Predicting the effects of gut microbiota and diet on an individual’s drug response and safety
Precision medicine is an emerging paradigm that aims at maximizing the benefits and minimizing the harm of drugs. Realistic mechanistic models are needed to understand and limit heterogeneity in drug responses. Consequently, novel approaches are required that explicitly account for individual variations in response to environmental influences, in addition to genetic variation. The human gut microbiota metabolizes drugs and is modulated by diet, and it exhibits significant variation among individuals. However, the influence of the gut microbiota on drug failure or drug side effects is under-researched. In this project, we will combine whole-body, genome-scale molecular resolution modeling of human metabolism and human gut microbial metabolism, which represents a network of genes, proteins, and biochemical reactions, with physiological, clinically relevant modeling of drug responses. We will perform two pilot studies on human subjects to illustrate that this innovative, versatile computational modeling framework can be used to stratify patients prior to drug prescription and to optimize drug bioavailability through personalized dietary intervention. With these studies, BugTheDrug will advance mechanistic understanding of drug-microbiota-diet interactions and their contribution to individual drug responses. We will perform the first integration of cutting-edge approaches and novel insights from four distinct research areas: systems biology, quantitative systems pharmacology, microbiology, and nutrition. BugTheDrug conceptually and technologically addresses the demand for novel approaches to the study of individual variability, thereby providing breakthrough support for progress in precision medicine.
Overview of the project
The BugTheDrug project sought to address the significant challenge of individual variability in drug response, a concern that impacts not only patients and caregivers, but also strains healthcare systems worldwide. Medications are developed to be processed by the human body – absorbed, metabolised, transported, and ultimately eliminated – to achieve their intended therapeutic effect. These pharmacokinetic properties, assessed during drug development, guide the determination of optimal dosages. Yet, individual differences in genetic makeup can lead to diverse drug responses, with some individuals metabolising drugs more slowly or less efficiently. Lifestyle factors, including diet and exercise, alongside the gut microbiome, which has recently been discovered to extensively metabolise commonly prescribed drugs, further complicate drug response predictability. The composition of gut microbes, varying significantly among individuals due to diet and age, necessitates novel approaches for optimal drug response management.
In response, the BugTheDrug project developed an innovative computational framework that integrates genetic, dietary, and microbial data to predict an individual's drug response. This forward-thinking approach aimed to enable personalised treatment strategies, moving away from a currently pervasive one-size-fits-all mentality. The project achieved its goals through several key objectives:
The creation of novel computational methods to account for the highly complex interdependencies between human, microbial, dietary, and drug metabolism.
The creation of digital models of humans and associated microbes that allow for the personalised prediction of drug responses based on customisable queries and input data, such as genetic makeup, diet, and gut microbiome composition
The application and validation of these novel technologies in the context of colon cancer and Parkinson’s disease.
The project's conclusions underscore its transformative potential in precision health care. The development of digital metabolic twins represents a leap forward in creating personalised health interventions based on mechanism-derived hypotheses. By fostering a vast network of stakeholders from academia, industry, policy, regulators, and society, BugTheDrug has not only paved the way for technological advancements in healthcare, as demonstrated by the total expected 45 scientific manuscripts, but also ensured these innovations are accessible and beneficial to all, as demonstrated by the successful Virtuome programme with focus on community engagement. This initiative has laid a solid foundation for future exploration and expansion, evidenced by securing further funding ensuring the project's lasting impact and evolution.
Main work and results of the project
The BugTheDrug project initiated with the ambitious goal of enhancing our understanding and prediction of individual drug responses. Central to this effort was the development of the Virtual Metabolic Human (VMH, www.vmh.life) database, a comprehensive web resource that integrates curated biochemical knowledge of human and microbial metabolism with disease and nutritional data. This resource, freely available to the research community, connects extensive biochemical information from peer-reviewed scientific publications to other scientific databases, facilitating the simulation of human metabolism in health and disease states, as well as the interaction with gut microbial metabolism.
Key achievements include the development of digital metabolic models, including sex-specific and organ-resolved human models, and extensive microbial metabolic reconstructions, now including almost a quarter million strains. These models are the foundation for the personalised and mechanism-derived prediction of host-microbe co-metabolism, including drug responses.
The creation and application of these human and microbiome models required the co-development of the requisite computational methods and toolboxes. Therefore, we developed the requisite methods to analyse human and gut microbiome data along with nutritional and physiological information, for comprehensive simulations of human and microbial metabolism, with particular focus on drug metabolism.
The COVID-19 pandemic posed a significant challenge on the initially envisaged project operations, particularly clinical study aspects. Nevertheless, the project team adapted its approach, focusing on tackling the colorectal cancer and Parkinson's disease aspects through close collaboration with already established clinical cohorts and existing datasets. Thereby, we were offered the opportunity to apply our methodologies to a broader range of diseases, such as Alzheimer’s disease, irritable bowel disease, and COVID-19, showcasing the versatility and impact of the project's work.
The project's tenure yielded 29 peer-reviewed publications, alongside pre-prints and manuscripts in preparation, demonstrating the team's productivity and relevance of their research. The VMH, which is currently updated and expanded, has an international user base of currently ~1,000 users per month, with 194,000 accesses from 164 countries since October 2018. The dissemination of the project's findings extended beyond academic publications to engage a wider audience, through opinion pieces, workshops, and videos.
As the project concludes, the foundations laid by the BugTheDrug team in computational frameworks, the VMH database, and disease investigation stand as a testament to the project's commitment to advancing personalised medicine. The project not only contributes to our scientific understanding but also opens avenues for future healthcare innovations, marking a significant step forward in the pursuit of tailored treatment strategies for individual patients.
Progress beyond the state of the art
The BugTheDrug project has made significant strides beyond the existing state of the art in computational biology and personalised medicine. Through the development and enhancement of the Virtual Metabolic Human (VMH) database, the project has established a cornerstone for biomedical research, interconnecting otherwise scattered biochemical knowledge in a manner unprecedented before this endeavour. The VMH database, which has attracted nearly 194,000 users from 164 countries since its inception in October 2018, serves as a testament to its global impact and utility in the biomedical community. This resource stands out not only for its comprehensive collection of data on human, microbiome, diet, and disease but also for its user-friendly interface that facilitates access to complex datasets and visualisations.
Fundamental to our advancements are Harvey and Harvetta, the sex-specific and organ-resolved whole-body models, which represent a monumental leap towards the creation of digital metabolic twins. These models, encompassing the metabolism of 26 organs and six blood cell types through 80,000 biochemical reactions, embody the current pinnacle of anatomical and physiological consistency in computational human modelling. Their ability to be parameterised with diverse datasets, including physiological, dietary, and omics data, underscores the depth of insight they provide into human metabolism.
Another groundbreaking achievement is the AGORA2 resource, which includes detailed metabolic reconstructions of 7,302 human gut microbes. This resource unlocks metabolic modelling for the complex interplay between microbe-microbe and human-microbe interactions, including the biotransformation capabilities of microbes for 98 drugs. Such insights are crucial for understanding the role of the microbiome in drug metabolism and human health.
The establishment of the Virtuome summer school and the engagement of a broad community through 114 events have been instrumental in diversifying our stakeholder base. This engagement spans the scientific community, policy makers, charities, industry, patients, and the general public, showcasing our commitment to fostering dialogue across various sectors for achieving positive societal impact in a systematic approach.
Together, these achievements not only represent progress beyond the state of the art but also set new benchmarks for the integration of computational modelling with biomedical research, to ultimately contribute towards the creation of Virtual Humans. The project was instrumental in securing complementary funding of over €5 million, including an ERC Consolidator Grant award of €2 million. This testament to the robust foundation laid for ongoing and future research now enables the continuation and expansion of our work towards establishing Digital Metabolic Twins, marking a significant step forward in personalised healthcare.