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A Remarkable Community Project to Improve the Tools for Predicting Developability of Antibodies: The Highland Games

Competition among colleagues in science advances knowledge in the field, pushes boundaries, and leads to the production of new therapeutics. Often, companies compete against each other to develop the next best therapeutic, keeping data on their molecules as closely guarded secrets. In October of 2018, a different kind of competition was envisaged. The first “Highland Games” competition was held in conjunction with the Recovery of Biological Products Conference in Ashville, NC, USA. Scientists were encouraged to work in “coopetition” (mutually-beneficial collaboration between competitors) with each other instead of against each other. The goal of this competition was to benchmark and assess the ability to predict development-related properties of six antibodies from their amino acid sequences alone. Predictions included purification-influencing properties such as stability and viscosity at high concentrations.  This was truly a community project.  Key contributions were made by many individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook to prepare and characterize these materials and prediction teams who attempted to predict antibody properties from sequence alone.  Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as were areas presenting opportunities for improvement.  Predictions of isoelectric point and Protein A elution pH were especially good.  Other properties such as viscosity proved more challenging to predict.  The authors conclude that the accumulated data set from this first Highland Games can serve as a benchmarking tool for further development of in silico prediction tools.

Details of the Highland Games, with all of the methods and results, are available in the paper, “Highland Games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences,” published in Biotechnology and Bioengineering on April 7, 2020 by Jonathan Coffman and colleagues.

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