Women's Health Network Seminar: Pilar Cacheiro & Joseph Taylor

When: Tuesday, February 10, 2026, 3:00 PM - 5:00 PM
Where: Empire House Basement area, 67 New Road E1 1HH, Whitechapel

Speaker: Dr Pilar Cacheiro (WHRI) and Dr Joseph Taylor (PHURI)

Join us for the latest Women’s Health Network Seminars.

Dr Pilar Cacheiro (WHRI) and Dr Joseph Taylor (PHURI) will be presenting their work followed by Q&A and an opportunity for informal discussions with colleagues from across QMUL over tea and coffee. 

All welcome. This is an in-person only event.

Pilar Cacheiro, Senior Lecturer in Computational Biology, Centre for Clinical Pharmacology and Precision Medicine, William Harvey Research Institute

Essential genes and their role in early human development: Genetic factors in miscarriage and stillbirth

Essential genes are those whose function is required for cell proliferation or organism viability. They are usually identified through knockout studies in human cell lines and mouse models. Many of these genes are linked to genetic conditions in humans, particularly those that affect early development, and may therefore contribute to severe conditions that result in pregnancy loss or early infant death. 

We are currently investigating the impact of variants in these genes on miscarriage and stillbirth using data from the Genes and Health programme, in which exome sequencing data are linked to primary and secondary health records. As part of this project, we are establishing a recurrent pregnancy loss cohort to better understand the underlying genetic factors contributing to this adverse pregnancy outcome.

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Joseph Taylor, Clinical Senior Lecturer  and Honorary Consultant in Haematology, Precision Healthcare University Research Institute 

Improving Screening for Iron Deficiency by Applying Machine Learning to the Rich Full Blood Count

Iron deficiency is both common and systematically underdiagnosed. Its importance is multifaceted and lies in:

• direct effects (anaemia, loss of productivity, child development)
• indirect effects (outcomes in heart disease, sepsis, kidney disease, maternity)
• as a diagnostic flag for other hidden conditions (menorrhagia, colorectal cancer)

Modern FBC analysers measure thousands of cells, generating high-dimensional data compressed into summary statistics. By applying machine learning to this "rich FBC" data we show that we can significantly improve FBC-based screening without change to care pathways or laboratory equipment. Building upon this work we are evaluating ways to correct for the influence of inflammation that limits the effectiveness of ferritin, the standard diagnostic test, in conditions from pregnancy to cancer.