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A Predictive Computational Platform for Gut Microbiome Precision Medicine


Project Summary / AbstractThe human gut microbiome has recently become a primary focus of therapeutic research. This trend has been driven by agrowing understanding of the intimate ties between the gut microbiome and various diseases, as well as interactions withdifferent types of xenobiotics such as drugs. Specifically, evidence for the role of the gut microbiome as a determiningfactor in drug pharmacokinetics and therapeutics response has exponentially expanded. The pharmaceutical industry hasbecome increasingly interested in the use of microbiome therapeutics that target and manipulate the gut microbiota toimprove health conditions or prevent/treat diseases. A major challenge, however, is the high variability of the gutmicrobiome composition across individuals. Leading pharmaceutical researchers have begun to recognize that inter-individual variations should be accounted for in attempts to develop personalized medicine. However, despite extensiveprogress in gut microbiome research, no current effort had been able to leverage personalized ?omics? data to explore thedynamics of gut microbiome in interacting with therapeutics.This Phase I proposal targets an essential need at the intersection of two recent research initiatives announced by theWhite House, namely the Precision Medicine Initiative (2015) and the National Microbiome Initiative (2016). This projectseeks to develop a predictive computational platform by integrating novel state-of-the-art computational techniques andmodeling approaches. By simulating the personalized, multi-scale dynamics of the gut microbiome in interaction withtherapeutics, new information can be leveraged to improve the effectiveness of drug design and development. We willemploy complex systems approaches, combined with computational biology techniques, to explicitly model the individualcomponents of the complex network of gut microbiota as well as the rules governing their behavior (e.g. interactions) andpredict systems-level emergent behavior of the whole system. This multi-scale platform will be validated using targeted invitro experiments and in vivo studies.The outcome of this Phase I project will be a proof-of-concept of an integrated, multi-scale computational platform forpredicting the functional dynamics of gut microbiome in the context of pharmacomicrobiomics, i.e. interactions of the gutmicrobiome with therapeutics. This in-silico platform would reduce the cost and timeframe of drug development byreducing the need for iterative pre-clinical experiments and better directing clinical trials, while increasing theeffectiveness of the therapeutics themselves. Moreover, this platform can help increase the safety of pharmaceuticals byevaluating the mechanisms of toxicity as they may differ from individual-to-individual. As a result, the pharmaceuticalindustry as well as academic researchers in the gut microbiome and precision medicine fields would benefit from thesuccessful outcome of this project and, in addition, this platform could eventually become an essential tool inpersonalizing the prescription of drug types and doses for specific therapeutics.

Soheilypour, Mohammad; Shirazi, Fatemeh
Nexilico, Inc.
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