Recommender systems are one of the most pervasive applications of machine learning in industry, with many services using them to match users to products or information. As such it is important to ask: what are the possible fairness risks, how can we quantify them, and how should we address them?In this paper we offer a set of novel metrics for evaluating algorithmic fairness concerns in recommender systems. In particular we show how measuring fairness based on pairwise comparisons from randomized experiments provides a tractable means to reason about fairness in rankings from recommender systems. Building on this metric, we offer a new regularizer to encourage improving this metric during model training and thus improve fairness in the resulting rankings. We apply this pairwise regularization to a large-scale, production recommender system and show that we are able to significantly improve the system's pairwise fairness.

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Current proof-of-concept in clinical trials suggests that FFA1 agonists have a significant improvement for T2DM without the risk of hypoglycemia. However, there are still several challenging problems including the mechanism of the receptor and the efficacy and safety of the ligands.

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The free fatty acid receptor 1 (FFAR1/GPR40) amplifies glucose-dependent insulin secretion; therefore, it has attracted widespread attention as a promising antidiabetic target. Current clinical proof of concept also indicates that FFAR1 agonists achieve the initially therapeutic endpoint for the treatment of type 2 diabetes mellitus (T2DM) without the hypoglycemic risk. Thus, many pharmaceutical companies and academic institutes are competing to develop FFAR1 agonists. However, several candidates have been discontinued in clinical trials, often without reporting the underlying reasons. Herein, we review the challenges and corresponding strategies chosen by different medicinal chemistry teams to improve the physicochemical properties, potency, pharmacokinetics, and safety profiles of FFAR1 agonists, with a brief introduction to the biology and pharmacology of related targets.