Harnessing the power of genomics to improve malaria control products

From discovering actionable drug targets to post-market surveillance, harnessing genomics at every step of the pipeline can transform disease control products.?

The rise of genomic technologies has spurred incredible advances in our understanding of the biology and evolution of malaria. Genomic research has illuminated the mechanisms of resistance, diversity, and adaptations that drive malaria’s persistence. Yet, the path to developing a new product is complex.?

At every step of the process, how can we ensure that the products being developed not only address current challenges but also remain safe, effective, and durable?

Here’s a closer look at how genomics can transform each stage of the development pipeline for malaria control products.

Research and Development (R&D)

At the earliest stages of R&D, genomics enables researchers to uncover molecular targets — these can be genes, proteins, or pathways critical to pathogen survival or vector fitness. Genomic screening has already highlighted promising drug targets in Plasmodium falciparum, offering insights into the viability of these molecular systems as potential targets for informing antimalarial design.

Large genomic datasets also help streamline compound screening and lead identification. With computational modelling, researchers can predict how a candidate molecule might interact with its target, reducing the need for trial-and-error experiments in a lab. Similarly, genome-wide association studies (GWAS) in mosquitoes can reveal mutations linked to insecticide resistance, guiding the design of next-generation vector control tools like dual active ingredient insecticides.

Use case: The discovery of Pfkelch13 mutations as a marker for artemisinin resistance is a pivotal example of how genomic surveillance can directly impact malaria therapeutics. Initially identified in Southeast Asia, mutations in the PfKelch13 gene were shown to reduce the efficacy of the front-line antimalarial drug artemisinin. These mutations are being identified and validated by the WHO to enable public health officials to adapt treatment regimens accordingly. As genomic monitoring expands, there is an opportunity to tackle resistance by proactively adapting drug candidates to emerging resistance patterns in genetic targets.

Pre-clinical Studies

In preclinical studies, genomics can enhance both in vitro (performed in test tubes, culture dishes, or a similar set-up outside a living organism) and in vivo (in a living organism) evaluations of candidate drugs and vaccines. This is an important step that can assess and predict off-target effects of compounds like toxicity, and evaluate the broader implications of a compound’s mechanism of action.

Use case: The K13 propeller gene in P. falciparum is a key molecular marker that has been linked to artemisinin resistance. Through genomic data analysis embedded into in vitro and in vivo studies, mutations identified in the K13 gene helped predict resistance before it became widespread in clinical settings in the Greater Mekong Subregion.

Clinical Trials?

Genomics transforms clinical trials by providing key pathogen data to inform trial design. By sequencing parasites from trial populations, researchers can acquire baseline data on the genetic diversity of molecular targets and monitor how they evolve in response to trialled therapies. With the feedback from genomic data, clinical trials could be iteratively refined to account for genetic variability in parasite or host populations. This data-driven approach has the potential to ensure that interventions are tested and optimised against relevant and diverse target populations.

Use case: In the clinical trial stage, therapeutic efficacy studies (TES) remain the gold standard for assessing the efficacy of antimalarial treatments by directly observing clinical outcomes (like parasite clearance rates) in treated patients over time. However, this method may not always capture genetic factors that underlie resistance mechanisms, which can emerge even if the clinical outcomes are met in the short term. A dual-pronged approach to assessing efficacy that combines molecular and genomic data with TES can significantly enhance its speed and precision. This can capture the full diversity of parasite populations and detect emerging resistance quicker, which is not possible with TES alone.?

Review and Approval

Once a therapeutic product has been developed and trialled, demonstrating evidence of safety, efficacy, and relevance across diverse populations is a critical step in the regulatory review and approval phase. Genomic data can support this by providing evidence on the genetic variability of parasite populations and their alignment with therapeutic targets.

By incorporating genomic tools, regulatory decisions are better informed, and a more accurate evaluation of emerging malaria interventions is possible.

Use case: In 2015, genomic analysis of circulating parasite strains was incorporated into the RTS,S/AS01 malaria vaccine trials to assess whether the vaccine’s target – the P. falciparum circumsporozoite (Pfcsp) protein found on the parasite’s cell surface – aligned with regional parasite populations. As RTS,S/AS01 would become the first WHO-approved malaria vaccine for use in vulnerable populations in 2023, genomic insights are continuing to demonstrate the genetic diversity of the Pfcsp gene in different endemic areas in which it would be used.

Post-Market Surveillance

The utility of genomics doesn’t stop after a product is approved. Continuous genomic surveillance allows tracking the effectiveness of interventions in dynamic environments. Resistance can emerge rapidly under selective pressures, as seen with artemisinin-based combination therapies and insecticide-treated bed nets targeting mosquitoes.

With genomics, we can get to the genetic roots of resistance and provide an early warning system by detecting potential mutations long before they manifest as clinical treatment failures. Once biomarkers are established, genomic surveillance works faster than therapeutic efficacy studies, reducing the time between detecting markers of interest and rolling out interventions designed using them.

Use case: The vast malaria parasite and vector genome datasets maintained by MalariaGEN exemplify how coordinated global genomic surveillance can identify emerging resistance to guide targeted responses. With tools like Pf-HaploAtlas and the data analysis pipelines offered through the Malaria Vector Genome Observatory, we can track known mutations across vector and parasite genomes that may be involved in resistance to the new product.

For more, tune in live for our next webinar, Harnessing genomics: The future of malaria drug and vaccine development at 4PM GMT on 27th November.