PHA3005: Pharmaceutical Materials Science Coursework Assessment Briefing Template 2024-25

Published: 28 Jul, 2025
Category Assignment Subject Science
University University of Lincoln (UOL) Module Title PHA3005: Pharmaceutical Materials Science
Assessment Type Coursework
Academic Year 2024-25

Module learning outcomes of PHA3005

LO1 Demonstrate detailed understanding of materials on both the nano and the supramolecular scale.
LO2 Understand, and interpret the outcomes of, analytical techniques relevant to pharmaceutical materials.
LO3 Critically evaluate the process and development of pharmaceutical materials with respect to their applications. 

PHA3005 Assessment title and format Coursework: 

The coursework is in two parts which comprises, a) 2 short answer questions on biomedical imaging techniques and analysis followed by b) demonstrating the technical skills of bioimaging using open-source image analysis Fiji will be used to examine, enhance, segment, and quantify provided 3D data.

Description of assessment task

Section A - Core knowledge and literature research skills 

1. Explain in a short paragraph what biomedical image segmentation is and name some factors that can impact it? [3 marks]
2. Name 3 reasons why biomedical image analysis is important in medicine, and expand on each with two-three sentences. [3 marks]

Section B - Technical skills

3. In the tutorial one image was explored, but in the dataset, you have 3 images. You are to:

  1. Apply one general image filter of your choice and explain in 2 sentences why you chose that particular one. - Include a screenshot. [2 marks]
  2. Using the filtered images, apply one thresholding method of your choice, and explain in 2 sentences why you chose that particular one. - Include a screenshot. [2 marks]
  3. Using the thresholded image, use the 3D object counter and measure the vascular volume. - Include a screenshot. [2 marks] 
  4. Repeat for all three images in the dataset and report:
  • The average vascular volume across the three images. [1 mark]
  • The standard deviation of vascular volume across the three images. [1 mark]

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