BIOTECHNOLOGY USE CASE

For a biotech in GUT-MICROBIOME THERAPEUTICS

Biotechnology use case

R E Q U I R E M E N T

EXPLORE the existence of metagenomic signatures that would be predictive of a response to a developed drug for inflammatory bowel disease patients in a Phase IIa clinical trial

S E R V I C E S  P R O V I D E D

  • AGGREGATE data from more than 900 metagenomic signatures with clinical variables (Gender, Weight…) on 40 patients
  • DEVELOP univariate methodology to keep relevant metagenomic signatures and clinical variables in the global model
  • IMPLEMENT appropriate supervised Machine Learning algorithms for prediction of response/non-response
  • COMPARE & CHOOSE the best algorithm for prediction using bootstrap and cross-validation
  • IDENTIFY metagenomic signatures and clinical variables best explaining response/non-response to the treatment

D E L I V E R A B L E S  &  B E N E F I T S

PREDICTIVE MODEL for the response/non-response of patients

REPORT summarizing the methodology used, the algorithms developed and the results obtained

Requirement

EXPLORE the existence of metagenomic signatures that would be predictive of a response to a developed drug for inflammatory bowel disease patients in a Phase IIa clinical trial

Services provided

  • AGGREGATE data from more than 900 metagenomic signatures with clinical variables (Gender, Weight…) on 40 patients
  • DEVELOP univariate methodology to keep relevant metagenomic signatures and clinical variables in the global model
  • IMPLEMENT appropriate supervised Machine Learning algorithms for prediction of response/non-response
  • COMPARE & CHOOSE the best algorithm for prediction using bootstrap and cross-validation
  • IDENTIFY metagenomic signatures and clinical variables best explaining response/non-response to the treatment

Deliverables  & benefits

PREDICTIVE MODEL for the response/non-response of patients

REPORT summarizing the methodology used, the algorithms developed and the results obtained

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