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Hey JA, Yu JY, Abushakra S, Schaefer JF, Power A, Kesslak P, Tolar M. Analysis of Cerebrospinal Fluid, Plasma β-Amyloid Biomarkers, and Cognition from a 2-Year Phase 2 Trial Evaluating Oral ALZ-801/Valiltramiprosate in APOE4 Carriers with Early Alzheimer's Disease Using Quantitative Systems Pharmacology Model. Drugs 2024; 84:825-839. [PMID: 38902572 PMCID: PMC11289344 DOI: 10.1007/s40265-024-02068-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/14/2024] [Indexed: 06/22/2024]
Abstract
INTRODUCTION ALZ-801/valiltramiprosate is an oral, small-molecule inhibitor of beta-amyloid (Aβ) aggregation and oligomer formation in late-stage development as a disease-modifying therapy for early Alzheimer's disease (AD). The present investigation provides a quantitative systems pharmacology (QSP) analysis of amyloid fluid biomarkers and cognitive results from a 2-year ALZ-801 Phase 2 trial in APOE4 carriers with early AD. METHODS The single-arm, open-label phase 2 study evaluated effects of ALZ-801 265 mg two times daily (BID) on cerebrospinal fluid (CSF) and plasma amyloid fluid biomarkers over 104 weeks in APOE4 carriers with early AD [Mini-Mental State Examination (MMSE) ≥ 22]. Subjects with positive CSF biomarkers for amyloid (Aβ42/Aβ40) and tau pathology (p-tau181) were enrolled, with serial CSF and plasma levels of Aβ42 and Aβ40 measured over 104 weeks. Longitudinal changes of CSF Aβ42, plasma Aβ42/Aβ40 ratio, and cognitive Rey Auditory Verbal Learning Test (RAVLT) were compared with the established natural disease trajectories in AD using a QSP approach. The natural disease trajectory data for amyloid biomarkers and RAVLT were extracted from a QSP model and an Alzheimer's disease neuroimaging initiative population model, respectively. Analyses were stratified by disease severity and sex. RESULTS A total of 84 subjects were enrolled. Excluding one subject who withdrew at the early stage of the trial, data from 83 subjects were used for this analysis. The ALZ-801 treatment arrested the progressive decline in CSF Aβ42 level and plasma Aβ42/Aβ40 ratio, and stabilized RAVLT over 104 weeks. Both sexes showed comparable responses to ALZ-801, whereas mild cognitive impairment (MCI) subjects (MMSE ≥ 27) exhibited a larger biomarker response compared with more advanced mild AD subjects (MMSE 22-26). CONCLUSIONS In this genetically defined and biomarker-enriched early AD population, the QSP analysis demonstrated a positive therapeutic effect of oral ALZ-801 265 mg BID by arresting the natural decline of monomeric CSF and plasma amyloid biomarkers, consistent with the target engagement to prevent their aggregation into soluble neurotoxic oligomers and subsequently into insoluble fibrils and plaques over 104 weeks. Accompanying the amyloid biomarker changes, ALZ-801 also stabilized the natural trajectory decline of the RAVLT memory test, suggesting that the clinical benefits are consistent with its mechanism of action. This sequential effect arresting the disease progression on biomarkers and cognitive decline was more pronounced in the earlier symptomatic stages of AD. The QSP analysis provides fluid biomarker and clinical evidence for ALZ-801 as a first-in-class, oral small-molecule anti-Aβ oligomer agent with disease modification potential in AD. TRIAL REGISTRY https://clinicaltrials.gov/study/NCT04693520.
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Affiliation(s)
- John A Hey
- Alzheon, Inc., 111 Speen Street, Suite 306, Framingham, MA, 01701, USA.
| | - Jeremy Y Yu
- Alzheon, Inc., 111 Speen Street, Suite 306, Framingham, MA, 01701, USA
- Division of Endocrinology, Diabetes and Metabolic Diseases, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Susan Abushakra
- Alzheon, Inc., 111 Speen Street, Suite 306, Framingham, MA, 01701, USA
| | - Jean F Schaefer
- Alzheon, Inc., 111 Speen Street, Suite 306, Framingham, MA, 01701, USA
| | - Aidan Power
- Alzheon, Inc., 111 Speen Street, Suite 306, Framingham, MA, 01701, USA
| | - Patrick Kesslak
- Alzheon, Inc., 111 Speen Street, Suite 306, Framingham, MA, 01701, USA
| | - Martin Tolar
- Alzheon, Inc., 111 Speen Street, Suite 306, Framingham, MA, 01701, USA
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Santos Oliveira L, Kueirislene Amâncio Ferreira M, Wagner de Queiroz Almeida-Neto F, Wlisses da Silva A, Ivo Lima Pinto Filho J, Nunes da Rocha M, Machado Marinho E, Henrique Ferreira Ribeiro W, Machado Marinho M, Silva Marinho E, Eire Silva Alencar de Menezes J, Dos Santos HS. Synthesis, molecular docking, ADMET, and evaluation of the anxiolytic effect in adult zebrafish of synthetic chalcone (E)-3-(4-(dimethylamino)phenyl)-1-(2-hydroxyphenyl)prop-2-en-1-one: An in vivo and in silico approach. Fundam Clin Pharmacol 2024; 38:290-306. [PMID: 37845792 DOI: 10.1111/fcp.12960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/17/2023] [Accepted: 09/29/2023] [Indexed: 10/18/2023]
Abstract
BACKGROUND Anxiety disorders represent the complex interaction between biological, psychological, temperamental, and environmental factors; drugs available to treat anxiety such as benzodiazepines (BZDs) are associated with several unwanted side effects. Although there are useful treatments, there is still a need for more effective anxiolytics with better safety profiles than BZDs. Chalcones or 1,3-diphenyl-2-proper-1-ones can be an alternative since this class of compounds has shown therapeutic potential mainly due to interactions with GABAA receptors and serotonergic system. OBJECTIVES This study evaluated the anxiolytic potential of chalcone (E)-3-(4-(dimethylamino)phenyl)-1-(2-hydroxyphenyl)prop-2-en-1-one (C2OHPDA) in adult zebrafish (Danio rerio) (ZFa). METHODS Each animal (n = 6/group) was treated intraperitoneally (i.p.; 20 μL) with the chalcone (4, 20, and 40 mg/kg) and with the vehicle (DMSO 3%; 20 μL), being submitted to the tests of locomotor activity and 96-h acute toxicity. The light/dark test was also performed, and the serotonergic mechanism (5-HT) was evaluated through the antagonists of the 5-HTR1 , 5-HTR2A/2C , and 5-HTR3A/3B receptors. It was investigated the prediction of the chalcone's position and preferential orientation concerning its receptor, as well as the pharmacokinetic parameters (ADMET) involved in the process after administration. RESULTS As a result, C2OHPDA was not toxic and reduced the locomotor activity of ZFa. Furthermore, chalcone demonstrated an anxiolytic effect on the central nervous system (CNS), mediated by the serotonergic system, with action on 5-HT2A and 5-HTR3A/3B receptors. The interaction of C2OHPDA with 5-HT2A R and 5-HT3A receptors was confirmed by molecular docking study, the affinity energy observed was -8.7 and -9.1 kcal/mol, respectively. CONCLUSION Thus, this study adds new evidence and highlights that chalcone can potentially be used to develop compounds with anxiolytic properties.
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Affiliation(s)
- Larissa Santos Oliveira
- Science and Technology, Graduate Program in Natural Sciences, State University of Ceará, Fortaleza, Ceará, Brazil
| | | | | | - Antonio Wlisses da Silva
- Northeast Biotechnology Network, Graduate Program of Biotechnology, State University of Ceará, Fortaleza, Ceará, Brazil
| | | | - Matheus Nunes da Rocha
- Science and Technology, Graduate Program in Natural Sciences, State University of Ceará, Fortaleza, Ceará, Brazil
| | - Emanuelle Machado Marinho
- Department of Organic and Inorganic Chemistry, Federal University of Ceará, Fortaleza, Ceará, Brazil
| | | | | | - Emmanuel Silva Marinho
- Science and Technology, Graduate Program in Natural Sciences, State University of Ceará, Fortaleza, Ceará, Brazil
| | | | - Hélcio Silva Dos Santos
- Science and Technology, Graduate Program in Natural Sciences, State University of Ceará, Fortaleza, Ceará, Brazil
- Northeast Biotechnology Network, Graduate Program of Biotechnology, State University of Ceará, Fortaleza, Ceará, Brazil
- Chemistry Course, State University of Vale do Acaraú, Sobral, Ceará, Brazil
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Paul SM, Potter WZ. Finding new and better treatments for psychiatric disorders. Neuropsychopharmacology 2024; 49:3-9. [PMID: 37582978 PMCID: PMC10700311 DOI: 10.1038/s41386-023-01690-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 07/07/2023] [Accepted: 07/24/2023] [Indexed: 08/17/2023]
Abstract
In contrast to most fields of medicine, progress to discover and develop new and improved psychiatric drugs has been slow and disappointing. The vast majority of currently prescribed drugs to treat schizophrenia, mood and anxiety disorders are arguably no more effective than the first generation of psychiatric drugs introduced well over 50 years ago. With only a few exceptions current psychiatric drugs work via the same fundamental mechanisms of action as first-generation agents. Here we describe the reasons for this slow progress and outline a number of areas of research that involve a greater reliance on experimental therapeutics utilizing recent advances in neuroscience to better understand disease biology. We exemplify the potential impact of these areas of research focus with several recent examples of novel agents that have emerged and which support our optimism that newer, more effective and better tolerated agents, are on the horizon. Together with existing drugs these newer agents and novel mechanisms could offer markedly improved functional outcomes for the millions of people still disabled by psychiatric disorders.
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Affiliation(s)
- Steven M Paul
- Karuna Therapeutics, Washington University School of Medicine, St. Louis, MO, USA.
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4
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Gaiteri C, Connell DR, Sultan FA, Iatrou A, Ng B, Szymanski BK, Zhang A, Tasaki S. Robust, scalable, and informative clustering for diverse biological networks. Genome Biol 2023; 24:228. [PMID: 37828545 PMCID: PMC10571258 DOI: 10.1186/s13059-023-03062-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 09/19/2023] [Indexed: 10/14/2023] Open
Abstract
Clustering molecular data into informative groups is a primary step in extracting robust conclusions from big data. However, due to foundational issues in how they are defined and detected, such clusters are not always reliable, leading to unstable conclusions. We compare popular clustering algorithms across thousands of synthetic and real biological datasets, including a new consensus clustering algorithm-SpeakEasy2: Champagne. These tests identify trends in performance, show no single method is universally optimal, and allow us to examine factors behind variation in performance. Multiple metrics indicate SpeakEasy2 generally provides robust, scalable, and informative clusters for a range of applications.
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Affiliation(s)
- Chris Gaiteri
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA.
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA.
| | - David R Connell
- Rush University Graduate College, Rush University Medical Center, Chicago, IL, USA
| | - Faraz A Sultan
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Artemis Iatrou
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Harvard University, Belmont, MA, USA
| | - Bernard Ng
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Boleslaw K Szymanski
- Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, USA
- Network Science and Technology Center, Rensselaer Polytechnic Institute, Troy, NY, USA
- Academy of Social Sciences, Łódź, Poland
| | - Ada Zhang
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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Sadri A. Is Target-Based Drug Discovery Efficient? Discovery and "Off-Target" Mechanisms of All Drugs. J Med Chem 2023; 66:12651-12677. [PMID: 37672650 DOI: 10.1021/acs.jmedchem.2c01737] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Target-based drug discovery is the dominant paradigm of drug discovery; however, a comprehensive evaluation of its real-world efficiency is lacking. Here, a manual systematic review of about 32000 articles and patents dating back to 150 years ago demonstrates its apparent inefficiency. Analyzing the origins of all approved drugs reveals that, despite several decades of dominance, only 9.4% of small-molecule drugs have been discovered through "target-based" assays. Moreover, the therapeutic effects of even this minimal share cannot be solely attributed and reduced to their purported targets, as they depend on numerous off-target mechanisms unconsciously incorporated by phenotypic observations. The data suggest that reductionist target-based drug discovery may be a cause of the productivity crisis in drug discovery. An evidence-based approach to enhance efficiency seems to be prioritizing, in selecting and optimizing molecules, higher-level phenotypic observations that are closer to the sought-after therapeutic effects using tools like artificial intelligence and machine learning.
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Affiliation(s)
- Arash Sadri
- Lyceum Scientific Charity, Tehran, Iran, 1415893697
- Interdisciplinary Neuroscience Research Program (INRP), Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran, 1417755331
- Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran, 1417614411
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Caianiello S, Bertolaso M, Militello G. Thinking in 3 dimensions: philosophies of the microenvironment in organoids and organs-on-chip. HISTORY AND PHILOSOPHY OF THE LIFE SCIENCES 2023; 45:14. [PMID: 36949354 DOI: 10.1007/s40656-023-00560-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 02/03/2023] [Indexed: 06/18/2023]
Abstract
Organoids and organs-on-a-chip are currently the two major families of 3D advanced organotypic in vitro culture systems, aimed at reconstituting miniaturized models of physiological and pathological states of human organs. Both share the tenets of the so-called "three-dimensional thinking", a Systems Physiology approach focused on recapitulating the dynamic interactions between cells and their microenvironment. We first review the arguments underlying the "paradigm shift" toward three-dimensional thinking in the in vitro culture community. Then, through a historically informed account of the technical affordances and the epistemic commitments of these two approaches, we highlight how they embody two distinct experimental cultures. We finally argue that the current systematic effort for their integration requires not only innovative "synergistic" engineering solutions, but also conceptual integration between different perspectives on biological causality.
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Affiliation(s)
- Silvia Caianiello
- Institute for the History of Philosophy and Science in the Modern Age (ISPF), Consiglio Nazionale delle Ricerche, Naples, Italy.
- Stazione Zoologica "Anton Dohrn", Naples, Italy.
| | - Marta Bertolaso
- Faculty of Science and Technology for Sustainable Development and One Health, Universitá Campus Bio-Medico di Roma, Rome, Italy
| | - Guglielmo Militello
- Faculty of Science and Technology for Sustainable Development and One Health, Universitá Campus Bio-Medico di Roma, Rome, Italy
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Hampel H, Gao P, Cummings J, Toschi N, Thompson PM, Hu Y, Cho M, Vergallo A. The foundation and architecture of precision medicine in neurology and psychiatry. Trends Neurosci 2023; 46:176-198. [PMID: 36642626 PMCID: PMC10720395 DOI: 10.1016/j.tins.2022.12.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/18/2022] [Accepted: 12/14/2022] [Indexed: 01/15/2023]
Abstract
Neurological and psychiatric diseases have high degrees of genetic and pathophysiological heterogeneity, irrespective of clinical manifestations. Traditional medical paradigms have focused on late-stage syndromic aspects of these diseases, with little consideration of the underlying biology. Advances in disease modeling and methodological design have paved the way for the development of precision medicine (PM), an established concept in oncology with growing attention from other medical specialties. We propose a PM architecture for central nervous system diseases built on four converging pillars: multimodal biomarkers, systems medicine, digital health technologies, and data science. We discuss Alzheimer's disease (AD), an area of significant unmet medical need, as a case-in-point for the proposed framework. AD can be seen as one of the most advanced PM-oriented disease models and as a compelling catalyzer towards PM-oriented neuroscience drug development and advanced healthcare practice.
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Affiliation(s)
- Harald Hampel
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Peng Gao
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV, USA
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy; Athinoula A. Martinos Center for Biomedical Imaging and Harvard Medical School, Boston, MA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yan Hu
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Min Cho
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Andrea Vergallo
- Alzheimer's Disease & Brain Health, Eisai Inc., Nutley, NJ, USA
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8
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Zhu J, Liang Q, He S, Wang C, Lin X, Wu D, Lin G, Wang Z. Research trends and hotspots of neurodegenerative diseases employing network pharmacology: A bibliometric analysis. Front Pharmacol 2023; 13:1109400. [PMID: 36712694 PMCID: PMC9878685 DOI: 10.3389/fphar.2022.1109400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 12/28/2022] [Indexed: 01/15/2023] Open
Abstract
Background: Employing network pharmacology in neurodegenerative diseases (NDs) has been extensively studied recently. However, no comprehensive study has conducted on this subject employing bibliometrics so far. The purpose of this study was to find out the developmental trends and hotspots, and to predict potential research directions in this filed. Methods: Relevant research were collected from the Web of Science Core Collection Bibliometrics and visual analysis were executed using CiteSpace, VOSviewer, Histcite and R-bibliometrix. Results: A total of 420 English articles on network pharmacology in NDs published in 2008-2022 were obtained from the WOSCC database. From 2008 to 2022, annual publications showed a steady growing trend, especially in 2014-2022. China, Beijing Univ Chinese Med, Frontiers in Pharmacology, and Geerts H are the most prolific country, institution, journal, and author, respectively. China, Nucleic Acids Research, and Hopkins AL are the most highly cited country, journal, and author, respectively. Moreover, network pharmacology and Alzheimer's disease are the focal areas of current researches according to analysis of co-cited references and keywords. Finally, in the detection of burst keywords, systems pharmacology and database are new approaches to disease and drug research, while traditional Chinese medicine (TCM) and Alzheimer's disease are hot research directions. The above keywords are speculated to be the research frontiers. Conclusion: Network pharmacology and Alzheimers' disease are the main topics of researches on network pharmacology in NDs. Network pharmacology and the TCM treatment of Alzheimer's disease have been the recent research hotspots. To sum up, the potential for exploring TCM treatment of AD with network pharmacology is huge.
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Affiliation(s)
- Jie Zhu
- Department of Anesthesiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Qingchun Liang
- Department of Anesthesiology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, China
| | - Siyi He
- Department of Anesthesiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Chen Wang
- Department of Anesthesiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Xiafei Lin
- Department of Anesthesiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Duozhi Wu
- Department of Anesthesiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Guanwen Lin
- Department of Anesthesiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China,*Correspondence: Guanwen Lin, ; Zhihua Wang,
| | - Zhihua Wang
- Department of Anesthesiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China,*Correspondence: Guanwen Lin, ; Zhihua Wang,
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Gieschke R, Carr R. Conceptual and organizational barriers to quantitative systems pharmacology modeling of pathophysiological systemic drug hypotheses. CPT Pharmacometrics Syst Pharmacol 2022; 11:1556-1559. [PMID: 36343097 PMCID: PMC9755914 DOI: 10.1002/psp4.12873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/20/2022] [Accepted: 09/22/2022] [Indexed: 11/09/2022] Open
Affiliation(s)
| | - Robert Carr
- In Silico BiosciencesLexingtonMassachusettsUSA
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10
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Stephenson D, Ollivier C, Brinton R, Barrett J. Can Innovative Trial Designs in Orphan Diseases Drive Advancement of Treatments for Common Neurological Diseases? Clin Pharmacol Ther 2022; 111:799-806. [PMID: 35034352 PMCID: PMC9305159 DOI: 10.1002/cpt.2528] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 12/27/2021] [Indexed: 11/10/2022]
Abstract
Global regulatory agencies have transformed their approach to approvals in their processes for formal review of the safety and efficacy of new drugs. Opportunities for innovation have expanded because of the coronavirus disease 2019 (COVID-19) pandemic. Several regulatory-led initiatives have progressed rapidly during the past year, including patient-focused drug development, model-informed drug development, real-world evidence, and complex innovative trial designs. Collectively, these initiatives have accelerated the rate of approvals. Despite demands to focus on urgent needs imposed by the COVID-19 pandemic, the number of new drug approvals over the past year, particularly for rare diseases, has outpaced expectations. Advancing therapeutics for nervous system disorders requires adaptive strategies that align with rapid developments in the field. Three relentlessly progressive diseases, amyotrophic lateral sclerosis, Duchenne muscular dystrophy, and Parkinson's disease are in urgent need of new treatments. Herein, we propose new regulatory initiatives, including innovative trial designs and patient-focused drug development that accelerate clinical trial conduct while meeting critical regulatory requirements for therapeutic approval.
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Affiliation(s)
| | | | - Roberta Brinton
- Center for Innovation in Brain SciencesUniversity of Arizona Health SciencesTucsonArizonaUSA
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Chelliah V, van der Graaf PH. Model‐informed target identification and validation through combining quantitative systems pharmacology with network‐based analysis. CPT Pharmacometrics Syst Pharmacol 2022; 11:399-402. [PMID: 35178891 PMCID: PMC9007604 DOI: 10.1002/psp4.12766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/10/2022] [Accepted: 01/17/2022] [Indexed: 11/20/2022] Open
Affiliation(s)
| | - Piet H. van der Graaf
- Certara QSP Certara UK Limited Sheffield UK
- Leiden Academic Centre for Drug Research University of Leiden Leiden The Netherlands
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12
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Murata Y, Neuhoff S, Rostami-Hodjegan A, Takita H, Al-Majdoub ZM, Ogungbenro K. In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition. AAPS J 2022; 24:28. [PMID: 35028763 PMCID: PMC8817058 DOI: 10.1208/s12248-021-00675-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/09/2021] [Indexed: 11/30/2022] Open
Abstract
Drug development for the central nervous system (CNS) is a complex endeavour with low success rates, as the structural complexity of the brain and specifically the blood-brain barrier (BBB) poses tremendous challenges. Several in vitro brain systems have been evaluated, but the ultimate use of these data in terms of translation to human brain concentration profiles remains to be fully developed. Thus, linking up in vitro-to-in vivo extrapolation (IVIVE) strategies to physiologically based pharmacokinetic (PBPK) models of brain is a useful effort that allows better prediction of drug concentrations in CNS components. Such models may overcome some known aspects of inter-species differences in CNS drug disposition. Required physiological (i.e. systems) parameters in the model are derived from quantitative values in each organ. However, due to the inability to directly measure brain concentrations in humans, compound-specific (drug) parameters are often obtained from in silico or in vitro studies. Such data are translated through IVIVE which could be also applied to preclinical in vivo observations. In such exercises, the limitations of the assays and inter-species differences should be adequately understood in order to verify these predictions with the observed concentration data. This report summarizes the state of IVIVE-PBPK-linked models and discusses shortcomings and areas of further research for better prediction of CNS drug disposition. Graphical abstract ![]()
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Affiliation(s)
- Yukiko Murata
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.,Sohyaku.Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, 1000, Kamoshida-cho, Aoba-ku, Yokohama, Kanagawa, 227-0033, Japan
| | - Sibylle Neuhoff
- Certara UK Ltd, Simcyp Division, 1 Concourse Way, Level 2-Acero, Sheffield, S1 2BJ, UK
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.,Certara UK Ltd, Simcyp Division, 1 Concourse Way, Level 2-Acero, Sheffield, S1 2BJ, UK
| | - Hiroyuki Takita
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.,Development Planning, Clinical Development Center, Asahi Kasei Pharma Corporation, Hibiya Mitsui Tower, 1-1-2 Yurakucho, Chiyoda-ku, Tokyo, 100-0006, Japan
| | - Zubida M Al-Majdoub
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK
| | - Kayode Ogungbenro
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.
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Ribba B. Reinforcement learning as an innovative model-based approach: Examples from precision dosing, digital health and computational psychiatry. Front Pharmacol 2022; 13:1094281. [PMID: 36873047 PMCID: PMC9981647 DOI: 10.3389/fphar.2022.1094281] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 12/12/2022] [Indexed: 02/19/2023] Open
Abstract
Model-based approaches are instrumental for successful drug development and use. Anchored within pharmacological principles, through mathematical modeling they contribute to the quantification of drug response variability and enables precision dosing. Reinforcement learning (RL)-a set of computational methods addressing optimization problems as a continuous learning process-shows relevance for precision dosing with high flexibility for dosing rule adaptation and for coping with high dimensional efficacy and/or safety markers, constituting a relevant approach to take advantage of data from digital health technologies. RL can also support contributions to the successful development of digital health applications, recognized as key players of the future healthcare systems, in particular for reducing the burden of non-communicable diseases to society. RL is also pivotal in computational psychiatry-a way to characterize mental dysfunctions in terms of aberrant brain computations-and represents an innovative modeling approach forpsychiatric indications such as depression or substance abuse disorders for which digital therapeutics are foreseen as promising modalities.
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Affiliation(s)
- Benjamin Ribba
- Roche Pharma Research and Early Development (pRED), F. Hoffmann-La Roche Ltd, Basel, Switzerland
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14
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Di Cesare Mannelli L, Palma Esposito F, Sangiovanni E, Pagano E, Mannucci C, Polini B, Ghelardini C, Dell’Agli M, Izzo AA, Calapai G, de Pascale D, Nieri P. Pharmacological Activities of Extracts and Compounds Isolated from Mediterranean Sponge Sources. Pharmaceuticals (Basel) 2021; 14:ph14121329. [PMID: 34959729 PMCID: PMC8715745 DOI: 10.3390/ph14121329] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 12/13/2021] [Accepted: 12/14/2021] [Indexed: 12/11/2022] Open
Abstract
Marine pharmacology is an exciting and growing discipline that blends blue biotechnology and natural compound pharmacology together. Several sea-derived compounds that are approved on the pharmaceutical market were discovered in sponges, marine organisms that are particularly rich in bioactive metabolites. This paper was specifically aimed at reviewing the pharmacological activities of extracts or purified compounds from marine sponges that were collected in the Mediterranean Sea, one of the most biodiverse marine habitats, filling the gap in the literature about the research of natural products from this geographical area. Findings regarding different Mediterranean sponge species were individuated, reporting consistent evidence of efficacy mainly against cancer, infections, inflammatory, and neurological disorders. The sustainable exploitation of Mediterranean sponges as pharmaceutical sources is strongly encouraged to discover new compounds.
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Affiliation(s)
- Lorenzo Di Cesare Mannelli
- Department of Neuroscience, Psychology, Drug Research and Child Health—Neurofarba—Section of Pharmacology and Toxicology, University of Florence, 50139 Florence, Italy;
- Correspondence:
| | - Fortunato Palma Esposito
- Department of Marine Biotechnology, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy; (F.P.E.); (D.d.P.)
| | - Enrico Sangiovanni
- Department of Pharmacological and Biomolecular Sciences, University of Milan, 20133 Milan, Italy; (E.S.); (M.D.)
| | - Ester Pagano
- Department of Pharmacy, School of Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (E.P.); (A.A.I.)
| | - Carmen Mannucci
- Department of Biomedical and Dental Sciences and Morphological and Functional Imaging, University of Messina, 98125 Messina, Italy; (C.M.); (G.C.)
| | - Beatrice Polini
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy; (B.P.); (P.N.)
| | - Carla Ghelardini
- Department of Neuroscience, Psychology, Drug Research and Child Health—Neurofarba—Section of Pharmacology and Toxicology, University of Florence, 50139 Florence, Italy;
| | - Mario Dell’Agli
- Department of Pharmacological and Biomolecular Sciences, University of Milan, 20133 Milan, Italy; (E.S.); (M.D.)
| | - Angelo Antonio Izzo
- Department of Pharmacy, School of Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy; (E.P.); (A.A.I.)
| | - Gioacchino Calapai
- Department of Biomedical and Dental Sciences and Morphological and Functional Imaging, University of Messina, 98125 Messina, Italy; (C.M.); (G.C.)
| | - Donatella de Pascale
- Department of Marine Biotechnology, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy; (F.P.E.); (D.d.P.)
| | - Paola Nieri
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy; (B.P.); (P.N.)
- Interdepartmental Center of Marine Pharmacology (MarinePHARMA), University of Pisa, 56126 Pisa, Italy
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15
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Geerts H, van der Graaf P. Computational Approaches for Supporting Combination Therapy in the Post-Aducanumab Era in Alzheimer’s Disease. J Alzheimers Dis Rep 2021; 5:815-826. [PMID: 34966890 PMCID: PMC8673549 DOI: 10.3233/adr-210039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Accepted: 10/14/2021] [Indexed: 01/25/2023] Open
Abstract
With the approval of aducanumab on the “Accelerated Approval Pathway” and the recognition of amyloid load as a surrogate marker, new successful therapeutic approaches will be driven by combination therapy as was the case in oncology after the launch of immune checkpoint inhibitors. However, the sheer number of therapeutic combinations substantially complicates the search for optimal combinations. Data-driven approaches based on large databases or electronic health records can identify optimal combinations and often using artificial intelligence or machine learning to crunch through many possible combinations but are limited to the pharmacology of existing marketed drugs and are highly dependent upon the quality of the training sets. Knowledge-driven in silico modeling approaches use multi-scale biophysically realistic models of neuroanatomy, physiology, and pathology and can be personalized with individual patient comedications, disease state, and genotypes to create ‘virtual twin patients’. Such models simulate effects on action potential dynamics of anatomically informed neuronal circuits driving functional clinical readouts. Informed by data-driven approaches this knowledge-driven modeling could systematically and quantitatively simulate all possible target combinations for a maximal synergistic effect on a clinically relevant functional outcome. This approach seamlessly integrates pharmacokinetic modeling of different therapeutic modalities. A crucial requirement to constrain the parameters is the access to preferably anonymized individual patient data from completed clinical trials with various selective compounds. We believe that the combination of data- and knowledge driven modeling could be a game changer to find a cure for this devastating disease that affects the most complex organ of the universe.
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Affiliation(s)
- Hugo Geerts
- Certara UK-SimCyp, Canterbury Innovation Centre, University Road, Canterbury, United Kingdom
| | - Piet van der Graaf
- Certara UK-SimCyp, Canterbury Innovation Centre, University Road, Canterbury, United Kingdom
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16
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Aghamiri SS, Amin R, Helikar T. Recent applications of quantitative systems pharmacology and machine learning models across diseases. J Pharmacokinet Pharmacodyn 2021; 49:19-37. [PMID: 34671863 PMCID: PMC8528185 DOI: 10.1007/s10928-021-09790-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 10/07/2021] [Indexed: 12/29/2022]
Abstract
Quantitative systems pharmacology (QSP) is a quantitative and mechanistic platform describing the phenotypic interaction between drugs, biological networks, and disease conditions to predict optimal therapeutic response. In this meta-analysis study, we review the utility of the QSP platform in drug development and therapeutic strategies based on recent publications (2019-2021). We gathered recent original QSP models and described the diversity of their applications based on therapeutic areas, methodologies, software platforms, and functionalities. The collection and investigation of these publications can assist in providing a repository of recent QSP studies to facilitate the discovery and further reusability of QSP models. Our review shows that the largest number of QSP efforts in recent years is in Immuno-Oncology. We also addressed the benefits of integrative approaches in this field by presenting the applications of Machine Learning methods for drug discovery and QSP models. Based on this meta-analysis, we discuss the advantages and limitations of QSP models and propose fields where the QSP approach constitutes a valuable interface for more investigations to tackle complex diseases and improve drug development.
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Affiliation(s)
- Sara Sadat Aghamiri
- Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Rada Amin
- Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, USA.
| | - Tomáš Helikar
- Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, USA.
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17
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Factor Xa inhibitors: critical considerations for clinical development and testing. J Thromb Thrombolysis 2021; 52:397-402. [PMID: 33991266 PMCID: PMC8122197 DOI: 10.1007/s11239-021-02455-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/13/2021] [Indexed: 12/25/2022]
Abstract
The selection of factor (F) X and its activated protease FXa for targeted inhibition to prevent and treat thrombotic conditions is based on an understanding of coagulation biochemistry, sequential steps that occur on tissue factor bearing cells and the interface of coagulation proteins, platelets, mononuclear cells and the nuclear constituents of inflammatory cells. The goal for developing direct oral FXa inhibitors was to achieve rapid, selective, predictable, safe and effective anticoagulation across a broad group of patients expected to derive benefit. The history and development in patient care are exemplars of knowledge, translation and collaboration between the public and private sectors.
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18
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Bloomingdale P, Karelina T, Cirit M, Muldoon SF, Baker J, McCarty WJ, Geerts H, Macha S. Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2021; 10:412-419. [PMID: 33719204 PMCID: PMC8129713 DOI: 10.1002/psp4.12607] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 12/02/2020] [Accepted: 02/03/2021] [Indexed: 11/12/2022]
Abstract
The development and application of quantitative systems pharmacology models in neuroscience have been modest relative to other fields, such as oncology and immunology, which may reflect the complexity of the brain. Technological and methodological advancements have enhanced the quantitative understanding of brain physiology and pathophysiology and the effects of pharmacological interventions. To maximize the knowledge gained from these novel data types, pharmacometrics modelers may need to expand their toolbox to include additional mathematical and statistical frameworks. A session was held at the 10th annual American Conference on Pharmacometrics (ACoP10) to highlight several recent advancements in quantitative and systems neuroscience. In this mini‐review, we provide a brief overview of technological and methodological advancements in the neuroscience therapeutic area that were discussed during the session and how these can be leveraged with quantitative systems pharmacology modeling to enhance our understanding of neurological diseases. Microphysiological systems using human induced pluripotent stem cells (IPSCs), digital biomarkers, and large‐scale imaging offer more clinically relevant experimental datasets, enhanced granularity, and a plethora of data to potentially improve the preclinical‐to‐clinical translation of therapeutics. Network neuroscience methodologies combined with quantitative systems models of neurodegenerative disease could help bridge the gap between cellular and molecular alterations and clinical end points through the integration of information on neural connectomics. Additional topics, such as the neuroimmune system, microbiome, single‐cell transcriptomic technologies, and digital device biomarkers, are discussed in brief.
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Affiliation(s)
- Peter Bloomingdale
- Quantitative Pharmacology and Pharmacometrics, Merck & Co. Inc, Kenilworth, New Jersey, USA
| | | | - Murat Cirit
- Javelin Biotech, Inc, Woburn, Massachusetts, USA
| | - Sarah F Muldoon
- Mathematics Department, CDSE Program, Neuroscience Program, University at Buffalo, SUNY, Buffalo, New York, USA
| | - Justin Baker
- Harvard Medical School, Boston, Massachusetts, USA
| | | | | | - Sreeraj Macha
- Quantitative Pharmacology, Sanofi, Bridgewater, New Jersey, USA
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19
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Koola MM. Alpha7 nicotinic-N-methyl-D-aspartate hypothesis in the treatment of schizophrenia and beyond. Hum Psychopharmacol 2021; 36:1-16. [PMID: 32965756 DOI: 10.1002/hup.2758] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/08/2020] [Accepted: 09/09/2020] [Indexed: 12/12/2022]
Abstract
Development of novel treatments for positive, cognitive, and negative symptoms continue to be a high-priority area of schizophrenia research and a major unmet clinical need. Given that all randomized controlled trials (RCTs) conducted to date failed with one add-on medication/mechanism of action, future RCTs with the same approach are not warranted. Even if the field develops a medication for cognition, others are still needed to treat negative and positive symptoms. Therefore, fixing one domain does not completely solve the problem. Also, targeting the cholinergic system, glutamatergic system, and cholinergic plus alpha7 nicotinic and N-methyl-D-aspartate (NMDA) receptors failed independently. Hence, targeting other less important pathophysiological mechanisms/targets is unlikely to be successful. Meta-analyses of RCTs targeting major pathophysiological mechanisms have found some efficacy signal in schizophrenia; thus, combination treatments with different mechanisms of action may enhance the efficacy signal. The objective of this article is to highlight the importance of conducting RCTs with novel combination treatments in schizophrenia to develop antischizophrenia treatments. Positive RCTs with novel combination treatments that target the alpha7 nicotinic and NMDA receptors simultaneously may lead to a disease-modifying therapeutic armamentarium in schizophrenia. Novel combination treatments that concurrently improve the three domains of psychopathology and several prognostic and theranostic biomarkers may facilitate therapeutic discovery in schizophrenia.
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Affiliation(s)
- Maju Mathew Koola
- Department of Psychiatry and Behavioral Health, Stony Brook University Renaissance School of Medicine, Stony Brook, New York, USA
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20
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Adonias GL, Siljak H, Barros MT, Marchetti N, White M, Balasubramaniam S. Reconfigurable Filtering of Neuro-Spike Communications Using Synthetically Engineered Logic Circuits. Front Comput Neurosci 2020; 14:556628. [PMID: 33178001 PMCID: PMC7593240 DOI: 10.3389/fncom.2020.556628] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 08/28/2020] [Indexed: 01/13/2023] Open
Abstract
High-frequency firing activity can be induced either naturally in a healthy brain as a result of the processing of sensory stimuli or as an uncontrolled synchronous activity characterizing epileptic seizures. As part of this work, we investigate how logic circuits that are engineered in neurons can be used to design spike filters, attenuating high-frequency activity in a neuronal network that can be used to minimize the effects of neurodegenerative disorders such as epilepsy. We propose a reconfigurable filter design built from small neuronal networks that behave as digital logic circuits. We developed a mathematical framework to obtain a transfer function derived from a linearization process of the Hodgkin-Huxley model. Our results suggest that individual gates working as the output of the logic circuits can be used as a reconfigurable filtering technique. Also, as part of the analysis, the analytical model showed similar levels of attenuation in the frequency domain when compared to computational simulations by fine-tuning the synaptic weight. The proposed approach can potentially lead to precise and tunable treatments for neurological conditions that are inspired by communication theory.
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Affiliation(s)
- Geoflly L Adonias
- Telecommunications Software & Systems Group, Waterford Institute of Technology, Waterford, Ireland
| | - Harun Siljak
- CONNECT Centre, Trinity College Dublin, Dublin, Ireland
| | - Michael Taynnan Barros
- CBIG at Biomeditech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom
| | | | - Mark White
- Research, Innovation & Graduate Studies, Waterford Institute of Technology, Waterford, Ireland
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21
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Fang J, Pieper AA, Nussinov R, Lee G, Bekris L, Leverenz JB, Cummings J, Cheng F. Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing. Med Res Rev 2020; 40:2386-2426. [PMID: 32656864 PMCID: PMC7561446 DOI: 10.1002/med.21709] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 06/23/2020] [Accepted: 06/27/2020] [Indexed: 12/16/2022]
Abstract
Following two decades of more than 400 clinical trials centered on the "one drug, one target, one disease" paradigm, there is still no effective disease-modifying therapy for Alzheimer's disease (AD). The inherent complexity of AD may challenge this reductionist strategy. Recent observations and advances in network medicine further indicate that AD likely shares common underlying mechanisms and intermediate pathophenotypes, or endophenotypes, with other diseases. In this review, we consider AD pathobiology, disease comorbidity, pleiotropy, and therapeutic development, and construct relevant endophenotype networks to guide future therapeutic development. Specifically, we discuss six main endophenotype hypotheses in AD: amyloidosis, tauopathy, neuroinflammation, mitochondrial dysfunction, vascular dysfunction, and lysosomal dysfunction. We further consider how this endophenotype network framework can provide advances in computational and experimental strategies for drug-repurposing and identification of new candidate therapeutic strategies for patients suffering from or at risk for AD. We highlight new opportunities for endophenotype-informed, drug discovery in AD, by exploiting multi-omics data. Integration of genomics, transcriptomics, radiomics, pharmacogenomics, and interactomics (protein-protein interactions) are essential for successful drug discovery. We describe experimental technologies for AD drug discovery including human induced pluripotent stem cells, transgenic mouse/rat models, and population-based retrospective case-control studies that may be integrated with multi-omics in a network medicine methodology. In summary, endophenotype-based network medicine methodologies will promote AD therapeutic development that will optimize the usefulness of available data and support deep phenotyping of the patient heterogeneity for personalized medicine in AD.
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Affiliation(s)
- Jiansong Fang
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, China
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Andrew A Pieper
- Harrington Discovery Institute, University Hospital Case Medical Center; Department of Psychiatry, Case Western Reserve University, Geriatric Research Education and Clinical Centers, Louis Stokes Cleveland VAMC, Cleveland, OH 44106, USA
| | - Ruth Nussinov
- Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, MD 21702, USA
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Garam Lee
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA
| | - Lynn Bekris
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
| | - James B. Leverenz
- Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Jeffrey Cummings
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA
- Department of Brain Health, School of Integrated Health Sciences, UNLV, Las Vegas, NV 89154, USA
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
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22
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van der Graaf PH. The Role of the Microbiome in Central Nervous System Clinical Pharmacology: More Than a Gut Feeling. Clin Pharmacol Ther 2020; 108:907-909. [PMID: 33058163 DOI: 10.1002/cpt.2036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 09/02/2020] [Indexed: 12/16/2022]
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23
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Mayburd A. A public-private partnership for the express development of antiviral leads: a perspective view. Expert Opin Drug Discov 2020; 16:23-38. [PMID: 32877233 DOI: 10.1080/17460441.2020.1811676] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
INTRODUCTION The COVID-19 pandemic raises the question of strategic readiness for emergent pathogens. The current case illustrates that the cost of inaction can be higher in the future. The perspective article proposes a dedicated, government-sponsored agency developing anti-viral leads against all potentially dangerous pathogen species. AREAS COVERED The author explores the methods of computational drug screening and in-silico synthesis and proposes a specialized government-sponsored agency focusing on leads and functioning in collaboration with a network of labs, pharma, biotech firms, and academia, in order to test each lead against multiple viral species. The agency will employ artificial intelligence and machine learning tools to cut the costs further. The algorithms are expected to receive continuous feedback from the network of partners conducting the tests. EXPERT OPINION The author proposes a bionic principle, emulating antibody response by producing a combinatorial diversity of high q uality generic antiviral leads, suitable for multiple potentially emerging species. The availability of multiple pre-tested agents and an even greater number of combinations would reduce the impact of the next outbreak. The methodologies developed in this effort are likely to find utility in the design of chronic disease therapeutics.
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Affiliation(s)
- Anatoly Mayburd
- School of Systems Biology, George Mason University , Manassas, USA
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24
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Yoneyama T, Sato S, Sykes A, Fradley R, Stafford S, Bechar S, Howley E, Patel T, Tagawa Y, Moriwaki T, Asahi S. Mechanistic Multilayer Quantitative Model for Nonlinear Pharmacokinetics, Target Occupancy and Pharmacodynamics (PK/TO/PD) Relationship of D-Amino Acid Oxidase Inhibitor, TAK-831 in Mice. Pharm Res 2020; 37:164. [PMID: 32901384 PMCID: PMC7478952 DOI: 10.1007/s11095-020-02893-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 07/24/2020] [Indexed: 02/06/2023]
Abstract
Purpose TAK-831 is a highly selective and potent inhibitor of D-amino acid oxidase (DAAO) currently under clinical development for schizophrenia. In this study, a mechanistic multilayer quantitative model that parsimoniously connects pharmacokinetics (PK), target occupancy (TO) and D-serine concentrations as a pharmacodynamic (PD) readout was established in mice. Methods PK, TO and PD time-profiles were obtained in mice and analyzed by mechanistic binding kinetics model connected with an indirect response model in a step wise fashion. Brain distribution was investigated to elucidate a possible mechanism driving the hysteresis between PK and TO. Results The observed nonlinear PK/TO/PD relationship was well captured by mechanistic modeling framework within a wide dose range of TAK-831 in mice. Remarkably different brain distribution was observed between target and reference regions, suggesting that the target-mediated slow binding kinetics rather than slow penetration through the blood brain barrier caused the observed distinct kinetics between PK and TO. Conclusion A quantitative mechanistic model for concentration- and time-dependent nonlinear PK/TO/PD relationship was established for TAK-831 in mice with accounting for possible rate-determining process. The established mechanistic modeling framework will provide a quantitative means for multilayer biomarker-assisted clinical development in multiple central nervous system indications. Electronic supplementary material The online version of this article (10.1007/s11095-020-02893-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tomoki Yoneyama
- Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Pharmaceutical Company Limited, Fujisawa, Kanagawa, Japan.
| | - Sho Sato
- Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Pharmaceutical Company Limited, Fujisawa, Kanagawa, Japan
| | - Andy Sykes
- Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Cambridge Ltd, Cambridge, UK
| | - Rosa Fradley
- Pharmacology, Takeda Cambridge Ltd, Cambridge, UK
| | | | - Shyam Bechar
- Pharmacology, Takeda Cambridge Ltd, Cambridge, UK
| | | | - Toshal Patel
- Pharmacology, Takeda Cambridge Ltd, Cambridge, UK
| | - Yoshihiko Tagawa
- Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Pharmaceutical Company Limited, Fujisawa, Kanagawa, Japan
| | - Toshiya Moriwaki
- Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Pharmaceutical Company Limited, Fujisawa, Kanagawa, Japan
| | - Satoru Asahi
- Drug Metabolism and Pharmacokinetics Research Laboratories, Takeda Pharmaceutical Company Limited, Fujisawa, Kanagawa, Japan
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25
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Hawkins KG, Casolaro C, Brown JA, Edwards DA, Wikswo JP. The Microbiome and the Gut-Liver-Brain Axis for Central Nervous System Clinical Pharmacology: Challenges in Specifying and Integrating In Vitro and In Silico Models. Clin Pharmacol Ther 2020; 108:929-948. [PMID: 32347548 PMCID: PMC7572575 DOI: 10.1002/cpt.1870] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 04/22/2020] [Indexed: 12/18/2022]
Abstract
The complexity of integrating microbiota into clinical pharmacology, environmental toxicology, and opioid studies arises from bidirectional and multiscale interactions between humans and their many microbiota, notably those of the gut. Hosts and each microbiota are governed by distinct central dogmas, with genetics influencing transcriptomics, proteomics, and metabolomics. Each microbiota's metabolome differentially modulates its own and the host's multi‐omics. Exogenous compounds (e.g., drugs and toxins), often affect host multi‐omics differently than microbiota multi‐omics, shifting the balance between drug efficacy and toxicity. The complexity of the host‐microbiota connection has been informed by current methods of in vitro bacterial cultures and in vivo mouse models, but they fail to elucidate mechanistic details. Together, in vitro organ‐on‐chip microphysiological models, multi‐omics, and in silico computational models have the potential to supplement the established methods to help clinical pharmacologists and environmental toxicologists unravel the myriad of connections between the gut microbiota and host health and disease.
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Affiliation(s)
- Kyle G Hawkins
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA
| | - Caleb Casolaro
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Jacquelyn A Brown
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, USA
| | - David A Edwards
- Department of Anesthesiology and Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - John P Wikswo
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, USA.,Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA
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26
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Geerts H, Spiros A. Learning from amyloid trials in Alzheimer's disease. A virtual patient analysis using a quantitative systems pharmacology approach. Alzheimers Dement 2020; 16:862-872. [PMID: 32255562 PMCID: PMC7983876 DOI: 10.1002/alz.12082] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 01/12/2020] [Accepted: 02/17/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND Many trials of amyloid-modulating agents fail to improve cognitive outcome in Alzheimer's disease despite substantial reduction of amyloid β levels. METHODS We applied a mechanism-based Quantitative Systems Pharmacology model exploring the pharmacodynamic interactions of apolipoprotein E (APOE), Catechol -O -methyl Transferase (COMTVal158Met), and 5-HT transporter (5-HTTLPR) rs25531 genotypes and aducanumab. RESULTS The model predicts large clinical variability. Anticipated placebo differences on Alzheimer's Disease Assessment Scale (ADAS)-COG in the aducanumab ENGAGE and EMERGE ranged from 0.77 worsening to 1.56 points improvement, depending on the genotype-comedication combination. 5-HTTLPR L/L subjects are found to be the most resilient. Virtual patient simulations suggest improvements over placebo between 4% and 20% at the 10 mg/kg dose, depending on the imbalance of the 5-HTTLPR genotype and exposure. In the Phase II PRIME trial, maximal anticipated placebo difference at 10 mg/kg ranges from 0.3 worsening to 5.3 points improvement. DISCUSSION These virtual patient simulations, once validated against clinical data, could lead to better informed future clinical trial designs.
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Affiliation(s)
- Hugo Geerts
- In-Silico Biosciences, Certara-QSP, Berwyn, Pennsylvania, USA
| | - Athan Spiros
- In-Silico Biosciences, Certara-QSP, Berwyn, Pennsylvania, USA
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