| Course Name | Proteomics in Clinical Diagnostics |
| Course Code | 25CMD504 |
| Program | M. Sc. in Advanced Clinical and Molecular Diagnostics |
| Semester | 1 |
| Credits | 3 |
| Campus | Faridabad |
Unit 1:
Introduction to Clinical Proteomics, Overview of proteomics and its role in clinical diagnostics, Proteome complexity and dynamic range, Comparison with genomics and transcriptomics in clinical contexts, Key challenges and opportunities in clinical proteomics.
Unit 2:
Sample Collection and Preparation, Types of clinical samples: blood, serum, plasma, urine, tissue, etc., Protein extraction, quantification, and depletion strategies, Sample storage, handling, and preservation protocols.
Unit 3:
Mass Spectrometry and Proteomic Platforms, Fundamentals of mass spectrometry in proteomics, Techniques: MALDI-TOF, LC-MS/MS, and Orbitrap, Label-free vs. label-based quantification methods, Data acquisition and interpretation tools.
Unit 4:
Protein Profiling and Biomarker Discovery, Approaches for differential protein expression analysis, Discovery, validation, and qualification of biomarkers, Proteomic signatures for disease diagnosis, prognosis, and monitoring, Use of bioinformatics in clinical data mining and analysis.
Unit 5:
Translational and Clinical Proteomics, Workflow for moving from bench to bedside, Clinical assay development and validation, Case studies in oncology, cardiology, infectious disease, and neurology, Integration with other ‘omics’ and personalized medicine initiatives.
Unit 6:
Quality Control, Standardization, and Regulatory Aspects, Good Laboratory Practices (GLP) and quality assurance in clinical proteomics, Standardization of protocols and inter-laboratory reproducibility, Regulatory requirements for proteomic diagnostics (e.g., FDA, CLIA), Future trends: automation, AI integration, and next-generation proteomics.
(45 classes)
Preamble
Proteomics in clinical diagnostics focuses on the principles and clinical applications of proteomic technologies in diagnostics. The course covers sample preparation, mass spectrometry, protein profiling, and biomarker discovery for disease diagnosis and prognosis. Emphasis is placed on translational proteomics and quality control in clinical testing environments.
Course outcomes
CO1: Understand the role and challenges of proteomics in clinical diagnostics.
CO2: Master sample collection, preparation, and storage techniques for proteomics.
CO3: Learn mass spectrometry techniques and proteomic platforms for analysis.
CO4: Analyze protein profiles and identify biomarkers for disease diagnosis.
CO5: Apply translational proteomics and integrate it with personalized medicine.
CO6: Implement quality control, standardization, and regulatory practices in clinical proteomics.
Program outcome
PO1: Bioscience Knowledge
PO2: Problem Analysis
PO3: Design/Development of Solutions
PO4: Conduct Investigations of complex problems
PO5: Modern tools usage
PO6: Bioscientist and Society
PO7: Environment and Sustainability
PO8: Ethics
PO9: Individual & Team work
PO10: Communication
PO11: Project management & Finance
PO12: Lifelong learning
0 – No affinity; 1 – low affinity; 2 – Medium affinity; 3 – High affinity
| COs | PO1 | PO2 | PO3 | PO4 | PO5 | PO6 | PO7 | PO8 | PO9 | PO10 | PO11 | PO12 |
| CO1 | 3 | 3 | 2 | 2 | 3 | 2 | 1 | 2 | 1 | 2 | 2 | 3 |
| CO2 | 3 | 3 | 2 | 3 | 2 | 1 | 1 | 2 | 1 | 2 | 1 | 3 |
| CO3 | 3 | 2 | 3 | 3 | 3 | 1 | 1 | 2 | 2 | 2 | 1 | 2 |
| CO4 | 3 | 3 | 3 | 3 | 3 | 2 | 2 | 2 | 1 | 2 | 2 | 3 |
| CO5 | 3 | 3 | 3 | 3 | 3 | 2 | 1 | 3 | 1 | 2 | 2 | 3 |
| CO6 | 3 | 2 | 2 | 3 | 2 | 3 | 1 | 3 | 2 | 2 | 1 | 3 |
Program-specific outcome
PSO 1 – Emerging technologies in clinical diagnostics
PSO 2 – Biomolecules in Medicine
PSO 3 – Molecular dysregulation in diseases
PSO 4 – Molecular technology in diagnosis and therapy
PSO 5 – Applying lab discoveries to clinical practice
PSO 6 – Microorganisms in Medicine
PSO 7 – Statistical methods to interpret and validate diagnostic results
PSO 8 – Integrate molecular diagnostics into personalized medicine
PSO 9 – Compounds as biomarkers and its specificity
PSO 10 – Bioinformatics and biological data use
0 – No affinity; 1 – low affinity; 2 – Medium affinity; 3 – High affinity
| CO | PSO1 | PSO2 | PSO3 | PSO4 | PSO5 | PSO6 | PSO7 | PSO8 | PSO9 | PSO10 |
| CO1 | 3 | 2 | 2 | 3 | 3 | 1 | 1 | 3 | 2 | 2 |
| CO2 | 3 | 3 | 2 | 3 | 3 | 2 | 2 | 3 | 2 | 1 |
| CO3 | 3 | 3 | 3 | 3 | 3 | 2 | 1 | 3 | 2 | 2 |
| CO4 | 3 | 3 | 3 | 3 | 3 | 2 | 1 | 2 | 3 | 3 |
| CO5 | 3 | 2 | 3 | 3 | 3 | 1 | 1 | 3 | 3 | 2 |
| CO6 | 2 | 2 | 2 | 3 | 3 | 3 | 1 | 2 | 2 | 3 |
Textbook:
Levine KE, Cotter RJ. Proteomics in Domestic Animals: From Farm to Systems Biology. 1st ed. Hoboken (NJ): Wiley-Blackwell; 2011.
Reference Book:
Hamdan M. Proteomics for Biomarker Discovery: Methods and Protocols. 1st ed. New York (NY): Springer; 2017.
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