About the Project
In drug development, mitochondrial inhibition is an important ‘OFF-target’ mechanism of drug-induced toxicity in the clinic, contributing to drug attrition in clinical trials as well as drug withdrawal following approval due to severe adverse events (Will & Dykens, 2014). Drug-induced liver injury (DILI) is one example of a serious adverse drug reaction (ADR) and a common driver of drug attrition. Off-target inhibition of mitochondrial function is a recognised contributor to clinical DILI, and a principal toxicity driver for several DILI compounds (Weaver et al. 2020). In addition, there are several examples of drugs where patients have reported experiencing cardiotioxicity (Schmidinger et al. 2008), with mitochondrial toxicity proposed as the underlying mechanism. Improved prediction of mitochondrial toxicity and identification of the toxicophore(s) that have the potential to perturb mitochondrial function is therefore key.
In this project, we will use a machine learning (ML) algorithm involving neural networks to identify potential novel mitochondrial toxic drugs and the student will then focus on a subset of these drugs which may comprise different structural classes to first evaluate mitotoxicity in relevant model systems. The ML approach will involve a “supervised learning” methodology. A neural network will be trained on a curated list of chemical inhibitors of mitochondrial respiratory complexes. The trained neural network will be then used to identify novel mitochondrial toxins in datasets consisting of approved therapeutic agents. Using a suite of cellular and cell-free biochemical assays, we will then explore the molecular mechanisms underlying the mitochondrial toxicity. To confirm the propensity of candidates for off-target mitochondrial toxicity, we will employ the glucose-to-galactose metabolic shift assay (Marroquin et al. 2007). Assays will include analysis of cell death, mitochondrial dynamics and ultrastructure, cellular bioenergetics and respiratory chain function. In vitro approaches will be complemented by in vivo studies in Drosophila melanogaster, where mitochondrial ultrastructure in adult fly brain and thorax muscle can be simultaneously monitored for their impact on behaviour.
The project will provide the student with training in a wide range of wet lab approaches and importantly an opportunity to integrate experimental laboratory skills with in silico based approaches.
A key focus of the mission and strategy of the MRC Toxicology Unit is to train and develop the next generation of academic and policy leaders in the field of toxicology. Successful PhD candidates will be supported by a leading bespoke training programme to ensure that they are equipped with the appropriate skills and experience to become first class researchers at the interface of wet lab biology and in silico based approaches.
Candidates must expect to obtain qualifications at the level of a first-class or 2.1 Honours Degree in a relevant life science, have some statistical and computational skills and must be enthusiastic to collaborate closely with other members of the team.
In addition to an excellent academic record, we are also looking for outstanding candidates with an interest in mitochondrial biology and the application of in silico based approaches and the development of cross-disciplinary skills that bridge these disciplines.
Funding is available at the level of Home Fees and a stipend of £17,500 per annum. Information regarding eligibility for Home Fee classification can be found at:
It is strongly encouraged that you contact the supervisor prior to making your formal application: [Email Address Removed] or [Email Address Removed]
Further information can be found at the MRC Toxicology Unit Website:
If you do not meet the Home Fees criteria, you would be classed as an International student and would be required to cover the difference between the Home and International fee rate.
Formal applications should be sent to PhD in Biological Science (MRC Toxicology Unit) | Postgraduate Admissions (cam.ac.uk)
Meyer JN, Hartman JH, Mello, DF. 2018. Mitochondrial Toxicity. Toxicol Sci. Mar; 162, 15–23. doi: 10.1093/toxsci/kfy008
Schmidinger, M., Zielinski, C. C., Vogl, U. M., Bojic, A., Bojic, M., Schukro, C., Schmidinger, H. (2008). Cardiac Toxicity of Sunitinib and Sorafenib in Patients with Metastatic Renal Cell Carcinoma. Journal of Clinical Oncology, 26, 5204–5212. doi.org/10.1200/JCO.2007.15.6331
Weaver RJ, Blomme EA, Chadwick AE, Copple IM, Gerets HHJ, Goldring CE, Guillouzo A, Hewitt PG, Ingelman-Sundberg M, Jensen KG, Juhila S, Klingmüller U, Labbe G, Liguori MJ, Lovatt CA, Morgan P, Naisbitt DJ, Pieters RHH, Snoeys J, van de Water B, Williams DP, Park BK. 2020. Managing the challenge of drug-induced liver injury: a roadmap for the development and deployment of preclinical predictive models. Nature Reviews Drug Discovery, 19, 131–148.
WILL, Y. & DYKENS, J. 2014. Mitochondrial toxicity assessment in industry-a decade of technology development and insight. Expert Opin Drug Metab Toxicol, 10, 1061-7.
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