Dr Samuel Egieyeh is a seasoned and highly experienced pharmacist who holds bachelor and masters’ degrees in Pharmacy, and a PhD in Bioinformatics (University of the Western Cape (UWC)). He also has a postgraduate diploma in clinical research and drug development from the University of Basel, Switzerland. He is currently a senior lecturer in the discipline of Pharmacology and Clinical Pharmacy at the School of Pharmacy at UWC, where he leads the Computational Pharmacology and Cheminformatics Research Group.

His research focuses on computational drug discovery and design, as well as data science (including cheminformatics, bioinformatics and machine learning) for predictive drug development for infectious diseases and precision medicine.

In January this year, Dr Egieyeh led a successful NITheCS Colloquium titled ‘Bioinformatic, Chemoinformatic and Data Analytic Strategies for Drug Discovery and Development’ during which he explained that in drug discovery, the journey from ‘hits’ to ‘drug candidates’ may be tedious, long and expensive. A high-quality drug candidate must exhibit a balance of many properties, including potency, ADME (Absorption, Distribution, Metabolism and Excretion) and safety/toxicity.

Dr Egieyeh comments on the challenges of his work: ‘Although enriched with ethnobotanical medicine, Africa is ravaged by neglected communicable tropical diseases and, in recent times, by non-communicable diseases. The average cost of drug development for one of these diseases could be up to $1.5 billion mainly due to expensive high throughput compound screening programmes, expensive clinical development programmes, and a high attrition and failure rate in the whole drug development pipeline.’

Hence, he maintains, multi-parameter optimisation strategies that require rigorous modelling, chemical-bioactivity data analytics and data mining might aid rational selection of compounds with the highest chance of success in the drug development pipeline. ‘My research group is leveraging modern information and computational technology (bioinformatics, cheminformatics, data analytics and artificial intelligence) to simulate the high throughput compound screening and clinical development programmes, especially for phytochemicals from the rich African ethnobotanical medicine, thereby identifying likely-to-succeed drug candidates and thus reducing the overall cost of drug development for endemic diseases.’

His personal experiences contributed to his decision to become a scientist and make a difference: ‘Having suffered from malaria all my life (at least twice every month), I resolved to become a scientist a pharmacist) in order to contribute to the development of drugs for malaria and other childhood killer diseases in Africa. The traditional herbal remedies that were used for me and my siblings became the first point of call for me to explore as potential sources of a cure for malaria. Although I have not achieved my childhood dream of discovering that cure for malaria, my journey into the field of drug discovery has been exciting and revealing to say the least.’

He is also thinking of tomorrow’s researchers: ‘I am committed to my dream and I am training the next generation with the skills I have had the opportunity to acquire.’  Importantly he is ‘infusing them with the passion for an Africa-led solution to endemic African diseases.’