Teaching Responsibility
LJMU Schools involved in Delivery:
Pharmacy & Biomolecular Sciences
Learning Methods
Lecture
Practical
Workshop
Module Offerings
7122PHASCI-JAN-CTY
Aims
To develop an integrated understanding of the principles underpinning drug discovery process and of the approaches and rationale of drug optimisation.
Learning Outcomes
1.
Display a systematic understanding of the processes and technologies employed in the discovery and the selection of hits and leads.
2.
Critically evaluate the principles and rationale underpinning lead optimisation.
3.
Synthesise and communicate the impact of experimental findings on the life and fate of a drug candidate.
4.
Integrate and communicate the approaches for drug candidate selection in the context of successful drug development cases.
Module Content
Outline Syllabus:Drug discovery process (including target identification, hit/lead identification, hit-to-lead development step).
Compound screening (including experimental and virtual techniques and considering compounds with synthetic and natural sources).
Drug design principles (Physical properties, structure-activity relationship).
Computer-aided Drug Design. Chemoinformatics including QSAR.
Lead optimisation (including synthetic strategies, computational techniques).
The discovery of biopharmaceutical drugs
Successful drug design case studies (examples could include, but are not limited to, antimicrobials and opioids).
Module Overview:
This module aims to enable you to develop an integrated understanding of the principles underpinning drug discovery process and the approaches and rationale of drug optimisation.
This module aims to enable you to develop an integrated understanding of the principles underpinning drug discovery process and the approaches and rationale of drug optimisation.
Additional Information:Practical sessions will involve the synthesis of a library of antimicrobial drugs, their testing and the elaboration of structure activity relationships.
Exam will assess students understanding of the principles through data interpretation/problem solving questions