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Alexander Hasson

BEng (Hons)


Mechanistic Modelling of Multitargeted Therapeutics

Research Summary

Pancreatic cancers remain intractable, resulting in high mortality. Thus, there is an urgent need for innovative ways to tackle this disease. Aberrant epigenetics is a key “Hallmark of cancer" that cancer cells use to drive de-differentiation of normal cells into an embryonic squamous-like state which favours uncontrolled proliferation.

We recently identified the epigenetic mechanism defining these phenotypic changes and found that a combination of biologically-targeted agents (Metformin and Vitamin C) could restore epigenetic control and revert squamous pancreatic cancer cells to a more regulated differentiated state [1].  Although we observe a shift towards normal cell epigenetics, this drug combination is not fully optimised to drive the phenotypic shift. Therefore, we aim to use an innovative data-driven artificial intelligence (AI) approach developed by BedrockBio based on existing algorithms[2], to delineate novel molecules that can demonstrate improved and robust re-normalisation of epigenetic status and pancreatic differentiation, in order to offer new treatments for this hitherto intractable cancer.

[1] Eyres et al. (2021) Gastroenterology. 2021:S0016-5085(21)00682-X.

[2] Pham et al. (2021). Nat. Mach. Intell. 3, 247–257

[3] Kay et al (2017). PLoS Comp Biol. 2017; 13(2): e1005400.

[4] MacLean et al. (2015) PNAS. 2015; 112(9): 2652-2657.

Research Interests

My key interests in research lie in multidisciplinary computational sciences. My Honours thesis was in Computation by Biological Means (biological alternative computing).

I am currently involved primarily in computational mathematics, bioinformatics and machine learning. The applications of are namely computational medicine (oncology), computational biology and protein/cheminformatics.