Oluwatoyin Mary Oyinloye

Neglected tropical diseases (NTDs) continue to place a heavy burden on low- and middle-income countries. In these regions, drug development is often slow and expensive, and NTDs are rarely a priority due to limited financial incentives and complex science. This chapter looks at how combining drug repurposing and polypharmacology can offer faster and more affordable ways to discover treatments for NTDs. Using ideas from computational systems biology, we outline both a theoretical and practical approach to exploring lesser-known drug targets through multi-target strategies. We highlight modern computer-based tools, like network pharmacology, omics data analysis, and machine learning, that help identify new links between drugs and diseases in both humans and pathogens. We focus especially on in silico (computer-based) drug repurposing pipelines and how databases like DrugBank, ChEMBL, and SchistoDB can help match existing drugs to neglected diseases. Real-life examples, such as Miltefosine for leishmaniasis, the broad potential of Ivermectin, and using statins to treat schistosomiasis, show how targeting multiple disease pathways can be effective. The chapter also addresses challenges, such as gaps in our understanding of pathogens, drug delivery issues, and regulatory barriers, especially in settings with fewer resources. Looking ahead, we support moving toward more precise tropical medicine by combining genetic and biological data with AI tools, while keeping research ethically and inclusive of local communities. In summary, the chapter shows how drug repurposing can be a powerful and fair way to improve treatment options for neglected diseases.

This chapter looks at the growing importance of the environment in the process of making bioactive compounds useful in medicine. In the past, drug discovery often ignored the environment or saw it as unimportant. However, here, we suggest a new approach that considers both nonliving (abiotic) and living (biotic) environmental factors, such as climate, soil type, microbes, and ecosystems, when planning how to create these compounds. We introduce the idea of environmental fingerprinting, which involves identifying the unique environmental features that influence how and where certain bioactive compounds are produced. These features help scientists decide which compounds to focus on. By using advanced tools such as artificial intelligence (AI), machine learning, and metabolomics, we show how environmental data can improve the search for new medicines by helping predict how well a compound will work and how active it will be in the body. The chapter shares real-life examples, such as desert plants that produce helpful chemicals during droughts and marine bacteria that produce antibiotics in saltwater. These examples show how environmental conditions affect both the variety and power of natural compounds. This new way of thinking could greatly improve how we find new drugs, especially by helping us discover compounds suited to specific environments. The chapter also discusses the challenges of combining environmental data with computer models, such as missing data, ethical concerns, and the need for scientists from different fields to work together. By shifting the paradigm of retrosynthesis toward an environment-driven approach, the chapter paves the way for more efficient and ecologically informed therapeutic innovation.

Plants have long served as prolific sources of bioactive compounds with significant pharmacological. Drug repurposing has emerged as a promising strategy in antidiabetic drug discovery. This approach involves identifying new therapeutic uses for existing FDA-approved drugs, offering several advantages, including reduced development time, lower costs, and established safety profiles. Diabetes mellitus, particularly type 2 diabetes, continues to pose significant global health challenges due to its increasing prevalence and the multifactorial nature of the disease, including insulin resistance, pancreatic β-cell dysfunction, and chronic inflammation. Although traditional drug discovery methods are time-consuming and costly, they make drug repurposing an attractive alternative. The repurposing process often begins with the computational screening of existing drug libraries through advanced methods such as molecular docking, network pharmacology, and machine learning. These tools help identify promising compounds that may interact with diabetes-related targets. Pharmacological profiling and in-depth mechanistic studies have been conducted to elucidate how these drugs may enhance insulin sensitivity, glucose regulation, and β-cell function. Clinical trials are important in translating preclinical findings into real-life therapeutic applications. Repurposed drugs for diabetes undergo clinical evaluations to confirm their safety and efficacy in managing high blood glucose levels and diabetes-related complications. Drugs such as metformin have been explored not only for the treatment of diabetes but also for the treatment of cardiovascular diseases and cancer due to their broader pharmacological effects. Similarly, GLP-1 agonists, originally designed for diabetes, have shown significant promise in obesity management, highlighting their potential to address multiple aspects of diabetes care. Furthermore, cardiovascular drugs such as SGLT2 inhibitors are attracting attention for their dual therapeutic benefits in managing diabetes and cardiovascular diseases simultaneously.

Currently, there is no known cure for diabetes. Different pharmaceutical therapies have been approved for the management of type 2 diabetes mellitus (T2DM), some are in clinical trials and they have been classified according to their route or mechanism of action. Insulin types, sulfonylureas, biguanides, alpha-glucosidase inhibitors, thiazolidinediones, meglitinides, sodium–glucose cotransporter type 2 inhibitors, and incretin-dependent therapies (glucagon-like peptide-1 receptor agonists: GLP-1R, and dipeptidyl peptidase 4 inhibitors: DPP-4). Although some of the currently available drugs are effective in the management of T2DM, the side effects resulting from prolonged use of these drugs remain a serious challenge. GLP-1R agonists are currently the preferred medications to include when oral metformin alone is insufficient to manage T2DM. Medicinal plants now play prominent roles in the management of various diseases globally because they are readily available and affordable as well as having limited and transient side effects. Recently, studies have reported the ability of phytochemicals to activate glucagon-like peptide-1 receptor (GLP-1R), acting as an agonist just like the GLP-1R agonist with beneficial effects in the management of T2DM. Consequently, we propose that careful exploration of phytochemicals for the development of novel therapeutic candidates as GLP-1R agonists will be a welcome breakthrough in the management of T2DM and the co-morbidities associated with T2DM.

The recent outbreak of Coronavirus (COVID-19) pandemic has led to the total lockdown of major cities globally which resulted in the early closure of schools in the cities affected, Nigeria inclusive. It is hypothesized that COVID-19 may have a negative outcome on the performance of senior secondary school students in class 3 (SS3) who are yet to write their 2020 external examination (West Africa Senior Secondary Certificate Examination as well as National Examination Council) especially in the science subjects namely Biology, Physics and Chemistry. This study collected data from three teachers who are science experts and head of their respective departments in three government secondary schools in Ado-Ekiti local government area of Ekiti State, Nigeria. A semi-structured interview was used to collect data from the teachers through phone calls and WhatsApp chats. This qualitative study employed a case study research approach. Findings from this study revealed that there is the possibility of a further drop in the pass rate (%) of senior secondary school students’ in this year’s external examinations if this pandemic is not contained soon knowing fully well that the school academic calendar has already been disrupted due to early closure of schools in Nigeria. As part of COVID-19 relief package, recommendations are made to the Federal government of Nigeria and policymakers to distribute iPads and electronic tablets preloaded with e-textbooks in these subject areas to SS3 students and their teachers to facilitate online learning as this will enhance their performance in Science subjects in this year’s national examination.

This study investigated the impact of ‘assessment for learning’ on learner performance in Life Science. Simple random sampling was used to select four schools from the King Cetshwayo District of KwaZulu Natal Province, South Africa, to participate in the study. A quasi-experimental,...