3 citations · 4 across the 5 of their papers we have counts for
5 papers
Iterative AI-guided optimisation of selective triple-drug combinations for breast cancer
Oghenejokpeme Orhobor, Abbi Abdel-Rehim, Emma Tate +5
Personalised cancer therapy aims to tailor treatment to individual tumour profiles, yet tumour heterogeneity and adaptive resistance continue to limit clinical efficacy. Drug combi…
Advancing Drug Development Through Strategic Cell Line and Compound Selection Using Drug Response Profiles
Abbi Abdel-Rehim, Emma Tate, Larisa N. Soldatova +1
Early identification of sensitive cancer cell lines is essential for accelerating biomarker discovery and elucidating drug mechanism of action. Given the efficiency and low cost of…
Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture
Abbi Abdel-Rehim, Oghenejokpeme Orhobor, Gareth Griffiths +2
The concept of personalised medicine in cancer therapy is becoming increasingly important. There already exist drugs administered specifically for patients with tumours presenting…
Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment
Abbi Abdel-Rehim, Hector Zenil, Oghenejokpeme Orhobor +8
Large language models LLMs have transformed AI and achieved breakthrough performance on a wide range of tasks In science the most interesting application of LLMs is for hypothesis…
Beating the Best: Improving on AlphaFold2 at Protein Structure Prediction
Abbi Abdel-Rehim, Oghenejokpeme Orhobor, Hang Lou +2
The goal of Protein Structure Prediction (PSP) problem is to predict a protein's 3D structure (confirmation) from its amino acid sequence. The problem has been a 'holy grail' of sc…