All Awards

Joleen Masschelein of the VIB-KU Leuven Center for Microbiology in Belgium, with Paul Jensen of the University of California San Diego in the U.S., Lone Gram of Danmarks Tekniske Universitet in Denmark, Gilles van Wezel of Leiden University, Jos Raaijmakers of Netherlands Institute of Ecology, Bart Keijser of Netherlands Organisation for Applied Scientific Research all three in The Netherlands, Olga Genilloud at Medina in Spain and Nigel Mouncey at the Joint Genome Institute in the U.S., will apply ecology-inspired strategies to discover new antibiotics active against multidrug-resistant Klebsiella pneumoniae. The team will combine culture-independent metabolite capture, elicitation-based activation of microbial chemistry, high-throughput microfluidics, multi-omics and synthetic biology to access previously hidden natural product diversity from marine, plant, and human-associated microbiomes. Novel compounds will be prioritized, structurally characterized, and profiled for activity and safety to identify promising antibiotic scaffolds and mechanisms of action.

This grant is funded by The Novo Nordisk Foundation.

Annette von Delft and collaborators Nicole Stoesser, Lizbe Koekemoer, Ed Griffen, Paul Brennan, Frank von Delft, Phil Fowler, and Thomas Lanyon-Hoggat of the University of Oxford in the United Kingdom will utilize their well-established crystallographic fragment screening platform (XChem) and the newly developed Fast Forward Fragments (FFF) platform for rapidly progressing fragment hits into scaffolds, to identify novel small molecule hit series against three validated Klebsiella targets. Based on novel crystallographic fragment screening hits, they will generate novel chemical matter that directly addresses classical compound liabilities, by firstly prioritizing scaffolds that accumulate in efflux-pump expressing Klebsiella/Enterobacterales in design-make-test (DMT) cycles (assessed through a mass spectrometry based assay); secondly, by developing scaffolds by exclusively targeting resistance robust residues within the active site identified through an upfront assessment of target sequence variability; and thirdly by continuously optimizing for broad-spectrum Klebsiella spp. (plus other Enterobacterales) activity. Ultimately, they aim to enable a "ready-to-use", target-based antimicrobial discovery pipeline that can be applied to evaluating novel bacterial targets more broadly.

This grant is funded by The Novo Nordisk Foundation.

Joan Mecsas in collaboration with Bree Aldridge and Ralph Isberg all from Tufts University in the U.S. will develop portable tissue-specific in vivo and in vitro models that will be standardizable to accelerate Gram-negative drug discovery. In parallel, they will create a genetic target screening technology to identify drug-susceptible genes and pathways across a diverse set of multidrug-resistant Klebsiella pneumoniae strains in tissue-specific models. Their approach seeks to mitigate two key challenges to drug discovery: the high degree of bacterial genetic heterogeneity among multidrug-resistant Klebsiella, and the multiple distinct tissue environments inhabited by Klebsiella, both of which can significantly impact drug responses.  The overarching goals are to generate a compendium of pan-targets and dual-pan-targets, which include critical contextual information about conditionality on tissue niche and strain, and to de-risk drug discovery by using tractable tissue-based models for discovery, prioritization, and evaluation of new therapeutics.

This grant is funded by The Novo Nordisk Foundation.

Rebecca Page and her team at the University of Connecticut Health Center in the U.S. are developing a new class of antibiotic to target Klebsiella species. This strategy leverages their recent discovery that key steps in the formation of the bacterial cell wall, peptidoglycan recruitment and crosslinking, occur at different sites in penicillin binding proteins (PBPs). Their team will use an integrated approach combining sophisticated NMR spectroscopy, X-ray crystallography, high-throughput fragment screening, substrate synthesis, biochemistry and biophysics to identify the specific residues in Klebsiella PBPs responsible for peptidoglycan recruitment. They will then identify novel chemical matter that target these sites. This new class of antibiotics is predicted to have an exceptionally high barrier to resistance because mutations that inhibit antibiotic binding will also inhibit substrate recruitment and, in turn, the formation of the bacterial cell wall.

This grant is funded by The Novo Nordisk Foundation.

Gaurav Bhardwaj along with collaborators Joshua Woodward and Frank DiMaio all of the University of Washington in the U.S. will leverage recent advances in deep learning methods to build an AI-enabled platform for designing peptidomimetics and small-molecule inhibitors of essential bacterial proteins. The team will pursue three complementary strategies in parallel to design new antibiotic candidates against Klebsiella pneumoniae. First, they will redesign natural products into more stable, synthetically-accessible peptidomimetics. In parallel, they will use AI-enabled methods to de novo design new direct-acting inhibitors of critical bacterial proteins. Finally, the team will use bioactive macrocyclic peptides to identify potent small molecule inhibitors of bacterial proteins critical for growth and survival. Together, these approaches will establish a broadly applicable platform for the rapidly generating customized antibiotic candidates against a range of targets and bacterial pathogens.

This grant is funded by The Novo Nordisk Foundation.

Ian Gilbert and colleagues at the University of Dundee in the United Kingdom, along with Beverly Egyir of the Noguchi Memorial Institute for Medical Research in Ghana, will integrate microbiology and industrial drug discovery expertise to tackle drug-resistant and hypervirulent Klebsiella. They will screen compounds in infection-mimicking conditions to identify novel chemical start points and drug targets. In contrast to current antibiotic targets which are essential for growth, the team will seek drug targets which cause lethal damage to bacteria when they are in slow or non-growing states typical of infection environments. They will use their integrated drug discovery platform to validate and optimize hits, including testing against global clinical isolates, with the aim of establishing proof of concept for these new series.

This grant is funded by The Novo Nordisk Foundation.

Kim Lewis of Northeastern University in the U.S. will lead a team that will develop an advanced platform to resolve intractable bottlenecks in antibiotic discovery. The focus will be on 30 targets in the cell envelope of Gram-negative bacteria. An AI-based search of genomic libraries for biosynthetic gene clusters associated with these targets produces candidate hits for isolation and also identifies producing taxa for selective capture of soil microbes. Encapsulating single cells from the environment in microdroplets obviates library construction. A pair of differently colored detector strains, susceptible/resistant to a compound hitting the desired target, identifies attractive hits at a test rate of 1,000,000/hour. Uncultured bacteria are incorporated into the screen, and the platform provides access to silent operons. Antibiotics discovered in this project will serve as a starting point for subsequent medicinal chemistry optimization.

This grant is funded by The Novo Nordisk Foundation.

Andrew Edwards, Edward Tate, Matthew Child, Gad Frankel, Paul Freemont, Marko Storch, Alessandra Russo, Mauricio Barahona and Ramon Vilar of Imperial College London, part of the Fleming Initiative, in the United Kingdom, will use novel genomic and proteomic approaches to identify previously unrecognized targets for new anti-Klebsiella therapeutics. In parallel, the team will use high-throughput accumulation assays, physical chemistry, AI/Machine Learning, data science and molecular bacteriology approaches to decipher the chemical rules of small molecule accumulation in Klebsiella cells. Combined, this work will identify new targets and ensure that small molecule inhibitors accumulate at therapeutic concentrations, paving the way for the development of novel antibiotics active against Klebsiella and other Gram-negative priority pathogens.

This grant is funded by The Wellcome Trust.

Paul J. Hergenrother, along with collaborators at the University of Illinois in the US - Rohit Bhargava, William Metcalf, Gee Lau, and Emad Tajkhorshid - will develop tools that will ultimately lead to novel antibacterial compounds active against K. pneumoniae and other problematic Gram-negative pathogens. While there are many promising antibacterial targets in the periplasm, no convenient method exists to study the exact location of a compound in the Gram-negative cell, and there is no means to direct a compound to a specific subcellular localization. Using a novel imaging technology, the subcellular localization of scores of compounds will be tracked, and through this process the chemical traits that facilitate various subcellular localizations will be elucidated, with a special focus on the periplasm. This information will lead to a streamlined workflow for multi-parameter optimization of antibiotics and will be used to discover novel antibiotic candidates for important biological targets.

This grant is funded by The Wellcome Trust.

Andres Floto with Vitor Mendes, David Spring, Aaron Weimann, Sebastian Bruchmann, and José Miguel Hernández Lobato of the University of Cambridge in the United Kingdom will experimentally define the factors that control compound retention and xenometabolism in Klebsiella pneumoniae and the genetic determinants for variation in these processes across the phylogenetic diversity of this pathogen. The project will create predictive AI models of compound retention and stability by experimentally characterizing the chemical space of compounds that can accumulate inside this pathogen and remain stable. They will then use these models to steer chemical elaboration during structure-guided antibiotic discovery against novel targets, and make them freely available to academic and industry researchers.

This grant is funded by The Wellcome Trust.

Erick Strauss of Stellenbosch University in South Africa, in collaboration with co-investigators Andrew Whitelaw also of Stellenbosch University, Adrienne Edkins of Rhodes University in South Africa and Miquel Duran-Frigola of Ersilia Open Source Initiative in Spain will pursue the discovery of new Gram-negative antibacterials through the development of bacterial proteolysis targeting chimeras (BacPROTACs) - bifunctional molecules designed to engage high value protein targets and an endogenous intracellular protease in the pathogen to induce proteolytic degradation. In this manner, BacPROTACs use targeted protein degradation (TPD) as a highly innovative strategy to achieve an antibacterial outcome. The team proposes to use this approach to establish a BacPROTAC development workflow that can be applied for the identification of new chemical leads for any validated drug target or resistance-inducing factor that can be shown to be degraded by the pathogen’s endogenous protease, and for which a target-engaging ligand (TEL) can be identified.

This grant is funded by The Wellcome Trust.

Daniel Inaoka of the Institute of Tropical Medicine Nagasaki University and Yohei Doi of Fujita Health University, both in Japan, will aim to identify novel antibacterial compounds with new mechanisms of action (MoAs) against Klebsiella pneumoniae. By integrating high-throughput screening, transcriptomic profiling (Quartz-seq2), and genomic analysis, they will systematically discover and characterize compounds with distinct MoAs from existing antibiotics. Approximately 260,000 compounds from Japan’s two largest academic libraries will be screened. Active hits will be confirmed and validated, with transcriptomic clustering and machine learning applied to efficiently identify candidates with new MoAs. Resistant mutants will then be generated and analyzed by whole-genome sequencing to elucidate molecular targets.

This grant is funded by The Wellcome Trust.

Stephen Dela Ahator of the University of Ghana in Ghana, will pioneer a project involving multidisciplinary platform combining chemoproteomics and machine learning to accelerate the discovery of next-generation antimicrobials against Klebsiella. Using activity-based protein profiling, the project aims to map the functional landscape of bacterial bioactive enzymes to identify evolutionarily conserved and druggable targets. A hybrid graph neural network model will then predict and prioritize small-molecule inhibitors with high specificity and low human cross-reactivity. Lead compounds will be experimentally validated for potency, selectivity, and safety in infection models. By integrating functional proteomics with AI-driven compound screening, this project will aim to deliver new therapeutic scaffolds, establish an adaptable antimicrobial discovery pipeline, and strengthen research capacity through international collaboration between Ghana, Norway, the UK, and New Zealand.

This grant is funded by The Wellcome Trust.

Everett Tate of the University of Chicago in the U.S., with collaborators in the United Arab Emirates, Ghana, Kenya, South Africa, and India, will establish a multi-site consortium for research on heavy menstrual bleeding. Consortium sites, including hospitals, clinics, and universities, will standardize processes for collecting patient samples and data, and they will establish a database integrating immune and cytokine profiling, genetic analysis, and ultrasound imaging, including AI-based data modeling. They will also perform epidemiological analyses, incorporating data gathered from patients visiting mobile health vans, to better understand the geospatial distribution of heavy menstrual bleeding prevalence and risk. The consortium approach will provide a framework to improve the accuracy, efficiency, and accessibility of early diagnosis of the condition in low-resource settings.

Ayokunle Olanrewaju, and collaborators Ashleigh Theberge and Erwin Berthier, of the University of Washington in the U.S. will develop a platform for at-home self-collection of blood, serum separation, and sample stabilization at sufficient sample volumes for comprehensive HIV monitoring. An existing device for home blood collection will be expanded with the development of serum separation using a simple filtration system and connected to a standard blood collection tube with serum-stabilizing reagents. The device design will be optimized to ensure that over 1 mL of blood can be processed. The resulting design will then be tested for its effectiveness for RNA and protein analysis to monitor HIV viral load and biomarkers associated with HIV treatment and care. Performance of the device will be compared to standard blood processing, using blood from healthy volunteers spiked with either HIV RNA or C-reactive protein as a model biomarker. They envision a system that can readily integrate with standard laboratory or point-of-care diagnostic workflows to enable maximal deployability.

Hatice Ceylan Koydemir with Sandun Fernando at Texas A&M University in the U.S., working with Levent Beker and Ebru Celik of Koç University in Turkey, will develop an affordable point-of-care diagnostic platform for prediction and detection of preeclampsia early in pregnancy. By employing sensor miniaturization and integrating with low-cost electronic devices, they aim to provide a battery-less, easy-to-use, portable platform for automated data analysis at the point of care, particularly suitable for use in low- and middle-income countries (LMICs). They will evaluate the prototype device using human serum samples spiked with preeclampsia biomarker proteins, as well as serum samples collected from over 100 participants at Koç University Hospital in Turkey and an LMIC setting, comparing the device's results to hospital clinical reports.

Lisa Rohan of the University of Pittsburgh in the U.S., with Thesla Palanee-Phillips of the Wits Health Consortium (Pty) Ltd in South Africa, will develop a vaginal film technology for the sustained release of the hormone levonorgestrel as a product that provides contraception and reduces heavy menstrual bleeding. Levonorgestrel is a progestin, a synthetic hormone that mimics the effects of progesterone. They will create and compare vaginal films with differences in mechanical properties, mucoadhesion, and drug release profiles to design a product that is low-cost, self-administered, and active for one month. They will also conduct a pilot trial of two prototype placebo films without levonorgestrel, evaluating them for safety, acceptability, and mucoadhesion in 20 women in South Africa, half with heavy menstrual bleeding.

Joyce Were of the Kenya Medical Research Institute in Kenya will develop a screening tool for assessing heavy menstrual bleeding that is adapted for use in Kenya by integrating two globally used questionnaires, adding material to incorporate the impact on women in the Kenyan context, and translating it into the locally spoken languages Swahili and Luo. Through consultations with experts, the tool will combine the Menstrual Bleeding Questionnaire (MBQ) with the Screening Assessment and Measurement of Atypical and Normal Menstrual Patterns Tool for Adolescents and Adults (SAMANTA), and it will incorporate new questions. The tool will be iteratively modified through small pilot tests. It will then be administered to adolescent girls and young women in Western Kenya as part of the Health and Demographic Surveillance System (HDSS) of the Kenya Medical Research Institute (KEMRI), with 70,000 participants surveyed with either the new tool or the MBQ or SAMANTA tools for comparison.

Jennifer Anyanti of the Society for Family Health with Clara Ejembi from Ahmadu Bello University, both in Nigeria, will evaluate patient experiences and treatment outcomes in women with heavy menstrual bleeding in Nigeria, with a focus on increasing the effectiveness, acceptability, and accessibility of hormonal contraceptives as treatment. Clinical data will be collected for a cohort of women receiving care for the condition in Kaduna state in Nigeria, together with qualitative data from interviews with patients, care providers, and supply chain managers. This information will be used to design and pilot targeted interventions to increase access to acceptable and effective treatment, such as community health education, supply chain improvements, and treatment programs. Such interventions can be iteratively improved with the original evaluation framework, generating a sustainable data management system to guide improvements in patient-centered care for heavy menstrual bleeding.

Anne Beatrice Kihara with Moses Madadi, both of the University of Nairobi in Kenya, will pilot a multipronged approach to support research and development for women’s health in Kenya. They will co-develop a policy and regulatory framework that integrates gender equity, working with government stakeholders, including the Ministry of Health and regulators, as well as civil society groups and women-led organizations. They will develop case studies of healthcare technologies for women’s health, focused on how accessible these technologies are for women in underserved communities; launch community-based campaigns to increase awareness and understanding of women’s health and healthcare solutions; and train healthcare professionals in applying an equity perspective in women’s health research and care. Community feedback will guide an iterative approach throughout these efforts.

Mathew Njoroge of the University of Cape Town in South Africa, with Roslyn Thelingwani of the African Institute of Biomedical Science and Technology in Zimbabwe, will analyze liver tissue from an African patient biobank to characterize the variability in drug metabolism in African populations. The analysis will combine genotyping, in vitro physiology studies, and pharmacokinetic modeling. Using the biobank samples, they will perform targeted sequencing of genes known to be associated with drug absorption, distribution, metabolism, and excretion, and then use the genotyped samples for in vitro analysis of drug clearance. This data will be combined with data modeling to predict the variability of drug pharmacokinetics in vivo to guide drug development and inform the design, monitoring, and interpretation of clinical trials.

Eachan Johnson of the Francis Crick Institute in the United Kingdom will develop a platform to accelerate the discovery of new antibiotics for Klebsiella pneumoniae, a major cause of drug-resistant infections worldwide. The project aims to understand which bacterial genes are most critical for survival across diverse conditions, and to use that knowledge to identify new ways to disable the bacterium during infection. They will build an integrated, scalable approach that combines genetic tools with phenotypic screening to reveal how chemical compounds act on Klebsiella pneumoniae and to highlight those with the greatest promise as starting points for new treatments. The work will generate foundational datasets, resources, and protocols to strengthen drug-discovery capacity across the Gr-ADI consortium, with the long-term goal of enabling more reliable, mechanism-guided development of antibiotics for Gram-negative infections.

Daniel Kahne of Harvard University, Thomas Bernhardt and Andrew Kruse of Harvard Medical School, and Jiankun Lyu of the Rockefeller University, all in the U.S. will discover novel antibiotics that target essential processes required for cell surface biogenesis in the Gram-negative pathogen Klebsiella pneumoniae. This bacterium and its relatives surround themselves with a multilayered cell surface composed of two membranes - an inner and an outer membrane - sandwiching a cell wall matrix made of the heteropolymer peptidoglycan. This surface architecture prevents many drugs from entering Gram-negative bacterial cells, giving them a high intrinsic resistance to antibiotics. Few therapeutic options are available for treating infections caused by these organisms, especially those that have acquired resistance to carbapenem antibiotics. This project will address the urgent clinical need for novel antibiotics effective against K. pneumoniae and other Gram-negative bacteria by identifying new inhibitors of outer membrane and peptidoglycan biogenesis.

Denali Dahl of Kalia Health, Inc. in the U.S. will evaluate Activin A and Inhibin A as urinary biomarkers for prediction and detection of preeclampsia early in pregnancy. This work builds on an ongoing biomarker validation study in Bloemfontein, South Africa. Through collaborations, clinical studies will be performed with blood and urine sampling in cohorts of pregnant women. Studies in Stellenbosch, South Africa will assess how levels of the two proteins vary in urine during pregnancy, and studies in Bloemfontein, South Africa will assess how early in pregnancy they can serve to predict preeclampsia risk. Activin A and Inhibin A levels in urine will be measured by MSD, and their diagnostic value will be compared to a standard assay for the biomarker protein ratio sFlt1/PIGF in blood and to clinical diagnosis by the treating physician.

Cliveland Ogallo of the Center for Public Health and Development (CPHD) with Anne-Beatrice Kihara of the University of Nairobi, both in Kenya, will assess the impact of heavy menstrual bleeding on the health and well-being of adolescent girls in an underserved community in Kenya. Girls in the Kibera urban informal settlement will be surveyed, along with guardians and health workers, to assess the prevalence of self-reported heavy menstrual bleeding; menstrual health literacy and associated cultural narratives; hygiene practices; access to healthcare products and services; and impacts including anemia, school absenteeism, and psychosocial well-being. Small-scale interventions will also be piloted, such as introducing menstrual kits with educational packets and dedicated physical spaces for menstrual hygiene.

James Beeson of the Burnet Institute with Stephen Scally of The Walter and Eliza Hall Institute, both in Australia, will develop candidate malaria mRNA vaccines designed to confer multiple types of immunity over multiple lifecycle stages of the malaria parasite. They will start with lead candidates that target Plasmodium merozoites, screening them with a human organoid model of the germinal center for their ability to activate B cell responses. Based on these tests, they will add antigens and test the resulting multi-antigen vaccines in animal models to create candidates that confer anti-merozoite, anti-sporozoite, and transmission-blocking immunity.

Brian Sullivan of Arcturus Therapeutics, with Sean Murphy of the University of Washington Foundation, both in the U.S., will pilot test a self-amplifying mRNA vaccine technology as a platform for developing malaria vaccines. They will use a mouse model of malaria, establishing infections in parallel with two different Plasmodium parasite species. They will test preventive treatments in this model, comparing self-amplifying mRNA vaccine technology to conventional mRNA and comparing intramuscular versus intravenous administration. They will assess the ability of each test vaccine to protect against liver-stage infection, determining the number of liver-stage parasites and how well the vaccine elicits potent, malaria-specific T-cell responses in the liver. The prolonged antigen expression characteristic of self-amplifying mRNA vaccines could be particularly valuable in inducing long-term protection against malaria.

Pranay Lal of the Forum for Health Systems Design and Transformation in India will develop mechanisms for the Indian state of Odisha to manage heat stress and ensure the uninterrupted functioning of public health infrastructure during extreme weather events including heatwaves and floods. They will analyze historical data for climate and its impacts on human health, integrating data not only for temperature but also for humidity to generate heat risk profiles of two districts in Odisha. These profiles will help guide when, where, and how to implement public health interventions during heatwaves. They will also use data modeling approaches to assess the risks to healthcare facilities from severe weather under different climate-change scenarios. This will support health officials and other stakeholders in these two districts to develop a set of protective strategies.

Neha Lasure of Intignus Biotech Pvt. Ltd. in India will develop an affordable point-of-care diagnostic platform for prediction and detection of preeclampsia early in pregnancy. The diagnostic test is a lateral flow immunoassay that detects two key preeclampsia biomarker proteins in blood: sENG and PIGF. They will generate monoclonal antibodies against these proteins, manufacture test kits, and train frontline health care workers to administer and interpret the test. They will then perform a pilot study with 2,000 pregnant women in the Indian states of Pune and Mumbai, evaluating prediction accuracy compared to clinical outcomes and standard existing clinical tests.

Sarah Leeber of the University of Antwerp in Belgium, with Marie Josiane Kenfack of the Center for Research on Emerging and Reemerging Diseases (CREMER) in Cameroon, will add DNA sequencing analysis of the vaginal microbiota as a component for a set of clinical trials of menstrual hygiene products in Belgium, Switzerland, Cameroon, and Peru. The longitudinal trials compare use of different menstrual products, with participants using either the same product over time or different products in sequence, including pads, tampons, cups, and underwear. Surveys and group discussions will be used to gather data on user perceptions of the products and how acquiring knowledge of the microbiome may influence attitudes and practices. Shotgun metagenomic sequencing from self-collected samples will reveal changes in the vaginal microbiota associated with different products. Together, this data will provide a more comprehensive understanding of both the biological and behavioral dimensions of menstrual product use.

Almaz Negash of the African Diaspora Network in the U.S. will build an AI-augmented collaboration hub that matches senior African scientists with experienced researchers and innovators in the African diaspora. The hub will include AI-assisted profiling of skills and needs, focusing on areas including pharmacogenetics, pharmaceutical manufacturing for preclinical and clinical trials, infectious disease control, and data science. The hub will host monthly masterclasses and peer-learning sessions, and it will support co-designed research, co-supervision of students, joint grant applications, and technology transfers. It will be launched with an inaugural cohort of Africa-based scientists, including the Calestous Juma Fellows as an existing network of science leaders already embedded in African universities and research centers.

Margaret Ilomuanya of the University of Lagos in Nigeria will develop a multifunctional microneedle patch for delivery of agents that treat heavy menstrual bleeding while preventing disease from sexually-transmitted viral infections. The patch will be designed for use on the abdomen or thigh, and it will have a layered architecture to deliver multiple drugs: tranexamic acid and the progesterone-mimic levonorgestrel to reduce bleeding (with levonorgestrel also having contraceptive activity) and the antiviral drug tenofovir. Microneedle-delivered tranexamic acid and levonorgestrel will be tested, both for their safety and their ability to control bleeding, in assays including clotting in vitro, a rat model, and a rabbit model of menstruation. Women experiencing heavy menstrual bleeding will be engaged for group discussions to assess the acceptability, usability, and desirability of the microneedle patch compared to existing treatment options, such as oral tranexamic acid and hormonal intrauterine devices.

Sara Khalid of the University of Oxford in the United Kingdom will use large data sets from Kenya, Pakistan, and the United Kingdom to better understand the health impact and treatment challenges associated with heavy menstrual bleeding in low-resource settings. The project is a collaboration between Oxford University, Aga Khan University Kenya, and Aga Khan University Hospital Pakistan, with analysis of existing data sets in these three countries covering over twenty years of data for women diagnosed with heavy menstrual bleeding. For Kenya and Pakistan, analysis will encompass disease burden and epidemiology; patterns in treatment access, adherence, and effectiveness; and risk factors, with a risk prediction tool generated for heavy menstrual bleeding and its adverse outcomes. Equivalent analysis will be performed with data from the United Kingdom stratified by ethnic group to identify unique and shared features of the condition across settings.

Brandon DeKosky of the Massachusetts General Hospital, with Carole Long of the National Institute of Allergy and Infectious Diseases, both in the U.S., will develop a high-throughput, microfluidic screening platform to identify antibodies active against blood-stage malaria parasites. The platform is based on individual droplets containing a mix of Plasmodium parasite-infected and uninfected red blood cells together with mammalian cells secreting monoclonal antibodies. Each droplet serves as a parasite neutralization assay: antibodies that block parasite invasion of new red blood cells limit growth of the parasite population, and this is readily quantified using parasite-specific protein activity. With miniature droplets assayed in parallel, mammalian cells expressing a library of monoclonal antibodies can be rapidly screened for antimalarial activity.

Nadia Diamond-Smith of the University of California San Francisco in the U.S. will characterize the prevalence and impact of heavy menstrual bleeding as well as treatment preferences in a cohort of women in the state of Rajasthan in India. Building on an ongoing survey, new data will be acquired from 1,500 women in Rajasthan, including newly married women and their mothers-in-law. The prevalence of heavy menstrual bleeding will be determined, and the data will be modeled for its impact on women's physical and mental health. Twenty-five in-depth interviews will be performed, with the information used to design and launch a discrete choice experiment through a survey of 300 women from the cohort with heavy menstrual bleeding. This survey will uncover women's preferences across treatment options for the condition, including their willingness to pay for them, setting the stage for designing treatment programs based on the local context.

Ianessa Morantte of Prolific Machines Inc. in the U.S. with Arif Jetha of Radiant Biotherapeutics Inc. in Canada, are combining complementary platforms to enhance the production of broadly neutralizing antibodies (bnAbs) against HIV. Radiant has developed the Multabody platform™, which uses a self-multimerizing scaffold to multimerize antibody fragments. These fragments will be expressed using Prolific's proprietary Photomolecular Biomanufacturing Platform, which leverages light-controlled (optogenetic) cell lines that provide tunable gene expression control, facilitating expression of complex biotherapeutics. Stable, optogenetic host cell lines will be engineered by Prolific Machines to express multimers, each with a different combination of antibody fragments. The system will be assessed for its ability to increase Multabody yields by separating growth and production, and provide control over antibody fragment ratios with light, with the goal to pursue scale-up at a cost low enough to broadly increase access.

Annie McDougall of the Burnet Institute in Australia will develop a digital tool for point-of-care prediction of preeclampsia risk early in pregnancy, using data from clinical trials in Sub-Saharan Africa. A predictive model will be developed and validated using data from an ongoing set of clinical treatment studies in Ghana, Kenya, and South Africa: the PEARLS trial (Preventing Preeclampsia: Evaluating Aspirin Low-Dose Regimens Following Risk Screening). This model will be used to develop a tool for automated preeclampsia risk stratification to support clinical decision making by antenatal care workers. It will be designed for integration into existing digital health platforms, including real-time patient data entry. The tool will be evaluated for usability, feasibility, and acceptability through interviews and workshops with patients and care workers in two of the PEARLS trial countries.

Javan Esfandiari of Chembio Diagnostics, Inc. in the U.S. will develop an affordable point-of-care diagnostic platform for prediction and detection of preeclampsia early in pregnancy. The diagnostic test is a semi-quantitative lateral flow immunoassay to monitor the level of the key preeclampsia biomarker protein sFlt1 in whole blood from a finger prick. The test will discriminate between two levels of the biomarker, identifying patients at either low, medium, or high risk of developing preeclampsia, and it will be integrated into a low-cost, portable reader device. Through local collaboration, the prototype device will be tested in France, Nigeria, and Benin. In each country, 100 women with identified risk of preeclampsia will participate. For comparison with the diagnostic test results and predicted preeclampsia risk, patient clinical outcomes will be recorded, and serum samples will be tested at a central laboratory, using existing tests to measure sFlt1 and the sFlt1/PIGF biomarker ratio.

Brandon Wilder with Daniel Streblow, both of Oregon Health and Science University in the U.S., will develop a vaccine platform based on virus-like vesicles (VLVs) as a vaccine vector that can be launched in vivo from nucleic acids and express proteins that elicit cellular and humoral immunity. They will optimize in vitro-generated VLVs for expression of an established Plasmodium berghei antigen and for immunogenicity in a mouse model of malaria. They will then vaccinate mice with gene gun-delivered, optimized plasmid DNA to demonstrate that VLVs can be generated in vivo, to assess their persistence and tissue distribution, and to test whether immunity can be boosted by a second vaccination.

Irene Njuguna of Emory University in the U.S. will determine the prevalence and impact of heavy menstrual bleeding in adolescent girls and young women in a variety of community settings in Kenya, as well as the barriers to treatment delivery and uptake. Two thousand adolescent girls and young women aged 10-24 across rural and urban communities in Kenya will be surveyed to determine heavy menstrual bleeding prevalence, and their hemoglobin levels will be measured to assess for anemia as a consequence. Interviews and focus group discussions with participants as well as with care providers will be performed to assess the available options for care and treatment of the condition, including patient referral pathways, and to identify barriers hindering patients from seeking care and providers from delivering it.

Maneesha Inamdar of the Institute for Stem Cell Biology and Regenerative Medicine in India will develop a standardized organoid model of the human endometrium, together with a reproducible and scalable process for generating these organoids. Protocols for deriving endometrial organoids from established human pluripotent stem cell lines will be optimized. This includes generating fluorescent reporter cell lines as visible readouts of secreted products to monitor development and differentiation of the input cells, as well as determining the assays for comparing organoid function with that of human endometrial tissue. The resulting model system will enable automated analysis with equipment for routine cell culture and without the need for human clinical samples, and it will facilitate human endometrial biology research to identify therapeutic targets and treatments for heavy menstrual bleeding.

Jianghong Rao of Stanford University in the U.S. will develop a magnet-based system for capturing and concentrating the TB bacterium from sputum biosamples to facilitate TB diagnosis. The system is based on conjugating magnetic nanoparticles to bacteriophage specific to Mycobacterium tuberculosis, so that a simple magnet can capture phage-bound TB bacteria from patient sputum. This process will be optimized, including the stability and activity of the magnetized phage in a lyophilized powder form and at a high ambient temperature. A prototype device for the magnetic phage system will be designed and tested for its ability to generate purified target bacteria ready for lysis and PCR-based diagnostic testing. Initial tests will use a non-TB Mycobacterium species, and subsequent tests in collaboration with Niaz Banaei at Stanford Health Care Clinical Microbiology Laboratory will use clinical TB patient samples.

Jason Peters of the University of Wisconsin in the U.S. will identify high-priority Klebsiella genes for targeting with mono- or poly-therapies using comprehensive, state-of-the-art functional genomics approaches.

Suman Chakraborty of the Indian Institute of Technology Kharagpur in India will develop a membrane filtration system for Mycobacterium tuberculosis lysis and DNA purification from patient samples to enhance TB diagnosis. A paper-based membrane will be impregnated with two chemical agents, each in a separate layer, for sequential sample processing. Cell lysis will be performed in the first layer by zinc oxide nanoflowers, nanoscale structures that lyse bacterial cells through both mechanical and chemical mechanisms. DNA purification will be performed in the second layer by silica nanoparticles. This membrane system can be attached to a DNA amplification chamber with lyophilized reagents for colorimetric Loop-Mediated Isothermal Amplification (LAMP). This instrument-free, integrated process for TB diagnosis will be tested in a research setting and a clinical pathology laboratory setting.

Liya Wassie of the Armauer Hansen Research Institute in Ethiopia, with Richa Vashishtha of the Biotechnology Industry Research Assistance Council (BIRAC) in India, will develop resources for investigators in low- and middle-income countries (LMICs) to integrate ethical principles into the design and deployment of health-related AI technologies. They will establish and coordinate a multi-country AI ethics working group to develop a practical ethics guide for AI innovators, and the guide will be finalized through two public workshops. They will also launch public discussion sessions on key AI topics, such as algorithmic bias and data privacy, and coordinate an internship program on AI ethics for early- and mid-career LMIC investigators.

Sweta Kanavaje of the Myna Mahila Foundation in India will evaluate the effectiveness of the Myna Bolo chatbot in providing confidential, culturally sensitive, and medically accurate guidance on heavy menstrual bleeding to women in poor urban communities in Mumbai. The chatbot incorporates Large Language Models and currently provides tailored sexual and reproductive health information through multiple platforms in local languages. The chatbot will be evaluated specifically for advice on heavy menstrual bleeding through a randomized controlled trial with 400 women from Mumbai, comparing the chatbot to standard in-person counseling and to telehealth counseling. Primary outcomes of the trial, assessed through questionnaires and focus groups, include diagnostic accuracy compared to clinical assessments, reduction in time to seek and begin treatment, and improved understanding of menstrual health.

David Erickson of Cornell University in the U.S. will develop a device for heat inactivation and mechanical lysis of Mycobacterium tuberculosis from patient samples to enhance TB diagnosis. A prototype device will be engineered, using a non-TB Mycobacterium for testing as a proxy. The device combines an alternating magnetic field and magnetic beads to inductively heat inactivate bacterial samples and actuate lysis by a bead-beating mechanism. The protype will be pilot tested in a collaboration at the Infectious Diseases Institute in Kampala, Uganda where patient samples with presumptive TB will be processed with the standard protocol for TB diagnosis and in parallel with the prototype.

Sam Nugen of Cornell University in the U.S. will develop a bacteriophage-based system for the rapid concentration and lysis of Mycobacterium tuberculosis from patient samples to enhance TB diagnosis. A mycobacteriophage will be engineered to express the streptavidin protein, enabling low-cost magnetic particles to capture and concentrate the phage along with the TB bacterium to which it naturally binds. The phage will also be engineered to accelerate lysis of the TB bacterium after it is bound, and phage replication genes will be deleted to ensure that the phage can only replicate in a modified host bacterium or an in vitro system, not self-replicate. This low-cost, easily propagated system provides a streamlined, instrument-free solution to improve the efficiency of TB diagnosis in resource-limited settings.

Moses Madadi of the University of Nairobi in Kenya, with Annettee Nakimuli of Makerere University in Uganda, will establish a platform for coordinated advocacy to reduce the burden of postpartum hemorrhage, a major cause of maternal mortality and morbidity. The platform will build on the inaugural advocacy meeting called Run for Her, which was held in Kenya in 2024. This meeting brought together an international group of healthcare practitioners, politicians, policy makers, students, and religious leaders to raise awareness about postpartum hemorrhage. They will establish an African continent-wide network, expanding from Kenya to ten additional African countries, with annual advocacy events to directly engage local communities and other key stakeholders. The platform will raise awareness and inform data-driven policies for procuring essential medications and therapies, training and reskilling healthcare workers, and establishing systems for ongoing data collection.

Lily Telisinghe of University Hospitals Plymouth NHS Trust together with Ben Swift at PBD Biotech Ltd in the United Kingdom will develop a system combining a biological agent and mechanical disruption for the rapid lysis of Mycobacterium tuberculosis from patient samples to enhance TB diagnosis. Tests will be performed to determine if there are constraints for two biosample types, tongue swabs and blood, on how soon after sampling they must be analyzed. These sample types will then be spiked with the BCG vaccine strain and used to determine the optimal combination of factors for cell lysis. This combination of conditions will then be used to test how the lysis system performs for TB diagnosis in patients in the United Kingdom and Indonesia.

Meng Sun of the Zymeron Corporation in the U.S. will develop a small, handheld, low-cost device for rapid plasma separation from whole blood for HIV diagnostic testing. Existing versions of the device will be modified to be able to process a larger volume of blood and deliver 100-200 microliters of plasma. The device is designed for untrained users. It can readily be modified to connect with blood drawing devices, including automatically sampling a fixed volume of blood to process, either by capillary action or direct loading, and delivering a fixed volume of plasma. It can also readily be integrated to deliver plasma to different diagnostic platforms, such as those based on microfluidics and lateral flow systems.

Salus Discovery in the U.S. will optimize a prototype of their simple and inexpensive SnapTab platform technology for processing of finger-prick blood for HIV diagnostic testing. SnapTab components and chemistry will be optimized for blood plasma separation, viral lysis, and in a final step, nucleic acid purification and stabilization. The output can then be directly used in standard quantitative PCR amplification reactions for HIV detection. To evaluate the performance of SnapTab for HIV, sample extraction/purification results will be compared against existing approaches including the plasma separation card and traditional bead-based processing of plasma.

Yves Brun of the University of Montréal and Mike Tyers of the Hospital for Sick Children in collaboration with colleagues at the Québec Institute for Learning Algorithms, the Institute for Research in Immunology and Cancer, SickKids, the University of Toronto and Simmunome Inc., all in Canada, will combine generative machine learning (ML) with high-throughput phenotypic- and target-based screens to identify new antibiotics against multidrug-resistant Klebsiella. The multidisciplinary team will use high-content microscopy and genome-wide CRISPRi to generate phenotypic and genetic profiles of Klebsiella responses to compounds and then train ML models on antibiotic activity, penetration, and resistance. In parallel, the team will use generative ML to design novel, synthesizable compounds against key Klebsiella targets, which will be produced by parallelized chemical synthesis and tested for antibiotic activity. A lab-in-the-loop active learning approach will be used to iteratively optimize ML models to predict potent new antibiotics active against Klebsiella.

Jeffrey Burke of Prompt Diagnostics, Inc. in the U.S. will develop a low-cost, automated platform integrating blood sample input, plasma separation, and HIV RNA extraction for HIV diagnostic testing. The platform will be based on magnetofluidic cartridge technology in which sequential bioassay steps are conducted via transfer of magnetic beads between reagents: red blood cell-binding beads in the plasma separation step and RNA-binding beads in the virion lysis step. A prototype cartridge will be built and optimized, including reagents in shelf-stable formats, and a low-cost, battery-powered device will be built to house the cartridge and drive the transfer of magnetic beads. The prototype platform will be tested for RNA quality and extraction efficiency, using blood samples spiked with HIV virions and comparing directly to standard clinical laboratory procedures.

Rainer Ng of Baebies, Inc. in the U.S. will develop a system for finger-prick blood self-collection and sample processing that yields a sample ready for HIV diagnostic testing either at the point of care or after delivery to a central laboratory. A simple, disposable sample collection device will incorporate a membrane for plasma separation. Squeezing the device delivers plasma to a tube in which HIV-binding magnetic beads concentrate virions and reagents stabilize them. The prototype system will be optimized to ensure it generates over 100 microliters of plasma from self-collected blood, captures virions of sufficient quality and quantity to enable standard RT-PCR testing, and stabilizes virions sufficiently for diagnostic testing over three days after sample collection.

Atunga Nyachieo of the Kenya Institute of Primate Research (KIPRE) in Kenya, with Alfred Botchway of Attentive Science in the U.S., will perform a pilot study as a first step in creating an integrated, preclinical, toxicology testing hub at KIPRE to accelerate drug discovery. The pilot will begin with a toxicology study in rodents to assess existing protocols, including those for dose formulation, oral administration, observation and recording of clinical signs of toxicity, collection and processing of blood and tissue, and histopathology review of tissue slides. This assessment will identify gaps as well as guiding the development of standard operating procedures and of specialized training programs in toxicology and related disciplines.

Christopher Love with Hadley Sikes of the Massachusetts Institute of Technology in the U.S. will develop a biomanufacturing platform for low-cost production of monoclonal antibodies based on a multidomain synthetic protein enabling both capture and purification of the antibody in a chromatography-free process. The synthetic protein will concentrate and recover antibodies in a single, mobile fluid phase, based on studies of the liquid-liquid phase transition of proteins into condensates that occur naturally in key cellular processes. They will design and test protein agents for affinity-based capture and condensation of monoclonal antibodies including the antimalarial MAM01, assess the co-expression of the synthetic protein and the target antibody product in a microbial expression system, and determine conditions for continuous recovery of the product. They will also create models of the technical and economic factors required for low-cost production from either microbial or mammalian cell expression systems.

This grant is one of three grants that are funded and administered by LifeArc.

Rohini Nair of Gujarat Biotechnology University in India will explore the cellular heterogeneity and molecular pathways associated with heavy menstrual bleeding to better understand the condition, using single-cell transcriptional profiling of the endometrium in patients. In collaboration with Rohina Aggarwal of the Institute of Kidney Diseases and Research Centre in India, 60 premenopausal women with self-identified heavy menstrual bleeding will be recruited: one subgroup with irregular menstrual cycles (half with uterine fibroids and half with adenomyosis) and one subgroup with regular menstrual cycles and no discernible pelvic pathology. A control group of women without clinical symptoms will also be recruited. Single-cell RNA sequencing will be performed on endometrial samples taken during participants' menstrual period to reveal potential biological mechanisms shared and unique across patients with the condition.

Tim Bull of City St George's University of London in the United Kingdom will develop a system for the non-mechanical lysis of Mycobacterium tuberculosis from patient samples to enhance TB diagnosis. The system is based on lytic peptides that are active against host cells and can release intracellular TB bacteria, plus a combination of agents that directly lyse the TB bacterium, with candidates including a mycobacteriophage, antimicrobial peptides, and the lytic enzyme from the phage. Experiments will be performed to determine the components and conditions that optimize the speed and efficiency of lysis. These conditions will be used to test lysis across different sample types, using mock samples spiked with defined bacterial loads and focusing on sputum and tongue swabs. The mycobacteriophage will also be explored for selective capture of the TB bacterium in samples prior to lysis to improve the sensitivity of detection.

Lilian Okeke of the African Field Epidemiology Network in Uganda will develop a health index as a comprehensive, integrated measure of women’s health in Nigeria. The index will be based on existing datasets, including Nigeria’s Demographic and Health Surveys and its Health Management Information System as well as World Bank gender data, with new data collection to fill gaps where feasible. Health outcomes across women’s life course will be stratified by geography, socioeconomic status, and gendered barriers. The index will integrate factors such as education, employment, social protection, and gender-based violence; and data modeling and statistical methods will be incorporated to reveal hidden inequities. The index will be piloted in two Nigerian states, testing its ability to generate actionable evidence to guide health policy, resource allocation, and targeted interventions for more equitable women’s health outcomes.

Getachew Tilahun of Haramaya University in Ethiopia will develop a health index as a comprehensive, integrated measure of women’s health in Ethiopia. Health indicators will be developed that incorporate the sociocultural and economic context of women across their life course. Based on data from Ethiopia’s Demographic and Health Surveys, these indicators will be used to create a series of health indices, each specific for an age group. New data covering mental health will be integrated by adding questions to the household surveys conducted regularly under Ethiopia’s Health and Demographic Surveillance System. The age-specific indices will be aggregated into a composite index, spanning early childhood to late adulthood. Data modeling will be used to predict the effects on the women’s health index of changes over time in climate, land use, health policy, and health interventions.

Marisa Fabiana Nicolás of the National Laboratory for Scientific Computing in Brazil, alongside other research groups in Brazil and collaborators from Argentina, Chile, Mexico, Uruguay, Canada, and Portugal, will lead an interdisciplinary project to discover and validate small-molecule inhibitors targeting Klebsiella pneumoniae proteins. The team will integrate supercomputing, AI-driven modeling, CRISPRi knockdowns, Ribo-seq, enzymatic, and structural assays to identify high-value bacterial targets and generate validated small-molecule inhibitors. Target prioritization will be performed using the Target-Pathogen platform. Selected high-priority targets will be validated using CRISPRi strains, followed by virtual screening with DockThor-VS and rational design via DockTDesign to identify and optimize novel compounds. Hit compounds will be synthesized, tested in vitro, and evaluated through structure-activity relationship (SAR) analysis and on-target validation experiments to confirm antibacterial activity and target engagement. The ultimate goal is to deliver validated lead compounds with strong therapeutic potential against multidrug-resistant K. Pneumoniae.

Lyn-Marie Birkholtz with Erick Strauss, both of Stellenbosch University in South Africa, will develop antimalarial drugs that work by targeting parasite proteins for degradation rather than inhibiting their activity. This strategy involves creating proteolysis-targeting chimeras (PROTACs), which are linker proteins designed to bind specific parasite proteins and target them for degradation by an endogenous intracellular protease. This project builds on ongoing work with the approach applied to bacterial proteins for TB drug development. They will design and synthesize PROTACs against essential Plasmodium falciparum proteins, then evaluate their activity in phenotypic assays using drug-sensitive and drug-resistant parasite strains as well as multiple stages of parasite development. They will validate that any observed activity is due to the predicted PROTAC mechanism of action, as well as using in vitro assays to measure how effectively the parasites resist the antimalarial activity.

John Metcalfe of the University of California San Francisco in the U.S. will improve the turboLysis device for mechanical lysis of Mycobacterium tuberculosis from patient samples to enhance TB diagnosis. This device uses magnet-actuated steel beads to disrupt bacterial cells. A redesigned lower-cost version of the existing device will be built, and improvements will be tested, such as adding epoxy-coated paramagnetic beads in a sample cleanup step that eliminates the need for later centrifugation to remove cell debris. Patient samples in multiple formats will be tested for direct use in the device, including the tips of oral swabs and a filter with TB bacteria captured from sputum. Device performance will be compared to a commercial bead-beating device, including testing the turboLysis device in parallel to the standard protocol in an ongoing clinical trial in South Africa.

Susan Ontiri of the International Centre for Reproductive Health Kenya in Kenya will explore AI-enabled ultrasound for diagnosis of structural causes in the uterus of heavy menstrual bleeding, as well as exploring multiple treatment options for the condition. A cohort of 120 women with heavy menstrual bleeding will be recruited at the Coast General Teaching and Referral Hospital in Kenya. Participants will receive the standard clinical assessment together with an ultrasound evaluation. The accuracy and feasibility of the two diagnostic methods will be compared, and the ultrasound images will be annotated by experts and used to develop an AI-based model to enhance diagnosis by ultrasound. A pilot treatment trial will also be performed. Treatments including hormonal therapy, tranexamic acid, and non-steroidal anti-inflammatory drugs (NSAIDs) will be assessed, comparing feasibility, acceptability, adherence, and effectiveness.

Mathias Wipf of MOMM Diagnostics GmbH will improve their préXclude test to better enable its use in low- and middle-income countries (LMICs) as an affordable point-of-care diagnostic platform for prediction and detection of preeclampsia early in pregnancy. The existing test is contained in a single-use cartridge connected to an inexpensive handheld reader. It is based on an electrochemical enzyme-linked lateral flow immunoassay that quantifies the levels and ratio of two key preeclampsia biomarker proteins, sFlt1 and PIGF, in whole blood from a finger prick. Multiple aspects of the test will be improved to enhance usability and analytical performance, with the goal of developing a prototype platform that meets a target product profile appropriate for LMIC settings.

Sébastien Mazzuri of the EspeRare Foundation in Switzerland and its partners will reposition an oral drug previously evaluated in cardiovascular patients as a treatment candidate for early-onset preeclampsia. The drug has an extensive data package and advanced to Phase 3 trials before discontinuation for lack of superiority over standard of care. Leveraging preliminary research suggesting it could beneficially rebalance key physiological disruptions underlying preeclampsia, EspeRare will drive translational proof-of-concept studies in established preclinical models and coordinate advisory board consultations to guide the clinical trial design. The goal is to confirm the drug's therapeutic potential in preeclampsia and accelerate regulatory clearance for clinical evaluation. Ultimately this new therapeutic approach aims to significantly improve survival and health outcomes for pregnant women and their unborn children, with a focus on accessibility in high-burden regions.

Katherine Rucinski of Johns Hopkins University in the U.S. will develop a platform for understanding the determinants of women’s heath inequities in South Africa and for modeling the effects of health interventions. The project will be implemented through collaboration with the Pan African Centre for Epidemics Research, which is part of the University of Johannesburg and the South African Medical Research Council. Machine learning will be applied to datasets publicly available in South Africa to identify the factors underlying the co-occurrence of chronic health conditions that disproportionally affect women. Data modeling will then be performed to identify interventions that most efficiently and effectively reduce these health disparities. This approach will be integrated into a web-based simulation tool for epidemiological modeling of women’s health across diverse contexts.

Garry Pairaudeau of DaltonTx Limited in the United Kingdom, with Gemma Turon of the Fundació Ersilia Open Source Initiative in Spain, will develop a computational platform for analyzing large, in silico, chemical libraries to identify chemical starting points for drugs that target Mycobacterium tuberculosis. They will use AI-based protein structure modeling focused on the several-hundred known proteins whose targeting can inhibit M. tuberculosis growth. They will incorporate information on ligand binding from available databases of chemical library screening experiments and the ChemBL database of bioactive molecules with drug-like properties. Together, this information will highlight the target proteins and the binding sites most likely to be amenable to in silico screening. This predictive modeling will be distilled and deployed through the Ersilia Model Hub platform as an open resource for virtual screening of compound libraries for tuberculosis drug discovery.

Anne Yonkeu of the Clinton Health Access Initiative in Cameroon will develop a health index as a comprehensive, integrated measure of women’s health in Cameroon. Using existing national data sources that reflect the multidimensional determinants of women’s health, health indicators will be developed and integrated into a composite index. These determinants will include factors such as reproductive health, gender-based violence, unpaid care work, nutrition, and access to services. Data modeling and statistical methods including geospatial analysis will be incorporated so that the index can serve as a digital tool for revealing and visualizing hidden inequities in women’s health at the subnational level and strengthening gender-sensitive health monitoring. The tool will be piloted, testing its ability to generate actionable evidence at the national and subnational levels to guide health policy, resource allocation, and targeted interventions for more equitable women’s health outcomes.

Offer Erez with Gil Shalev of Ben-Gurion University of the Negev in Israel, in collaboration with Diomede Ntasumbumuyange of the University of Rwanda in Rwanda, will develop an affordable point-of-care diagnostic platform for prediction and detection of women at risk for preeclampsia early in pregnancy. The sensor system is an electronic biochip composed of biological field-effect transistors (bio-FETs) incorporating antibodies to sFlt1 and PIGF, two key preeclampsia biomarker proteins. It will be designed for simultaneous (multiplex) monitoring of blood and urine levels of these two biomarkers, accommodating whole blood and not requiring pre-measurement processing of the sample or the sensor, making it suitable for out-of-hospital use. They will evaluate the system with an existing inexpensive read-out device, testing it with samples of whole blood and urine spiked with the biomarker proteins, as well as samples collected from pregnant women in Israel and in Rwanda, and compare these clinical sample test results to those using a conventional FDA approved ELISA.

Alphonsus Neba of the African Population and Health Research Center in Kenya will develop a health index as a comprehensive, integrated measure of women’s health. Using existing global and regional data sources that reflect the multidimensional determinants of women’s health, life stage-specific health indicators will be developed and integrated into a composite index. These determinants will include factors such as unpaid care work, gender-based violence, access to services, reproductive autonomy, and mental health. Data modeling and statistical methods including geospatial analysis will be incorporated so that the index can serve as a digital tool to reveal and visualize hidden inequities in women’s health at the subnational level. The tool will be piloted in Kenya, Brazil, and India, testing its ability to generate actionable evidence to guide health policy, resource allocation, and targeted interventions for more equitable women’s health outcomes.

Qudsia Uzma of the World Health Organization in Pakistan will develop a health index as a comprehensive, integrated measure of women’s health in Pakistan. In collaboration with Pakistan’s Ministry of Planning Development & Special Initiatives, relevant existing data sources will be used to develop indicators that incorporate the sociocultural and economic context of women’s health across their life course. The indicators will reflect the intersection of diverse factors underlying inequities in women’s health and wellbeing, including communicable and non-communicable diseases, nutrition, education, empowerment, mental health, poverty, climate vulnerability, autonomy and personal rights, access to services, and gender-based violence. The indicators and the degree to which they each improve or worsen annually will be integrated into a composite index to guide health policy, resource allocation, and targeted interventions for more equitable women’s health outcomes.

The team at Isolere Bio, a Donaldson Life Sciences business in the U.S. will develop a biomanufacturing platform for low-cost production of monoclonal antibodies based on a multidomain synthetic protein enabling both capture and purification of the antibody in a chromatography-free process. The synthetic protein includes an antibody-binding affinity tag, and it enables liquid-liquid phase separation and selective concentration of the bound antibody. Key steps in the biomanufacturing process will be targeted to decrease costs and improve performance. This includes high-throughput experiments to identify conditions that improve the recycling of the synthetic protein, as well as tests to optimize the removal of viral contaminants during the purification process. Subsequently, larger-scale production will be piloted to identify the critical parameters required to scale up the platform.

Kelvin Lee of the University of Delaware in the U.S. will develop components of a biomanufacturing platform for low-cost production of monoclonal antibodies. The project will be implemented through the National Institute for Innovation in Manufacturing Biopharmaceuticals (NIIMBL) headquartered at the University of Delaware, with John Erickson of NIIMBL. It will focus on economic modeling, development of a mammalian cell line for expressing the antimalarial monoclonal antibody MAM01, and a head-to-head comparison of two antibody purification approaches, including isoelectric point purification (IPP) and continuous precipitation operations that reduce the number of process steps. Based on these tests, the platform components could be integrated into an end-to-end continuous processing system and co-developed with a next-generation facility design and regulatory strategy.

Liat Shenhav of New York University Grossman School of Medicine in the U.S. will develop a diagnostic platform, based on non-invasive retinal imaging, for prediction and detection of preeclampsia early in pregnancy. Previous results with a U.S.-based cohort of 1,400 pregnant women showed promise in using retinal vasculature features in the first trimester to predict the risk of preeclampsia. With local collaborators, the current study will recruit 2,000 pregnant women in clinical research centers in Belagavi and Nagpur in India, part of the Global Network for Women’s and Children’s Health Research. Each participant will get a retinal scan in the first and second trimester and be followed through pregnancy to determine clinical outcomes. An AI-based model will be developed to predict preeclampsia risk from the retinal scans, guided by parameters used in modeling for the U.S.-based cohort to help ensure generalizability.

Young Kim of Purdue University in the U.S. will develop a diagnostic platform for prediction and detection of preeclampsia early in pregnancy. The project is based on non-invasive imaging with an unmodified smartphone of the conjunctiva of the eye, and it will be a collaboration with Edwin Were of the Moi University Teaching and Referral Hospital (MTRH) in Kenya and Martin Were of Vanderbilt University Medical Center in the U.S. A cohort of 1,600 pregnant women at 12-15 weeks of gestation will be recruited from MTRH antenatal clinics, and they will be followed through pregnancy and delivery to determine clinical outcomes. Participants will get a conjunctival photo taken at enrollment, using a custom-made color chart to standardize images, and an AI-based model will be developed to predict preeclampsia risk from the vasculature features in the imaging data.

Gina Ogilvie of the BC Women's Health Foundation in Canada, with Carolyn Nakisige and Priscilla Naguti of the Uganda Cancer Institute in Uganda, will use community outreach to determine the prevalence and impact of heavy menstrual bleeding in women in rural Uganda, with a focus on better understanding the condition for perimenopausal women. Outreach will build on an existing mobile health program in Uganda for cervical cancer prevention and reproductive health. Village health teams will recruit 5,000 women, aged 30-49, across 15 villages. They will use a set of questionnaires to survey this age group, which includes women's transition to menopause (perimenopause) for which less is known about heavy menstrual bleeding. The survey will include assessment of the health, social, and economic impacts on women and their children; menstrual hygiene and product use; quality of life; and treatment availability and acceptability.

Muzungu Sylvain of the Ministry of Health in Rwanda will develop a health index as a comprehensive, integrated measure of women’s health in Rwanda. The index will be based on Rwanda’s National Health Intelligence Center that consolidates real-time and historical data from electronic medical records of all health facilities, the District Health Information System, Civil Registration and Vital Statistics, national surveys, and social protection databases. It will integrate factors encompassing the gendered burden of disease and health conditions, sexual and reproductive health, as well as economic and social determinants of health. The index will inform the design of equitable benefit packages under Rwanda’s Community-Based Health Insurance system and guide gender-sensitive strategies to improve women's health and wellbeing.

Ling-Jun Li of the National University of Singapore in Singapore will develop a diagnostic platform for prediction of preeclampsia early in pregnancy for women at high-risk of developing the condition. Two, existing, Singapore-based pregnancy cohorts will be used to develop and validate an AI-based risk prediction model for hypertensive disorders of pregnancy including preeclampsia. A non-invasive, preeclampsia screening test will then be developed, combining retinal imaging to identify vasculature features plus epidermal detection of the preeclampsia biomarker proteins PIGF and PAPP-A using a wearable forearm patch with a solid-state sensing system. The feasibility and acceptability of this test will be assessed with 60 pregnant women recruited at National University Hospital in Singapore, integrating the clinical data with the AI-based risk prediction model to guide further evaluation of the diagnostic platform.

Manel Mendoza of The Fetal Medicine Foundation in the United Kingdom will validate the safety and efficacy of giving aspirin prophylaxis to 30% of pregnant women at high risk of preeclampsia and discontinuing treatment before the end of pregnancy. Through collaborations, pregnant women at hospitals in Ghana, Senegal, and The Gambia will be screened in the first trimester for preeclampsia risk based on a combination of biomarkers and maternal characteristics. After the feasibility and suitability of this screening is validated, cohorts in the same three countries will be enrolled in a randomized controlled trial testing for non-inferiority of stopping aspirin treatment at 24-28 weeks of gestation versus at the end of pregnancy. These trials build on results from equivalent existing clinical trials in Spain and the United Kingdom. The shorter treatment duration could reduce the risk of negative side-effects and simplify treatment compliance.

Antti Aalto with Pedro Gonçalves of VTT Technical Research Centre of Finland Ltd in Finland will develop a biomanufacturing platform for low-cost production of the antimalarial monoclonal antibody MAM01 using the filamentous fungus Trichoderma reesei as the protein expression system. They will create candidate production strains, incorporating different expression cassettes for synthetic MAM01 sequences and pairing them with different host strain genetic backgrounds optimized for expression. The resulting strains will be cultivated in small-scale bioreactors, testing multiple bioprocess conditions from cultivation through sequential steps for antibody capture and purification. They will create models of the technical and economic factors required for low-cost production, as well as an analysis of environmental impact, including water usage and waste generation of the production process, comparing this impact with available data for antibody production using mammalian cell culture systems.

This grant is one of three grants that are funded and administered by LifeArc.

Christian Richardson of RiffTX in the U.S. will develop minibinder proteins targeting sFlt1 as a candidate preeclampsia treatment and a drug manufacturing process suitable for low- and middle-income countries (LMICs). Preeclampsia is a placental disease whose pathologies converge on elevated levels of sFlt1. The project will generate small, high-affinity binding proteins (minibinders) to inhibit sFLT1 function along with minibinders for human serum albumin (HSA) and for neonatal Fc receptor (FcRn) to maintain a long drug half-life in circulation. A manufacturing process will be developed to produce a high-quality drug while ensuring the cost and complexity of the process is suitable for implementation in LMICs. Drug candidates will be tested for an extended half-life using transgenic mice expressing HAS and human FcRN, and they will be tested for restoration of blood pressure and kidney function levels normal for pregnant rats using a rat model of preeclampsia.

Jennifer McIntosh of the Medical College of Wisconsin, Inc. in the U.S. will test the mitochondria-targeted antioxidant MitoQ as a treatment for preeclampsia. MitoQ is a nutritional supplement that has been used in human clinical trials for conditions other than preeclampsia, and it has been shown to reverse symptoms in a mouse model of preeclampsia. Two, pilot clinical trials will be performed with pregnant women with preeclampsia at 23-32 weeks of gestation: 30 in-hospital patients with severe symptoms not requiring immediate delivery and 50 outpatients without severe symptoms. All participants will be randomized to receive either oral MitoQ or a placebo, with standard care for preeclampsia continuing unchanged. Participants will be monitored regularly with a measure of endothelial dysfunction (brachial artery flow-mediated dilation) as primary outcome, and including measures of cutaneous circulation, blood-borne biomarkers of preeclampsia and oxidative stress, and post-delivery placental samples to measure vascular function and oxidative stress biomarkers.

Ashutosh Chilkoti of Duke University in the U.S. will develop a biomanufacturing platform for low-cost production of the antimalarial monoclonal antibody MAM01 based on a fusion protein enabling both capture and purification of the antibody in a chromatography-free process. The fusion protein will comprise an antibody-binding affinity tag fused to an elastin-like polypeptide (ELP) enabling liquid-liquid phase separation of the protein. It will be engineered to optimize its secretion by Chinese Hamster Ovary (CHO) cells and its reversible phase separation via its ELP domain. Protein co-expression strategies for antibody production will also be optimized, including comparing genomic integration of the fusion protein and MAM01 sequences in the same cell line versus in separate cell lines in the same bioreactor. These tests will be used to determine the purification strategy that maximizes MAM01 yield while minimizing process cost.

This grant is one of three grants that are funded and administered by LifeArc.

Alfredo Rubio of Monod Bio, Inc. in the U.S. will develop an affordable point-of-care diagnostic platform for prediction and detection of preeclampsia early in pregnancy. The assay system will use reporter proteins, designed de novo, for simultaneous (multiplex) monitoring of serum levels of two key preeclampsia biomarker proteins: sFlt1 and PIGF. The reporter system consists of a pair of proteins designed to bind different epitopes of the biomarker, together with a split luciferase reporter protein. It will be incorporated into a single-use microfluidic cartridge with a readout device for a rapid, one-step assay. This prototype device will be tested with human serum and whole blood samples spiked with the biomarker proteins. It will also be tested, in collaboration with Stephen McCartney of the University of Washington in the U.S., with 40 serum samples collected from the University of Washington Pregnancy Biorepository, half from patients with preeclampsia, comparing these clinical sample test results to those using a conventional ELISA.

Kolawole Akinjiola of mDoc Healthcare in Nigeria will build on mDoc’s digital health platform for maternal self-care to pilot test a wearable, vital signs monitor for real-time monitoring of preeclampsia risk during pregnancy. The project will be a collaboration with the University of Purdue in the U.S. and Corsano Health in The Netherlands. A cohort of pregnant women at 20 weeks of gestation will be recruited in two Nigerian cities, 250 participants in Ikorodu and 50 in Kano, and they will be followed through pregnancy and delivery. Women will be given a Corsano wearable device for passive, continuous monitoring of vital signs and wireless transmission to mDoc’s CompleteHealth application. Data modeling will be used to develop a preeclampsia risk prediction model, and a subset of the cohort will be tested to determine if the key underlying model data can be captured with simpler inexpensive wearable monitors.

Anurag Rathore of the Indian Institute of Technology (IIT) Delhi with Abhishek Mathur of Enzene Biosciences Limited, both in India, will pilot test a continuous processing platform for monoclonal antibody biomanufacturing for its advantages compared to batch processing. The pilot will build on lessons from the platform operating at the Center of Excellence for Biopharmaceutical Technology at IIT, Delhi. It will demonstrate that the existing biomanufacturing platform in an academic setting can be scaled up in a commercial setting. It will validate the decreased cost of goods and increased production relative to batch manufacturing, and it will provide technical and economic data, with details on integrating operations from cell culture through final formulation into a seamless, automated process. This data will guide efforts to increase access and affordability of monoclonal antibody products by manufacturing them in low- and middle-income settings.

James Brown of Bondi Bio Pty Ltd with Jake Baum at UNSW Sydney, both in Australia, will develop a biomanufacturing platform for low-cost production of the antimalarial monoclonal antibody MAM01 using the photosynthetic cyanobacterium Synechococcus as the protein expression system. They will engineer a cyanobacterial strain to express MAM01, grow it in high-density batch cultivation, optimize cell lysis and clarification to ensure maximum product yield and integrity, and purify fully assembled MAM01 by standard column chromatography. Purified MAM01 will be analyzed to confirm it has the correct mass, folding, and assembly, including complete disulfide bond formation and the expected glycosylation, and the strain will be engineered further where required. They will also use these experimental results to outline a facility design and an economic model for MAM01 biomanufacturing, focusing on the initial process steps of batch cultivation, centrifugation, and cell lysis.

Michael Betenbaugh with Honggang Cui of Johns Hopkins University in the U.S. will develop a biomanufacturing platform for low-cost production of the antimalarial monoclonal antibody MAM01, combining a fungal expression system with a nanofiber-bound peptide technology for antibody capture and purification. Collaborating with Dyadic International and with Thermo Fisher Scientific, they will optimize the fermentation media and bioprocess conditions in the expression system, which uses the thermophilic filamentous fungus Thermothelomyces heterothallica C1. They will also optimize conditions for the selective capture, separation, and recovery of the antibody along with recycling of the antibody-binding peptide. They will integrate these conditions, assess and further optimize them to reduce production costs, and demonstrate the scalability of the platform.

Cristiana Boi with Ruben Carbonell of North Carolina State University in the U.S. will develop a purification system for the antimalarial monoclonal antibody MAM01 that uses an all-membrane chromatography process with single-use membranes made from low-cost nonwoven materials. This system will be combined with a protein expression system using the thermophilic filamentous fungus Thermothelomyces heterothallica C1 to create a low-cost biomanufacturing platform. Collaborating with Dyadic International, they will obtain MAM01-containing supernatants from the expression system and analyze its components to guide development of the purification system. Based on these results, small-scale purification experiments will be performed, testing suitable membrane-coupled ligands, membrane configurations, purification conditions and steps, and integration of the system into single-use cassettes. They will also determine the process requirements to scale up the platform.

Jennifer Harikrishna of the University of Malaya in Malaysia will collect genetic resources from wild banana relatives in different regions across Malaysia, with a focus on Musa acuminata subspecies, and characterize their genotypes and associated phenotypes, including abiotic and biotic stress tolerance. Samples will be collected through field expeditions and in a citizen science initiative with sample and data collection by the public guided by a mobile app. Seeds will be tested for desiccation tolerance, and germinated plants will be assessed for drought and salinity tolerance and resistance to the fungal pathogen Fusarium Tropical Race 4 and to the nematode parasite Meloidogyne incognita. Based on these studies, selected species will be characterized by molecular marker genotyping and whole-genome sequencing. Banana breeders in Uganda, Tanzania, and Cameroon will be engaged early in the project for sharing knowledge and strategic approaches.

Vijayalakshmi Ramshankar of the Cancer Institute (WIA) in India will perform a study of air pollution's effects on lung cancer in India. To focus on the links specifically with air pollution they will recruit non-smoking lung cancer patients in the city of Chennai. They will screen these patients for EGFR driver mutations, known to promote air pollution-related lung cancer, and measure the cytokine and miRNA profiles in their blood through periodic sampling. They will also perform this blood analysis in patients' asymptomatic household family members, who will be offered further testing (low-dose spiral CT scanning) for early cancer detection. Air pollution will be assessed in these households using a device for continuously monitoring indoor exposure. They will perform statistical analysis combining the biological and environmental data to better understand how air pollution affects lung cancer risk and to identify a high-risk signature to guide early screening.

Ani Varghese of ZeroEarth Private Limited in India will pilot test a climate-smart dairy farming platform supporting rural women farmers in the Indian state of Tamil Nadu. Through partnerships with financial institutions, they will set up mechanisms facilitating farmers' access to credit to sustainably increase their farming income. They will launch a pilot business center, which will provide training in entrepreneurship and climate-smart farming practices; centralized access to veterinary services; and coordination between dairy, calf-rearing, and fodder farmers. Farming practices supported by the center will include those to improve the health of soil for growing fodder; to optimize feed to minimize greenhouse gas emissions and enhance milk quality; and to efficiently manage manure, with the launch of a biogas plant to generate electricity.

Satadal Saha of the Foundation for Innovations in Health in India will develop an AI-based platform to support public health interventions for women living in the Sundarban Biosphere Reserve, focusing on anemia, urogenital tract infections, and anxiety and depression. The Reserve is a river delta region highly susceptible to climate change-driven severe weather. The project will build on the team's existing digital platform for health data that supports community health workers deliver primary care to island communities. They will collect environmental data, including data for weather and air and water quality, and expand the platform with software enabling regular monitoring and integrated analysis of health and environmental data. This includes incorporating an AI-based predictive model to guide the proactive design and implementation of public health interventions for vulnerable women in this region.

Raghuram Dharmaraju of the I-Hub for Robotics and Autonomous Systems Innovation Foundation in India will improve heatwave forecasting using AI approaches and develop an early warning system for the Indian state of Karnataka to enhance preparedness for heat-induced health risks. The improvements in forecasting will encompass increases in accuracy, lead time, and spatial resolution. The early warning system will use web-based dashboards, mobile apps, and social media platforms to communicate heatwave alerts in local languages. It will include messages tailored to particularly vulnerable groups as well as alerts to healthcare providers to actively monitor these groups. It will also send notifications to relevant government agencies about the potential severity of health impacts. This system will guide public health interventions while helping establish data collection mechanisms for ongoing improvement of the system.

Tavpritesh Sethi of Indraprastha Institute of Information Technology Delhi in India will develop an AI-based platform to support responses to vector-borne diseases in the face of climate change in the Indian state of Uttar Pradesh. They will establish a comprehensive database that integrates climate data with data from existing programs for the control of vector-borne diseases (malaria, dengue, chikungunya, Zika, and Japanese encephalitis). Data will be at the block level of local government in Uttar Pradesh and will include real-time data. For analysis, they will develop an AI-based platform, named Sanketak, that includes modules to capture data, provide automated alerts, visualize changes in disease incidence, and identify early warning signs that predict disease hotspots. They will pilot test the platform, evaluating its potential to preempt, detect, and manage vector-borne disease outbreaks in a timely and effective manner.

Tavpritesh Sethi of Indraprastha Institute of Information Technology Delhi in India will develop an AI-based platform for AMR surveillance and management across a broad network of public and private hospitals in India. The platform will extract weekly data on AMR from the All India Institute of Medical Sciences, New Delhi (AIIMS Delhi) hospital and the Max Healthcare hospital network, including patterns of antibiotic prescriptions across the network. It will use a federated data analysis approach (joint analysis without sharing the data itself), and they will develop and integrate AI-based models to identify and predict trends in AMR. They will also create applications driven by these models to widely and effectively communicate the analyses to healthcare professionals. This will support antibiotic stewardship and data-driven AMR management at both the local and regional levels.

Sai Raj Reddy of Daia Tech Private Limited in India will develop a program to increase access to health education and related resources for adolescent girls in rural areas of the Indian state of Karnataka. The program will be developed in partnership with the Karnataka Health Promotion Trust, building on their ongoing work with local schools, healthcare providers, community leaders, and government agencies. After engaging community members to understand the local context, they will develop resources for adolescent girls including life skills courses and health education workshops and pilot test the program in selected villages. They will integrate AI tools across the program to broaden participation and to broaden the range of health outcomes improved for adolescent girls.

Chiranjay Mukhopadhyay of the Manipal Institute of Virology in India will perform a two-year longitudinal study in the Western Ghats region of India, focusing on sentinel surveillance of tick-borne pathogens and their transmission dynamics. This mountain range region is known for its high biological diversity, and they will sample across 12 sites representing diverse ecological habitats where people and wild and domestic animals interact most frequently. They will collect host-seeking ixodid ticks, screen them for eight tick-borne pathogen groups, and perform whole-genome sequencing for the pathogens identified. Corresponding weather data will be collected from the Indian Meteorological Department. They will combine this longitudinal data to develop statistical models that predict the spatial and temporal transmission of tick-borne pathogens and the corresponding disease risk, which will guide public health interventions.