The ability to combine emerging artificial intelligence (AI) technologies, data science, and traditional bioinformatics approaches present an opportunity to change drug discovery by generating models that are more effective in predicting drug-related toxicity compared to current methodologies. To harness the power of emerging computational biology approaches and public repositories, AstraZeneca is seeking to identify new or innovative methodologies that help predict drug-induced cardiac pathology and it's translation from data generated in a real-life case study.
This Theoretical Challenge requires only a written proposal.
Prior to receiving approval to market for a new drug, non-clinical in vitro and in vivo toxicity tests that meet regulatory authority requirements are conducted to demonstrate the safety of a candidate drug. Experiments to reveal toxicological mechanisms of action are sometimes conducted in order to improve translational understanding (i.e. potential for clinical toxicity). Here, AstraZeneca is seeking proposals that offer a testable hypothesis detailing the target(s) and proposed mechanism(s) of action for drug-induced cardiac pathology in a rodent model.
This is a Theoretical Challenge that requires only a written proposal to be submitted. The Challenge award will be contingent upon Seeker’s theoretical evaluation of the quality of the data analysis as detailed in the submission.
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 December 31, 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 commercialization 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 organization, AstraZeneca recognizes 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.