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research currently conducted uses outdated tools and is performed generally on model cell lines that have been subjected to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.