Awards

Jacqueline Weyer of the National Institute for Communicable Diseases in South Africa and Jinal Bhiman of Wits Health Consortium (Pty) Ltd also in South Africa will leverage a rapid monoclonal antibody (mAb) isolation and screening pipeline to develop diagnostics that differentiate between pathogens to support epidemic responses. Africa’s burden of many zoonoses and vector-borne diseases (VBD), such as Lassa fever and yellow fever, remains largely unknown, mainly due to diagnostic costs and limited access to reagents. They will leverage an existing screening pipeline, with infrastructure established by the Global Immunology and Immune Sequencing for Epidemic Response - South Africa (GIISER-SA) project, using a mouse model as a more readily available source of pathogen-specific B cells to identify mAbs that detect three ebolavirus species. These mAbs will be tested for sensitivity and specificity using patient samples and can be used to develop immunoassays, including rapid lateral flow assays, which are important for rapid, field-based diagnosis.

Anne Lee of Brigham and Women's Hospital in the U.S. and Yasir Shafiq of Aga Khan University in Pakistan will develop geospatial models to predict risks of undernutrition among adolescent girls and pregnant and lactating women in settings affected by conflict, climate and COVID-19 to help target interventions. Globally, around 30–40 million pregnant women and 50 million adolescent girls are underweight. Risks of undernutrition have recently been amplified by numerous armed conflicts, climatic shocks such as flooding and the COVID-19 pandemic. However, real-time data shortages prevent interventions, such as balanced energy-protein supplements, from reaching the highest-risk groups. Using Bayesian Hierarchical Spatial modeling, they will develop geospatial models for countries vulnerable to conflict and climate change, such as Ethiopia and Yemen. By incorporating socio-demographic and economic indicators, and climate-related and conflict-related shocks from national databases, they can estimate risks based on exposure and predict outcomes, such as undernutrition and anemia.

Margaret Kasaro and Soumya Benhabbour of the University of North Carolina at Chapel Hill in the U.S. will evaluate 3D-printed intravaginal ring (IVR) prototypes in Zambia to identify the design most acceptable to women for long-term use against unplanned pregnancy and HIV infection. In Zambia, HIV prevalence remains particularly high among women, and 41% of pregnancies are unplanned. IVRs are an effective, well-tolerated, and women-controlled contraceptive and HIV-preventative; however, their performance has suffered in large-scale clinical trials because of poor adherence. They have exploited a state-of-the-art 3D-printing process to rapidly engineer IVRs in a cost-effective, single-step process enabling the controlled release of multiple drugs for HIV prevention and contraception. They will recruit around 16 women, aged 18–45 from Kampala Health Centre, and use focus groups to evaluate their views on the proposed 90-day timeframe of use for four different IVR prototypes to guide the final design.

Yasir Shafiq of Aga Khan University in Pakistan and Anne Lee of Brigham and Women's Hospital in the U.S. will develop geospatial models to predict risks of undernutrition among adolescent girls and pregnant and lactating women in settings affected by conflict, climate and COVID-19 to help target interventions. Globally, around 30–40 million pregnant women and 50 million adolescent girls are underweight. Risks of undernutrition have recently been amplified by numerous armed conflicts, climatic shocks such as flooding and the COVID-19 pandemic. However, real-time data shortages prevent interventions, such as balanced energy-protein supplements, from reaching the highest-risk groups. Using Bayesian Hierarchical Spatial modeling, they will develop geospatial models for countries vulnerable to conflict and climate change, such as Ethiopia and Yemen. By incorporating socio-demographic and economic indicators, and climate-related and conflict-related shocks from national databases, they can estimate risks based on exposure and predict outcomes, such as undernutrition and anemia.

Raghavan Varadarajan in collaboration with Sudha Kumari, both of the Indian Institute of Science in India and Nico Callewaert of the VIB-UGent Center for Medical Biotechnology in Belgium will modify the microorganism, Pichia pastoris, used to produce lower-cost vaccines in low-resource settings, to generate more effective vaccines. Many vaccines are composed of pathogen-derived proteins that require production inside other cells. Although P. pastoris can produce these antigens at a lower cost than mammalian or insect cells, the viral proteins it produced for the SARS-CoV-2 vaccine were hyperglycosylated and poorly immunogenic, unlike those produced in mammalian cells. They will express different antigen forms in mammalian cells, and in different Pichia hosts, to determine whether altering glycosylation and protein size affects immunogenicity. They will also glycoengineer Pichia hosts to determine whether they can produce more effective vaccines. Ultimately, this approach could improve vaccine production for COVID-19 and other viruses.

Jinal Bhiman of Wits Health Consortium (Pty) Ltd in South Africa and Jacqueline Weyer of the National Institute for Communicable Diseases also in South Africa will leverage a rapid monoclonal antibody (mAb) isolation and screening pipeline to develop diagnostics that differentiate between pathogens to support epidemic responses. Africa's burden of many zoonoses and vector-borne diseases (VBD), such as Lassa fever and yellow fever, remains largely unknown, mainly due to diagnostic costs and limited access to reagents. They will leverage an existing screening pipeline, with infrastructure established by the Global Immunology and Immune Sequencing for Epidemic Response - South Africa (GIISER-SA) project, using a mouse model as a more readily available source of pathogen-specific B cells to identify mAbs that detect three ebolavirus species. These mAbs will be tested for sensitivity and specificity using patient samples and can be used to develop immunoassays, including rapid lateral flow assays, which are important for rapid, field-based diagnosis.

Simon Kariuki of the Liverpool School of Tropical Medicine, Kenya in Kenya and Holden Maecker of Stanford University in the U.S. will determine whether probiotics and synbiotics can boost infant immune responses to vaccines. Diarrhea is the second leading cause of death in young children, with rotavirus a leading culprit. Oral rotavirus vaccines are routinely administered in low- and middle-income countries (LMIC) but are only 50% effective compared to 85–98% effectivity in high-income countries. One major cause could be environmental enteric dysfunction (EED), which is pervasive in children in LMIC. Their clinical trial of 600 newborns from western Kenya indicated that administering weekly probiotics and synbiotics (Lactobacilli and Bifidobacteria) up to age six months improved gut health and prevented EED-associated inflammation. They will use stored plasma samples and vaccination records to determine the impact of EED and systemic inflammation, as well as pro- and synbiotic effects on rotavirus vaccine efficacy.

Georgia Tomaras and Nathanial Chapman of Duke University and Girija Goyal and Don Ingber of the Wyss Institute at Harvard University, both in the U.S., will test whether Organ-on-a-Chip technology can inform how antibodies protect humans from pathogen infections to design more effective vaccines. Identifying protective vaccine features and validating them in human clinical trials is time-consuming and costly. An alternative is to use primary human organ chips that reproduce human physiology in vitro. They will stimulate peripheral blood mononuclear cells on the human lymph-node-on-a-chip with existing COVID vaccines and extensively characterize the resultant antibodies, including evaluating epitope specificity, and isotype and glycan profiling. They will also assess the capacity of these antibodies to prevent or reduce SARS-CoV-2 infection using the lung-on-a-chip technology. This approach can ultimately be applied to other pathogens, such as those causing malaria.

Cameron Myhrvold of Princeton University and Mireille Kamariza of the University of California, Los Angeles, both in the U.S., will develop an assay to rapidly detect multiple drug resistance mutations in Plasmodium falciparum and Mycobacterium tuberculosis for malaria and tuberculosis (TB) surveillance, respectively. Malaria and TB are two of the world's deadliest infectious diseases. Rapid and accurate drug resistance testing can save lives but current assays are slow or difficult to scale. Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN) is a CRISPR-based diagnostic test that detects nucleic acid biomarkers, such as those in pathogens, with high specificity and throughput. They have developed microfluidic CARMEN (mCARMEN), which produces results in under five hours, and will use an algorithm to design assays that detect the top ten drug-resistant P. falciparum mutations from blood samples, and M. tuberculosis mutations from saliva samples that confer resistance to two first-line TB drugs.

Maurício Barreto and colleagues of Fiocruz in Brazil, together with Alexa Heeks and colleagues of the Health Foundation of South Africa in South Africa, will employ real-world data from two large countries of the Global South to develop a common data model of infectious diseases affecting pregnant women to identify causes and aid intervention development. Centro de Integração de Dados e Conhecimentos para Saúde (CIDACS), together with the Western Cape Provincial Health Data Centre (WCPHDC), have built data systems to utilize routinely collected health data for exploring disease impacts. They will leverage these data systems to explore the impact of gestational syphilis in Bahia, Brazil, and tuberculosis in the Western Cape province of South Africa, and the coverage and effects of screening interventions. Teams will include data curators, analysts and scientists, who will perform data discovery and processing, alongside epidemiologists, clinicians and public health specialists, who will perform epidemiological analyses and community engagements.