Using AI to eliminate the neglected tropical disease schistosomiasis, as a public health problem

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Using AI to eliminate the neglected tropical disease schistosomiasis, as a public health problem

Three main species of schistosome worms infect humans: Schistosoma haematobium, Schistosoma mansoni, and Schistosoma japonicum. People become infected when larval forms of the parasitic worm – released by freshwater snails – penetrate the skin during contact with contaminated water. Children are particularly vulnerable due to their activities, such as swimming or fishing, as well as inadequate hygiene practices.

“The parasite gains entry into the body as especially women go about their daily activities, such as washing clothes or giving their baby a bath,” explains Reinhard-Rupp. “Once these tiny worms have infiltrated the body, they circulate and lead to prolonged chronic infection if left untreated.”

Adult worms can live in human blood vessels for years, successfully evading the immune system while releasing hundreds to thousands of eggs every day. Without treatment, these eggs can remain lodged in parts of the body for many years, causing inflammation and tissue damage. The disease can cause a wide range of symptoms, such as anemia, abdominal pain, blood in urine or stool, problems with passing urine, or even bladder cancer. Children may experience hindered development, impaired cognitive function, and reduced capacity to engage in physical activities.

Additionally, female genital schistosomiasis (FGS) occurs in up to 70% of women infected by schistosomiasis – an estimated 56 million women and girls in sub-Saharan Africa, reflecting socio-economic and health inequalities. [3] If left untreated, FGS can cause reproductive organ damage, which may lead to infertility and stigmatization, an elevated risk of contracting HIV and HPV and – in pregnant women – miscarriage, premature birth, and even maternal death.

Eliminating schistosomiasis as a public health problem
Over a decade ago, we committed ourselves to the fight against schistosomiasis – working closely with our global partners.

Our drug, praziquantel, was initially approved as an anthelmintic in 1975 – and has since demonstrated being safe and efficacious against schistosomiasis. [2, 4, 5] Although re-infection remains a possibility, initiating and repeating treatment during childhood significantly reduces the risk of severe disease.

Harnessing the power of Data & AI
To preserve the efficacy of praziquantel while simultaneously searching for the next generation of schistosomiasis medical treatments, we’re applying the power of digital applications in several ways:

  • AI-assisted drug selection
    We are using AI-powered computational and mathematical modelling and deep learning techniques to pinpoint the critical features of new drugs with the highest potential to combat schistosomiasis. This project aims to guide the research community towards focusing on developing drugs that are most likely to have the biggest impact on disease elimination.
  • Using AI to crack the code of how praziquantel works
    Researchers have recently unveiled how praziquantel exerts its effects against parasitic worms, by combining lab-generated data and computational modelling. [6, 7] This analysis allowed us to understand what the molecular basis for sensitivity of various parasitic worms is to this important therapeutic.
    These findings may help the community to monitor potential rise of praziquantel resistance.
  • Monitoring parasite evolution
    Working as part of a global team, we are also applying the latest computational genomic and epidemiology techniques to monitor the genomic evolution and spread of the parasites that cause schistosomiasis.
    “This work is important for identifying any changes in the parasite that could potentially impact the efficacy of praziquantel in the future.” says Reinhard-Rupp.
  • Improving the diagnosis of FGS
    We are collaborating with researchers at the University of Oxford, UK, to develop an image-based AI-powered diagnostic tool for FGS. [8] This tool analyzes images of cell lesions on the cervix, helping to determine whether they result from schistosomiasis or another disease, such as a sexually transmitted infection. This knowledge could empower women to understand whether they are suffering from a parasitic disease that may be the cause of infertility and other morbidities. Early diagnosis may also accelerate progress towards better treatments that are urgently needed.

Global impact on healthcare
In Global Health, we predict a bright future for the integration of AI and digital solutions, with opportunities continuing to expand the application of AI-powered technologies to improve health outcomes.

“Every hour of every day, more data is being generated – and digital tools will serve as instruments to make sense of all these data, ultimately to help reduce human suffering, especially in the realm of health,” Reinhard-Rupp anticipates. “This digital revolution is providing new tools, innovations, and fresh perspectives to find solutions to combat a variety of diseases that have so far proven difficult to overcome.”

She also feels optimistic about leveraging these cutting-edge technologies to address global health inequalities – such as expediting the fight against NTDs like schistosomiasis.

“Globally, we should strive to ensure that everyone benefits from advances in science and technology,” she emphasizes. “Through our efforts, we are enabling the products of digital and other innovations to reach some of the world’s most underserved communities and address health disparities.”

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