B.Tech Biotechnology – 7th Semester Syllabus
Biostatistics and Research Methodology:
Introduces statistical tools and research techniques essential for data analysis and interpretation in biotechnology. Topics include hypothesis testing, experimental design, data visualization, regression analysis, and statistical software applications, laying a foundation for scientific research and publication.
Enzyme Engineering:
Focuses on the structure, function, and kinetics of enzymes, along with strategies for enzyme production, purification, immobilization, and modification. Emphasizes industrial applications of enzymes in pharmaceuticals, food processing, and biofuels.
Genetic Resources and IPRs:
Explores the conservation, characterization, and sustainable use of genetic resources, along with a comprehensive understanding of intellectual property rights (IPRs). Covers patents, copyrights, trademarks, biodiversity laws, and regulatory policies that influence biotechnology research and commercialization.
Pharmaceutical Biotechnology:
Covers the biotechnological production of pharmaceutical products such as therapeutic proteins, monoclonal antibodies, and recombinant vaccines. Discusses drug delivery systems, gene therapy, pharmacogenomics, and Good Manufacturing Practices (GMP) in pharmaceutical development.
Summer Internship – II:
A practical training component where students work in a research institute, industrial setup, or biotechnology lab during the summer break. This internship is aimed at providing hands-on experience and exposure to real-world applications of biotechnology.
Departmental Elective – III (Nano Biotechnology):
Offers an in-depth study of the integration of nanotechnology with biotechnology, covering the synthesis and characterization of nanomaterials, nanobiosensors, drug delivery systems, and applications in diagnostics, therapeutics, and agriculture.
Open Elective – III (Introduction to Artificial Intelligence):
Provides foundational knowledge of artificial intelligence (AI), including machine learning, neural networks, and data mining. Focuses on how AI tools can be applied in biological data analysis, bioinformatics, and automation in biotechnology research.
This semester is designed to enhance analytical, technical, and professional competencies by integrating interdisciplinary knowledge with core biotechnological advancements, preparing students for cutting-edge roles in academia, research, and industry.
