{"title":"REPO-TRIAL:基于共同机制的药物再利用和内表型","authors":"H. Schmidt","doi":"10.1109/BIBM.2018.8621156","DOIUrl":null,"url":null,"abstract":"Drug therapy and drug discovery are in a conceptual crisis. Hardly any new drug principles are discovered. Existing drugs have a catastrophic number needed to treat. Hardly any therapy targets a disease mechanism, because it is not known. Instead symptoms, biomarkers and risk factors are treated. Moreover we currently systemise medicine according to 19th and 20th century disease terms, which are mainly organ and symptom-based but not mechanistic. Network medicine utilizes common genetic origins, markers and co-morbidities to uncover mechanistic links between diseases. These links can be summarized in the diseasome, a comprehensive network of disease–disease relationships and clusters. The diseasome has been influential during the past decade, although most of its links are not followed up experimentally. We propose a new disease taxonomy based on mechanism and abolishing organ- and symptom-based disease definitions. Terms as hypertension, heart failure, arrhythmia will in future be considered mere disease phenotypes, most likely comprised of several endotypes and linked to several comorbities. Several such mechanistic clusters of disease phenotypes have been identified. One links to cyclic GMP and reactive oxygen species sources and targets. When examine the disease associations in a non-hypothesis based manner in order to identify possibly previously unrecognized clinical indications. Surprisingly, we find that sGC, the cardiovascular target of nitroglycerin, is closest linked to neurological disorders, an application that has so far not been explored clinically. Indeed, when investigating the neurological indication of this cluster with the highest unmet medical need, ischemic stroke, pre-clinically we find that sGC activity is virtually absent post-stroke. Conversely, a heme-free form of sGC, apo-sGC, was now the predominant isoform suggesting it may be a mechanism-based target in stroke. Indeed, this repurposing hypothesis could be validated experimentally in vivo as specific activators of apo-sGC were directly neuroprotective, reduced infarct size and increased survival. Thus, common mechanism clusters of the diseasome allow direct drug repurposing across previously unrelated disease phenotypes redefining them in a mechanism-based manner. Our example of repurposing apo-sGC activators for ischemic stroke should be urgently validated clinically as a possible first-in-class neuroprotective therapy and serves as a proof-of-concept for redefining disease, identifying new therapies. The REPO-TRIAL H2020 programme will develop an innovative in-silico based approach to improve the efficacy and precision of drug repurposing trials. We have chosen drug repurposing as it has the shortest time for clinical validation and translation. Validation of all putatively de novo discovered drug repositionings within the time-frame of this programme would be unrealistic. To improve efficacy and precision, and to adopt our computer simulation parameters and models, we choose a systems medicine based in-silico approach that identifies mechanistically related disease phenotypes and, as a result, a virtual patient cohort. We then validate this in-silico drug repurposing via high precision clinical trials in patients with cerebrocardiovascular phenotypes stratified using an exclusive mechanistic biomarker panel. We thus innovate two biomedical product classes, drugs and diagnostics. With this we will establish generally applicable in silico trials for other mechanistically related or defined disease phenotypes, for which size, duration, and risks will be reduced and precision increased. This generates rapid patient benefit, reduces drug development costs as well as risks, and enhances industrial competitiveness. Scientifically, we will contribute to reducing the uncertainty and vagueness of many of our current disease definitions that describe a symptom or apparent phenotype in an organ rather than defining diseases mechanistically as disturbance of self-regulation equilibria of biomolecular processes. Finally, we will reduce animal experimentation and animal numbers in general by applying a preclinical randomised confirmatory trial (pRCTs) concept and preclinical systematic reviews and meta-analyses facilitated by our open access pre-clinicaltrials.org platform, a pendant to clinicaltrials.gov.","PeriodicalId":108667,"journal":{"name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"REPO-TRIAL: Common mechanism-based drug repurposing and endophenotyping\",\"authors\":\"H. Schmidt\",\"doi\":\"10.1109/BIBM.2018.8621156\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Drug therapy and drug discovery are in a conceptual crisis. Hardly any new drug principles are discovered. Existing drugs have a catastrophic number needed to treat. Hardly any therapy targets a disease mechanism, because it is not known. Instead symptoms, biomarkers and risk factors are treated. Moreover we currently systemise medicine according to 19th and 20th century disease terms, which are mainly organ and symptom-based but not mechanistic. Network medicine utilizes common genetic origins, markers and co-morbidities to uncover mechanistic links between diseases. These links can be summarized in the diseasome, a comprehensive network of disease–disease relationships and clusters. The diseasome has been influential during the past decade, although most of its links are not followed up experimentally. We propose a new disease taxonomy based on mechanism and abolishing organ- and symptom-based disease definitions. Terms as hypertension, heart failure, arrhythmia will in future be considered mere disease phenotypes, most likely comprised of several endotypes and linked to several comorbities. Several such mechanistic clusters of disease phenotypes have been identified. One links to cyclic GMP and reactive oxygen species sources and targets. When examine the disease associations in a non-hypothesis based manner in order to identify possibly previously unrecognized clinical indications. Surprisingly, we find that sGC, the cardiovascular target of nitroglycerin, is closest linked to neurological disorders, an application that has so far not been explored clinically. Indeed, when investigating the neurological indication of this cluster with the highest unmet medical need, ischemic stroke, pre-clinically we find that sGC activity is virtually absent post-stroke. Conversely, a heme-free form of sGC, apo-sGC, was now the predominant isoform suggesting it may be a mechanism-based target in stroke. Indeed, this repurposing hypothesis could be validated experimentally in vivo as specific activators of apo-sGC were directly neuroprotective, reduced infarct size and increased survival. Thus, common mechanism clusters of the diseasome allow direct drug repurposing across previously unrelated disease phenotypes redefining them in a mechanism-based manner. Our example of repurposing apo-sGC activators for ischemic stroke should be urgently validated clinically as a possible first-in-class neuroprotective therapy and serves as a proof-of-concept for redefining disease, identifying new therapies. The REPO-TRIAL H2020 programme will develop an innovative in-silico based approach to improve the efficacy and precision of drug repurposing trials. We have chosen drug repurposing as it has the shortest time for clinical validation and translation. Validation of all putatively de novo discovered drug repositionings within the time-frame of this programme would be unrealistic. To improve efficacy and precision, and to adopt our computer simulation parameters and models, we choose a systems medicine based in-silico approach that identifies mechanistically related disease phenotypes and, as a result, a virtual patient cohort. We then validate this in-silico drug repurposing via high precision clinical trials in patients with cerebrocardiovascular phenotypes stratified using an exclusive mechanistic biomarker panel. We thus innovate two biomedical product classes, drugs and diagnostics. With this we will establish generally applicable in silico trials for other mechanistically related or defined disease phenotypes, for which size, duration, and risks will be reduced and precision increased. This generates rapid patient benefit, reduces drug development costs as well as risks, and enhances industrial competitiveness. Scientifically, we will contribute to reducing the uncertainty and vagueness of many of our current disease definitions that describe a symptom or apparent phenotype in an organ rather than defining diseases mechanistically as disturbance of self-regulation equilibria of biomolecular processes. Finally, we will reduce animal experimentation and animal numbers in general by applying a preclinical randomised confirmatory trial (pRCTs) concept and preclinical systematic reviews and meta-analyses facilitated by our open access pre-clinicaltrials.org platform, a pendant to clinicaltrials.gov.\",\"PeriodicalId\":108667,\"journal\":{\"name\":\"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2018.8621156\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2018.8621156","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
REPO-TRIAL: Common mechanism-based drug repurposing and endophenotyping
Drug therapy and drug discovery are in a conceptual crisis. Hardly any new drug principles are discovered. Existing drugs have a catastrophic number needed to treat. Hardly any therapy targets a disease mechanism, because it is not known. Instead symptoms, biomarkers and risk factors are treated. Moreover we currently systemise medicine according to 19th and 20th century disease terms, which are mainly organ and symptom-based but not mechanistic. Network medicine utilizes common genetic origins, markers and co-morbidities to uncover mechanistic links between diseases. These links can be summarized in the diseasome, a comprehensive network of disease–disease relationships and clusters. The diseasome has been influential during the past decade, although most of its links are not followed up experimentally. We propose a new disease taxonomy based on mechanism and abolishing organ- and symptom-based disease definitions. Terms as hypertension, heart failure, arrhythmia will in future be considered mere disease phenotypes, most likely comprised of several endotypes and linked to several comorbities. Several such mechanistic clusters of disease phenotypes have been identified. One links to cyclic GMP and reactive oxygen species sources and targets. When examine the disease associations in a non-hypothesis based manner in order to identify possibly previously unrecognized clinical indications. Surprisingly, we find that sGC, the cardiovascular target of nitroglycerin, is closest linked to neurological disorders, an application that has so far not been explored clinically. Indeed, when investigating the neurological indication of this cluster with the highest unmet medical need, ischemic stroke, pre-clinically we find that sGC activity is virtually absent post-stroke. Conversely, a heme-free form of sGC, apo-sGC, was now the predominant isoform suggesting it may be a mechanism-based target in stroke. Indeed, this repurposing hypothesis could be validated experimentally in vivo as specific activators of apo-sGC were directly neuroprotective, reduced infarct size and increased survival. Thus, common mechanism clusters of the diseasome allow direct drug repurposing across previously unrelated disease phenotypes redefining them in a mechanism-based manner. Our example of repurposing apo-sGC activators for ischemic stroke should be urgently validated clinically as a possible first-in-class neuroprotective therapy and serves as a proof-of-concept for redefining disease, identifying new therapies. The REPO-TRIAL H2020 programme will develop an innovative in-silico based approach to improve the efficacy and precision of drug repurposing trials. We have chosen drug repurposing as it has the shortest time for clinical validation and translation. Validation of all putatively de novo discovered drug repositionings within the time-frame of this programme would be unrealistic. To improve efficacy and precision, and to adopt our computer simulation parameters and models, we choose a systems medicine based in-silico approach that identifies mechanistically related disease phenotypes and, as a result, a virtual patient cohort. We then validate this in-silico drug repurposing via high precision clinical trials in patients with cerebrocardiovascular phenotypes stratified using an exclusive mechanistic biomarker panel. We thus innovate two biomedical product classes, drugs and diagnostics. With this we will establish generally applicable in silico trials for other mechanistically related or defined disease phenotypes, for which size, duration, and risks will be reduced and precision increased. This generates rapid patient benefit, reduces drug development costs as well as risks, and enhances industrial competitiveness. Scientifically, we will contribute to reducing the uncertainty and vagueness of many of our current disease definitions that describe a symptom or apparent phenotype in an organ rather than defining diseases mechanistically as disturbance of self-regulation equilibria of biomolecular processes. Finally, we will reduce animal experimentation and animal numbers in general by applying a preclinical randomised confirmatory trial (pRCTs) concept and preclinical systematic reviews and meta-analyses facilitated by our open access pre-clinicaltrials.org platform, a pendant to clinicaltrials.gov.