Predictive Microbiome
Risk Management

Next generation genomic techniques monitoring factory wide microbiome. Machine Learning is used to predict the likelihood of safety or quality concerns.

Predict the likelihood of occurrence of a safety or quality issue in a manufacturing environment.

Methodology

We use the latest genomic techniques, machine learning and fundamental microbiological growth information to determine the conditions compatible for pathogen or spoiler presence or growth.

Unique Offering

Combining the strengths of fundamental microbiology, genomics and machine learning enables the prediction of the likelihood of occurrence of a safety or quality issue. This gives a far greater degree of accuracy and detail than possible from using current traditional microbiological techniques while also benefiting from the insights of domain experts and world-leading academics.

The Process

1 – Assessment and Agreement

Initial site screening and service contract

2 – Setting the Frame

Swab-plan tailored to your site, staff training, organisation of kits and shipment

3 – Access to Online Tool

Login to secure site and prepare the process flow map

4 – Collect Swabs and Metadata

Take swabs and record metadata

5 – Logistics

Kit is collected and shipped

6 – Extracting and Sequencing

Anonymous DNA extraction and sequencing in 3rd party lab

7 – Data Processing and Analysis

Converting raw sequence data into meaningful insights

8 – Your Results 

Results available for viewing on a secure site

 

Download Brochure

Understand the results and insights we provide