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      Current Concepts in Pharmacometabolomics, Biomarker Discovery, and Precision Medicine

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          Abstract

          Pharmacometabolomics (PMx) studies use information contained in metabolic profiles (or metabolome) to inform about how a subject will respond to drug treatment. Genome, gut microbiome, sex, nutrition, age, stress, health status, and other factors can impact the metabolic profile of an individual. Some of these factors are known to influence the individual response to pharmaceutical compounds. An individual’s metabolic profile has been referred to as his or her “metabotype.” As such, metabolomic profiles obtained prior to, during, or after drug treatment could provide insights about drug mechanism of action and variation of response to treatment. Furthermore, there are several types of PMx studies that are used to discover and inform patterns associated with varied drug responses (i.e., responders vs. non-responders; slow or fast metabolizers). The PMx efforts could simultaneously provide information related to an individual’s pharmacokinetic response during clinical trials and be used to predict patient response to drugs making pharmacometabolomic clinical research valuable for precision medicine. PMx biomarkers can also be discovered and validated during FDA clinical trials. Using biomarkers during medical development is described in US Law under the 21st Century Cures Act. Information on how to submit biomarkers to the FDA and their context of use is defined herein.

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          2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults

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            Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies.

            To estimate the incidence of serious and fatal adverse drug reactions (ADR) in hospital patients. Four electronic databases were searched from 1966 to 1996. Of 153, we selected 39 prospective studies from US hospitals. Data extracted independently by 2 investigators were analyzed by a random-effects model. To obtain the overall incidence of ADRs in hospitalized patients, we combined the incidence of ADRs occurring while in the hospital plus the incidence of ADRs causing admission to hospital. We excluded errors in drug administration, noncompliance, overdose, drug abuse, therapeutic failures, and possible ADRs. Serious ADRs were defined as those that required hospitalization, were permanently disabling, or resulted in death. The overall incidence of serious ADRs was 6.7% (95% confidence interval [CI], 5.2%-8.2%) and of fatal ADRs was 0.32% (95% CI, 0.23%-0.41%) of hospitalized patients. We estimated that in 1994 overall 2216000 (1721000-2711000) hospitalized patients had serious ADRs and 106000 (76000-137000) had fatal ADRs, making these reactions between the fourth and sixth leading cause of death. The incidence of serious and fatal ADRs in US hospitals was found to be extremely high. While our results must be viewed with circumspection because of heterogeneity among studies and small biases in the samples, these data nevertheless suggest that ADRs represent an important clinical issue.
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              Metagenomic Shotgun Sequencing and Unbiased Metabolomic Profiling Identify Specific Human Gut Microbiota and Metabolites Associated with Immune Checkpoint Therapy Efficacy in Melanoma Patients1

              This is the first prospective study of the effects of human gut microbiota and metabolites on immune checkpoint inhibitor (ICT) response in metastatic melanoma patients. Whereas many melanoma patients exhibit profound response to ICT, there are fewer options for patients failing ICT—particularly with BRAF-wild-type disease. In preclinical studies, specific gut microbiota promotes regression of melanoma in mice. We therefore conducted a study of the effects of pretreatment gut microbiota and metabolites on ICT Response Evaluation Criteria in Solid Tumors response in 39 metastatic melanoma patients treated with ipilimumab, nivolumab, ipilimumab plus nivolumab (IN), or pembrolizumab (P). IN yielded 67% responses and 8% stable disease; P achieved 23% responses and 23% stable disease. ICT responders for all types of therapies were enriched for Bacteroides caccae. Among IN responders, the gut microbiome was enriched for Faecalibacterium prausnitzii, Bacteroides thetaiotamicron, and Holdemania filiformis. Among P responders, the microbiome was enriched for Dorea formicogenerans. Unbiased shotgun metabolomics revealed high levels of anacardic acid in ICT responders. Based on these pilot studies, both additional confirmatory clinical studies and preclinical testing of these bacterial species and metabolites are warranted to confirm their ICT enhancing activity.
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                Author and article information

                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                27 March 2020
                April 2020
                : 10
                : 4
                : 129
                Affiliations
                [1 ]Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA
                [2 ]Advanced Pattern Analysis and Countermeasures Group, Boulder, CO 80301, USA; mschmidtphd@ 123456patternanalysis.org
                [3 ]Sovaris Aerospace, Boulder, CO 80301, USA
                [4 ]Psychiatry and Behavioral Sciences, Duke Medicine and Duke Institute for Brain Sciences Duke University Medical Center, Box 3903, Durham, NC 27710, USA; rima.kaddurahdaouk@ 123456duke.edu
                Author notes
                Author information
                https://orcid.org/0000-0003-4380-2356
                Article
                metabolites-10-00129
                10.3390/metabo10040129
                7241083
                32230776
                39434760-8a5e-4ac7-beb9-77217ec6eca3
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 13 December 2019
                : 20 March 2020
                Categories
                Review

                pharmacometabolomics,pharmacometabonomics,precision medicine,drug response,metabotypes

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