2024 Finalist and Award-Winning Solutions

Congratulations to the awardees and finalists!

Vivli is pleased to announce the awardees of the 2024 AMR (Antimicrobial Resistance) Surveillance Data Challenge. The data challenge aims to stimulate and support the innovative re-use of surveillance data available in the AMR Register.

The AMR Data Challenge, funded by GARDP, Paratek, Pfizer and Vivli, was launched in June 2024, as a catalyst for innovation and support for the inventive reutilization of the wealth of surveillance data available within the AMR Register.

A total of 55 teams with members from 27 different countries participated in the AMR Data Challenge. This event served as a unique platform for multidisciplinary teams to leverage high-quality industry AMR surveillance data, proposing groundbreaking advancements and tools for use in AMR surveillance. The Challenge culminated in the recognition of six outstanding winners, selected by a distinguished judging panel.

Vivli would like to thank everyone who took part. The submissions displayed an amazing array of innovative ideas, and dedication to helping solve the AMR crisis. Learn more about 2024’s Data Challenge here.

 

Grand Prize Winners

Team 10396, led by Kasim Allel of University of Oxford, UK, with David Smith, Koen Pouwels, Nam Nguyen, and Sam Lipworth

Title: “Advancing monitoring and prediction of antimicrobial resistance trajectories using flexible spatiotemporal modelling: A roadmap for early warning systems”

Expression of Interest

Final Submission

Student Innovation Award Winners

Student Team 10397, led by Harry Akligoh of Northeastern University, USA, with Charlie Huh and Thomas Lim,and Alexander Kwakye of Stony Brook University, USA.

Title: “MicroBIS – An integrated AI laboratory Assistant for Bacteria and Antimicrobial Resistance Identification”

Expression of Interest

Team’s Final Submission

ML model API


Impact Award

Team 10410, led by Rachael Kanguha of Chuka County Referral Hospital, Kenya, with Fred Mutisya of Narok County Government, Kenya

Title: “Using AI to Incorporate Dynamic Antibiograms and Research into Electronic Medical Records for antibiotic decision support”

Expression of interest

Team’s App

Team’s Final Submission: 1

Team’s Final Submission: 2

Link to App Demo

Rachael, K., & Mutisya, F. (2024). Insightcare.ai: Using AI to Incorporate Dynamic Antibiograms and Research into Electronic Medical Records for antibiotic decision support (Insightcare.v01.00). https://doi.org/10.5281/zenodo.14063253

Impact Award

Team 10416, led by Quentin Leclerc of Institut Pasteur, France, with Aleksandra Kovacevic and Lulla Opatowski, also of Institut Pasteur, Gwen Knight of London School of Hygiene & Tropical Medicine, and Catrin Moore of City St George’s University of London, UK

Title: “Rethinking AMR sampling: can non-sterile samples predict resistance in blood/sterile samples at a country level?”

Expression of Interest

Team’s Final Submission

 

Innovation Award

Team 10321, led by Tavpritesh Sethi and Jasmine Kaur of Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), India

Title: “AMROrbit Scorecard: A Dynamic Phase Space Model for Strategic Monitoring and Actionable Insights on Global AMR Trajectories”

Expression of Interest

Team’s App

Team’s Final Submission

Innovation Award

Team 10311, led by Naomi Waterlow with Alastair Clements, Chaelin Kim, Simon Procter and Gwen Knight of London School of Hygiene & Tropical Medicine, UK

Title: “Unveiling the Sex-Specific Impact on Antimicrobial Resistance (AMR): A Bayesian Hierarchical Model Approach Using Vivli Data”

Expression of Interest

Team’s Final Submission

Honorable Mention for Impact

Team 10323, led by Tochukwu Agboeze of Global Health Research Unit on Genomic Surveillance of AMR, University of Ibadan, with Oluwasegun Isaac Daramola, Ayobami Akomolafe and Roqeeb Adedeji of University of Ibadan, Nigeria

Title: “Predictive Analytics and Genotypic Evaluation for AMR in Africa (PANGEA)”

Expression of Interest

Team’s Final Submission

 

Finalists

Team 10429, led by Neha Nityadarshini with Jaya Biswas and Tamanna Bordoloi of All India Institute of Medical Sciences, New Delhi, India

Title: “Can artificial intelligence models be trusted? Determining the variables for building accurate prediction models for antimicrobial resistance”

Expression of Interest

Team’s App

Team’s Final Submission

Team 10427, led by Sasikala Rajendran with Srimathy Ramachandran, Akilandeswari Ramu, Yashwenth S. and Surya Murugan M.S. of SASTRA Deemed University, India

Title: “Exploring the evolution of multidrug resistance patterns in ESKAPEE pathogens using association mining: Key to antibiotic stewardship?”

Expression of Interest

Team’s App

Team’s Final Submission: 

  1. Dataset Overview
  2. Association Mining & Track MDR Patterns 
  3. AMR Trends

Student Team 10278, led by Adewale Ogunleye with Martina Airoldi of University of Tuebingen, Germany

Title: “Geography-Aware Optimization of Antimicrobial Combinations”

Expression of Interest

Team’s Final Submission

Student Team 10425, led by Miriam Puschel with Brian Matemba, Frijenia Sumbai, Happiness Kajoka, and Sia Msuya of Kilimanjaro Christian Medical University College, Tanzania

Title: “DISTRIBUTION OF EXTENDED SPECTRUM BETA-LACTAMASE ANTIBIOTIC RESISTANCE IN AFRICA 2005-2022”

Expression of Interest

Team’s Final Submission

Student Team 10415, led by Jake Hitch with Murong Yang, Aislinn Cook, Madison Luick and Natasha Salant of University of Oxford, UK

Title: “Income, antibiotic consumption and carbapenem resistance in Klebsiella pneumoniae: Proof of concept for copula-based distributional regression modelling to inform targeted public health investment”

Expression of Interest

Team’s Final Submission

Team 10424, led by Irishadullah-Akbar Sanusi with Abeeb Adeniyi, Clement Ojo, Josephine Binuyo and Joseph Adegoke of University of Ibadan, Nigeria

Title: “Mapping Global Antimicrobial Resistance species-wise and Creating an Online Vaccine Targets Repository Site”

Expression of Interest

Team’s Final Submission

Team 10340 led by Emily Dickens with Robert Beardmore of The University of Exeter, UK and Pablo Catalan of Universidad Carlos III Madrid, Spain

Title: “ATLAS predicts a vast number of novel antibiotic pairs for empirical therapy”

Expression of Interest

Team’s Final Submission