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Advanced Analytical Chemistry - Method Development and Validation
Provider: Faculty of Science

Activity no.: 5730-22-09-31 
Enrollment deadline: 17/10/2022
PlaceDepartment of Plant and Environmental Sciences
Date and time21.11.2022, at: 00:00 - 25.01.2023, at: 16:00
Regular seats10
Course fee8,000.00 kr.
ECTS credits7.50
Contact personJan H. Christensen    E-mail address: jch@plen.ku.dk
Enrolment Handling/Course OrganiserJan H. Christensen    E-mail address: jch@plen.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 2
Scheme groupMonday 13.00 - 17.00 and Wednesday 8.00 - 17.00
Exam requirementsHanded in project report as a scientific article
Exam formOral examination
Grading scalePassed / Not passed
Internal/external examiner
Course workload
Course workload categoryHours
Practical exercises56.00
Theoretical exercises14.00


The course topics include: An introduction to problem solving in analytical chemistry (method development and quality assurance). Guidelines for method development in analytical chemistry will be presented and discussed with special focus on chromatographic, spectroscopic and mass spectrometric methods. Experimental design for optimizing analytical methods. Guidelines for method validation and quality control at different stages of the analytical process will be presented, discussed and tested (e.g., precision, robustness, accuracy, limit of detection, limit of quantification). The main focus will be on an experimental project involving method development, validation, quality assurance (QA), quality control (QC), Good Laboratory Practice (GLP), data processing, data evaluation and documentation and scientific writing.

Learning outcome
The course objective is to introduce the participants to the methods and techniques used to solve problems in analytical chemistry: method development, quality assurance, quality control as well as GLP and documentation. This background is useful for all kinds of experimental analytical work including applications within plant biology, environmental- food- and soil chemistry.

David C Harris, Quantitative Chemical Analysis edition 9. Notes and selected articles will be used extensively.

Target group
If you would like to participate please:
1) Register online by clicking on "Apply" and
2) Send an e-mail to Jan H. Christensen ( jch@plen.ku.dk ) stating your motivations (max 10 lines) and which previous experience you have had with sample preparation, chromatography and mass spectrometry (max 5 lines)

Teaching and learning methods

Lectures: The lectures will present the general theory for problem oriented analytical chemistry, experimental design, method development, quality assurance, method validation and scientific writing.

Theoretical and minor laboratory exercises: these will train the students to carry out QA/QC and to perform optimize analytical methods based on theory. Theoretical exercises and minor laboratory exercises are performed in groups of 2 to 4 students.

Laboratory project: The Laboratory projects represent the heart of the course. Here, the participants train aspects of method development, quality assurance and control as well as GLP and documentation for analytical work. The laboratory exercise comprises one project performed in groups of 2-4 students, the subject of which could be an experimental study related to the participants own research.

Several guest lectures, but non confirmed yet


All PhD students (including Danish Universities) are charged for instrument-time, laboratory expenses and expenses related to excursions amounting to a total of 8000 dkr. A course in instrumental analysis, like the course “Analytical Chemistry 1 LKEF10076”, is required. Knowledge of, or a course in basic statistics, is also recommended.

For questions feel free to contact contact persons/course organisers: Jan H Christensen ( jch@plen.ku.dk ) or Peter Waaben Thulstrup ( pwt@chem.ku.dk ).

UCPH discloses non-sensitive personal data to course leader/speakers, if any. In addition, we will disclose non-sensitive personal data to the other participants in the course. Non-sensitive personal data includes names, job positions, institution names & addresses, telephone numbers and e-mail addresses.

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