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Cheminformatics and Toxicology (MSc)
Cheminformatics is the use of computational techniques to solve chemistry, pharmacology and toxicology problems. Students will understand and apply a range of computational tools to address toxicological questions in preparation for a career in in silico toxicity prediction in the pharma, industry, consultancy, academia and government. The course is delivered over one year by the disciplines of Pharmacology and Therapeutics, Mathematics and Chemistry.
What makes this course unique ...
- Integrated training in toxicology and computational approaches (analytics) to develop a highly marketable skill-set for a career in the Pharma industry or organizations that regulate chemical safety
- Guest lecturers from regulators and industry that teach from "real-life" cases and that can provide career development advice
- An independent research project focussed on solving real world toxicity/toxicity assessment problems
Find out about our Postgraduate Scholarships here.
Applications and Selections
Applications are made online via the University of Galway Postgraduate Applications System.
A shortlisting procedure will be applied that evaluates:
- Undergraduate academic performance throughout their time at university
- The content and quality of their personal statement
- Prior research or work experience
- Reference letters
The ideal student will have a BSc or MSc in chemistry with an interest in toxicology, and computational approaches to toxicity prediction. Students with a background in Pharmacology or Bio-informatics (or related disciplines) will also be encouraged to apply.
Who Teaches this Course
- Professor Cathal Seoighe
- Dr Pilib Ó Broin
- Dr Aaron Golden
Biomedical Sciences Building
Upper Newcastle Road
Pharmacology & Therapeutics
Human Biology Building
Requirements and Assessment
Primary degree: A 2.2 degree or higher (or equivalent) in Chemistry, Pharmacology, Biochemistry, or a related discipline.
Language skills: An IELTS score of 6.5 or greater in all categories is required.
Recognition of Prior Learning (RPL)
1 year, full-time
Next start date
A Level Grades ()
QQI/FET FETAC Entry Routes
Please view the offer rounds website.
Mode of study
The course is delivered over three semesters. In Semester 1 students learn the fundamentals of pharmacology, toxicology and are introduced to computational drug-design, programming for biology and statistical computing in R. This forms a foundation for more advanced material explored in Semester 2.
In Semester 2 students consider more advanced concepts in toxicology and investigate controversial areas of toxicology. They also develop a theoretical and a practical understanding of high through put and high content screening technologies that are used to generate large data sets for analysis. The students also learn to apply bioinformatic and cheminformatic tools to such large data sets. This semester equips the students to develop and test a novel hypothesis through independent research that is completed in the third semester.
In Semester 3 students work independently but with the guidance of an academic or industry-based thesis supervisor on a cheminformatics research project.
The course involves lectures, laboratory-based training, self-directed learning and a three month independent research project. Competence is assessed through a mixture of written examinations, computer-based examinations, course work (including verbal presentations and poster presentations) and a research thesis.
Curriculum InformationCurriculum information relates to the current academic year (in most cases).
Course and module offerings and details may be subject to change.
Glossary of Terms
- You must earn a defined number of credits (aka ECTS) to complete each year of your course. You do this by taking all of its required modules as well as the correct number of optional modules to obtain that year's total number of credits.
- An examinable portion of a subject or course, for which you attend lectures and/or tutorials and carry out assignments. E.g. Algebra and Calculus could be modules within the subject Mathematics. Each module has a unique module code eg. MA140.
- Some courses allow you to choose subjects, where related modules are grouped together. Subjects have their own required number of credits, so you must take all that subject's required modules and may also need to obtain the remainder of the subject's total credits by choosing from its available optional modules.
- A module you may choose to study.
- A module that you must study if you choose this course (or subject).
- Required Core Subject
- A subject you must study because it's integral to that course.
- Most courses have 2 semesters (aka terms) per year, so a three-year course will have six semesters in total. For clarity, this page will refer to the first semester of year 2 as 'Semester 3'.
Year 1 (90 Credits)Required PM208: Fundamental Concepts in Pharmacology - 5 Credits - Semester 1
Required PM311: Introduction to Toxicology - 5 Credits - Semester 1
Required MA5108: Statistical Computing with R - 5 Credits - Semester 1
Required PM5108: Applied Toxicology - 5 Credits - Semester 1
Required MA5114: Programming for Biology - 5 Credits - Semester 1
Required CH5106: Computational Approaches to Drug Design and Biomolecular Structure - 5 Credits - Semester 1
Optional RPL005: Recognised Prior Learning - 5 Credits - Semester 1
Optional RPL010: Recognised Prior Learning - 10 Credits - Semester 1
Optional BI5107: Introduction to Molecular and Cellular Biology - 5 Credits - Semester 1
Optional BI5108: Green Lab Principles and Practice - 5 Credits - Semester 1
Required PM5114: Screening Molecular Libraries - 5 Credits - Semester 2
Required MA5118: Advanced Chemoinformatics - 5 Credits - Semester 2
Required PM5112: Research Project in Toxicology - 30 Credits - Semester 1
Required MA324: Introduction to Bioinformatics (Honours) - 5 Credits - Semester 2
Required PM5111: Advanced Toxicology - 5 Credits - Semester 2
Required PM5110: Current Topics in Toxicology - 10 Credits - Semester 2
Optional REM506: Independent Study Module - 5 Credits - Semester 2
Why Choose This Course?
It costs approximately $1bn and 10–20 years to get a drug from conception to market. While many candidate molecules enter the drug development pipeline, most will fail to become drugs, mainly due to unexpected toxicity. The failure to identify toxicity early in the development process costs the pharmaceutical industry billions of dollars in either failed clinical trials or in withdrawing drugs from the market. At the same time national and trans-national regulatory bodies work to identify the toxicity of chemicals used in food-stuffs, consumer products, industry and agriculture with the aim of building a chemically safe society. Consequently the global ADME toxicology testing market, which aims to identify potential toxicity is projected to surpass $16.2 billion by 2024. In an era when Pharma investment in research and development is falling, scientists to develop and use computational tools that better predict toxicity are at a premium. The value of these skills is further enhanced by the scarcity of training programmes to produce toxicologists with the appropriate computational skills.
Graduates from the course will be employed in the Pharmaceutical industry, the Cosmetics Industry, National and EU Regulatory bodies, Toxicology Consultancies and academia.
Who’s Suited to This Course
Transferable Skills Employers Value
Related Student Organisations
Fees: Student levy
Fees: Non EU
Postgraduate students in receipt of a SUSI grant—please note an F4 grant is where SUSI will pay €4,000 towards your tuition (2024/25). You will be liable for the remainder of the total fee. A P1 grant is where SUSI will pay tuition up to a maximum of €6,270. SUSI will not cover the student levy of €140.
Postgraduate fee breakdown = Tuition (EU or NON EU) + Student levy as outlined above.
Note to non-EU students: learn about the 24-month Stayback Visa here
Find out More
Howard Fearnhead, PhD
T: +353 91 495 240