Data Science and Artificial Intelligence for Modern, Innovative and Sustainable Afrocentric Drug R&D
Coordinators: Ozlem Tastan Bishop ([email protected]), Francesco Petruccione ([email protected])
Researchers involved: Prof Carolina Wahlby , Prof Ola Spjuth, Prof Prashant Singh (Uppsala University); Prof John Mango, Dr Henry Kasumba (Makerere University)
Africa comprises 17% of the global population, and the United Nations estimates that Africa’s population will exponentially expand to account for 40% of the world’s population by 2100. Importantly, considering that Africa currently accounts for 25% of the global disease burden, this predicted population growth will profoundly exacerbate the continent’s perennial problems of poverty and inadequate healthcare provision for infectious and non-communicable diseases. Moreover, although Africa has the most diverse human genomes, only 2% of genetic material used in medical research comes from the continent – meaning that only ~2% of clinical trials are conducted in the continent. Therefore, the contribution of African patient population data in the development of new therapies is under-represented by a factor of about 2/17. Furthermore, most treatments for human diseases originate from outside Africa and are too costly or not tailored for diseases prevalent in African populations. Hence, initiatives to stimulate research, training and development of new therapeutics for diseases relevant to Africa by harnessing the diverse continental genetic data need to be supported.
The proposed Research Hub under CoRE-AI, DAtAcentricDrug, brings together a cohort of experienced and young academics from the disciplines of genomics, bioinformatics, computational chemistry, data science, mathematics, pharmacogenomics and quantum computing under the broad theme of “Data Science and Artificial Intelligence for Drug R&D for Diseases in Africa”. DAtAcentricDrug is broadly aimed at establishing integrated, multinational and collaborative drug research and development programs within the Research Hub to serve as a vehicle for the expansion of Afrocentric drug discovery research capacity specifically targeted at improving scientific competences that will potentially lead to improved healthcare of the African population and stimulation of economic growth on the continent. Ultimately, DatAcentricDrug aims to develop sustainable world-class drug discovery research capacity in Africa by melding teaching and research in collaboration with other ARUA and the GUILD partners within CoRE-AI as well as between the other CoREs in a unique framework focused on Africa-centric diseases.
Africa has enormous potential given its vast natural resources, extensive indigenous knowledge and well-trained human capital. In the last decade, ambitious scientific initiatives such as the Human Heredity and Health in Africa (H3Africa) have generated a colossal volume of Afrocentric genomic data by sequencing thousands of genomes from varied populations in Africa and have identified significant genomic diversity3. African genome research is particularly pertinent to studies of human origin, disease susceptibility and precision medicine. Hence, existing data has opened new avenues for additional in-depth analysis of African genomes data to delineate single nucleotide variations (SNVs) associated with diseases prevalent on the continent and the genetic basis of drug susceptibility and toxicity (pharmacogenomics). A recent Nature publication by the H3Africa consortium members reported an estimated three million novel genetic variants in over 300 African genomes. These findings are foundational for further Afrocentric drug discovery research, particularly for deciphering how the reported variations lead to susceptibility or resistance to particular diseases among African populations. In addition to human genome studies, pathogen genome studies, spearheaded by Africa CDC’s Institute for Pathogen Genomics, aimed at harnessing genetic information for disease epidemiology, monitoring of drug resistance and infection prevention and control, are currently ongoing in Africa.
While enormous genome data ranging from pathogens to healthy and sick cohorts of African human populations has been generated, the transition to post genomic analysis has been relatively slow, thus widening the gap between data generation and translational utilization. Deciphering the effects of SNVs, and more specifically, missense mutations on protein structure and function is highly critical to the understanding of the underlying causes of many inherited diseases, mechanisms of drug resistance, and drug sensitivity and toxicity in particular populations for precision medicine purposes. Thus, determination of the landscape of missense mutations in African populations would greatly aid the development of novel precision medicines for Africa’s populations. DAtAcentricDrug aims to utilize collectively a large variety of computational approaches coupled with wet-lab experiments to determine the molecular effects of missense mutations and apply the knowledge gleaned to design more efficacious and safe drugs or safe use of current drugs. Further, DatAcentricDrug aims to collaborate with industry to commercialize some of the end products.