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               STUDY PLAN & MODULE DESCRIPTIONS
                 Code         Module                          Credits   Duration  Prerequisite(s)

                                            Table I: Compulsory Modules
                 AIDD8121     Research Methodology and Ethics     3    45 hrs   ---
                              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.
                 AIDD8122     Advanced   Topics   in   Artificial  3   45 hrs   ---
                              Intelligence Drug Discovery
                              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.
                 AIDD8299     Thesis                          21       ---      ---

                              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.















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