Spectroscopic Analysis Methods II

Overview

Summary of Lecture Content:

• Advanced data processing
• Advances in Mass Spectrometry
• AI & Automation in Analytical Science
• Process Analytical Technology (PAT) & Real-Time Monitoring
• Miniaturised & Portable Analytical Devices
• Peptide and protein characterisation (1)
• Peptide and protein characterisation (2)
• Green Analytical Chemistry & Sustainable Methods
• Titrations
• Electrochemistry and Electrochemical Biosensors (1)
• Electrochemistry and Electrochemical Biosensors (2)
• Detection of counterfeit medications

Summary of Practical Content:

• Practical 1: Data processing
• Practical 2: Electrochemistry

Learning Objectives

At the end of the module students will be able to:

• Critically evaluate emerging technologies in pharmaceutical analysis, including AI, automation,
portable devices, and real-time monitoring systems.
• Apply data processing techniques to analyse, interpret, and visualise complex datasets
generated from advanced analytical instrumentation.
• Assess the principles and applications of electrochemical methods and biosensors for
pharmaceutical detection, including their use in sustainability and counterfeit detection.
• Demonstrate an understanding of modern bioanalytical techniques, including mass
spectrometry and protein/peptide characterisation approaches.
• Evaluate the principles of green analytical chemistry and propose more sustainable analytical
workflows in pharmaceutical analysis.
• Apply practical and theoretical knowledge to contemporary challenges in pharmaceutical
analysis, including quality control, authenticity testing, and regulatory compliance.

Skills

Skills associated with module:
 Ability to process, interpret, and visualise complex analytical data using advanced software and digital tools.
 Understanding and critical appraisal of cutting-edge technologies (e.g. AI, PAT, portable devices) and their application in modern pharmaceutical analysis.
 Capability to incorporate green chemistry principles and ethical considerations (e.g. counterfeit detection) into analytical strategies and decision-making.

Assessment

Assessment Profile
Element type Element weight (%)
Coursework 100

Course Requirements:

• Coursework submission 100 %
• Laboratory Class attendance 100 %
• Total coursework elements must be passed at 50%.