MSc Model-based Drug Development - Pharmacokinetic and Pharmacodynamic Modelling

Please apply via our online application form . See the application and selection section for details of the supporting documents we require.

We recommend that you apply as early as possible. We reserve the right to close applications if the course is full.

Contact us at pgtaught.pharmacy@manchester.ac.uk  for more information or if you would like to speak with the course director before applying.

Please make sure you understand the aims of the MSc course and that you have carefully considered your reasons for applying.

Before applying, please make sure all supporting documents are scanned and ready to upload. The documents you will need to supply are:

• evidence of qualifications (certificates or transcripts) to show that you meet, or expect to meet the entry requirements;
• evidence of English language ability, if English is not your first language;
• one reference.

Our MSc Model-based Drug Development course provides the knowledge and skills in pharmacokinetics and pharmacodynamics for making evidence-based decisions at various stages of drug development. It is perfect for students who want to avoid lab work but stay in science.

You will develop your mathematical modelling skills, there are no laboratory or animal-based components. Bioinformatics and molecular modelling are also not part of the course.

It covers the scientific and regulatory aspects of evaluating a drug, with emphasis on the use of mathematical modelling and simulation methods. You will learn why these methods are so highly valued by industry and regulatory authorities as effective, cost-saving, decision-making tools. Learning is reinforced via application of modelling and simulation skills to real pharmacokinetic and pharmacodynamic data.

The course has been developed with an emphasis on mechanistic approaches to assessing and predicting pharmacokinetics and pharmacodynamics (PKPD), such as physiologically-based pharmacokinetics (PBPK).

As this comes under the general umbrella of systems biology, you will be able to apply your knowledge of modelling and simulation in various areas of research within the pharmaceutical industry.

Full-time students benefit from immersion in the varied biomedical research environment at The University of Manchester, including interaction with research staff at the renowned Centre for Applied Pharmacokinetic Research .

Alternatively, part-time students already working in the pharmaceutical industry can take advantage of the flexible, distance learning mode of the course, which allows you to fit study around other commitments.

The aim of the course is to provide specialist knowledge and skills in pharmacokinetics and pharmacodynamics that are highly relevant for a career linked to drug development and pharmaceutical industry.

It is designed for science (physical, biological or health), engineering or mathematics graduates who want to acquire:

• training in pharmacokinetic and pharmacodynamics, with the use of mathematical modelling and simulation methods to guide drug development;
• awareness of the commercial and regulatory factors in drug development;
• understanding of the physiological, chemical, and mathematical foundations used to define the safe and effective use of potential medicines.

The course aims to:

• provide background information on the theory and methods for quantitative assessment of drug absorption, distribution and elimination;
• provide an understanding of the role of pharmacometrics in the process of drug development;
• provide background information on in vitro assays used to characterise ADME properties of new drug entities;
• indicate the mathematical framework that is capable of integrating in vitro information with knowledge of the human body to predict pharmacokinetics;
• provide familiarity and experience of using different software platforms related to pharmacometric data analysis including R, Phoenix, NONMEM, MATLAB, Simcyp,MONOLIX and GastroPlus;
• equip you to reflect upon influential research publications in the field, to critically assess recent published literature in a specific area;
• provide awareness of the elements of a convincing research proposal based on modelling and simulation;
• provide the opportunity to undertake a project and carry out original research.

Distance learning option

Our distance learning option is ideal for scientists linked to the pharmaceutical industry who wish to expand their expertise while working in the industry.

Full-time mode

The full-time mode allows suitably trained mathematics, physical, biological or health science or engineering graduates to focus on obtaining the advanced skills needed for a career in this area. We utilise a blended learning approach in which online learning content is supported by regular face-to-face contact with tutors.

Hands-on learning

Your learning will be reinforced over the duration of the course via application of acquired skills to real pharmacokinetic and pharmacodynamic data using mathematical modelling and simulation techniques.

The course emphasises the development of problem-solving skills. A large portion of the learning involves structured problems requiring you to apply theory of pharmacokinetics and pharmacodynamics, and practical modelling and simulation skills to solve typical problems that arise in drug development.

The following teaching and learning methods are used throughout the course:

• taught lectures;
• computational modelling and simulation workshops;
• self-directed learning to solve given problems;
• webinars and tutorials by leading scientists in industry/academia;
• supervised research;
• mentorship in solving problems and writing the research dissertation;
• independent study.

We assess your achievement of the learning outcomes for this course through:

• unit assignments (submitted electronically);
• unit examinations;
• research project dissertation and oral presentation.

'The course has been an incredibly stimulating and rewarding experience for me. The content has increased and broadened, and in some cases refreshed, my knowledge of the principles and the modelling element. The course provided the hands-on experience I was looking for and fulfilled all my expectations. Balancing the course alongside family and work was certainly a challenge but rewarding, nonetheless. From my perspective the content remains highly relevant to industry and beneficial for those with a variety of experience, either perfect as a career platform or for a change of direction into modelling.'

Simon Taylor, Pharmaron, UK (Part-time student, Sept 2017 -Sept 2019)

Full-time students in residence will have access to general university facilities, including language and library support, computing, and sports facilities.

In addition to regular face-to-face contact with course tutors, residential students are encouraged to take advantage of the academic and cultural environment at Manchester. You will be able to access a range of facilities throughout the University.

Distance learning students interact with staff and students and are supported via an online virtual learning environment that includes webinars, discussion forums, and access to recorded lectures and other learning resources.

You will have access to the most commonly used data analysis platforms such as R, Phoenix, NONMEM, MATLAB, Simcyp, MONOLIX and GastroPlus.

Pharmaceutical companies and government regulatory agencies are recognising the value of pharmacokinetic (PK) and pharmacodynamic (PD) modelling and simulation in making the best use of laboratory and clinical data, guiding and expediting drug development, and saving time and costs.

A range of well-paid jobs exist in this area across the globe. Scientific and industry publications often discuss the current shortage and growing need for modellers.

The full-time course is appropriate for science and engineering graduates who wish to enter the pharmaceutical industry. Career roles for alumni in industry include working on drug development projects, modelling and simulation research, and consultancy. The course also prepares students for further research studies eg PhD.