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Grand Challenges is a family of initiatives fostering innovation to solve key global health and development problems. Each initiative is an experiment in the use of challenges to focus innovation on making an impact. Individual challenges address some of the same problems, but from differing perspectives.

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NoV - Cohort Mobile Payment Solution for Bottom of Pyramid

Michael OluwagbemiLoftyinc Allied Partners LimitedLagos, Nigeria
Grand Challenges Explorations
Mobile Money
1 May 2015

Michael Oluwagbemi from Loftyinc Allied Partners Limited in Nigeria is developing an affordable mobile phone-based payment card reader with an array of functions (ProNov) so that poor, small-scale retailers in Nigeria can accept digital payments from customers, and better manage their businesses to reduce costs. Low-income retailers handle around 90% of transactions in Nigeria, but many have no way of accepting card payments. To facilitate adoption by retailers, they are working to reduce the upfront costs of the technology, and focusing on groups of related retailers from a single market, pharmaceuticals, to test their approach. In Phase I, they assessed the needs of 500 chemists, designed the software and device, and built an alpha version that was pilot tested on a small group over three months. They found that ProNov improved inventory management, and could reduce the cost of goods by up to 70% by enabling bulk purchasing. In Phase II, they will refine the technology, implement a monitoring program, build add-on features that can, for example, help sellers procure credit, and increase the user base to 1500 retailers.

Mobile Money, Schooling, and the Poor

Claire AdidaUniversity of California at San DiegoLa Jolla, California, United States
Grand Challenges Explorations
Mobile Money
1 May 2015

Claire Adida working with Jennifer Burney of the University of California, San Diego, in the U.S. will develop a simple and secure system enabling the rural poor in West Africa to transfer money directly using mobile phones. Mobile money is not widely used in West Africa and many individuals do not have banks. Often money for things like school fees has to be physically transferred over long distances, which is unsafe and takes time. They will build on existing mobile money technology and develop an application for recording transactions so that individuals can send money at low cost directly to a specified institution such as a school, which can issue receipts and maintain a database of transactions. They will partner with two mobile phone companies and pilot-test their system on a secondary school in Benin.

Gestational Dating at Birth by Metabolic Profile

Laura Jelliffe-PawlowskiUniversity of California San FranciscoSan Francisco, California, United States
Grand Challenges Explorations
Brain Function/Gestational Age
16 Oct 2014

Laura Jelliffe-Pawlowski of the University of California, San Francisco in the U.S. is developing an algorithm to measure gestational age from metabolic markers taken during routine newborn screening. Measuring accurate gestational age is important for assessing infant health such as brain development, but it is challenging in developing countries without specialized equipment and expertise. In Phase I, they developed a statistical model using data on 51 metabolic markers from around 730,000 newborns in the U.S. that predicted gestational age at birth within around an average of one week margin of error. In Phase II, they will further adapt and test their algorithm for use in Malawi and Uganda by using existing data from 500 pregnancies in Malawi and 1000 in Uganda, and also determine its value for identifying newborns at risk of neonatal death or complications.

Gestational Age, Metabolic Markers, and Academic Achievement

George WehbyUniversity of IowaIowa City, Iowa, United States
Grand Challenges Explorations
Brain Function/Gestational Age
16 Oct 2014

George Wehby and colleagues at the University of Iowa in the U.S. will evaluate newborn metabolic biomarkers for their ability to predict gestational age, and identify associations between them and long-term academic achievement. They will analyze existing newborn metabolic profiles and academic tests from almost one million children in Iowa born between 1980 and 2006 to identify the most predictive biomarkers. In the future they will expand their method to developing countries to help estimate gestational age and identify newborns at risk of neurodevelopmental defects. Being able to accurately determine gestational age is critical in preterm birth, which is the leading cause of child death worldwide. And knowing which regions have the highest incidence of preterm births would help better target prevention strategies. In Phase I, they identified candidate biomarkers that can be detected by tandem mass spectrometry using existing dried blood spot samples and based on around 150,000 children born between 1980 and 2006 in Iowa, they developed a predictive model for gestational age. In Phase II, through a grant awarded to Kelli Ryckman, their model will be tested using around 2,000 cord blood samples from newborns in Bangladesh, Pakistan and Tanzania, and refine it to improve accuracy by measuring additional biomarkers such as hemoglobin.

Measuring Changes in Functional Brain Activity with fNIRS

John SpencerUniversity of IowaIowa City, Iowa, United States
Grand Challenges Explorations
Brain Function/Gestational Age
13 Oct 2014

John Spencer of the University of East Anglia in the United Kingdom along with Sean Deoni of the University of Colorado in the U.S. are assessing the trajectory of brain development during the first two years of age using a range of imaging, physiological and behavioral assessment tools to understand how development is affected by environmental factors such as nutrition, stress, and parent-child interaction. In their Phase I project, Spencer and colleagues (while at the University of Iowa in the U.S.) used a neuroimaging technology – functional near-infrared spectroscopy (fNIRS) – to localize brain activity during a preferential looking task as a representation of visual working memory in children between four months and four years of age. They used this data to create a developmental trajectory for this visual working memory task and the underlying functional brain network. Sean Deoni and colleagues in their Phase I project (while at Brown University in the U.S.) used MRI to characterize developmental trajectories of myelination in healthy infants and young children to understand the relationship between myelination and cognitive ability. In Phase II, these two research groups will partner together along with an organization in the state of Uttar Pradesh in India, and use the same methods to assess functional brain development over the first two years of age in two cohorts from different socioeconomic-educational settings starting at six and nine months of age. They will also analyze the effects of various factors such as sleep and nutrition on brain development. In addition, they will develop and test a new tablet-based application for larger-scale studies by untrained assessors in the field, and identify tailored approaches for parents to help them promote healthy cognitive development in their children.

Smartphone Ophthalmoscope Image Analysis for Gestational Age

Jennifer GriffinResearch Triangle InstituteResearch Triangle Park, North Carolina, United States
Grand Challenges Explorations
Brain Function/Gestational Age
10 Oct 2014

Jennifer Griffin of RTI International in the U.S. will test whether the gestational age of infants born prematurely can be determined by combining simple physical measurements with an automated analysis of the blood vessels in the retina using the camera on a mobile phone. As the fetus develops in the womb, blood vessels in the anterior lens gradually disappear, which closely correlates with gestational age at delivery. An automated approach increases accuracy and reproducibility, and their new method is also lower cost and requires less skill than traditional ultrasound-based methods of gestational age dating, and therefore should be useful also in low-middle income settings. In Phase I, they developed methods for acquiring quality images of the eye using an ophthalmoscope and smartphone. In Phase II, they will perform a multisite cross-sectional study to generate retinal images and biophysical parameter datasets from preterm neonates for developing the image analysis software and producing an algorithm to identify the best predictors of gestational age. They will evaluate their approach by comparing it to the gold standard of ultrasound.

Using Newborn Screening Data to Estimate Gestational Age

Kumanan WilsonOttawa Hospital Research InstituteOttawa, Ontario, Canada
Grand Challenges Explorations
Brain Function/Gestational Age
8 Oct 2014

Kumanan Wilson of Ottawa Hospital Research Institute in Canada is developing an algorithm to estimate gestational age using specific metabolic analytes found in blood spots collected routinely from newborns in many countries. Knowing the precise age of infants is important for evaluating development particularly of brain function. It is currently measured by ultrasound, which requires expertise and expensive equipment, and is not available in many countries. In Phase I, they used data from around one million ethnically-diverse Canadian newborns to demonstrate that specific metabolites along with sex and birth weight shortly after birth could be used to predict gestational age within one to two weeks. In Phase II, they will further adapt and test their algorithm using existing newborn data from varied international settings, and evaluate the performance of the resultant global algorithm on samples from Bangladesh and Zambia.

Durable and Sensitive Tough Hydrogel Condoms

Robert GorkinUniversity of WollongongWollongong, New South Wales, Australia
Grand Challenges Explorations
Next Generation Condom
24 Apr 2014

Robert Gorkin of the University of Wollongong in Australia is developing tough hydrogels as an alternative material to latex for making male condoms with enhanced tactile (touch) sensitivity to improve sexual experience. Tough hydrogels are highly elastic and mechanically tough materials. Unlike latex, they can increase sensitivity to touch, incorporate lubrication, and be coupled to other components, such as stimulants and antiviral drugs. In Phase I, they synthesized candidate tough hydrogel formulations and showed that they had sufficient mechanical and barrier properties to be suitable condom materials, and could be manufactured to international safety standards. A preliminary trial of target users rated tough hydrogels nicer to touch than latex. In Phase II, they will tailor the condoms to the needs of specific communities by surveying target populations to identify desirable properties that will promote use. They will also optimize production and engineer prototypes for a user acceptance and performance trial to evaluate whether they enhance sexual experience.

Transcutaneous Assessment of Gut Function in Enteropathy

Phillip TarrWashington University in St. LouisSt. Louis, Missouri, United States
Grand Challenges Explorations
Enteric Disease Models
24 Apr 2014

Phillip Tarr of Washington University in the U.S. is developing a method to evaluate gut permeability by measuring levels of ingested fluorescent molecules non-invasively through the skin. Gut permeability is increased in infants with environmental enteropathy, which is associated with impaired growth and development, and is prevalent in developing countries. Current tests are problematic due to the required collection and handling of body fluids from young children, and can produce varying results. In contrast, this new method would allow direct measurement in the field, and be suitable for resource-poor settings. In Phase I, they showed that orally ingested pyrazine-based fluorophores could be measured through the skin and could detect gut injury in a rat model of enteropathy. In Phase II, they will optimize the fluorophores to improve solubility, and evaluate them in a preliminary trial in human volunteers.

A Mouse Model for Heat-Stable Enterotoxin Diarrhea

James NataroUniversity of VirginiaCharlottesville, Virginia, United States
Grand Challenges Explorations
Enteric Disease Models
15 Apr 2014

James Nataro of the University of Virginia in the U.S. is developing new mouse models of environmental enteric dysfunction (EED) to explore how enteric pathogens commonly found among children in developing countries can affect intestinal function and cause growth retardation. In Phase I, they developed mouse models for five of the common pathogens and found that, as in humans, malnutrition (protein or zinc deficiency) enhanced the severity of infection, associated growth retardation, or the presence of intestinal inflammation. In Phase II, they will study the molecular mechanisms involved and analyze human candidate EED-associated biomarkers and metabolic states in their new mouse models to better compare them to the human disease. They will also test the effect of simultaneous and repeat infections on growth, and treat one of the models with alanine-glutamine to determine whether they can be used to evaluate new drugs.

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