Modeling new immunoregulatory therapeutics as antimicrobial alternatives for treating Clostridium difficile infection
作者：
Highlights：
• Pipeline for hybrid equation based and machine learning disease modeling used to predict efficacy of novel therapeutics against Clostridium difficile infection.
• Decreased rates of recurrence predicted for therapies in development, such as fecal microbiota transplantation and anti-toxin antibodies, compared to current standard of care antimicrobials.
• Immunoregulation, validated by LANCL2 activation, is a novel strategy for the treatment of C. difficile associated disease.
摘要
•Pipeline for hybrid equation based and machine learning disease modeling used to predict efficacy of novel therapeutics against Clostridium difficile infection.•Decreased rates of recurrence predicted for therapies in development, such as fecal microbiota transplantation and anti-toxin antibodies, compared to current standard of care antimicrobials.•Immunoregulation, validated by LANCL2 activation, is a novel strategy for the treatment of C. difficile associated disease.
论文关键词：Clostridium difficile,In silico clinical trials,Gastrointestinal disease modeling,LANCL2,Immunoregulation
论文评审过程：Received 27 December 2016, Revised 6 March 2017, Accepted 6 May 2017, Available online 9 May 2017, Version of Record 15 May 2017.
论文官网地址：https://doi.org/10.1016/j.artmed.2017.05.003
