Post Graduate Diploma/Executive Diploma in AI-Enabled Network Pharmacology (PGDANP/EDANP)

The Post Graduate Diploma/Executive Diploma in AI-Enabled Network Pharmacology is an advanced, industry-oriented programme designed to equip participants with modern computational drug discovery skills by integrating pharmacology, bioinformatics, systems biology, artificial intelligence (AI), machine learning (ML), and network-based drug discovery approaches. The programme provides comprehensive theoretical knowledge together with extensive hands-on training using internationally recognised biomedical databases and computational software employed in pharmaceutical industries, biotechnology companies, contract research organisations (CROs), and academic research laboratories.

Participants will learn the complete computational drug discovery workflow—from disease target identification and biomolecular database mining to protein–protein interaction network analysis, pathway enrichment, molecular docking, molecular visualisation, AI-assisted biological interpretation, and scientific publication. The curriculum also introduces participants to modern concepts including multi-target drug discovery, drug repurposing, and computer-aided drug design.

The programme is designed to develop independent research capabilities by enabling participants to design computational research projects, analyse biological datasets, generate publication-quality scientific figures, interpret complex biological networks, prepare scientific manuscripts, and undertake integrated computational drug discovery studies. Upon completion, participants will possess the competencies required for careers in pharmaceutical R&D, computational biology, bioinformatics, AI-driven drug discovery, regulatory science, precision medicine, translational research, and higher academic research.

Programme Modules

International Affiliation with

Module 1. Biomolecules and Cellular Biology

• Biomolecules: carbohydrates, lipids, proteins and nucleic acids
• Cell structure, organelles and membrane organisation
• DNA, RNA, gene expression and protein synthesis
• Enzymes and biological macromolecules as therapeutic targets

Module 2. Fundamentals of Pharmacology

• Drug targets: receptors, enzymes, ion channels and transporters
• Drug–receptor interactions and receptor theories
• Receptor types, agonists, antagonists, partial agonists and inverse agonists
• Signal transduction pathways and second messengers
• Dose–response relationships, potency, efficacy and therapeutic index

Module 3. Foundations of Computational Drug Discovery

• Evolution of computational drug discovery and network pharmacology
• Drug discovery and development workflow
• Systems pharmacology, polypharmacology and precision medicine
• Research design, literature search and hypothesis development
• Research ethics, reproducibility and publication workflow

Module 4. Biomedical Databases and Target Identification

• Disease target identification using GeneCards, OMIM and DisGeNET
• Drug and phytochemical databases: PubChem and ChEMBL
• Protein annotation using UniProt and target prediction using SwissTargetPrediction
• Protein interaction databases (STRING/STITCH)
• Dataset preparation, target filtering and overlapping target identification

Module 5. Network Pharmacology Analysis

• Protein–protein interaction (PPI) network construction using STRING
• Network visualization and analysis using Cytoscape
• Hub gene identification using CytoHubba
• Functional module detection using MCODE
• Network topology analysis and biological interpretation

Module 6. Functional Enrichment and Pathway Analysis

• Gene Ontology (GO) enrichment analysis
• KEGG pathway enrichment analysis
• Functional enrichment using DAVID, Enrichr and g:Profiler
• Biological process and signalling pathway interpretation
• Mechanism of action prediction

Module 7. Molecular Docking and Structure-Based Drug Discovery

• Protein structure retrieval from the Protein Data Bank (PDB)
• Ligand and protein preparation using PubChem, Open Babel and ChimeraX
• Molecular docking using AutoDock Vina
• Protein–ligand interaction analysis using PyMOL and ChimeraX
• Docking interpretation and lead compound selection

Module 8. Integrated Computational Drug Discovery

• Integration of network pharmacology, enrichment analysis and molecular docking
• Therapeutic target prioritisation
• Mechanistic interpretation of computational findings
• Lead compound selection for biological validation
• Critical appraisal of published computational studies

Module 9. Scientific Writing and Research Publication

• Preparation of publication-quality figures and tables
• Scientific writing: Materials & Methods, Results and Discussion
• Reference management and journal selection
• Publication ethics, plagiarism and manuscript submission
• Addressing reviewer comments and manuscript revision

Module 10. Drug Discovery and Development

• Target identification and validation
• Lead identification and lead optimisation
• Preclinical drug development
• Clinical development and regulatory approval
• Drug repurposing and precision medicine

Module 11. Experimental Validation

• Designing in vitro validation studies
• Biomarker and endpoint selection
• Correlation of computational and experimental findings
• Independent capstone research project
• Project presentation and viva voce

Module 12. Industry Case Studies

Module 13: Capstone Project

Eligibility

Graduates in any discipline are eligible for our Post Graduate Diploma, Executive Diploma and Professional Certifications Programmes. 10+2 pass-outs are eligible for our Under Graduate Diploma and Diploma holders of two to three years course duration are also eligible for the PG Diploma.

Programme Duration

The minimum duration to complete the PG diploma programme is 12 months and maximum is 24 months. The minimum duration to complete the executive diploma programme is 6 months and maximum is 12 months.

Programme Mode

Registrations are currently open for regular and Part-time (Online Live Classes) both modes.

Programme Deliverables

A comprehensive study material for all the modules in hard copies ensuring the needs of the participants. The accompanying training material is appropriately aligned with the current Industry’s expectations.

• Interactive or online live sessions on all key areas of the programme giving all flexibility to the participants.
• Online Live Classes/Part-time for all the modules will be conducted on the weekends. Moreover, a doubt clearing session will also be scheduled before the examination.
• All the efforts are made by IGMPI faculty members to make the entire programme modules easily understandable.
• Assessment and evaluation for all the programme modules in order to enhance the levels of competencies and skills of the participants leading towards the objective of application in the job.
• At the end of each programme modules, the trainers shall obtain feedback from the participants using specially designed questionnaires.
• All learning and training delivery initiatives shall be conducted in English.

Examination & Certification

After successful completion, the participants will be awarded Post Graduate Diploma/Executive Diploma in AI-Enabled Network Pharmacology by IGMPI. For all the above-mentioned modules, Online Live Classes/Part-time or face-to-face classes (Regular mode), elaborate programme material, self-assessment assignments would be provided by the Institute. Details get updated on the webpage as well.

Discipline in Classes and Examination

Every student is required to observe a disciplined behaviour during her/his classes, assessments & examinations and to follow instructions from the Professors. Any act of indiscipline may result into discredit & it will be mentioned in her/his academic report.

Placement Assistance & Corporate Relations

For the Post Graduate Diploma and Undergraduate Diploma Programmes, we will provide placement assistance after the completion of the programme. The Institute has partnered with many organizations for providing placement assistance to its students. The robust placement cell comprises senior level Human Resources professionals and Talent Acquisition experts which maintains close links with business and industry. The efforts of our placement cell also include helping with professional resume writing, interview skills & conducting mock interviews etc.

In recent months the Institute has witnessed more and more participation from professionals working with global healthcare like , Jhpiego, SELCO Foundation, TATA Foundation, Samarthan NGO, PSI, UNICEF, WHO, HCL Foundation, IPE Global, Optum, PATH, AIIMS, Action against Hunger, Ekta Shakti Foundation, Seva Foundation, India HIV-AIDS Alliance, HLFPPT, Deepak Foundation, Novartis, LalPath Labs Ltd., Fortis Healthcare Ltd., HealthCare Global Enterprises Ltd., Indraprastha Medical Corporation Ltd., Narayana Hrudayalaya Ltd., Piramal Enterprises Ltd., Wockhardt Ltd., Cactus Communications, Public Health Foundations of India, Cytel, Religare Health Insurance Company Ltd., Deloitte, DuPont Sustainable Solutions, Bain & Company, Alvarez & Marsal, McKinsey & Company, etc. The IGMPI’s Corporate Resource Division actively recommends our students and training participants for various job requirements and specialized roles to Human Resource, Talent Acquisition as well as the heads of various departments in Pharmaceutical, Healthcare industries on regular basis.

Future Career Prospects

The Post Graduate Diploma/Executive Diploma in AI-Enabled Network Pharmacology prepares participants for careers at the intersection of pharmacology, bioinformatics and artificial intelligence. Graduates develop competencies in computational drug discovery, systems pharmacology, molecular docking, network biology, AI-assisted drug design and scientific research, making them highly competitive in the rapidly evolving pharmaceutical and biotechnology sectors.

Career opportunities include positions in pharmaceutical research and development, biotechnology companies, contract research organisations (CROs), bioinformatics and healthcare AI companies, precision medicine programmes, academic and government research institutions, regulatory organisations, computational biology laboratories and translational medicine centres. The programme also provides an excellent foundation for doctoral studies, interdisciplinary research, scientific publications, and careers in AI-driven drug discovery and computational pharmacology.

View Prospectus

Apply Online

Last date for submitting completed Application Form: 20^th Aug 2026.

For further enquiries, call or write to us on:
18001031071 (Toll Free -9:00 am to 5:30 pm IST-except on Central Government holidays)/ info@igmpi.ac.in