Anushruti Gupta Claire Vania

Claire Vania & Anushruti Gupta Named Grand Prize Winners of 2025 Vivli AMR Surveillance Data Challenge

Vivli has announced that it has selected two Johns Hopkins alumnas, Claire Vania (Whiting School of Engineering ’23), MS, Imaging Research Data Scientist at St. Jude Children’s Research Hospital and Dr. Anushruti Gupta (Bloomberg School of Public Health ’22), MBBS, MSPH, Senior Research Data Analyst at the Center for Infectious Diseases in India at Johns Hopkins, as recipients of its 2025 AMR Visionary Award Grand Prize.  The award is part of Vivli’s AMR (Antimicrobial Resistance) Surveillance Data Challenge, and the duo was selected for creatively and independently developing a dashboard that can predict the rate of resistance change using datasets from Vivli’s AMR Register.

Funded by Johnson & Johnson, Paratek, Pfizer and the National Institutes of Health, the AMR Data Challenge was launched to stimulate innovative re-use of surveillance data available in the Vivli AMR Register, which comprises surveillance datasets provided by the biopharmaceutical industry. The Register is made freely available to researchers, governments, and organizations for research efforts that seek to identify patterns and trends and develop strategies to combat AMR.

Gupta and Vania were selected from among 58 teams across 22 countries attempting to leverage high-quality industry AMR surveillance data into new advancements and tools for AMR surveillance.

The dashboard was conceptualized out of the recognition that policymakers need better information than trend charts for proactively addressing antimicrobial resistance. Using machine learning, the dashboard takes past trend data and extrapolates the results of AMR policies in different countries if they had been enacted in a specific year. 

The dashboard analyzes two main elements: Policy Impact and Policy Potential. For AMR policies that have already been implemented, they sought to determine if the policy worked. For new or planned policies, they looked to see how effective (or ineffective) the policy would be if enacted immediately. By employing a DoWhy model, a type of Python program, Gupta and Vania could go beyond correlation and look at causal inference, supported by graphical modeling and refutation testing.

“It was more thrilling to present the work and answer questions than to actually win the award,” Gupta said. “I would like to see the dashboard become a go-to resource for policymakers. This would be particularly relevant in countries where limited resources make it essential to invest in policies with a higher likelihood of success, rather than relying on trial and error.”

“We combined data science and curiosity to look at AMR in a new way,” Vania said. “Now we’re looking forward to expanding our approach and seeing how it can help inform real-world decisions.”