2019 Finalists and Proposals

Below are the five finalist proposals selected for the 2019 NTD Innovation Prize. You can read about the 2019 award here.

Dr. David Ascher - Bio21 Institute, Baker Institute - Australia
Proposal:
Improving NTD surveillance and optimizing treatment through insights from protein 3D structure. 

As drug resistance (AMR) increases, the introduction of new antibiotics to treat and manage NTDs is decreasing. Advances in genomic sequencing have the potential to revolutionize this problem. The proposed solution is a comprehensive and scalable computational platform for understanding the structural, functional and biophysical consequences of genetic variants. This platform has demonstrated advantages over current AMR molecular diagnostic approaches. Using these structural insights, evidence shows it is possible to preemptively identify drug-resistant mutations in the absence of previous genomic data. This framework will enable rapid detection of AMR NTDs, where structural and genomic information is often limited. This will increase learning across pathogens, predict variants that could lead to resistance and support the design of resistance-resistant therapies.

About: David is head of the Computational Biology and Clinical Informatics group at the Baker Institute and the Structural Biology and Bioinformatics Laboratory at Bio21 Institute. He is a director of the Australian Society for Medical Research, an associate editor of PBMB and he holds honorary positions at Cambridge University, FIOCRUZ, and the Tuscany University Network. He earned a Ph.D. from the University of Melbourne in Biochemistry. His research focuses on unravelling the link between genotype and phenotype, using computational and experimental approaches to understand the effects of mutations on protein structure and function. David and his colleagues developed a platform of 22 widely used programs for assessing the molecular consequences of coding variants (>500,000 hits per month). In particular they are interested in exploring how these molecular consequences lead to disease and drug resistance, and how we can use this information to better inform clinical decisions, public health policy and drug development.

Dr. Joydeepa Darlong - The Leprosy Mission Trust India - India
Proposal:
Developing a user-centered feedback system for NTDs services.

In India, care providers often recommend protective footwear for people living with leprosy and other disabilities to prevent chronic ulcers; this reduces impairment, but patients are often reluctant to use these shoes for various reasons. The proposed solution is a user-centered feedback system allowing wearers to communicate their preferences. This idea was inspired by India’s electronic voting machines and will be developed through an inclusive design process.  With this information, organizations can better strategize and also monitor change. The main motivation is to transform health-seeking behavior. The hope is that, through the practice of providing feedback, patients will see themselves as enabled users of this service and not its beneficiaries. 

About: Joydeepa, a family physician, has worked at The Leprosy Mission Trust India (TLMTI) for 19 years. She earned her medical degree at Tribhuvan University and currently serves as the head of knowledge management for TLMTI, overseeing research, training, and monitoring and evaluation of the programs. Additionally, she facilitates training programs for medical officers and specialists. She has expertise in treating multiple areas related to leprosy, including reactions, neuritis, relapse, resistance, ulcers and neuropathic pain; she has authored and co-authored studies on these topics. She has successfully participated in a RCT of Azathioprine for nerve complications in leprosy, as well as ENLIST.

Dr. Sara Eyangoh - Pasteur Center of Cameroon - Cameroon
Proposal:
Improving the performance in molecular amplification-based diagnostics for Buruli ulcer and yaws in endemic African countries through a solid laboratory network.

Laboratory confirmation of clinical suspected cases for BU and yaws is a persistent challenge. The proportion of labs reporting false results remains high. This project seeks to develop a new external quality assessment program (EQAP) through the establishment of a robust network with the goal of obtaining high-performing laboratories conducting molecular-based diagnostics for BU and yaws.  The novelty of the EQAP lies in the capacity-building component through a holistic approach supported by a network. 

About: Sara holds a Ph.D. in Biochemistry from the University of Yaoundé I, and a Ph.D. and HDR (accreditation to direct research) in Microbiology from the University Paris Diderot. She heads the Mycobacteriology Service, which acts as the National Reference Laboratory for tuberculosis, Buruli ulcer and leprosy programs in Cameroon. For over 15 years, she has carried out several research projects on evaluation of new diagnostic tools, molecular epidemiology and control of mycobacterial diseases. She has also organized international courses dedicated to mycobacterial diseases. She is listed by the Women in Global Health Initiative among "200 women presenting outstanding achievement in relation to public health in the French-speaking realm".


Dr. Tito Tresor Melachio - Centre for Research in Infectious Diseases - Cameroon
Mr. John Pryce - London School of Hygiene and Tropical Medicine - United Kingdom
Proposal:
Exploring the viability of excreta sampling for monitoring Human African Trypanosomiasis (HAT).

Human African Trypanosomiasis (HAT) is targeted for elimination as a public health concern. However, the low prevalence requires exhaustive screening to identify areas of transmission. Achieving adequate surveillance coverage is difficult and expensive. This idea proposes a technique to collect and concentrate the excreta from mosquitos, which has already been optimized for malaria, filarial worm and trypanosomes in the laboratory. This tool is now ready to be applied to detecting the presence of HAT within a community in order to justify scaled-up vector control. 

About: Tito is a medical entomologist based at the Centre for Research in Infectious Diseases (CRID) in Yaoundé, Cameroon. He has a Ph.D. in Molecular Parasitology and Population Genetics from the University of Yaoundé I. He is interested in designing protocols using cheaper tools to fight vector-borne diseases. His current research focuses on the use of “Tiny Targets” for sleeping sickness elimination in Cameroon, especially the impact of these impregnated screens on tsetse fly population density, genetic structure, infection with trypanosomes, and their ability to transmit sleeping sickness to humans.


Dr. Marcin J. Skwark - University of Cambridge - United Kingdom
Proposal:
Deep learning platform for classification of lesions across skin NTDs in the field.

Skin lesions are one of the diagnostic criteria for many NTDs. Due to their diversity, they remain notoriously difficult to classify by non-experts. An impartial, accurate tool to analyze and classify photographs of skin lesions will alleviate the number of diagnostic errors. This idea proposes an inexpensive solution for computer-aided diagnoses of skin lesions, in particular differential diagnosis of leprosy. It requires no internet connection or extensive training. This will be developed through the application of machine learning, applying analogous methods to develop a multi-label classifier aiding in the diagnostic process. 

About: Marcin is a Research Associate at the University of Cambridge and he received his Ph.D. in Biochemistry from Stockholm University. He is a data scientist and a biochemist, working on combating emerging antibiotic resistance. A trained computer engineer, Marcin has over fifteen years of experience in translational research at the interface of computation and life sciences. His machine learning work garnered international acclaim both in computer science (NIPS 2016), and structural biology; since 2008 he’s been among the best-performing groups worldwide in the CASP protein structure prediction experiment. Prior affiliations include Stockholm University, Aalto University, Abo Akademi University, Vanderbilt University, and Tsinghua University.