Quantitative and Systems Pharmacology in the Post-Genomic Era: New Approaches to Discovering Drugs and Understanding Therapeutic Mechanisms
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Functional Selectivity and Classical Concepts of Quantitative Pharmacology
JPET Fast Forward. Published on June 27, 2006 as DOI: 10.1124/jpet.106.104463 JPET ThisFast article Forward. has not been Published copyedited andon formatted.June 27, The 2006 final versionas DOI:10.1124/jpet.106.104463 may differ from this version. JPET #104463 PiP Title Page Functional selectivity and classical concepts of quantitative pharmacology Jonathan D. Urban, William P. Clarke, Mark von Zastrow, David E. Nichols, Brian Kobilka, Harel Weinstein, Jonathan A. Javitch, Bryan L. Roth, Arthur Christopoulos Patrick M. Sexton, Keith J. Miller, Michael Spedding, Richard B. Mailman Downloaded from Curriculum in Toxicology (JDU, RBM) and Departments of Pharmacology, Psychiatry Medicinal Chemistry (BLR, RBM), and Neurology (RBM), University of North Carolina, Chapel Hill, NC Department of Pharmacology, University of Texas Health Science Center, San Antonio, jpet.aspetjournals.org TX (WPC) Departments of Psychiatry and Cellular and Molecular Pharmacology, University of California, San Francisco, CA (MvZ) at ASPET Journals on September 25, 2021 Department of Medicinal Chemistry and Molecular Pharmacology, School of Pharmacy and Pharmaceutical Sciences, Purdue University, West Lafayette, IN (DEN) Department of Molecular and Cellular Physiology, Stanford University, Palo Alto, CA Department of Physiology and Biophysics, and Institute for Computational Biomedicine, Weill Medical College of Cornell University, New York, NY (HW) Center for Molecular Recognition, and Departments of Psychiatry and Pharmacology, Columbia University College of Physicians and Surgeons, New York, NY (JJ) Department of Pharmacology, Monash University, Clayton, Victoria, Australia (AC, PMS) Obesity Department, Pharmaceutical Research Institute, Bristol-Myers Squibb, Princeton, NJ (KJM) Institute de Recherches Servier, Suresnes 92150, France MS) 1 Copyright 2006 by the American Society for Pharmacology and Experimental Therapeutics. -
Pharmacogenetic Testing: a Tool for Personalized Drug Therapy Optimization
pharmaceutics Review Pharmacogenetic Testing: A Tool for Personalized Drug Therapy Optimization Kristina A. Malsagova 1,* , Tatyana V. Butkova 1 , Arthur T. Kopylov 1 , Alexander A. Izotov 1, Natalia V. Potoldykova 2, Dmitry V. Enikeev 2, Vagarshak Grigoryan 2, Alexander Tarasov 3, Alexander A. Stepanov 1 and Anna L. Kaysheva 1 1 Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; [email protected] (T.V.B.); [email protected] (A.T.K.); [email protected] (A.A.I.); [email protected] (A.A.S.); [email protected] (A.L.K.) 2 Institute of Urology and Reproductive Health, Sechenov University, 119992 Moscow, Russia; [email protected] (N.V.P.); [email protected] (D.V.E.); [email protected] (V.G.) 3 Institute of Linguistics and Intercultural Communication, Sechenov University, 119992 Moscow, Russia; [email protected] * Correspondence: [email protected]; Tel.: +7-499-764-9878 Received: 2 November 2020; Accepted: 17 December 2020; Published: 19 December 2020 Abstract: Pharmacogenomics is a study of how the genome background is associated with drug resistance and how therapy strategy can be modified for a certain person to achieve benefit. The pharmacogenomics (PGx) testing becomes of great opportunity for physicians to make the proper decision regarding each non-trivial patient that does not respond to therapy. Although pharmacogenomics has become of growing interest to the healthcare market during the past five to ten years the exact mechanisms linking the genetic polymorphisms and observable responses to drug therapy are not always clear. Therefore, the success of PGx testing depends on the physician’s ability to understand the obtained results in a standardized way for each particular patient. -
Emergency Use Authorization (EUA) for Bamlanivimab 700 Mg and Etesevimab 1400 Mg IV Administered Together Center for Drug Evaluation and Research (CDER) Review
________________________________________________________________ Emergency Use Authorization (EUA) for Bamlanivimab 700 mg and Etesevimab 1400 mg IV Administered Together Center for Drug Evaluation and Research (CDER) Review Identifying Information Application Type (EUA or Pre-EUA) EUA If EUA, designate whether pre-event or intra-event EUA request. 1 EUA Application Number(s) EUA 000094 Sponsor (entity requesting EUA or Eli Lilly and Company pre-EUA consideration), point of Christine Phillips, PhD, RAC contact, address, phone number, fax Advisor, Global Regulatory Affairs - NA (b) (6) number, email address Mobile: Email: [email protected] Manufacturer, if different from Eli Lilly and Company Sponsor Submission Date(s) November 16, 2020 Receipt Date(s) November 16, 2020 OND Division / Office Division of Antivirals/Office of Infectious Diseases Reviewer Name(s)/Discipline(s) Natalie Pica, MD, PhD – Clinical Reviewer Wendy Carter, DO – Cross Discipline Team Lead Michael Thomson, PhD – Clinical Virology Reviewer Jules O’Rear, PhD – Clinical Virology Team Lead Daniel Rubin, PhD – Statistics Reviewer Thamban Valappil, PhD – Statistics Team Lead Dionne Price, PhD – Director, Division of Biometrics IV Jason Moore, PharmD – Clinical Pharmacology Reviewer Su-Young Choi PharmD, PhD – Clinical Pharmacology Team Lead Kellie Reynolds, PharmD – Division Director, DIDP Ye Xiong, PhD – Pharmacometrics Reviewer Justin Earp, PhD – Pharmacometrics Team Lead Yaning Wang, PhD – Division Director, DPM 1 If a Pre-EUA is in existence at the time -
A Brief View of Molecular Modeling Approaches to P2 Receptors Anael V.P
Chapter A Brief View of Molecular Modeling Approaches to P2 Receptors Anael V.P. Alberto, Lucianna H.S. Santos, Rafael Ferreira, Dinarte N.M. Ferreira and Luiz A. Alves Abstract Purinergic receptors are a class of receptors distributed into two groups, P1 and P2. P1 receptors are activated by nucleosides, like adenosine, while nucleotides active P2 receptors. In turn, P2 receptors comprise two families, metabotropic P2Y and ionotropic P2X. P2Y receptors consist in eight members, namely, P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12, P2Y13, and P2Y14, described in mammals, while P2X includes seven members, numbered P2X1 to P2X7. These receptors have been described as expressed in practically all cells studied to date. In this context, P2 receptors are suggested as participating in certain diseases. The general approach applied in the discovery of new drugs is expensive and lengthy. Alternatively, in the last 20 years, molecular modeling has emerged as an exciting tool for the design of new drugs, in less time and at low costs. These tools allow for in silico testing of thousands of molecules against a target protein, as well as toxicity, absorption, distribution, metabolism, and constant affinity predictions of a given interaction. Thus, molecular modeling algorithms emerge as an increasingly important tool for the design of drugs targeting purinergic receptors as therapeutic targets of many diseases, including cancer, pain, inflammation, cardiovascular, and endocrine conditions. Keywords: molecular modeling, molecular dynamics, virtual screening, homology modeling, drug discovery, P2X receptors, P2Y receptors 1. Introduction Purinergic receptors are a class of transmembrane proteins activated by extracellular nucleotides and nucleosides. They consist in the P1 receptor (mainly activated by adenosine) and P2 receptors distributed into two families, P2Y (G protein-coupled receptors) and P2X (ionotropic receptor). -
Hierarchical Mechanistic Modelling of Clinical Pharmacokinetic Data
Hierarchical mechanistic modelling of clinical pharmacokinetic data A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Medical and Human Sciences 2015 Thierry Wendling Manchester Pharmacy School Contents List of Figures ........................................................................................................ 6 List of Tables .......................................................................................................... 9 List of abbreviations ............................................................................................ 10 Abstract ................................................................................................................ 13 Declaration ........................................................................................................... 14 Copyright ............................................................................................................. 14 Acknowledgements .............................................................................................. 15 Chapter 1: General introduction ...................................................................... 16 1.1. Modelling and simulation in drug development ........................................ 17 1.1.1. The drug development process .......................................................... 17 1.1.2. The role of pharmacokinetic and pharmacodynamic modelling in drug development .................................................................................................. -
Current Screening Methodologies in Drug Discovery for Selected Human Diseases
marine drugs Review Current Screening Methodologies in Drug Discovery for Selected Human Diseases Olga Maria Lage 1,2,*, María C. Ramos 3, Rita Calisto 1,2, Eduarda Almeida 1,2, Vitor Vasconcelos 1,2 ID and Francisca Vicente 3 1 Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre s/nº 4169-007 Porto, Portugal; [email protected] (R.C.); [email protected] (E.A.); [email protected] (V.V.) 2 CIIMAR/CIMAR–Centro Interdisciplinar de Investigação Marinha e Ambiental–Universidade do Porto, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, S/N, 4450-208 Matosinhos, Portugal 3 Fundación MEDINA, Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía, Parque Tecnológico de Ciencias de la Salud, 18016 Granada, Spain; [email protected] (M.C.R.); [email protected] (F.V.) * Correspondence: [email protected]; Tel.: +351-22-0402724; Fax.: +351-22-0402799 Received: 7 August 2018; Accepted: 11 August 2018; Published: 14 August 2018 Abstract: The increase of many deadly diseases like infections by multidrug-resistant bacteria implies re-inventing the wheel on drug discovery. A better comprehension of the metabolisms and regulation of diseases, the increase in knowledge based on the study of disease-born microorganisms’ genomes, the development of more representative disease models and improvement of techniques, technologies, and computation applied to biology are advances that will foster drug discovery in upcoming years. In this paper, several aspects of current methodologies for drug discovery of antibacterial and antifungals, anti-tropical diseases, antibiofilm and antiquorum sensing, anticancer and neuroprotectors are considered. -
Application of Pharmacometric Methods to Improve Pediatric Drug Development
Virginia Commonwealth University VCU Scholars Compass Theses and Dissertations Graduate School 2011 Application of Pharmacometric Methods to Improve Pediatric Drug Development Mallika Lala Virginia Commonwealth University Follow this and additional works at: https://scholarscompass.vcu.edu/etd Part of the Pharmacy and Pharmaceutical Sciences Commons © The Author Downloaded from https://scholarscompass.vcu.edu/etd/2467 This Dissertation is brought to you for free and open access by the Graduate School at VCU Scholars Compass. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of VCU Scholars Compass. For more information, please contact [email protected]. School of Pharmacy Virginia Commonwealth University This is to certify that the dissertation prepared by Mallika A. Lala entitled APPLICATION OF PHARMACOMETRIC METHODS TO IMPROVE PEDIATRIC DRUG DEVELOPMENT has been approved by her committee as satisfactory completion of the dissertation requirement for the degree of Doctor of Philosophy (Ph.D.) Jogarao V.S. Gobburu, FDA and F. Douglas Boudinot, School of Pharmacy Jurgen Venitz, School of Pharmacy Patricia W. Slattum, School of Pharmacy D’arcy P. Mays, College of Humanities and Sciences Susanna Wu-Pong, Graduate Program Director, School of Pharmacy Victor A. Yanchick, Dean, School of Pharmacy Dr. F. Douglas Boudinot, Dean of the Graduate School May 9th, 2011 i © Mallika A. Lala 2011 All Rights Reserved ii APPLICATION OF PHARMACOMETRIC METHODS TO IMPROVE PEDIATRIC DRUG DEVELOPMENT A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. by MALLIKA A. LALA Bachelor of Pharmaceutical Science, UICT, India, 2006 Ph.D. -
Drug Development
DRUG DEVELOPMENT www.acuteleuk.org Drug Development Process Only about 2% of substances evaluated in early research make it to the market as new medicines Number of drugs in the R&D pipeline Number of drugs in the R&D pipeline worldwide 2019 vs. 2020, by development phase Source: https://www.statista.com/ A minimum of a 10-year plan It takes over 10 years and on average costs between €400 million and €1.5 billion before a new medicine can be made available to patients and reimbursement starts Drug development means … What is the rationale to initiate drug development ? • Scientific and Intellectual Property – How does the drug work? • Molecule structure and properties • Mechanism of action • Biological activity (bioassays, drug/target interaction, affinity, specificity,…) – What data support the approach? • Literature validation • In-house preclinical/clinical data – Who owns the intellectual property? What is the rationale to initiate drug development ? • Disease overview and unmet medical need – What is known about disease pathogenesis (translational medicine)? – Where in the disease process should drug enter? Greatest unmet need? – Is this disease part of a disease family? If so which fits best with drug and regulatory history? Is there an orphan approach? – Is this disease field crowded? – Has the indication been clinically studied before (in drug studies)? – What is the event rate for target medical problems? (Make the statisticians happy) – Are there “approvable” endpoints for the unmet needs? – If not, what endpoints seem reasonable: -
Page | 1 Tuesday 7 June 14:00-18:00 Registration at the Conference
Tuesday 7 June 14:00-18:00 Registration at the Conference Venue 19:30-21:00 Welcome reception Wednesday 8 June 08:00-08:45 Registration 08:45-09:00 Welcome and Introduction Chair: Oscar Della Pasqua, 09:00-10:20 Immune response to drug treatment and immunotherapy Dinesh De Alwis A biological perspective on immune response to drug treatment 09:00-09:40 Nigel Klein (intended and unintended effects) Intricate PK and PD for the novel immunocytokine CEA-IL2v and their 09:40-10:00 Hans Peter Grimm pre-clinical to clinical translation Investigation of anti-CTLA-4 immuno-oncology therapy through a 10:00-10:20 Kirill Peskov quantitative systems pharmacology model 10:20-11:40 Coffee break, Poster and Software session I Posters in Group I (with poster numbers starting with I-) are accompanied by their presenter 11:40-12:20 Systems pharmacology Chair: Charlotte Kloft 11:40-12:00 Kapil Gadkar A Six-Stage Workflow for Robust Application of Systems Pharmacology The zebrafish as model for translational systems pharmacology: 12:00-12:20 Rob van Wijk expanding the allometric scale in vertebrates with five orders of magnitude 12:20-13:50 Lunch Chair: Leon Aarons, Shasha 13:50-15:05 Growth (I) Jumbe Introduction to the Gates' Healthy Birth, Growth & Development 13:50-14:05 Shasha Jumbe knowledge integration project 14:05-14:45 Louise Ryan Trajectory modelling based on early childhood longitudinal growth data Page | 1 Determinants for physical growth patterns in low- and middle-income 14:45-15:05 Niclas Jonsson countries 15:05-15:10 Announcement of WCoP 2016 -
Diet As a Modulator of Intestinal Microbiota in Rheumatoid Arthritis
nutrients Review Diet as a Modulator of Intestinal Microbiota in Rheumatoid Arthritis Eduardo Dourado 1,2 , Margarida Ferro 3 , Catarina Sousa Guerreiro 3,4 and João Eurico Fonseca 1,2,* 1 Serviço de Reumatologia e Doenças Ósseas Metabólicas, Centro Hospitalar Universitário Lisboa Norte, Centro Académico de Medicina de Lisboa (CAML), 1649-028 Lisboa, Portugal; [email protected] 2 Unidade de Investigação em Reumatologia, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, CAML, 1649-028 Lisboa, Portugal 3 Laboratório de Nutrição, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal; [email protected] (M.F.); [email protected] (C.S.G.) 4 Instituto de Saúde Ambiental, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal * Correspondence: [email protected] Received: 28 September 2020; Accepted: 12 November 2020; Published: 14 November 2020 Abstract: Rheumatoid arthritis (RA) is a chronic immune-driven inflammatory disease characterised by synovial inflammation, leading to progressive cartilage and bone destruction, impacting patients’ functional capacity and quality of life. Patients with RA have significant differences in gut microbiota composition when compared to controls. Intestinal dysbiosis influences the intestinal barrier strength, integrity and function, and diet is considered the main environmental factor impacting gut microbiota. Over the last few years, researchers have focused on the influence of single components of the diet in the modulation of intestinal microbiota in RA rather than whole dietary patterns. In this review, we focus on how the Mediterranean diet (MD), a whole dietary pattern, could possibly act as an adjuvant therapeutic approach, modulating intestinal microbiota and intestinal barrier function in order to improve RA-related outcomes. -
Proof of Concept: Network and Systems Biology Approaches Aid in the Discovery of Potent Anticancer Drug Combinations
Published OnlineFirst November 1, 2010; DOI: 10.1158/1535-7163.MCT-10-0642 Molecular Cancer Review Therapeutics Proof of Concept: Network and Systems Biology Approaches Aid in the Discovery of Potent Anticancer Drug Combinations Asfar S. Azmi1, Zhiwei Wang1, Philip A. Philip2, Ramzi M. Mohammad2, and Fazlul H. Sarkar1 Abstract Cancer therapies that target key molecules have not fulfilled expected promises for most common malignancies. Major challenges include the incomplete understanding and validation of these targets in patients, the multiplicity and complexity of genetic and epigenetic changes in the majority of cancers, and the redundancies and cross-talk found in key signaling pathways. Collectively, the uses of single-pathway targeted approaches are not effective therapies for human malignances. To overcome these barriers, it is important to understand the molecular cross-talk among key signaling pathways and how they may be altered by targeted agents. Innovative approaches are needed, such as understanding the global physio- logic environment of target proteins and the effects of modifying them without losing key molecular details. Such strategies will aid the design of novel therapeutics and their combinations against multi- faceted diseases, in which efficacious combination therapies will focus on altering multiple pathways rather than single proteins. Integrated network modeling and systems biology have emerged as powerful tools benefiting our understanding of drug mechanisms of action in real time. This review highlights the significance of the network and systems biology–based strategy and presents a proof of concept recently validated in our laboratory using the example of a combination treatment of oxaliplatin and the MDM2 inhibitor MI-219 in genetically complex and incurable pancreatic adenocarcinoma. -
Drug-Gut Microbiota Interactions: Implications for Neuropharmacology Author(S) Walsh, Jacinta; Griffin, Brendan T.; Clarke, Gerard; Hyland, Niall P
UCC Library and UCC researchers have made this item openly available. Please let us know how this has helped you. Thanks! Title Drug-gut microbiota interactions: implications for neuropharmacology Author(s) Walsh, Jacinta; Griffin, Brendan T.; Clarke, Gerard; Hyland, Niall P. Publication date 2018-05-21 Original citation Walsh, J., Griffin, B. T., Clarke, G. and Hyland, N. P. (2018) 'Drug-gut microbiota interactions: implications for neuropharmacology', British Journal of Pharmacology. doi:10.1111/bph.14366 Type of publication Article (peer-reviewed) Link to publisher's http://dx.doi.org/10.1111/bph.14366 version Access to the full text of the published version may require a subscription. Rights © 2018, British Pharmacological Society. All rights reserved. Published by John Wiley & Sons Ltd. This is the peer reviewed version of the following article: Walsh, J., Griffin, B. T., Clarke, G. and Hyland, N. P. (2018) 'Drug-gut microbiota interactions: implications for neuropharmacology', British Journal of Pharmacology. doi:10.1111/bph.14366, which has been published in final form at https://doi.org/10.1111/bph.14366. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Embargo information Access to this article is restricted until 12 months after publication by request of the publisher. Embargo lift date 2019-05-21 Item downloaded http://hdl.handle.net/10468/6243 from Downloaded on 2021-10-02T02:32:36Z Drug-Gut Microbiota Interactions: Implications for Neuropharmacology Walsh, Jacinta 1,4, Griffin, Brendan T. 2,4, Clarke, Gerard 3,4*, Hyland, Niall P. 1,4 1 Department of Pharmacology and Therapeutics, University College Cork, 2 School of Pharmacy, University College Cork, 3 Department of Psychiatry and Neurobehavioural Science, University College Cork, 4 APC Microbiome Ireland, University College Cork.