Insights from pharmacokinetic models of host-microbiome drug metabolism

Zimmermann-Kogadeeva, Maria; Zimmermann, Michael; Goodman, Andrew L.

doi:10.1080/19490976.2019.1667724

Cited by 30 publications

(29 citation statements)

References 45 publications

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“…It is now also evident that the microbiota can help mediate the effect of some drugs that target the immune system, and that changes to the structure or function of the microbiome represent an unanticipated limitation of the treatment (163). These data support the use of Ciona robusta as a model organism for investigating the impact of natural products/drugs on innate immune responses, and for studies of the role of the microbiota in metabolizing drugs and other dietary compounds that may explain observed variation in drug pharmacokinetics (165,166). These data emphasize the importance of also focusing pharmacogenomics studies on genes encoded by the gut microbiota (163).…”

Section: Multi-omics Approaches In Ciona Model For Studies In Ecotoximentioning

confidence: 78%

Reflections on the Use of an Invertebrate Chordate Model System for Studies of Gut Microbial Immune Interactions

et al. 2021

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The functional ecology of the gastrointestinal tract impacts host physiology, and its dysregulation is at the center of various diseases. The immune system, and specifically innate immunity, plays a fundamental role in modulating the interface of host and microbes in the gut. While humans remain a primary focus of research in this field, the use of diverse model systems help inform us of the fundamental principles legislating homeostasis in the gut. Invertebrates, which lack vertebrate-style adaptive immunity, can help define conserved features of innate immunity that shape the gut ecosystem. In this context, we previously proposed the use of a marine invertebrate, the protochordate Ciona robusta, as a novel tractable model system for studies of host-microbiome interactions. Significant progress, reviewed herein, has been made to fulfill that vision. We examine and review discoveries from Ciona that include roles for a secreted immune effector interacting with elements of the microbiota, as well as chitin-rich mucus lining the gut epithelium, the gut-associated microbiome of adults, and the establishment of a large catalog of cultured isolates with which juveniles can be colonized. Also discussed is the establishment of methods to rear the animals germ-free, an essential technology for dissecting the symbiotic interactions at play. As the foundation is now set to extend these studies into the future, broadening our comprehension of how host effectors shape the ecology of these microbial communities in ways that establish and maintain homeostasis will require full utilization of “multi-omics” approaches to merge computational sciences, modeling, and experimental biology in hypothesis-driven investigations.

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Section: Multi-omics Approaches In Ciona Model For Studies In Ecotoximentioning

confidence: 78%

Reflections on the Use of an Invertebrate Chordate Model System for Studies of Gut Microbial Immune Interactions

et al. 2021

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“…Firstly, data describing humanmicrobiome-drug interactions have only begun to reach a rapid rate of discovery in recent years, with studies such as the high-throughput screening of microbiota drug metabolism by Zimmerman et al, and work from the field-leading APC Microbiome Ireland. 10,[151][152][153][154] Whilst this new abundance of information is clearly positive, to facilitate ML projects data should be collated and formatted into accessible databases. Such databases could provide information on microbiota drug metabolism, formulation parameters for microbiome therapeutics, and pharmacokinetic details for microbiotatargeted medicines.…”

Section: Barriers To Overcomementioning

confidence: 99%

Harnessing machine learning for development of microbiome therapeutics

et al. 2021

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The last twenty years of seminal microbiome research has uncovered microbiota's intrinsic relationship with human health. Studies elucidating the relationship between an unbalanced microbiome and disease are currently published daily. As such, microbiome big data have become a reality that provide a mine of information for the development of new therapeutics. Machine learning (ML), a branch of artificial intelligence, offers powerful techniques for big data analysis and predictionmaking, that are out of reach of human intellect alone. This review will explore how ML can be applied for the development of microbiome-targeted therapeutics. A background on ML will be given, followed by a guide on where to find reliable microbiome big data. Existing applications and opportunities will be discussed, including the use of ML to discover, design, and characterize microbiome therapeutics. The use of ML to optimize advanced processes, such as 3D printing and in silico prediction of drug-microbiome interactions, will also be highlighted. Finally, barriers to adoption of ML in academic and industrial settings will be examined, concluded by a future outlook for the field.

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“…Drugs that are highly absorbed in the small intestine, due to their physicochemical properties, are not significantly affected by the GI microbiome unless a biliary excreted metabolite undergoes further metabolism in the GI. The largest effects will be on drugs that pass into the large intestine or undergo enterohepatic circulation [52].…”

Section: Microbiome Contributions To Small Molecule Drug Metabolism and Its Impact On Bioanalytical Assaysmentioning

confidence: 99%

2020 White Paper on Recent Issues in Bioanalysis: BMV of Hybrid Assays, Acoustic MS, HRMS, Data Integrity, Endogenous Compounds, Microsampling and Microbiome ( Part 1 –Recommendations on Industry/Regulators Consensus on BMV of Biotherapeutics by LCMS, Advanced Application in Hybrid Assays, Regulatory Challenges in Mass Spec, Innovation in Small Molecules, Peptides and Oligos)

et al. 2021

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The 14th edition of the Workshop on Recent Issues in Bioanalysis (14th WRIB) was held virtually on June 15–29, 2020 with an attendance of over 1000 representatives from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations, and regulatory agencies worldwide. The 14th WRIB included three Main Workshops, seven Specialized Workshops that together spanned 11 days in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccine. Moreover, a comprehensive vaccine assays track; an enhanced cytometry track and updated Industry/Regulators consensus on BMV of biotherapeutics by Mass Spectrometry (hybrid assays, LCMS and HRMS) were special features in 2020. As in previous years, this year's WRIB continued to gather a wide diversity of international industry opinion leaders and regulatory authority experts working on both small and large molecules to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance and achieving scientific excellence on bioanalytical issues. This 2020 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop and is aimed to provide the Global Bioanalytical Community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2020 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication covers the recommendations on (Part 1) Hybrid Assays, Innovation in Small Molecules, & Regulated Bioanalysis. Part 2A (BAV, PK LBA, Flow Cytometry Validation and Cytometry Innovation), Part 2B (Regulatory Input) and Part 3 (Vaccine, Gene/Cell Therapy, NAb Harmonization and Immunogenicity) are published in volume 13 of Bioanalysis, issues 5, and 6 (2021), respectively.

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Insights from pharmacokinetic models of host-microbiome drug metabolism

Cited by 30 publications

References 45 publications

Reflections on the Use of an Invertebrate Chordate Model System for Studies of Gut Microbial Immune Interactions

Reflections on the Use of an Invertebrate Chordate Model System for Studies of Gut Microbial Immune Interactions

Harnessing machine learning for development of microbiome therapeutics

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