Data
Official data in SubjectManager for the following academic year: 2024-2025
Course director
Das Sourav
assistant lecturer,
Institute of Pharmaceutical Technology and Biopharmacy
Number of hours/semester
Lectures: 28 hours
Practices: 0 hours
Seminars: 0 hours
Total of: 28 hours
Subject data
- Code of subject: OPF-ADR-T
- 2 Credit
- Pharmacy
- Optional module
- autumn
OPG-C3E-T parallel
Course headcount limitations
min. 5 people – max. 30 people
Topic
This course will offer undergraduate students foundational knowledge in utilizing computational tools and handling scientific information for pharmaceutical research. Throughout the course, students will learn about data mining techniques, statistical designing, and computational modeling in preclinical studies. They will explore the ethical considerations of computing in pharmaceutical research and gain practical experience through case studies and written exams. Additionally, the course will cover data visualization techniques and introduce students to literature-based drug research using computational tools.
Lectures
- 1.
Introduction
- Das Sourav - 2.
Introduction
- Das Sourav - 3.
Data mining for knowledge
- Das Sourav - 4.
Data mining for knowledge
- Das Sourav - 5.
Scientific information handling
- Das Sourav - 6.
Scientific information handling
- Das Sourav - 7.
Computer applications in use
- Das Sourav - 8.
Computer applications in use
- Das Sourav - 9.
Computational modeling in preclinical studies
- Das Sourav - 10.
Computational modeling in preclinical studies
- Das Sourav - 11.
Statistical designing and data handling
- Das Sourav - 12.
Statistical designing and data handling
- Das Sourav - 13.
Case studies I / written exam I
- Das Sourav - 14.
Case studies I / written exam I
- Das Sourav - 15.
Computer application in Pharmaceutical formulation
- Das Sourav - 16.
Computer application in Pharmaceutical formulation
- Das Sourav - 17.
Ethics of computing in pharmaceutical research
- Das Sourav - 18.
Ethics of computing in pharmaceutical research
- Das Sourav - 19.
Introduction to literature-based drug research I
- Das Sourav - 20.
Introduction to literature-based drug research I
- Das Sourav - 21.
Literature-based drug research II and computational tools
- Das Sourav - 22.
Literature-based drug research II and computational tools
- Das Sourav - 23.
Data visualization techniques
- Das Sourav - 24.
Data visualization techniques
- Das Sourav - 25.
Case studies II
- Das Sourav - 26.
Case studies II
- Das Sourav - 27.
Discussion / Written exam II
- Das Sourav - 28.
Discussion / Written exam II
- Das Sourav
Practices
Seminars
Reading material
Obligatory literature
Literature developed by the Department
Notes
Class notes and materials issued during the semester.
Recommended literature
Conditions for acceptance of the semester
A maximum of 25 % absence allowed
Mid-term exams
Students have to write an end-of-semester assessment from the lecture at an acceptable level of 60%.
Making up for missed classes
In case absences exceed 25% of total class time, the course will be regarded as uncompleted. There is no opportunity to make up missed classes.
Exam topics/questions
Students have to write an end-of-semester assessment from the lecture at an acceptable level of 60%.
Examiners
- Das Sourav
Instructor / tutor of practices and seminars
- Das Sourav