This is an integrated pre-intermediate module to establish knowledge of and skills in the theory and laboratory practice associated with bioscience. The module will expand on knowledge in cell biology and biochemistry leading to an understanding of disease mechanisms. This will be integrated with lab-based skills training on methodologies that will support their senior years. The module will include building a code portfolio to support data analysis and implementation of statistical in assessing data to build competency for more advance aspects of data analytics in senior years. Professionalization through writing and presentation (both poster and oral format) will form a theme throughout the module. The skills acquired in this module will provide training for working in a professional scientific environment. The module will prepare students for their first residency through project work on industry provided data and presentation of results in a mini-conference setting.

The module will cover: 1. Enzymology and enzyme kinetics 2. Intermediate spectroscopic methods including Absorbance and fluorescent spectroscopic techniques 3. Intermediate separation and analytical techniques including chromatography and electrophoretic methods 4. Central metabolism 5. Cell signaling 6. Cell cycle - mitosis, meiosis, DNA replication 7. Mendelian and non-Mendelian genetics 8. Cell culture and aseptic technique 9. Immunodetection methods and bioassays 10. Non-communicable disease mechanisms 11. Introduction to metabolomics data and methods to acquire this data 12. Transferable skills including: Intermediate Excel for data handling, technical writing, data presentation skills, informatics, team work and team management. 13. Pre-intermediate bioanalytics including statistical modelling 14. Pre-intermediate scripting for data handling and analysis using R and Python 15. Introduction to working in a regulated environment 16. Regulatory considerations for laboratory work 17. Intermediate Lean practices 18. Entrepreneurship and innovation

On successful completion of this module, students will be able to: 1. Explain enzyme catalysis 2. Distinguish between the different classes of enzyme inhibitor 3. Demonstrate data handling for determination of enzyme parameters and inhibition mechanisms 4. Create a code to perform a Lineweaver-Burke analysis of enzyme kinetic data. 5. Explain how cells harvest energy from metabolism 6. Describe the 3 key stages of central metabolism 7. Predict the impact of defective enzymes at different points in central metabolism 8. Specify, describe and distinguish the different signaling mechanisms employed by cells 9. Compare and differentiate between mitosis and meiosis 10. Describe DNA replication 11. Explain the basis of Mendelian inheritance 12. Describe and explain non-Mendelian inheritance 13. Interpret data to determine inheritance patterns 14. Create a code for analysis of data for determination of linked vs unlinked Mendelian inheritance 15. Create a code for data input and perform pre-intermediate statistical analysis 16. Demonstrate how to grow mammalian cells in culture 17. Describe the molecular basis for three different classes of non-communicable diseases 18. Evaluate the quality of new scientific information

On successful completion of this module, students will be able to: 1. Appreciate the rigors of correct scientific procedures 2. Value the importance of aseptic techniques 3. Display a professional manner when performing laboratory experimentation 4. Appreciate and implement Lean working habits 5. Cooperate in teamworking activities

On successful completion of this module, students will be able to: 1. Operate basic scientific equipment. 2. Demonstrate competency to Good Laboratory Practice (GLP) standard. 3. Execute cell culture experimentation with good aseptic technique. 4. Perform a scientific experiment.

The module will be taught through a series of tutorials, workshops and lab practice sessions employing techniques in active learning (Bloom's Taxonomy levels). The module will use self-directed team learning focused on problem-based learning. The students will work in teams to extract information on syllabus topics and incorporate those into presentations for peer-learning. Workshop-style delivery of new material to the student will be used in conjunction with supervised and non-supervised group work. Use will be made of computer-based learning tools and self-testing. Laboratory practice will focus on mastery of a toolbox of essential basic skills which will be taught by small group demonstration and practice. Self-directed practical learning will be supported. Learning will involve students integrating aspects of theory, practice, coding, analytics and professional skills. Team based project work on the analysis of Industry provided data will form the basis of a self-organized mini-conference.