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MSc Model-based Drug Development

Year of entry: 2020

Overview

Degree awarded
MSc
Duration
12 months FT, 29 months PT
Entry requirements

We require an UG honours degree (minimum Lower Second or equivalent) from a reputable internationally-recognised institution in:

  • Pharmaceutical sciences;
  • Biomedical sciences;
  • Pharmacology;
  • Chemistry;
  • Engineering;
  • Mathematics;
  • Statistics.

Full entry requirements

Number of places/applicants
15 places
How to apply

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.

Course options

Full-time Part-time Full-time distance learning Part-time distance learning
MSc Y N N Y

Course overview

  • Qualify as a modeller with key skills in computational approaches in pharmacokinetics and pharmacodynamics.
  • Study at a university ranked 5th in the UK for Pharmacy and Pharmacology (QS World University Rankings 2020).
  • Undertake full-time learning or fit study around other commitments with our part-time option.
  • Benefit from workshop sessions by applying the skills you develop to real-world data.

Open days

Attending an open day is a great way to find out what studying at Manchester is like. Find out about our upcoming open days .

You can also watch a webinar recording from our recent virtual open week about studying pharmacy at postgraduate taught level: Introduction to pharmacy (video).

See more sessions from the postgraduate taught virtual open week .

Fees

For entry in the academic year beginning September 2020, the tuition fees are as follows:

  • MSc (full-time)
    UK/EU students (per annum): £14,000
    International students (per annum): £27,000
  • MSc (part-time distance learning)
    UK/EU students (per annum): £7,000 per annum
    International students (per annum): £13,500

The fees quoted above will be fully inclusive for the course tuition, administration and computational costs during your studies.

All fees for entry will be subject to yearly review and incremental rises per annum are also likely over the duration of courses lasting more than a year for UK/EU students (fees are typically fixed for International students, for the course duration at the year of entry). For general fees information please visit: postgraduate fees . Always contact the department if you are unsure which fee applies to your qualification award and method of attendance.

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Scholarships/sponsorships

Alumni Bursary

The Faculty of Biology, Medicine and Health (School of Health Sciences) offers an alumni bursary of a 10% reduction towards tuition fees for successful applicants who are recent University of Manchester graduates and who are commencing one of our postgraduate taught master's programmes in 2020.

The bursary is available to students or alumni who:

  • have graduated since 2015;
  • are registered for an MSc, PGDip or PGCert course at Manchester;
  • hold a first class or 2:1 honours degree;
  • have home or overseas fee status;
  • are applying for full- or part-time study;
  • are self-funded and not in receipt of any other funding support.

The bursary will be applied as a fee reduction automatically for those students and alumni who meet the alumni bursary criteria so there is no application process.

Contact details

School/Faculty
Faculty of Biology, Medicine and Health
Email
Website
https://www.bmh.manchester.ac.uk/pharmacy/
School/Faculty
Faculty of Biology, Medicine and Health

Courses in related subject areas

Use the links below to view lists of courses in related subject areas.

Entry requirements

Academic entry qualification overview

We require an UG honours degree (minimum Lower Second or equivalent) from a reputable internationally-recognised institution in:

  • Pharmaceutical sciences;
  • Biomedical sciences;
  • Pharmacology;
  • Chemistry;
  • Engineering;
  • Mathematics;
  • Statistics.

English language

English language students whose first language is not English require a minimum of one of the following:

  • IELTS: 6.5 with at least 6.0 in writing
  • Internet-based TOEFL: 90 with a minimum of 22 in each component.

We may also accept evidence of a confirmed place on a University pre-sessional English language course if your current IELTS scores are:

  • minimum 6.0 overall with 6.0 in writing plus enrolment and attendance on the 5-week pre-sessional course (PS5);
  • minimum 5.5 overall with 5.5 in writing plus enrolment and attendance on the 10-week pre-sessional course (PS10).

See further information about requirements for your country .

English language test validity

Some English Language test results are only valid for two years. Your English Language test report must be valid on the start date of the course.

Application and selection

How to apply

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.

Advice to applicants

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;
  • two references.

How your application is considered

Applicants are considered based on their educational background and professional experience. You may be required to attend an interview.

Re-applications

If you applied in the previous year and your application was not successful you may apply again. Your application will be considered against the standard course entry criteria for that year of entry. In your new application you should demonstrate how your application has improved. We may draw upon all information from your previous applications or any previous registrations at the University as a student when assessing your suitability for your chosen course.

Course details

Course description

Our MSc Model-based Drug Development course provides the knowledge and skills for making evidence-based decisions at various stages of drug development.

It covers the scientific and regulatory aspects of evaluating a drug, with emphasis on the use of 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.

Aims

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

It is designed for science, engineering or mathematics graduates who want to acquire:

  • 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;
  • training in the use of mathematical modelling and simulation methods to guide drug development.

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, and MONOLIX;
  • 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.

Special features

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, 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 modelling and simulation techniques.

Additional course information

The course focuses on the following topics.

  • Pharmacokinetics: addressing how a drug dose is administered to the body and the fate of drug molecules that enter the body.
  • Pharmacodynamics: addressing the chemical and physiological response of the body to drug.
  • Pharmacometrics: the science that quantifies drug, disease and trial information to aid efficient drug development and/or regulatory decisions (definition used by the US FDA).
  • Systems pharmacology: analysis of interactions between drug and a biological system, using mathematical models.
  • In vitro: in vivo extrapolation using physiologically based pharmacokinetic models (IVIVE-PBPK).

Teaching and learning

The course emphasises the development of problem-solving skills. A large portion of the learning involves structured problems requiring you to apply theory and practical 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.

Coursework and assessment

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

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

Course unit details

Year 1 (full-time)

Term 1 

  • Introduction to clinical trials (15 credits). This online unit provides an overview of the drug development process followed by in-depth coverage of scientific, statistical and regulatory considerations in the design and interpretation of clinical trials.
  • Basic Pharmacokinetics and Pharmacodynamics (15 credits). This unit provides information on how drugs get into the body, how they get around the body and how they are removed from the body
  • In Vitro - In Vivo Extrapolation in ADME (15 credits). The applications of modelling and simulation have been limited to the so-called phase I-III of drug development. This unit provides information on modelling and simulation as applied to extrapolating data from in vitro systems to the in vivo conditions (IVIVE) prior to phase I.
  • Biostatistics in Clinical Trials (15 credits). This unit is designed to give the student an understanding of fundamental statistical concepts that are routinely used in designing clinical trials or interpreting trial results.

Term 2 

  • Data Analysis in PKPD (30 credits). This addresses the specialised area of modelling that combines mathematical and statistical knowledge in data fitting with the sound knowledge of the human body as a system. The unit emphasises the value and implementation of mechanistic models. You will be introduced to different types of modelling packages and learn how to choose which package is best for a given application.
  • Advanced topics in modelling and simulation (15 credits). This unit focuses on the elements that make up a successful modelling and simulation project. We consider the scientific and commercial rationale for undertaking a modelling project, and how these rationales then guide the project design. After reviewing case studies which illustrate the characteristics of a successful project, you will create a research proposal on a topic of current importance in the general area of modelling, simulation and data analysis. The primary aim should be to identify a gap in knowledge and investigate this area by proposing a detailed research project.
  • Advanced topics in Physiologically-based PK models (15 credits). This unit provides further training on the use of mechanistic pharmacokinetic models, which use mathematical descriptions of physiological processes to predict the fate of drug molecules within the human body. The unit addresses two key aspects of IVIVE: 1) developing mathematical representation of key chemical and physiological processes that affect drug molecules in the body, and 2) defining the relationships that link these processes.

 Term 3

  • Supervised research project/dissertation (60 credits). This unit follows on directly from the research proposal in modelling and simulation (PHAR69924). You will require both an academic and an industrial supervisor and will carry out the research project (typically at a place of work) proposed in PHAR69924.

Course content for part-time mode

If you are planning to complete the course in 29 months, the content will be delivered in the following sequence:

Year 1

  • Basic Pharmacokinetics and Pharmacodynamics (PKPD)
  • Biostatistics in Clinical Trials
  • Data Analysis in PKPD

Year 2

  • Introduction to Clinical trials
  • In Vitro - In Vivo Extrapolation in ADME
  • Advanced topics in modelling
  • Advanced topics in Physiologically-based PK models

Supervised research project/dissertation

Course unit list

The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.

TitleCodeCredit ratingMandatory/optional
Supervised Research Project on M&S - Dissertation PHAR69920 60 Mandatory
Basic Pharmacokinetics and Pharmacodynamics PHAR69921 15 Mandatory
PBPK and In Vitro In Vivo Extrapolation (IVIVE) (1) Fundamental Concepts PHAR69922 15 Mandatory
Data Analysis in Pharmacokinetics and Pharmacodynamics PHAR69923 30 Mandatory
Advanced Research Topics and Project Development in Modelling and Simulation PHAR69924 15 Mandatory
Biostatistical concepts in clinical trials PHAR69931 15 Mandatory
PBPK and IVIVE 2 Advanced Concepts and Applications PHAR69932 15 Mandatory
Introduction to Clinical Trials (CT1) PHAR72010 15 Mandatory

Facilities

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 and MONOLIX.

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service .

Careers

Career opportunities

This course was originally developed for scientists working within the pharmaceutical industry who wished to qualify as modellers with hands-on experience. The qualification will enhance your abilities within your current role or provide you with skills to progress into new posts.

The course is also appropriate for science and engineering graduates who wish to enter the industry. The role of modelling and simulation or pharmacometrics is assuming greater and greater importance in the pharmaceutical industry.

Pharmaceutical companies and government regulatory agencies are recognising its value in making best use of laboratory and clinical data, guiding and expediting 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.