DRUG DISCOVERY AND MEDICINAL CHEMISTRY - 2023/4

Module Overview

The purpose of this module is to provide a systematic understanding of the physicochemical properties of API, drug action, metabolisms, toxicology effect of drugs, excipients and degradation products as well as methods used to evaluate potential drug candidates and their synthesis. Knowledge obtained in this module will be vital for understanding the overall impact of pharmaceutical sciences as well as how modern technologies, IT and artificial intelligence can work together to develop and deliver safe and effective medicines to patients.

Module provider

Chemistry and Chemical Engineering

Module Leader

DOBBS Adrian (Chst Chm Eng)

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

N/A

Module content

This module can be divided into several subparts with specific topics covered in each and they are:

• Medicinal chemistry topics include structure-activity relationships (SAR), QSAR and modern synthetic techniques, such as fragment-based drug discovery chemistry and diversity-orientated synthesis.


• The expanding role of computational science will be examined through lectures and practical exercises and will examine the use of target analysis, virtual screening for lead discovery, structure-based and ligand-based design methods and the use of computational techniques in library preparation and data handling.


• Drug absorption, distribution, metabolism & excretion (ADME), factors affecting ADME.


• Pharmacokinetics, phase 1 & 2 drug metabolism factors affecting drug metabolism.


• Introduction to experimental toxicology, mechanisms of toxicity (oxidative stress, receptor-mediated toxicity, biopharmaceuticals, nanotoxicology, and genotoxins).

Assessment pattern

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate that they have successfully met the learning outcomes of the module.

 

  Thus, the summative assessment for this module consists of:

• Pharmacokinetics online coursework taken through SurreyLearn, (addresses learning outcome: 4)


• Computational coursework demonstrating the knowledge of computational chemistry and drug development (addresses learning outcomes: 3)


• In-class test on the principles of lecture material covering drug processes and modern medicinal chemistry aspects of drug development and drug metabolism (addresses learning outcomes: 1, 2 and 3)

 

Formative assessment:

Informal formative assessment is conducted throughout the module during IT sessions, workshops and online where students have the opportunity to engage in a variety of activities and to receive both peer and tutor feedback, with the aim of allowing students to assess their progress week by week.

 

Feedback:

Feedback and feedforward on summative assignments will be provided via SurreyLearn. This will indicate what students did well, less well, and what they need to do to improve in the future and will relate both to issues specific to the module and to transferable skills. Formative feedback will be provided throughout the module through in-class discussions and activities, and tutorials.

Module aims

• ¿ Provide a theoretical understanding of the kinetic disposition of drugs and focus on systems of current interest as active research areas and areas of potential drug development.
• ¿ Introduce students to modern techniques involved in the drug discovery process illustrated by case studies.
• ¿ Expand the role of computational science in the development of lead discovery structure-based and ligand-based design methods and the use of computational techniques in library preparation and data handling.
• ¿ Provide an understanding of the enzymology, molecular biology, regulation and chemistry of drug metabolism.
• ¿ Develop an understanding of concepts of pharmacokinetic parameters and grow knowledge about the toxicological tests necessary to evaluate potential toxicity, assess risk and assess safety in the use of pharmaceuticals, food additives, and chemicals in consumer products.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

 

• Reinforce understanding of the drug action and factors influencing the fate of drug one in the human body.


• Enable students to propose and explain the mechanism of action of a pharmacotherapeutic target in a condition of their choice. Students are expected to critically appraise their proposals. 


• Encourage students to engage with modern technologies (computational chemistry) and understand their importance in speeding up the drug discovery process.

 

To achieve this a range of learning environments will be used from lectures where basic concepts will be explained through workshops and IT sessions where the application of the knowledge will happen. Feedback will be provided during the interactive sessions to strengthen the learning process and challenge students to critically evaluate the information and suggest further testing methodologies and propose a new hypothesis. Captured video content and supporting workshops will be another avenue for developing students’ skills. Parts of this module are delivered in a flipped-classroom format. This is to enable students to attend face-to-face sessions with knowledge of the area and enable greater exploration of the depth of the subject and concrete students’ understanding. This method of teaching is particularly useful for such an applied subject. 

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: CHEM043

Other information

Surrey's Curriculum Framework is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following area:

 

Employability: This module allows students to develop their understanding of the key topics within drug discovery and medicinal chemistry in pharmaceutical sciences. Students will be exposed to and will acquire the latest and best available information relating to their subject area. Industrial examples and strategies used in medicinal chemistry will promote in-depth knowledge acquisition. Transferable skills will be addressed as the module allows students to further practice wider attributes that will be attractive to employers in this field. The focus of the assessment strategy will help to prepare students for the realities of the world of work as it allows them to be familiar with time management, reporting and the use of IT to predict and speed up development in the area of medicinal chemistry.  

 

Sustainability: Students will develop their appreciation, understanding and critical thinking focused on the use of green solvents, novel approaches to synthesis that shortens the time of the and energy input. The use of IT and artificial intelligence will enable students to think about shorter and less intense experimental work in delivering the desired outcomes. Furthermore, from a toxicology point of view, no harmful chemicals should be produced limiting the negative impact on human health and the environment. 

 

Digital skills: The module concentrates on practical laboratory skills so will enhance the digital capabilities of the students as they will need to use industry-standard software to make relevant chemical predictions. Computational drug discovery is a major part of the modern drug screening process and students will have a great hands-on experience that will increase their digital capabilities.

 

Resourcefulness and Resilience: The need to solve problems in the practical laboratory, working with complex software design that may not always deliver the intended outcome will increase the resourcefulness and resilience of the students. They will learn how to accept and adapt to these situations and find the correct reasoning procedure to get them out of the dead end and put them back on the right track.

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 2023/4 academic year.