The ability to express large quantities of high quality protein is essential for characterizing its structure and function in the pursuit of developing protein therapeutics/proteins for small molecule drug discovery research. Rapid iteration of a large number of constructs to find the one that yields the largest amount of pure homologous protein is an effective way of establishing robust protocols. New approaches to protein expression and purification are being discovered, yet the process can be further improved. The Seeker wants to streamline and automate protein production efforts by improving key areas of the gene-to-protein process.
The Challenge has a special award structure. A solution that addresses both protein expression and the optimisation of protein purification will be eligible for two awards of $25,000 each.
This Theoretical Challenge requires only a written proposal.
There are machines that perform parts of the gene-to-purified protein process. Examples of new technology include chemical gene synthesis, digital to biological converters, and cell-free production of proteins from plasmid. Machines offer cell-based production combined with single step purification or protein purification from cell extracts or supernatants. Commercially available systems, work well for expression screening as long as protein targets are straightforward and behave well (e.g. no formation of inclusion bodies during growth, no precipitation, no protein degradation). Therefore, the Seeker desires new approaches to enable the delivery of more protein reagents with reduced timelines to support drug discovery projects.
This is a Theoretical Challenge that requires only a written proposal to be submitted. The Challenge award will be contingent upon theoretical evaluation of the proposal by the Seeker.
To receive an award, the Solvers will not have to transfer their exclusive IP rights to the Seeker. Instead, Solvers will grant to the Seeker a non-exclusive license to practice their solutions.
Submissions to this Challenge must be received by 11:59 PM (US Eastern Time) on January 26, 2018.
Late submissions will not be considered.
ABOUT THE SEEKER
AstraZeneca is a global, science-led, biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines, primarily for the treatment of diseases in three main therapy areas – Oncology, Cardiovascular & Metabolic Diseases and Respiratory. AstraZeneca also is selectively active in the areas of autoimmunity, neuroscience and infection. As an innovation-driven research organisation, AstraZeneca recognises that great ideas come from many sources. Open innovation is an avenue by which ideas can be shared and AstraZeneca recently launched a pavilion to further its commitment to facilitate the advancement of pharmaceutical research.
What is a Theoretical-Licensing Challenge?
An InnoCentive Theoretical Challenge builds upon an idea but is not yet a proof of concept. A solution to a Theoretical Challenge will solidify the Solver's concept with detailed descriptions, specifications and requirements necessary to bringing a good idea closer to becoming an actual product or service.
This Challenge is a Theoretical-Licensing Challenge, meaning that the Seeker is requesting non-exclusive rights to use the winning solution. By contrast, Theoretical-IP Transfer means that Solvers must relinquish all rights to the Intellectual Property (IP) for which they are awarded. For these forms of a Theoretical Challenge, Solvers that do not win retain the rights to their solution after the evaluation period is complete. The Seeker retains no rights to any IP not awarded.