Ascertaining the best formulation to take to the clinic requires organizations to balance the formulative properties of protein therapeutics against material, time, and cost constraints. Traditionally, organizations were forced to take a trial-and-error approach to formulation development. Different parameters were tested one by one based on historical experience, expertise of specialized contract research organizations (CROs), or gut instinct. Such approaches often limit outcomes, preventing scientists from seeing alternate or unexpected possibilities that might result in a unique and possibly more effective formulation.

An information-driven approach to formulation development and manufacturing focuses expertise and technology on formulation-related problems. Specifically, the appropriate use of high-productivity research tools and scientific informatics can reveal important possibilities while simultaneously making R&D efforts more efficient.

Consider a typical scenario in which scientists want to identify the best surfactant composition for a given protein. The traditional workflow would require scientists to formulate and analyze each possible combination singly in a study that might take several months to complete. Microscale, parallel experimentation, however, enables scientists to design an experiment in a single 48 or 96-well plate that explores the impact of different ratios and amounts of surfactant on protein stability in a matter of days (see Figure 1).

Figure 1: 48 experiment design with varying protein and surfactants

Formulations are prepared automatically and critical data is collected along the way. For instance, the system adds all formulation components by weight, tracking exactly what is added to each well in real-time. A built in camera enables scientists to monitor precipitation automatically. This visual record enables scientists to maintain a connection to the samples so that even in an automated environment, they can “see” what has happened with a specific sample.

Analysis is also streamlined with microscale, parallel experimentation. In this example, scientists have opted to employ dynamic light scattering (DLS), a fast, plate-based technique that produces results that correlate well to size exclusion chromatography (SEC), a more expensive and time consuming technique (see Figure 2).

Figure 2: DLS and SEC comparison

Conveniently, DLS combined with the images taken by the digital camera enables scientists to prescreen compounds before running SEC. Figure 3 shows an array view of chromatograms for the data plated in Figure 1. The blank wells are intentional—DLS or visual examination indicated that the samples in these wells had crashed out and the samples were not prepped for SEC. Thanks to the appropriate use of technology, scientists can focus analytical resources on all and only the most interesting samples. This not only lets them conduct quicker, more targeted analyses, but also helps them protect the column and instrument from problematic samples.

Figure 3: Array view for comparing SEC Chromatograms

The emphasis in an integrated approach to formulation development and manufacturing is managing data and laboratory workflows and connecting and streamlining functions to empower subject-matter experts. Within the integrated framework, scientists, technicians, engineers, and business managers are armed with the data they need to make decisions, work effectively, and apply innovative methods that meet specific client needs at the right time in the overarching business process. Ultimately, scientists obtain a wider, richer view of the formulation development space that lets them discover new techniques or match formulation properties to specific applications while simultaneously reducing costs and conserving material.

Byeong S. Chang, Ph.D.
Chief Scientific Officer at Symyx Contract Development and Manufacturing Organization

For further information regarding this and other formulation technologies or article information contact:

Symyx
Biopharm.info@Symyx.com
(805) 445-8422
www.Symyx.com/cdmo

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