Associate Professor Brett Lidbury

B.Sc (Hons) (Newcastle) PhD (ANU) FFSc (RCPA)
Senior Fellow


I completed undergraduate and honours degrees at the University of Newcastle, followed by a Ph.D. at the ANU (JCSMR). Post-doctoral experience was gained in molecular virology and mucosal vaccine development, followed by a lecturing position (molecular biology, genetics, medical science) at the University of Canberra, which included contributions to a research programme investigating viral pathogenesis (e.g., virus-host interaction) at the molecular and cellular foundations to explain disease formation and severity. This research theme of virus-host interaction and pathogenesis was further advanced while attached to the Department of Microbiology and Immunology at the University of North Carolina-Chapel Hill in the United States, supported by a NIH-R01 grant.

Interests in virology and pathogenesis have moved in silico, with the application of machine-learning/pattern-recognition techniques to support the study of human susceptibility to disease post viral infection (e.g., HBV, HCV). Techniques include recursive partitioning (trees - forests) and support vector machines (SVMs), as both classification and regression applications to biomedical data. This research theme has diversified into other aspects of quality in diagnostic pathology, supported by the Quality Use of Pathology Programme (QUPP - Commonwealth Department of Health), and in collaboration with the Royal College of Pathologists (RCPAQAP).

From 2017 - 2022 an honorary affiliation as Associate Professor with the SYRCLE research group within the Department of Health Evidence, Radboud University Medical Centre (Nijmegen, The Netherlands), was established, supported by funding via the Erasmus travel - academic exchange scheme. This collaboration at Radboudumc was concerned with the application of machine learning to systematic review procedures, particularly to accelerate the synthesis of evidence from biomedical animal studies, to ultimately improve clinical translation. This collaboration on animal alternatives with Dutch colleagues continues, including a formal collaboration with the start-up TenWise B.V.

Myalgic Encephalomyelitis (ME - also referred to chronic fatigue syndrome) studies are ongoing in collaboration with the ME-CFS Discovery Research Network (MDRN), a collaborative network of researchers, community and clinical partners from Australia and the UK.

Our ME projects benefited from funding from the Alison Hunter Memorial Foundation, the Judith J. Mason Foundation and ME Research UK (Scotland). Further funding from the Judith J. Mason Foundation was awarded to develop an ME Biobank, with our NCEPH - ANU role requiring leadership on data-driven analysis and experimentation.

In addition to the above research and academic endeavours, experience in diagnostic pathology has been obtained, as well as a period in regulatory science while a Senior Toxicologist with the Therapeutic Goods Administration (TGA).


Research interests

  • Infection and Immunity (In silico)
  • Chronic disease (ME and post-viral fatigue)
  • Diagnostic pathology
  • Animal alternatives (biomedical models)


  1. Ajuwon BI, Yujuico I, Roper K, Richardson A, Lidbury BA. Hepatitis B virus infection in Nigeria: a systematic review and meta-analysis of data published between 2010 and 2019. BMC Infect Dis 21, 1120 (2021).
  2. Lidbury BA, Koerbin G, Richardson AM, Badrick T. Gamma-Glutamyl Transferase (GGT) Is the Leading External Quality Assurance Predictor of ISO15189 Compliance for Pathology Laboratories. Diagnostics (Basel). 2021;11(4):692.
  3. Lidbury BA. Ross River Virus Immune Evasion Strategies and the Relevance to Post-viral Fatigue, and Myalgic Encephalomyelitis Onset. Front Med (Lausanne). 2021;8:662513.
  4. St.John A, Morris H, Richardson A, Lidbury B, Ward G, Badrick T. Vitamin D testing: Impact of changes to testing guidelines on detection of patients at risk of vitamin D deficiency. Ann Clin Biochem. 2021;58(3):196-202.
  5. Missailidis D, Annesley SJ, Allan CY, Sanislav O, Lidbury BA, Lewis DP, et al. An Isolated Complex V Inefficiency and Dysregulated Mitochondrial Function in Immortalised Lymphocytes from ME/CFS Patients. Int J Mol Sci. 2020; 21(3), 1074.
  6. Cortes Rivera M, Mastronardi C, Silva-Aldana CT, Arcos-Burgos M, Lidbury BA. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Comprehensive Review. Diagnostics (Basel). 2019;9(3), 91.
  7. Lidbury BA, Kita B, Richardson AM, Lewis DP, Privitera E, Hayward S, de Kretser D, Hedger M. Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning, and the Utility of Activin B for Defining Symptom Severity. Diagnostics (Basel). 2019:9(3), 79.
  8. Lidbury BA. Predicting liver disease post hepatitis virus infection: In silico pathology and pattern recognition. EBioMedicine. 2018;35:10-11. doi: 10.1016/j.ebiom.2018.08.032.
  9. Richardson AM, Lewis DP, Kita B, Ludlow H, Groome NP, Hedger MP, de Kretser DM, Lidbury BA. Weighting of orthostatic intolerance time measurements with standing difficulty score stratifies ME/CFS symptom severity and analyte detection. J Transl Med. 2018;12;16:97.
  10. Lidbury BA, Kita B, Lewis DP, Hayward S, Ludlow H, Hedger MP, et al. Activin B is a novel biomarker for chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) diagnosis: a cross sectional study. J Transl Med. 2017;15(1):60.


ME Pathology in silico - There are data available from past and current projects that will benefit from student involvement. A background in medical science and experience in statistics and/or data mining will be required. Other ME projects are available using systematic review methods and meta-analyses. With the advent of COVID-19, research projects will aim to explore the pathogenesis of post-viral fatigue more broadly.

Infection and Immunity in silico: Hepatitis B virus - Biological validation of machine learning models for HBV infection and disease, suitable for a medical science graduate with experience in laboratory diagnosis or pathology testing - involvement in this project will require specialised training and vaccination prior to commencement, due to contact with potentially infected human samples. Some experience in statistics and/or machine learning will be advantageous.

Genetics and Machine Learning - Through research collaborator Professor Mauricio Arcos-Burgos, future projects for students with an interest in human genetics will be available, primarily as in silico investigations on complex diseases like ME.

Supervisors (for students)

  • Brett Lidbury
  • Alice Richardson
  • Tony Badrick (Hon. Associate Professor)
  • Katrina Roper (Hon. Senior Lecturer)
  • Mauricio Arcos-Burgos (Colombia)