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

Activity no.: 5730-24-09-31 
Enrollment deadline: 08/11/2024
PlaceDepartment of Plant and Environmental Sciences
Date and timeNovember 2024 - January 2025
Regular seats16
Course fee9,000.00 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. Oral examination in the report and theoretical aspects of the course
Exam formOral examination
Grading scalePassed / Not passed
Internal/external examiner
Course workload
Course workload categoryHours
Lectures18.00
Practical exercises56.00
Theoretical exercises14.00
Excursions4.00
Preparation116.00
Colloquia4.00
Examination1.00

Sum213.00


Content
Analytical chemistry and generic method development and validation tools. Applied analytical sciences (food science, environmental science, biotechnology, natural products research, bioanalysis)

Aim and content

The course aim is to introduce participants to the methods and techniques for solving problems in analytical chemistry, including method development, quality assurance, quality control, GLP, and documentation. This foundational knowledge is valuable for various types of experimental analytical work, with applications in plant biology, environmental chemistry, food chemistry, and soil chemistry.

The course topics include an introduction to problem solving in analytical chemistry, with a focus on method development and quality assurance. Guidelines for method development in analytical chemistry will be presented and discussed, with special emphasis on chromatographic, spectroscopic, and mass spectrometric methods.

The course will cover experimental design strategies for optimizing analytical methods. Guidelines for method validation and quality control at various stages of the analytical process will be explored, including aspects such as precision, robustness, accuracy, limit of detection, and 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, documentation, and scientific writing.

Formal requirements
As prerequisite a course in instrumental analysis, like the course "Analytical Chemistry", is strongly recommended, since all basic theory of sampling, separation, chromatographic instruments and mass spectrometry is assumed to be known.

Please contact Jan H Christensen on 
jch@plen.ku.dk  directly before registering online and if you have any questions.

Learning outcome

Knowledge:
>Explore the theory and practice of method development, validation, quality assurance (QA), Good Laboratory Practice (GLP), and documentation in analytical chemistry.
>Examine the statistical theory underpinning QA for quantitative chemical analysis

Skills:
>Independently setup experiments, develop, validate and make documentation for an analytical method.
>Set up and apply a quality control system for an entire analytical method.

Competences:
>Develop, validate and apply analytical methods in different field of research.
>Evaluate and discuss analytical chemical quality data from the literature.
>Do problem solving in analytical chemistry: method development and QA/QC measures.


Literature
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)


Target group

PhD-students who needs to develop and validate analytical methods from sampling to data treatment. There is a strong focus on project work. This is basically all PhD students that are going to quantify known compounds in different matrices (food, environment, industrial…) as part of their PhD.

As prerequisite a course in instrumental analysis, like the course "Analytical Chemistry", is strongly recommended, since all basic theory of sampling, separation, chromatographic instruments and mass spectrometry is assumed to be known.


Teaching and learning methods

Lectures will cover the general theory of problem-oriented analytical chemistry, experimental design, method development, quality assurance, method validation, and scientific writing.

Theoretical and minor laboratory exercises will train students in QA/QC and optimizing analytical methods based on theoretical principles. These exercises are conducted in groups of 2 to 4 students.

The laboratory project is the core of the course, allowing participants to practice method development, quality assurance and control, GLP, and documentation for analytical work. Each group of 2 to 4 students will undertake an experimental study related to their own research.

Lecturers

Several guest lectures, but non confirmed yet

***

Collaborating Department: Peter Waaben Thulstrup pwt@chem.ku.dk


Remarks

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)

***

All PhD students, including those from Danish universities, will be charged 9000 DKR for instrument time, laboratory expenses, and excursion costs. Completion of a course in instrumental analysis, such as "Analytical Chemistry 1 LKEF10076," is required. Additionally, knowledge of basic statistics or a relevant course is recommended

***

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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