MSc Molecular Pathology of Cancer / Course details

• Explore the key concepts of Personalised Medicine: more precise diagnosis, prognosis and prevention
• Current approaches to identify cancer subtypes that will be more responsive to treatment
• Gain an essential understanding into the ethics of precision oncology
• Gain insights into how molecular profiling is reshaping cancer medicine
• Learn about the value of characterising molecular alterations to aid cancer treatment planning
• Understand the potential barriers to research and the importance of effective community engagement
• Understanding the integration of multi-modal data to predict cancer risk
• Analysing population data to inform individual patient outcome
• Integrating new technologies to improve future data collection

This unit focusses on key principles and discoveries which underpin the drive towards personalised medicine. In the technological era, both biological and genetic understanding and technological capability are evolving at a rapid rate. We will cover current approaches to identify treatment sensitive cancer subtypes, the benefits accessing and integrating big data to inform new personalised strategies and look at innovative approaches to assess cancer risk in specific populations. We will also explore the essential role of patient and public involvement and reflect on the importance of taking steps to address cancer disparities as we strive for precision medicine for all.

Students' learning for the taught element of this course unit is 100% online (distance learning). There will be a combination of online materials provided that students must engage with, including podcasts, videos, lectures and interviews. Students will be able to complete diverse online tasks to monitor and evidence their achievement of the learning objectives. Students will also learn through engaging in directed and independent wider reading. Whilst the majority of this unit will be accessible in an asynchronous manner increasing the agility and flexibility of learning, there will be opportunities to interact with Unit leads and peers during synchronous teaching sessions. We will use online tools to facilitate peer-peer interaction and small group activities.

An important differentiating element of this course unit is the students' requirement to keep a reflective learning journal which will create their portfolio of knowledge enabling direct reference and integration into clinical or research practise. Students will make notes on their day-to-day experiences of key aspects learned within the unit. Through this, they will learn to be present in and conscious of their practice, which will inform their assessment and provide a practice-based context for their learning and assessment.

Students should/will be able to:

• Show an understanding of the key concepts of personalised medicine 
• Gain critical insights into appropriate methodologies and key considerations
• Appraise current approaches to cancer risk stratification
• Understand the ethical considerations attached to personalised medicine

Students should/will be able to:

• Draw on learning to make critical judgement on the current strategies for precision oncology
• Demonstrate efficient and effective problem solving strategies related to population based research
• Analyse and evaluate multi-modal data to identify high risk populations
• Critically reflect on current practise to seek new approaches

Students should/will be able to:

• Plan and execute guided and independent research
• Audit current thinking in the development of precision oncology
• Retrieve relevant, supplementary information from a variety of sources (library, electronic and online)
• Report findings in a concise and structured manner

Students should/will be able to:

• Present findings in a clear and concise way using appropriate media
• Constructively deliver feedback to peers
• Demonstrate independent thinking and evidence integration to formulate hypotheses
• Manage time and show evidence of scheduling tasks in order of importance

Other = Online tests (MCQs): 30%

Feedback will be provided within the required timeframes.