--- 

3

45 hrs

---

AIDD8121 

Ethics are a set of moral principles that guide a person’s behavior. In this course, ethics will be emphasized and considered the core value throughout all our daily and research activities. In addition, both the theoretical and the practical aspects of artificial intelligence (AI) drug discovery will be introduced, including the fundamental mathematical models and the state-of-the-art tools for drug design problem solving. The topics also include data collection and proposal/paper writing. The course covers a wide range of key topics in modern AI drug discovery, from ethics to fundamental and professional research methodology.

3

45 hrs

---

AIDD8122 

Over the past few years, artificial intelligence (AI) has played an important role in new drug development. AI can potentially save time and money as well as increase the success rate of new drug development. This module covers the advanced topics of AI in drug discovery from target structure prediction, lead discovery to lead optimization and drug-likeness evaluation. The main topics include the basic principles of modern drug discovery, the prediction of drug-target interaction, virtual screening of small molecular database, in silico prediction of properties of drug molecules, de novo drug design, prediction of drug retrosynthesis route.

3

45 hrs

---

AIDD8299 

The doctoral thesis aims to allow students, by tackling advanced research problems over diverse settings, to significantly contribute to the expansion of knowledge in the field of Artificial Intelligence driven Drug Discovery, especially in applied technology and produce a coherent body of work that is of scholarly value and worthy of publication. The work must be original and be the student’s own. There must be evidence that the field has been thoroughly surveyed by the student with critical exposition of relevant works, clearly demonstrating the mastery of a body of knowledge in the field and strong analytical skills. Students are responsible for ensuring that the thesis is presented in a clear, accessible and consistent format. Good project management practices and effective writing and oral presentation skills are essential to the successful completion of the thesis.

21

---

---

AIDD8123

Societies across the world are looking to combat a greater range of human diseases but at the same time contain spiralling healthcare costs. This, together with global competition and increasing regulatory standards, puts enormous pressure on the pharmaceutical industry to discover and develop a greater number of therapeutic candidates even faster and cheaper than ever before. This course develops the key themes in the drug discovery and development pipeline and highlights the multi-disciplinary nature of the research and development process. The course deals with different phases in drug development, including target identification and validation, hit discovery, hit-to-lead optimization, pre-clinical and clinical testing, registration and commercialisation, regulatory and manufacturing considerations.

3

45 hrs

---

AIDD8124

Chemobioinformatics brings together two very important fields in pharmaceutical sciences that have been mostly seen as diverging from each other: chemoinformatics and bioinformatics. The course provides introduction to the area of chemobioinformatics in relation to drugs, omics, chemical biology, protein function, and biomedicine, and includes databases, sequence analysis, proteins and their interactions, chemical descriptions of proteins and organic compounds, data modeling, QSAR modeling, proteochemometrics modeling, drug discovery and development, and use of chemobioinformatics software.

3

45 hrs

---