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Industry Academia Collaboration

Life Sciences Informatics Lab

Where Biology Meets Technology. Decode Life with Data.

About the Industry Partner — Bioxplora

Bioxplora is a specialist life sciences informatics training organisation operating at the intersection of biology, data science, and artificial intelligence. Their trainers bring active domain experience in pharmaceutical informatics, medical coding, and AI-driven biological research — delivering training grounded in real industry tools and career pathways. Through their partnership with KGCAS, Bioxplora deploys dedicated industry trainers across three focused lab modules in Semesters III, IV, and VI.

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About the Life Sciences Informatics Lab

A purpose-built, industry-integrated lab within the School of BioSciences at KGCAS, exclusively for B.Sc. Biotechnology students. Students work with professional-grade tools — including RDKit, Open Babel, molecular visualisation platforms, ICD-10/CPT medical coding systems, and Python-based AI environments — using real chemical, genomic, and clinical datasets across three targeted semesters, each addressing a distinct high-value career pathway in the life sciences sector.

Why This Course?

Industry trainers deliver every session — active life sciences informatics professionals, not generalists

Three focused modules: Cheminformatics & Drug Discovery → Medical Coding → AI in Life Sciences

Biotechnology graduates with computational skills are significantly more competitive across pharma, healthcare IT, and medical research

Medical Coding offers one of the most stable and accessible career pathways for life sciences graduates in India's growing healthcare IT sector

AI in Life Sciences is among the fastest-growing areas globally — from drug discovery to genomic analysis and personalised medicine

Bioxplora's domain-specific expertise ensures training reflects real life sciences industry applications

Learning Journey

Cybersecurity Semester Plan
Semester Focus Area
Semester III Cheminformatics
Semester IV Medical Coding
Semester VI AI in Life Sciences

Course curriculum

III
Semester IIII
Cheminformatics
Introduction to cheminformatics — what it is, where it fits in the drug discovery pipeline, and why it matters
Chemical data representation — SMILES notation, InChI strings, and molecular file formats
Chemical databases — PubChem, ChEMBL, and ZINC — navigating, querying, and extracting chemical data
Molecular descriptors — calculating and interpreting physicochemical properties of compounds
Structure-Activity Relationship (SAR) and Quantitative SAR (QSAR) — fundamentals and applications in drug design
Molecular similarity and diversity — fingerprinting methods and similarity searching
Virtual screening — ligand-based and structure-based approaches to identifying drug candidates
Cheminformatics tools — RDKit, Open Babel, and related platforms for chemical data handling
Introduction to molecular visualisation — PyMOL and related tools for viewing and analysing molecular structures
Project — a cheminformatics workflow applied to a real chemical dataset — from data retrieval and descriptor calculation through similarity analysis and QSAR modelling
IV
Semester IV
Medical Coding
Introduction to medical coding — what it is, how it works, and its role in the healthcare industry
Healthcare documentation and the medical record — understanding clinical notes, diagnoses, procedures, and terminology
ICD-10-CM — International Classification of Diseases coding system — structure, conventions, and application
CPT coding — Current Procedural Terminology — understanding procedure codes for physician services
HCPCS coding — Healthcare Common Procedure Coding System — Level II codes and their applications
Medical terminology for coders — anatomy, physiology, pharmacology, and clinical terminology relevant to accurate coding
Coding guidelines — inpatient vs outpatient coding rules, principal diagnosis selection, and sequencing
Insurance and reimbursement — how medical codes drive billing, claims processing, and healthcare revenue cycles
Coding compliance and ethics — avoiding fraud, understanding auditing, and maintaining coding accuracy
Practical coding exercises — applying ICD-10, CPT, and HCPCS codes to real clinical scenarios and case studies
Certification preparation — introduction to CPC (Certified Professional Coder) and CCA (Certified Coding Associate) examination formats
VI
Semester V
AI in Life Sciences
Introduction to AI in life sciences — the current landscape, key applications, and the future of biology-driven AI
Machine learning fundamentals for life scientists — supervised, unsupervised, and reinforcement learning concepts
Python for life sciences AI — key libraries including NumPy, Pandas, Scikit-learn, and Biopython
AI in drug discovery — target identification, lead optimisation, and de novo drug design using machine learning
Genomics and AI — sequence analysis, variant calling, and gene expression analysis using computational tools
AI in medical imaging — how deep learning is applied to radiology, pathology, and diagnostic imaging
Natural language processing (NLP) in healthcare — extracting insights from clinical notes, medical literature, and electronic health records
Personalised medicine and AI — how patient data, genomics, and machine learning are converging toward precision healthcare
AI ethics in life sciences — data privacy, algorithmic bias, regulatory frameworks, and responsible AI in healthcare
Hands-on project — an end-to-end AI application in a life sciences context — from dataset preparation and model building through to result interpretation and presentation

Certifications & Outcomes

Students completing the lab modules are prepared for industry-relevant certifications in medical coding, cheminformatics, and AI in life sciences, aligned with Bioxplora's training framework and communicated to students at the start of each relevant semester.

Roles students are equipped for:

01

Medical Coder — Hospital, Insurance & Healthcare BPO

02

Cheminformatics Analyst — Pharmaceutical & Drug Discovery

03

Bioinformatics Research Associate

04

Healthcare IT Analyst

05

AI in Healthcare Associate

06

Clinical Data Analyst

07

Pharmacovigilance Associate

08

Life Sciences Data Scientist (with experience)

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