Outline

Overview

Do you want to be the designer of the next billion dollar drug? In this unit of study you will apply your foundational knowledge and skills in medicinal chemistry and pharmacology to understand the discovery, design and development of major drug classes. You will gain knowledge into what makes a good drug target and how to design a new drug from lead drug identification to target optimisation. Drugs targeting a wide variety of genes, proteins, enzymes and receptors are explored through practicals and tutorials on molecular modelling and structure-activity relationships. The course also extends to a section on the design of diverse pharmacological agents, including compounds for imaging by positron emission tomography (PET) and drug applications based on proteomic and genomic big data. You will be set special advanced assignments related to the material covered in core areas. These may also involve advanced practical work or detailed investigation of a theoretical problem. This unit of study is highly recommended for students interested in careers in drug discovery and development including pharmaceutical industry, government, and medical research pathways.

Unit details and rules

Academic unit	Pharmacy
Credit points	6
Prerequisites ?	a mark of 70 or above in {(PCOL2011 or PCOL2021 or MEDS2002) or [BMED2401 and 6cp from (BMED2402 or BMED2405)] or 12cp from BCMB2XXX}
Corequisites ?	None
Prohibitions ?	PCOL3012
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Pegah Varamini, pegah.varamini@sydney.edu.au
Lecturer(s)	Pegah Varamini, pegah.varamini@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Take-home extended release)	Final examination Examination including written questions	50%	Formal exam period	48 hours
Outcomes assessed:
Online task	Online quiz Multiple choice questions	5%	Progressive	10 MCQs / 15mins
Outcomes assessed:
Tutorial quiz	Online Canvas lecture/tutorial quiz Multiple choice	15%	Week 07	40 minutes during online lecture slot
Outcomes assessed:
Presentation	Individual drug: oral Oral presentation	7.5%	Week 09	3 min presentation + 2 min questions
Outcomes assessed:
Assignment	Individual drug: worksheet One page based on template completed in the class.	7.5%	Week 09	One page based on template
Outcomes assessed:
Assignment	Discipline project report Written assessment with contribution assessed through Spark Plus.	15%	Week 10	8–12 pages, 1.5 spacing and 2cm margins
Outcomes assessed:
= group assignment ? = Type E final exam ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Information is clearly planned, presented logically, & well integrated; sophisticated grasp of the principles & interpretation including the possibility of theorizing/hypothesizing (evidence of originality of thought); references beyond lab material, lectures, textbooks and learning topics.
Distinction	75 - 84	As above but without evidence of originality of thought; well written/ coherent/logical aand flows well; i.e. sentences are linked together; contains most surface knowledge (basic facts from provided materials with some material coming from other literature sources; references must be relevant).
Credit	65 - 74	Contains most surface knowledge (basic facts from provided materials with some material coming from other literature sources); lacks linking between sentences and paragraphs; an attempt has been made to incorporate the minimum of two references beyond lectures or textbook.
Pass	50 - 64	Important facts have been mentioned relevant to the question, but gaps in knowledge; material may be correct but not entirely relevant; poor written expression and style
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

To successfully complete this unit of study you must demonstrate a threshold (pass) standard of attainment of the unit of study learning outcomes as measured by performance on the unit of study summative assessments. Students who do not reach a threshold standard of proficiency of the learning outcomes will receive a mark no greater than 49 FA. In addition, to pass the unit of study, you must participate in all assessment tasks and the end of semester theory examination: failure to participate in any one or more of these will result in a grade of Absent Fail (AF) for the unit.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

All assignments must be submitted by the due date and quizzes and exams attended when they are scheduled. Students are expected to manage their time and to prioritise tasks to meet deadlines. Assessment items submitted after the due date without an approved extension using a special consideration or special arrangement form or request will incur penalties. Failure to meet assessment deadlines will incur mark deductions of 5% of the maximum awardable mark available for every day past the due date (for electronic submissions, days late includes Saturdays, Sundays and public holidays). These deductions will continue for 10 calendar days, until the solutions for the assignment are released, or marked assignments are returned to other students. At that point the mark awarded will be zero. For example, on an assignment given a mark of 70/100, the penalty would be 5 marks if submitted up to 24 hours late, resulting in a final mark of 65/100. If the assignment is submitted 6 days late, the penalty would be 30 marks and the final mark would be 40/100. If the assignment is more than 10 days late, submitted after the solutions for the assignment are released, or marked assignments are returned to other students, the final mark will be 0/100.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1. Overview of course; Chirality and thalidomide; 2. Binding to a target - shape and intermolecular forces	Lecture (2 hr)
Week 01	Molecular modelling 1	Practical (3 hr)
Week 02	1. Quantitative structure activity relationships 1; 2. Quantitative structure activity relationships 2	Lecture (2 hr)
Week 02	Introduction	Practical (3 hr)
Week 03	1. Structure of drug targets: proteins; 2. Receptors as drug targets	Lecture (2 hr)
Week 03	Synthesis	Practical (3 hr)
Week 04	1. Protein structure determination; 2. Proteins as a drug target: antivirals	Lecture (2 hr)
Week 04	Activity	Practical (3 hr)
Week 05	1. Quantitative structure activity relationships: Opioids; 2. Quantitative structure activity relationships: Opioids	Lecture (2 hr)
Week 05	Molecular modelling 2	Practical (3 hr)
Week 06	1. Polynucleotides as drug targets: cisplatin; 2. Isolation from nature	Lecture (2 hr)
Week 06	Principles	Tutorial (3 hr)
Week 07	Lecture and Tutorial Online Quiz	Lecture (2 hr)
Week 07	Analysis	Practical (3 hr)
Week 08	1. Chelation therapy; 2. Drug Discovery: Finding a Lead	Lecture (2 hr)
Week 09	Molecular modelling 3	Practical (3 hr)
Week 09	1. Drug design: optimizing target interactions; 2. Kinase Inhibitors	Lecture (2 hr)
Week 10	1. Protein therapeutics 1; 2. Protein therapeutics 2	Lecture (2 hr)
Week 11	1. Parameters used to describe drug activity; 2. Prodrugs and drug transformations	Lecture (2 hr)
Week 11	Drug development	Tutorial (3 hr)
Week 12	1. Combinatorial synthesis; 2. PET and SPECT agents 1	Lecture (2 hr)
Week 12	Methods	Tutorial (2 hr)
Week 13	1. PET and SPECT agents 2; 2. Genomics, proteomics, big data & drug development	Lecture (2 hr)

Attendance and class requirements

Attendance: Attendance at a minimum of 80% of all timetabled classes is compulsory for successful completion of the course. Attendance will be recorded. If you do not show sufficient cause for absence from any part of the course you may not be allowed to sit the final examination. Absences from scheduled practical, workshop or tutorial sessions must be supported by appropriate documentation (you must also see Guidelines for Special consideration/Arrangements for important information relating to absence from scheduled classes). Late arrival at classes (>15 minutes) without a valid reason will be counted as being absent.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

Recommended textbook: G.L. Patrick: An Introduction to Medicinal Chemistry (5th edition, Oxford University Press, 2013)

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. identify classes of pharmacologically important macromolecules as drug targets
LO2. recognise the role that structure and molecular properties (e.g. pKa, log P, log D) play in intramolecular interactions and their importance in drug action and design
LO3. explain principles underpinning the design of new drug molecules
LO4. explain principles underpinning the design of new protein therapeutics
LO5. understand the concept of a pharmacophore in drug-receptor interactions
LO6. explain various pharmacological assays used in drug discovery and interpret the significance of obtained data (e.g. IC 50, K)
LO7. demonstrate a basic understanding of various techniques and research fields (e.g. combinatorial chemistry, protein crystallography, PET, SPECT) and how they relate to drug discovery process
LO8. gain confidence in the use of computer programs for studying pharmacology and for writing pharmacology reports
LO9. use the most relevant pharmacology and medicinal chemistry databases to locate specific papers and to find relevant resources related to topics as allocated.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Close the loop feedback on your Unit of Study Survey feedback will be provided via Canvas announcement following the release of marks.

Additional information

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

General Laboratory Safety Rules

No eating or drinking is allowed in any laboratory under any circumstances
A laboratory coat and closed-toe shoes are mandatory
Follow safety instructions in your manual and posted in laboratories
In case of fire, follow instructions posted outside the laboratory door
First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory
As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

PCOL3912: Drug Design and Development (Advanced)

Semester 1, 2022 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect