Anika Liu

Educational background

Before I joined the group as PhD student, I studied Molecular Biotechnology with major Bioinformatics at the University of Heidelberg (BSc+MSc), which provided me with a broad background in life sciences and drug research. The structure of my MSc program allowed me to gain practical experience at the bench and at the desk at excellent institutions in Heidelberg and abroad (Cambridge, Vancouver, Madrid, and Taipei) which was only possible through scholarships awarded by DAAD, ERASMUS and  MOST.

Thereby, my two bigger thesis projects were in the field of systems biology: Understanding cellular information and regulation using ODE Systems with Dr. Jürgen Pahle, and causal reasoning to infer upstream signalling networks from transcriptomics data with Prof. Julio Saez-Rodriguez which has resulted in the open-source R package CARNIVAL. Scientifically shaped by both groups, I developed an interest in interpretable models which help to understand biological processes at different levels of complexity and can hence provide useful insights to understand diseases or drugs.

Current research

I am studying the biological mechanisms of drug side effects supported by the GSK Black Swans scholarship and part of the Cambridge Alliance on Medicines Safety. The overall aim of my work is to help identify safety risks earlier in drug development contributing to an increase in productivity while protecting human safety and animal welfare. To do so, I integrate different kinds of data generated in the drug development process and try to derive tangible results in the form of potential adverse outcome pathways (AOPs) or safety biomarkers. In my current project together with GSK, for example, I am using gene expression and histopathological data to study drug-induced vascular injury which leads to compound termination in pre-clinical studies despite little evidence for translation to human health.

I am additionally pleased to work as a scientific/computational consultant with two start-ups, which spun out of the Department of Chemistry in Cambridge, which gives me the opportunity to gain further insights into how data-driven approaches can support real-world drug development.