers are also faced with the intricacy of the production process itself. For each product, a cell line with sufficient production phenotypes has to be developed. Current strategies involve time consuming, labor–intensive steps, from the introduction of the product genes to the isolation and characterization of candidate clones. Cell-line development spans several months, or in some cases, years, and involves the screening of several hundred cell clones for high productivity before a few dozen are selected as candidate production lines. The process typically lasts for up to six months for each candidate before it can enter the evaluation phase, where its efficacy and safety in animal and human subjects are determined (2). Once the process has been established and approved, follow–on improvements become very costly, each of which must address FDA's requirements for quality and safety. In the past, insufficient knowledge of the biology of the production organism and the impact of the conditions it is grown under made it difficult to maintain stabile product quality attributes when variables had changed. We believe that NGG provides a modern and comprehensive approach to address this gap.
There is also a regulatory benefit to implementing NGG techniques. In an innovative and forward–thinking move, FDA's QbD initiative emphasizes the achievement of product quality by thorough process understanding, monitoring, and control. The approach allow manufacturers to identify critical process parameters (CPPs) and the direct effects they have on product quality. Adopting QbD principles and process analytical technology (PAT) guidelines, can help ensure an overall understanding of the bioprocess, ultimately assisting manufactures to achieve process robustness, stability and quality. PAT has been defined by FDA as a mechanism to design, analyze, and control pharmaceutical manufacturing processes through the measurement of CPPs that affect various critical quality attributes (CQA). The belief is that with more complete understanding comes the ability to not only develop products more quickly, but also to knowledgably and safely optimize products and processes downstream, while continuing to maintain higher levels of quality control than previously achievable.