Magazine Article | September 1, 2015

Quality In The Biologics Discovery And Development Continuum

Source: Life Science Leader

By Tim Moran, product manager, life science research, Dassault Systèmes BIOVIA

With biologics filling the pipelines of life sciences companies more than ever, the industry needs to rethink its view toward quality. Once primarily considered a focus in downstream drug development and manufacturing, the issue of quality now demands attention in upstream discovery research as well. In fact, the line between discovery and development in biologics looks more like the intersection of a Venn diagram than a line at all, with discovery and development sharing space in the drug development quality continuum.

The need to focus on quality early on in biologics results, in part, simply from the complexity of biologics, as well as the increased regulatory scrutiny required when working with living organisms as source materials from early research through production of biologics. Added complexity in the development and manufacturing processes can often be mitigated by instituting quality processes in the early stages of biologics discovery. The concept of Quality by Design (QbD), postulating that quality cannot be inspected into products, but rather is created by processes, has become an increasing focus for companies committed to designing and developing successful therapeutic candidates.

The cost of adhering to quality processes in late-stage development can often be drastically reduced by adhering to and understanding quality methods early in the discovery process and then adhering to those processes in development and manufacturing. Done well, QbD works like a lever, enhancing good scientific practices and encouraging scientists to take the long view and not cut quality corners on the road to releasing an approved therapeutic product; as such, QbD can confer significant competitive advantages.

The industry is facing increased regulatory requirements for documenting the use of predictive analytics on vast data sets, combining knowledge from early-stage research, historical data from the public domain, preclinical experimentation, clinical trials data, and even post-market analysis data. Many of the regulations imposed during biologics development and manufacturing to produce reports on processes such as biophysical characterization, post-translational modifications, aggregation propensity, and other developability properties can be tested early in the product development life cycle. Additionally, regulatory agencies require comparability studies from preclinical to clinical product development samples.

Preventing aggregation in solution provides an interesting example of how the research stage can contribute to QbD in biologic entity development. Two challenges arise: first, how to get the biologic to a therapeutic concentration without unwanted aggregation and, second, how to get the biologic through scale-up without aggregating. An organization obviously wants to avoid aggregation in a phase separation column that costs over $1 million to pack. Better understanding of the design space through the use of in silico tools enables scientists to modify the biologic to reduce aggregation prior to scaled-up production. The cost and time-to-market benefits can be immense.

Biologics are often produced in cell lines. Cells themselves are complex entities. Even heterogeneous populations are susceptible to such things as somatic mutations and environmental stimulation, leading to changes in such things as methylation states and subsequently expression. Cell-line developers in discovery now may have responsibility to ensure that they have the necessary traceability, documentation, and security in place to support handoff to process development. For example, a cell-line developer in discovery may need to prove to the FDA that the biologic came from a single (mono) clonal cell line. Life sciences research companies have been submitting plate-based images as proof of monoclonality along the discovery and development continuum. The development of standard operating procedures around functional assays (for example, studies and cell-based assays) can often be optimized in early research, saving both time and money in later stages of development.

It is in the industry’s best interest to focus on QbD early in discovery research. Applying quality results from early research and preclinical studies in safety and efficacy can not only enhance the predictive models on developability but also reduce variability, produce more effective therapeutics, and reduce late-stage costs and failures. Quality, after all, is a business as well as a technical imperative.