The Nutritional Immunology and Molecular Medicine Laboratory (NIMML), a leading lab at the Biocomplexity Institute of Virginia Tech is applying artificial intelligence (AI) methods to personalized nutrition and health. These efforts are aligned with the Precision Medicine Initiative (PMI) which not only aids the researchers and physicians cure people, but also empowers individuals to monitor and take a more active role in their own health. As opposed to the PMI, personalized nutrition refers to tailored nutritional recommendations aimed at the promotion, maintenance of health and prevention against diseases. However, there are numerous challenges in the path of making personalized nutritional recommendations for the health well-being and disease prevention. The "one-size-fits-all" template is based on generic suggestions regarding nutritional recommendations for improving an individual's health are not helpful.

Autoimmune diseases, infectious disease and cancer have become increasingly difficult to treat using conventional methods that do not take into account individual genetic, environmental, and lifestyle differences. Developing new personalized treatments is like trying to work a vast, multidimensional jigsaw puzzle with pieces that are constantly changing shape. The Nutritional Immunology and Molecular Medicine Laboratory (NIMML), a leading lab at the Biocomplexity Institute of Virginia Tech and Biotherapeutics, a biotech startup, are applying artificial intelligence methods to accelerate the path to cures for complex human diseases. These efforts are aligned with the Precision Medicine Initiative which gives researchers and medical practitioners tools to cure people, but it is also empowers individuals to monitor and take a more active role in their own health. Artificial intelligence algorithms are used to create synthetic patient populations with the properties of actual patient cohorts, build personalized predictive models of drug combinations and unravel complex relationships between diet, microbiome and genetic lineup to determine the comparative treatment response.

May 11, 2017 – Studying human diseases is the equivalent of solving a massive and dynamic jigsaw puzzle with pieces that are constantly changing shape. A team involving researchers from the Nutritional Immunology and Molecular Medicine Laboratory (NIMML) at Virginia Tech and the Biomedical and Translational Informatics (BTI) Institute at Geisinger Health System are working together to advance precision medicine by integrating clinical data, artificial intelligence (AI) systems, and advanced machine-learning (ML) methods. In a new study, the collaborative team of experts have developed new computational methods to stratify stroke patients in an emergency setting, paving the way to data-driven triage process with higher fidelity. The rich, longitudinal data warehouse of the Geisinger Health System (GHS) has detailed electronic health records (EHR) of over 3 million active participants. This rich data is one of the major strengths that allowed Geisinger to be selected to participate in the national Precision Medicine Initiative (PMI) Cohort Program with the goal of improving the ability to prevent and treat diseases based on individual differences in lifestyle, environment, and genetics.