Machine Learning to Identify Predictors of Glycemic Control in Type 2 Diabetes: An Analysis of Target HbA1c Reduction using Empagliflozin/Linagliptin Data

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Disclosures

Funding The studies were sponsored by the Boehringer Ingelheim & Eli Lilly and Company Diabetes Alliance; this analysis was supported by Boehringer Ingelheim Pharmaceuticals, Inc. (BIPI).

Conflicts of interest Richard Pratley has received research funding from Lexicon Pharmaceuticals, Lilly, Merck, Novo Nordisk, Sanofi Aventis US, LLC, and Takeda; speaker fees from AstraZeneca, Boehringer Ingelheim, Novo Nordisk, and Takeda; and consultancy fees from AstraZeneca, Boehringer Ingelheim, Janssen Scientific Affairs, LLC, Ligand Pharmaceuticals, Inc, Lilly, Merck, Novo Nordisk, Sanofi Aventis US, LLC, and Takeda. All honoraria and fees are directed to a non-profit organization; he received no direct compensation. Dacheng Liu and Wenbo Tang are employees of Boehringer Ingelheim. Angelo Del Parigi and Christopher Lee were employees of Boehringer Ingelheim at the time of these studies.

Ethical approval In the studies analyzed, all procedures performed involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent Informed consent was obtained from all individual participants included in the studies.

Data availability The datasets generated during and/or analyzed during the current study are available in the clinicalstudydatarequest.com repository, https://clinicalstudydatarequest.com/

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