Cheminformatics & Toxicology
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.
| Award Name | Degree - Masters (Level 9 NFQ) |
|---|---|
| NFQ Classification | Major |
| Awarding Body | National University of Ireland |
| NFQ Level | Level 9 NFQ |
| Award Name | NFQ Classification | Awarding Body | NFQ Level |
|---|---|---|---|
| Degree - Masters (Level 9 NFQ) | Major | National University of Ireland | Level 9 NFQ |
Duration
1 year, full-time.
Entry Requirements
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.
Careers / Further progression
Career Opportunities
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.
Further information
Next start date September 2024
6
Fees: EU
€8,890 p.a. (including levy) 2024/25
Fees: Tuition
€8,750 p.a. 2024/25
Fees: Student levy
€140 p.a. 2024/25
Fees: Non EU
€23,000 p.a. (€23,140 including levy) 2024/25
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.
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
Course Outline
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.
Howard Fearnhead, PhD
T: +353 91 495 240
E: howard.fearnhead@universityofgalway.ie
www.universityofgalway.ie/our-research/people/howardfearnhead/