| Module Title |
Regulation & Data Analysis |
| Module Code |
CHM1026 (ITS: CS306) |
|
Faculty |
Chemical Sciences |
School |
Science & Health |
|
NFQ level |
8 |
Credit Rating |
5 |
|
|
Description
Regulation:
To introduce students to the world of regulation, especially the areas of quality control, quality assurance and validation.
To give an understanding of relevant guidelines and practices in relation to chemistry in industry.
Data Analysis:
To introduce students to the most important and widely used statistical techniques for the evaluation of laboratory based data. The focus is to demonstrate the use of these techniques from a practical problem-solving viewpoint and to acquaint them with the interpretation of the results arising from a statistical analysis. Particular emphasis will be placed on understanding the assumptions on which these statistical techniques are based and how to check or validate these assumptions.
|
Learning Outcomes
1. - describe and interpret the regulations for quality control, quality assurance and validation.
2. - apply these guidelines and practices in relation to chemistry in industry.
3. - apply statistical techniques for the evaluation of laboratory based data.
4. - validate the assumptions associated with statistical analysis.
|
| Workload | Full time hours per semester | | Type | Hours | Description |
|---|
| Online activity | 21 | Pre-recorded material and online activities. | | Lecture | 12 | Weekly online synchronous lectures/tutorials | | Lecture | 3 | Guest lecturers | | Independent Study | 89 | Practising statistical analysis. Preparing for lectures and guest lectures. Reviewing and learning course material |
| Total Workload: 125 |
|
|
| Section Breakdown | | CRN | 20182 | Part of Term | Semester 2 | | Coursework | 0% | Examination Weight | 0% | | Grade Scale | 40PASS | Pass Both Elements | Y | | Resit Category | RC1 | Best Mark | N | | Module Co-ordinator | Margaret McCaul | Module Teacher | Blanaid White, Kieran Nolan, Mary Pryce, Patrick O'Malley, Susan Kelleher |
| | Section Breakdown | | CRN | 21146 | Part of Term | Semester 2 | | Coursework | 0% | Examination Weight | 0% | | Grade Scale | 40PASS | Pass Both Elements | Y | | Resit Category | RC1 | Best Mark | N | | Module Co-ordinator | Margaret McCaul | Module Teacher | Mary Pryce, Nessan Kerrigan |
|
| Assessment Breakdown |
| Type | Description | % of total | Assessment Date |
|---|
| Loop Exam | Online exam or assignment that will cover the students knowledge of and ability to apply a range of data analysis approaches to different problems. | 50% | Week 7 | | Assignment | Examining the student's knowledge of regulations, and their application to industry | 50% | Week 8 |
| Reassessment Requirement Type |
Resit arrangements are explained by the following categories;
RC1: A resit is available for both* components of the module.
RC2: No resit is available for a 100% coursework module.
RC3: No resit is available for the coursework component where there is a coursework and summative examination element.
* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment
|
|
Pre-requisite |
None
|
|
Co-requisite |
None |
| Compatibles |
None |
| Incompatibles |
None |
|
|
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml
|
Indicative Content and Learning Activities
Regulation
Quality Control Quality Assurance Method Topics covered will include validation, Process validation, The Food and Drug Administration (FDA), Good Manufacturing Practice (GMP), Good Laboratory Practice (GLP), Accreditation
Data Analysis
Topics covered will include significance testing, ANOVA, non-parametric statistics and testing, linear & weighted regression, calibration curves, limit of detection, method of standard addition
|
Indicative Reading List
Books:
- James M. Miller and Jonathan B. Crowther (Eds.). Wiley: 2000, Analytical Chemistry in a GMP Environment: A Practical Guide,
- Good Laboratory Practice : The Why And the How.: 2005, Jurg P. Seiler, Springer Verlag,,
- Good Manufacturing Practices for Pharmaceuticals.: 2006, Joseph D Nally, Informa Healthcare,
- Principles and Practice of Pharmaceutical Medicine,: 2002, Andrew J. Fletcher, Lionel D. Edwards, Anthony W. Fox, Peter Stonier. Wiley,
- James N. Miller, Jane C. Miller: 2010, Statistics and Chemometrics for Analytical Chemistry, 6th, Pearson, England, 9780273730422
Articles:
None |
Other Resources
None |
|
Update change for Susan Kelleher as module coordinator. |
|
|
