Biostatistics and AI/ML for Drug Discovery

Developing machine learning frameworks to understand complex diseases and identify novel therapies.

Explore Our Research Join Our Team

Our Research Focus

Empowering the next generation of drug target identification, drug repositioning and precision medicine

The mission of our research group is to develop biostatistical and machine learning frameworks applied to biomedical data, to retrieve insights in the aetiology of complex diseases and identify novel intervention strategies. For this, we explore deep molecular characterised biomedical datasets, environmental factors, and tailor our models depending on disease specific knowledge gained through collaborations, literature and data driven analyses, thus empowering the next generation of drug target identification, drug repositioning and precision medicine.

Computational Cancer Pharmacogenomics

We have strong expertise in computational method development for cancer pharmacogenomics including the analysis of monotherapy and drug combination high-throughput screens, and CRISPR lethality and drug resistance screens, which is highlighted by our ERC project and publication record.

The Menden Lab customises machine learning and biostatistical methods to predict drug sensitivity and synergy, as well as derived genetic biomarkers of these responses. Our work focuses on clinical translatability for enabling patient stratification based on deep molecular profiles, which is the key pillar of precision medicine.

Translational Computational Pharmacogenomics

The foundation of our endeavour is our strong expertise in Computational Cancer Pharmacogenomics (ERC StG), which we envision to generalise to Translational Computational Pharmacogenomics.

In particular, we expand our research focus to:

  • Tuberculosis drug resistance (bayresq.net, UNITE4TB)
  • Inflammatory skin diseases (IGSSE)
  • Neurodegenerative diseases (JPND, MUDS)
  • Diabetes research (DZD)

Common across all projects, we are experts in analysing biological models which are deep molecularly and phenotypic characterised, which ultimately enables precision medicine. In essence, our research vision is to establish a Translational Computational Pharmacogenomics programme in cancer and beyond, in order to accelerate the delivery of urgently needed targeted therapies.

Key Recent Publications

View all works on Google Scholar

Featured Projects

Open-source tools and research initiatives driving scientific discovery

View All Projects on GitHub

Our Team

Menden Lab Team



A/Prof Michael Menden

Head of Laboratory

Faculty Page
View Previous Members

Dr Göksu Avar

Postdoctoral Fellow

Alina J Arneth

PhD student

Xixi Li

PhD student

Linpeng Xie

PhD student

Xuan Liu

PhD student

Qiyang Wu

PhD student

Daksh Pamar

PhD student

Wenjie Shan

PhD student

Chen Gong

PhD student

Anthony Basilone

PhD student

Liam Mcinerney

Masters student

I Putu Prakasa Wiprayoga

Masters student

Keisuke Yasuda

Masters student

Jesamine Newman

Masters student

Yazhu Liu

Honours student

Nicolo Fabila

PhD student

Join Our Team

Opportunities are available for student applicants and potential collaborators to join our research activities.

Available Opportunities

  • Who Can Apply

    This research project is available to PhD students, Masters by Research, Honours students, Master of Biomedical Science students, and postdoctoral researchers as part of their thesis or research training.

Collaborators Welcome

  • Potential collaborators interested in interdisciplinary projects are encouraged to reach out.
  • Please contact the Research Group Leader to discuss your options.

Get in Touch

Interested in applying or collaborating? Please email the Research Group Leader with your background and areas of interest.

michael.menden@unimelb.edu.au
Department of Biochemistry and Pharmacology
The University Melbourne
Melbourne, Australia
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