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Computational Drug Repositioning

The London College, Cranford

Dr. Anum Munir is a PhD computational biologist specialising in multiomics integration and acquired drug resistance. She is the creator of the Resistant Cancer Cell Line (RCCL) database and has authored over 67 peer-reviewed publications in high-impact peer-reviewed journals.

Currently a computational biology/bioinformatics researcher (honorary) at the University of Kent and a lecturer at The London College UCK, Dr Anum has extensive expertise in building bioinformatics pipelines using Python, R, and Bash. Her mentorship focuses on helping clinicians and scientists apply machine learning to solve complex problems in oncology and drug discovery.

Main Areas of Interest

• Computational drug repositioning and repurposing strategies
• Multi-omics integration for target identification
• Network biology and pathway analysis in disease mechanisms
• Systems biology approaches to drug–disease interactions
• Biomarker discovery for therapeutic targeting

Specialties

Computational Biology

Techniques You Will Learn

• Integration of genomics, transcriptomics, and proteomics datasets for drug repositioning
• Construction and analysis of biological networks (gene–gene, protein–protein, drug–target)
• Identification of differentially expressed genes and pathway enrichment analysis
• Use of computational tools and programming (Python/R) for systems-level analysis
• Network-based approaches to identify novel drug targets and repositioning candidates
• Application of machine learning for prioritizing drug–target interactions
• Interpretation of biological and clinical relevance of repositioning findings

Modules

1. Study Design & Data Integration for Drug Repositioning
Overview of drug repositioning concepts and study design. Introduction to multi-omics datasets and strategies for integrating heterogeneous biological data.

2. Network Construction & Systems Biology Approaches
Building and analyzing gene, protein, and drug interaction networks. Understanding disease modules and identifying key regulatory nodes.

3. Target Identification & Drug Prioritization
Using network and omics data to identify potential therapeutic targets. Computational approaches to prioritize existing drugs for new indications.

4. Validation, Challenges & Translational Applications
Interpreting results, validating findings using databases and literature, and understanding challenges in computational drug repositioning. Translating insights into clinically relevant hypotheses.

Program Fee


Total Number of Modules	4
Time duration of Each module	45 minutes
Total Program Cost	$502.5

Who Can Apply

Postgraduate students (Master’s/PhD) in Bioinformatics, Computational Biology, Systems Biology, Biotechnology, or related life sciences
Early-career researchers, postdoctoral fellows, and research scientists interested in drug discovery and repositioning
Professionals from pharmaceutical, biotech, or healthcare sectors involved in computational biology or translational research
Individuals with a foundational understanding of molecular biology, genetics, and disease mechanisms
Basic knowledge of bioinformatics tools, omics data analysis, or network biology is desirable
Prior exposure to programming (Python or R) is beneficial but not mandatory

Host Details

Host Name: Anum Munir

Affiliation: The London College, Cranford

Address: The London College, Cranford

Website URL:

Disclaimer:It is mandatory that all applicants carry workplace liability insurance, e.g., https://www.protrip-world-liability.com (Erasmus students use this package and typically costs around 5 € per month - please check) in addition to health insurance when you join any of the onsite Trialect partnered fellowships.

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