BSEN40470 Predictive Modelling and Risk Assessment

Academic Year 2023/2024

The specific objectives of this module are:
(i) to develop each participants capacity to collect and analyse data for use in risk assessment
(ii) to build skills in developing or selecting modelling structures appropriate to describe quantitatively chemical, microbiological and physical phenomena and develop capabilities for quantifying accurately the sources of stochasticity,
(iii) to make participants familiar with dose-response modelling approaches and model simulation, that can be exploited for developing decision-making and quantitative risk assessment tools.
(iv) to integrate exposure assessment and hazard characterisation steps into a coherent Risk Characterisation.

Theoretical lectures will be alternated with problem-based learning (PBL). Theoretical lectures will cover all the fundamentals and basic principles of modelling approaches. Additionally, PBL pedagogical tools will be used in which students will work in groups to solve realistic multifaceted problems with the use of relevant software tools.

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Curricular information is subject to change

Learning Outcomes:

By the end of the programme students will:
(i) have attained a fundamental understanding of the substantial body of applied modelling, statistics and recent developments in the field of Predictive Modelling and Quantitative Risk Assessment of foods,
(ii) have exercised personal responsibility and autonomous initiative in solving complex microbiological problems that are solved in a rigorous and professional approach,
(iii) have engaged in critical dialogue and learned to criticise the broader implication of Applied Modelling approaches in Food safety through interactive teaching,
(iv) have exploited available software packages and quantitative approaches for enriching current studies in the field in order to communicate results and innovations of research to peers.

Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities


Autonomous Student Learning




Computer Aided Lab




Approaches to Teaching and Learning:
Strong emphasis on students taking the initiative on active learning with mixture of active/task-based learning; pc lab work; enquiry & problem-based learning 
Requirements, Exclusions and Recommendations

Not applicable to this module.

Module Requisites and Incompatibles
Additional Information:
Participants will need experience in Quantitative Risk Assessment. It is advised participants have completed BSEN30060 - Quantitative Risk Assessment, or for Exchange/Erasmus Students an equivalent module will be considered on case by case basis.

Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Assignments Varies over the Trimester n/a Graded No


Multiple Choice Questionnaire: MCQ on theoretical elements of the module Varies over the Trimester n/a Graded No


Carry forward of passed components
Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Rajat Nag Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Computer Aided Lab Offering 1 Week(s) - Autumn: All Weeks Fri 14:00 - 15:50