From an industrial R&D perspective, the design and development of protein therapeutics today appears somewhat akin to the
rational design of small-molecule discovery back in the 1970s when lead compounds were generated from known physiological
substrates or ligands. Facing a need to find novel and diverse small-molecule leads, attention in the 1980s centered on high-throughput
screening (HTS) technologies and compound libraries. Those libraries, albeit large, were hardly diverse, with most therapeutic
agents coming from a few target protein classes. Complementation of libraries with natural products, the development of combinatorial
chemistry, and application of focused-library sets followed. This evolution, together with automated methods for content-rich
assay systems and fast make-test cycles, enhanced discovery of novel, potent, and diverse lead series.
Contrast this with the present analagous processes for protein therapeutics: the discovery and development of novel biologics
is hardly diverse, efficient or rapid. State-of-the art protein discovery and development use multiple expression hosts (e.g.,
mouse, E.coli, Chinese hamster ovary (CHO), and NS0) and several reformatting steps between hosts are often necessary during testing, scale-up,
and production. The process of developing cell-based protein expression systems that are efficient, consistent, and scalable
often is difficult and sometimes impossible using currently available technology.
To date, more than 150 protein drugs have been approved for clinical use, nearly all of which are produced in cell-based expression
systems, such as E. coli, CHO cells, and Saccharomyces cerevisiae (S. cerevisea). These cell-based systems have several limitations, and many biologics can't be developed in these systems. For example,
these systems only allow the overexpression of proteins that don't affect the physiology of the host cells. For many expression
systems, identifying cell lines that stably synthesize high protein titers of the desired product is a time-consuming and
labor-intensive process. Ideally, the same production host for rapid variant discovery, production for animal testing, and
manufacturing of a clinical candidate would be used.
Ideally, one would want to emulate the huge leap made in iterative drug design seen in small-molecule discovery, namely, rapid
make-test cycles and generation of multiple parallel libraries of drug candidates with diverse structural elements to optimize
activity while maintaining feasibility for manufacture. An ideal system would do the following:
- Make fast make-test cycles a prerequisite for re-iterative design on the order of three to five days, similar to those for
focused small-molecule libraries
- Create efficient and rapid expression and purification that allows for libraries of hundreds to thousands of protein-sequence
variants to be simultaneously tested per make-test cycle using standard off-the-shelf robotics equipment
- Incorporate preferred sequences defined from selection technologies, such as ribosome or phage display, into whole protein
therapeutics for testing
- Enhance the diversity of chemical structures by expanding the library of available amino acids at specifically targeted points
in the protein sequence from 20 natural to many hundreds of non-natural amino-acids
- Optimize several properties (e.g., agonist or antagonist, affinity, stability, and predictive manufacturability) simultaneously
through rapid high-throughput make-test cycles
- Create processes that are not only rapid but amenable to rapid scale-up and cGMP manufacturing once the desired therapeutic
construct has been identified.
As ambitious as such a system would seem, several exciting technologies are emerging that improve expression systems and enhance
diversity to enable modification of intrinsic properties of proteins, such as enzyme catalytic efficiency or binding. Others
combine different properties in single therapeutics by conjugation chemistries. Further emerging technologies can lead to
more rapid and parallel expression of many protein drug candidates. Getting all of these desirable technologies into a single
amenable platform that has the flexibility to be scaled and support cGMP manufacturing is in sight.