NIH grant: Building Robust Open-Source Software Applications for the Identification, Prioritization, Visualization, and Selection of Neoantigens in Cancer Immunotherapy (1R50CA305826-01A1)

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NIH grant 1R50CA305826-01A1: Building Robust Open-Source Software Applications for the Identification, Prioritization, Visualization, and Selection of Neoantigens in Cancer Immunotherapy
Institute: {'code': 'CA', 'abbreviation': 'NCI', 'name': 'National Cancer Institute', 'admin_org_id': '12500008', 'admin_funding_url': ''}. PI: Susanna  Kiwala. Award: $155500.
Start: 2026-08-07T00:00:00.
Project Summary/Abstract
The goal of this application is to support Susanna Kiwala, MSc, as a Research Software Engineer and
Software Developer at the Washington University in St. Louis School of Medicine as a significant contributor to
Griffith lab projects and open-source software under the direction of Malachi Griffith, PhD. Mrs. Kiwala has an
undergraduate degree in Biomedical Documentation Sciences and a Master’s degree in Computer Science.
Her area of expertise is in the development of open-source software related to precision oncology and
personalized immunotherapy using software development best practices and design principles. This Research
Software Engineer award would allow three years of funding to maintain protected time for Mrs. Kiwala to
continue developing, enhancing, and extending the immunotherapy tool suite pVACtools. In particular, she will
facilitate a large-scale neoantigen immunogenicity validation experiment that targets a large number of
neoantigens and HLAs by using pVACtools for the identification of potentially immunogenic neoantigens. She
will also incorporate validated neoantigen results into pVACtools for improved neoantigen prediction accuracy,
update the BigMHC-IM immunogenicity predictor using the generated validation data, and implement a novel
platform, MNATR, for the sharing of immunologically assessed neoantigens and patient-matched multiomic
sequence data. Furthermore, she will refactor the neoantigen prioritization and visualization R shiny web
application pVACview to a database-backed client-server web application in order to ensure its long-term
scalability and robustness, and to facilitate advanced features that address specific needs of clinical
applications. Lastly, she will expand the functionality of this web application to add support for the storage of
neoantigen data observed in patients and matched multiomics data, which are commonly siloed in individual
research labs. This new application, pVACdb, will allow researchers to share neoantigen data with the broader
community, enabling large scale research and clinical trials. To foster community adoption of pVACtools, Mrs.
Kiwala will disseminate the results of this award to the broader research community by presenting at national
and international meetings, authoring peer-reviewed publications, designing online courses, and organizing
pVACtools hackathons. Throughout the award period she expects to gain significant additional leadership as
well as software engineering skills, particularly in regard to designing a client-server application from the
ground up and using plotting libraries for data visualizations.

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