CURRENT AND FUTURE TRENDS IN INDUSTRIAL BIOTECHNOLOGY - 2025/6

Module Overview

The module is directed to the discussion of non-conventional Biotechnological processes and approaches, and the investigation of future directions for the area.

Module provider

School of Biosciences

Module Leader

KIM Youngchan (Biosciences)

Number of Credits: 30

ECTS Credits: 15

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

None

Module content

Indicative content includes:

• Artificial Intelligence in Biotechnology for Drug Discovery.

• Genetic engineering and process optimisation with advanced machine-learning technology.

• Predictive models and Biomarker discovery.

• Biomaterials and Natural products from uncommon sources.

• Enzyme and Protein Engineering.

• AI/ML in protein and small molecule prediction and design.

• Electrobiotechnology and biosensors.

• Waste upcycling, recycling and repurposing.

• Citizen science, biotechnological social movement, Biohacking, DIYbio and Biofoundries Environmental biotechnology ¿ bioremediation & biofuels.

Assessment pattern

Alternative Assessment

None

Assessment Strategy

The assessment strategy for this module will give the students the opportunity to demonstrate their understanding and analytical skills to build specialist knowledge in aspects of the subjects discussed in the lectures.
The summative assessment for this module consists of:

• One essay / literature review discussing the main issues involved in a chosen advanced bioprocess, including limitations and difficulties and how these can be overcome).

• Organisation of a conference style event, done as a group work.

• An oral presentation to discuss the chosen bioprocess.

The presentations will be done following the format of a Scientific Conference, where the students will present their subject in front of an audience composed by students and academics.
Formative assessment and feedback: Tutorials and seminars to discuss the preparation of the essay and the oral presentation. Written and verbal feedback will be given to the students on the draft versions presented.

Module aims

• Present the current status of the biotech industry and critically analyse the criteria used for expanding the scope of the industry.
• Introduce novel approaches such as machine learning and artificial intelligence for the design, analysis and control of bioprocesses for high-value molecules of biotechnological interest.
• Provide first-hand knowledge about the fast advances in biotechnology.

Learning outcomes

Methods of Teaching / Learning

This module consists of lectures and computer practicals given by leading experts, both local lecturers and external speakers, presenting new developments on biotechnology and how the industry has adopted those approaches to satisfy the need for sustainability and net-zero.
A combination of learning and teaching methods will be used: the lectures will be used to start discussion and analysis, and independent study by the students will be encouraged leading to the preparation of a monographic work or report where the analysis and discussion of a bioprocess (existing or imaginary) will be presented.
There will also be tutorials and problem-based sessions for the students to reflect on the information received.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: BMSM045

Other information

The contribution of the module to the 5 pillars can be described as follows
Digital capabilities: This module will present the latest advances in the application of ML and AI for bioprocess design.
Sustainability: Again, the module will highlight the need to design and operate sustainable bioprocesses, representing a contribution to net-zero emissions.
Resourcefulness and resilience: Searching and analysing different bioprocesses in the light of novel strategies will reflect in the organization and planning skills.
Global and cultural capabilities: Lecturers in this module will bring their extensive expertise in operation and application of bioprocesses addressing different needs. This will allow our students to build a flexible and adaptable portfolio of interpersonal skills.
Employability: The use of ML and Ai is currently driving the advances in biotechnology. This, accompanied by the wide range of novel bioprocesses discussed, will give the students a vantage position when looking for jobs.

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.