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Comparison between a computationally guided pipeline for optimizing protein-based biotherapeutics and currently used strategies. The computational analysis of a candidate pool and/or the reduction of their aggregation by introducing solubilizing mutations offers a powerful alternative to expensive and blinded trial/error approaches, being cost-effective strategies to increase the success rate in the development of protein-based therapeutics.
