Pharmacogenetic Testing: a Tool for Personalized Drug Therapy Optimization
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1: Clinical Pharmacokinetics 1
1: CLINICAL PHARMACOKINETICS 1 General overview: clinical pharmacokinetics, 2 Pharmacokinetics, 4 Drug clearance (CL), 6 Volume of distribution (Vd), 8 The half-life (t½), 10 Oral availability (F), 12 Protein binding (PB), 14 pH and pharmacokinetics, 16 1 Clinical pharmacokinetics General overview General overview: clinical pharmacokinetics 1 The ultimate aim of drug therapy is to achieve effi cacy without toxicity. This involves achieving a plasma concentration (Cp) within the ‘therapeutic window’, i.e. above the min- imal effective concentration (MEC), but below the minimal toxic concentration (MTC). Clinical pharmacokinetics is about all the factors that determine variability in the Cp and its time-course. The various factors are dealt with in subsequent chapters. Ideal therapeutics: effi cacy without toxicity Minimum Toxic Concentration (MTC) Ideal dosing Minimum Effective Concentration (MEC) Drug concentration Time The graph shows a continuous IV infusion at steady state, where the dose-rate is exactly appropriate for the patient’s clearance (CL). Inappropriate dosing Dosing too high in relation to the patient’s CL – toxicity likely Minimum Toxic Concentration (MTC) Minimum Effective Concentration (MEC) Dosing too low in relation to the Drug concentration patient’s CL – drug may be ineffective Time Some reasons for variation in CL Low CL High CL Normal variation Normal variation Renal impairment Increased renal blood fl ow Genetic poor metabolism Genetic hypermetabolism Liver impairment Enzyme induction Enzyme inhibition Old age/neonate 2 General overview Clinical Pharmacokinetics Pharmacokinetic factors determining ideal therapeutics If immediate effect is needed, a loading dose (LD) must be given to achieve a desired 1 concentration. The LD is determined by the volume of distribution (Vd). -
Mechanisms and Strategies to Overcome Multiple Drug Resistance in Cancer
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector FEBS Letters 580 (2006) 2903–2909 Minireview Mechanisms and strategies to overcome multiple drug resistance in cancer Tomris Ozben* Akdeniz University, Faculty of Medicine, Department of Biochemistry, 07070 Antalya, Turkey Received 30 January 2006; accepted 9 February 2006 Available online 17 February 2006 Edited by Horst Feldmann The cytotoxic drugs that are most frequently associated with Abstract One of the major problems in chemotherapy is multi- drug resistance (MDR) against anticancer drugs. ATP-binding MDR are hydrophobic, amphipathic natural products, such as cassette (ABC) transporters are a family of proteins that medi- the taxanes (paclitaxel and docetaxel), vinca alkaloids (vinorel- ate MDR via ATP-dependent drug efflux pumps. Many MDR bine, vincristine, and vinblastine), anthracyclines (doxorubicin, inhibitors have been identified, but none of them have been pro- daunorubicin, and epirubicin), epipodophyllotoxins (etoposide ven clinically useful without side effects. Efforts continue to dis- and teniposide), antimetabolites (methorexate, fluorouracil, cover not toxic MDR inhibitors which lack pharmacokinetic cytosar, 5-azacytosine, 6-mercaptopurine, and gemcitabine) interactions with anticancer drugs. Novel approaches have also topotecan, dactinomycin, and mitomycin C [4,6–8]. been designed to inhibit or circumvent MDR. In this review, Overexpression of ATP-binding cassette (ABC) transporters the structure and function of ABC transporters and development has been shown to be responsible for MDR [5]. Therefore eluci- of MDR inhibitors are described briefly including various ap- dation of the structure and function for each ABC transporter is proaches to suppress MDR mechanisms. -
Pharmacomicrobiomics: a Novel Route Towards Personalized Medicine?
Protein Cell 2018, 9(5):432–445 https://doi.org/10.1007/s13238-018-0547-2 Protein & Cell REVIEW Pharmacomicrobiomics: a novel route towards personalized medicine? Marwah Doestzada1,2, Arnau Vich Vila1,3, Alexandra Zhernakova1, Debby P. Y. Koonen2, Rinse K. Weersma3, Daan J. Touw4, Folkert Kuipers2,5, Cisca Wijmenga1,6, Jingyuan Fu1,2& 1 Departments of Genetics, University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, The Netherlands 2 Departments of Paediatrics, University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, The Netherlands 3 Departments of Gastroenterology & Hepatology, University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, The Netherlands 4 Departments of Clinical Pharmacy & Pharmacology, University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, The Netherlands Cell 5 Departments of Laboratory Medicine, University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, & The Netherlands 6 K.G. Jebsen Coeliac Disease Research Centre, Department of Immunology, University of Oslo, P.O. Box 1072, Blindern, 0316 Oslo, Norway & Correspondence: [email protected] (J. Fu) Received March 5, 2018 Accepted April 16, 2018 Protein ABSTRACT INTRODUCTION Inter-individual heterogeneity in drug response is a Individual responses to a specific drug vary greatly in terms serious problem that affects the patient’s wellbeing and of both efficacy and toxicity. It has been reported that poses enormous clinical and financial burdens on a response rates to common drugs for the treatment of a wide societal level. Pharmacogenomics has been at the variety of diseases fall typically in the range of 50%–75%, forefront of research into the impact of individual indicating that up to half of patients are seeing no benefit genetic background on drug response variability or drug (Spear et al., 2001). -
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. -
Antibiotic Resistance: from the Bench to Patients
antibiotics Editorial Antibiotic Resistance: From the Bench to Patients Márió Gajdács 1,* and Fernando Albericio 2,3 1 Department of Pharmacodynamics and Biopharmacy, Faculty of Pharmacy, University of Szeged, Dóm tér 10., 6720 Szeged, Hungary 2 School of Chemistry, University of KwaZulu-Natal, Durban 4001, South Africa 3 Department of Organic Chemistry, University of Barcelona, CIBER-BBN, 08028 Barcelona, Spain * Correspondence: [email protected]; Tel.: +36-62-341-330 Received: 20 August 2019; Accepted: 26 August 2019; Published: 27 August 2019 The discovery and subsequent clinical introduction of antibiotics is one of the most important game-changers in the history of medicine [1]. These drugs have saved millions of lives from infections that would previously have been fatal, and later, they allowed for the introduction of surgical interventions, organ transplantation, care of premature infants, and cancer chemotherapy [2]. Nevertheless, the therapy of bacterial infections is becoming less and less straightforward due to the emergence of multidrug resistance (MDR) in these pathogens [3]. Direct consequences of antibiotic resistance include delays in the onset of the appropriate (effective) antimicrobial therapy, the need to use older, more toxic antibiotics (e.g., colistin) with a disadvantageous side-effect profile, longer hospital stays, and an increasing burden on the healthcare infrastructure; overall, a decrease in the quality-of-life (QoL) and an increase in the mortality rate of the affected patients [4,5]. To highlight the severity of the issue, several international declarations have been published to call governments around the globe to take action on antimicrobial resistance [6–9]. Since the 1980s, pharmaceutical companies have slowly turned away from antimicrobial research and towards the drug therapy of chronic non-communicable diseases [10,11]. -
Narrow Therapeutic Index
Therapeutic Drug Monitoring Some drugs have a narrow therapeutic index, which means that there is only a small difference between the minimum effective concentrations and the minimum toxic concentrations in the blood. With such drugs, small increases in dose or in blood/serum concentrations could lead to toxic effects. Therapeutic drug monitoring may help to optimise treatment in cases where there is a firm relationship between the toxic/therapeutic effects and drug concentrations in whole blood/serum. A therapeutic interval has been defined for the drugs in the following tables. This is the minimum effective and maximum safe concentration for compliant patients, on stabilised regimens. Levels within these limits should prove satisfactory in most cases. Whole blood or serum drug concentrations are useful for determining patient compliance or for assessing whether or not: 1. adequate concentrations are being achieved or, 2. potentially toxic concentrations are being reached. Depending on clinical conditions, dosage adjustments may be needed when levels are outside the therapeutic interval. Therapeutic drug monitoring can also be useful when changes are made to other medications that could affect serum or whole blood concentrations and lead to a reduction in effectiveness or increased toxicity. Although plasma drug concentrations and the therapeutic interval are useful in evaluating drug therapy, they should not be the only criteria on which treatment is based. Always remember to treat the patient, not the level. Drug concentrations in serum or whole blood are only meaningful if the correct procedures are followed regarding the timing of specimens and selection of sample tube. It is vitally important to note the exact time the sample is taken and when each dose of the drug is given. -
GENOME GENERATION Glossary
GENOME GENERATION Glossary Chromosome An organism’s DNA is packaged into chromosomes. Humans have 23 pairs of chromosomesincluding one pair of sex chromosomes. Women have two X chromosomes and men have one X and one Y chromosome. Dominant (see also recessive) Genes come in pairs. A dominant form of a gene is the “stronger” version that will be expressed. Therefore if someone has one dominant and one recessive form of a gene, only the characteristics of the dominant form will appear. DNA DNA is the long molecule that contains the genetic instructions for nearly all living things. Two strands of DNA are twisted together into a double helix. The DNA code is made up of four chemical letters (A, C, G and T) which are commonly referred to as bases or nucleotides. Gene A gene is a section of DNA that is the code for a specific biological component, usually a protein. Each gene may have several alternative forms. Each of us has two copies of most of our genes, one copy inherited from each parent. Most of our traits are the result of the combined effects of a number of different genes. Very few traits are the result of just one gene. Genetic sequence The precise order of letters (bases) in a section of DNA. Genome A genome is the complete DNA instructions for an organism. The human genome contains 3 billion DNA letters and approximately 23,000 genes. Genomics Genomics is the study of genomes. This includes not only the DNA sequence itself, but also an understanding of the function and regulation of genes both individually and in combination. -
Narrow Therapeutic Index Drugs: a Clinical Pharmacological Consideration to Flecainide Juan Tamargo, Jean-Yves Le Heuzey, Phillipe Mabo
Narrow therapeutic index drugs: a clinical pharmacological consideration to flecainide Juan Tamargo, Jean-Yves Le Heuzey, Phillipe Mabo To cite this version: Juan Tamargo, Jean-Yves Le Heuzey, Phillipe Mabo. Narrow therapeutic index drugs: a clinical pharmacological consideration to flecainide. European Journal of Clinical Pharmacology, Springer Verlag, 2015, 71 (5), pp.549-567. 10.1007/s00228-015-1832-0. hal-01143095 HAL Id: hal-01143095 https://hal-univ-rennes1.archives-ouvertes.fr/hal-01143095 Submitted on 16 Apr 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Eur J Clin Pharmacol (2015) 71:549–567 DOI 10.1007/s00228-015-1832-0 REVIEW ARTICLE Narrow therapeutic index drugs: a clinical pharmacological consideration to flecainide Juan Tamargo & Jean-Yves Le Heuzey & Phillipe Mabo Received: 5 December 2014 /Accepted: 4 March 2015 /Published online: 15 April 2015 # The Author(s) 2015. This article is published with open access at Springerlink.com Abstract specify flecainide as an NTID. The literature review demon- Purpose The therapeutic index (TI) is the range of doses at strated that flecainide displays NTID characteristics including which a medication is effective without unacceptable adverse a steep drug dose–response relationship for safety and effica- events. -
Plague Plague
Disease Planning Guide - Plague Mass Post Exposure Prophylaxis I. Disease-specific guidance: The following guide should only be used in events where a plague epidemic has been identified, an Emergency Use Authorization from the Food and Drug Administration has been issued and a state and local emergency declaration has been issued by the proper authorities. Model Standing Order – Pg 1 Clients will arrive at dispensing sites with a voucher indicating which medication, if any, they should receive. Specific guidance related to dispensing is shown in red . Model Standing Order – Pg 2 Clients that present this voucher will not receive medication for the individual named on the form. Dispensers may collect “Do Not Dispense Medication” vouchers for records purposes. Model Standing Order – Pg 3 II. PERSONS FOR WHOM PROPHYLAXIS MAY BE ORDERED Persons who have a confirmed or suspect exposure to Yersinia pestis, the causative agent of plague, as determined by the local or State Health Officer. Table 1: Recommended Post-Exposure Prophylaxis for Inhalational Plague Patient Category Therapy Recommendation Duration 10 days Adults Doxycycline , 100 mg PO BID or Ciprofloxacin , 500 mg PO BID 10 days Ciprofloxacin , 15 mg/kg PO BID, max 500 mg/dose or Doxycycline : >45 kg: 100 mg PO BID Children <45 kg: 2.2 mg/kg PO BID ***************************************** If susceptibility to penicillin has been confirmed: Amoxicillin : >20 kg: 500 mg PO TID <20 kg: 80 mg/kg/day PO divided TID 10 days Doxycycline , 100 mg PO BID or Pregnant women Ciprofloxacin , 500 mg PO BID ***************************************** If susceptibility to penicillin has been confirmed: Amoxicillin 500 mg PO TID 10 days Immunocompromised Doxycycline , 100 mg PO BID or Ciprofloxacin , 500 mg PO BID Adapted from: Working Group on Civilian Biodefense. -
Antibiotic Resistance in Plant-Pathogenic Bacteria
PY56CH08-Sundin ARI 23 May 2018 12:16 Annual Review of Phytopathology Antibiotic Resistance in Plant-Pathogenic Bacteria George W. Sundin1 and Nian Wang2 1Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, Michigan 48824, USA; email: [email protected] 2Citrus Research and Education Center, Department of Microbiology and Cell Science, Institute of Food and Agricultural Sciences, University of Florida, Lake Alfred, Florida 33850, USA Annu. Rev. Phytopathol. 2018. 56:8.1–8.20 Keywords The Annual Review of Phytopathology is online at kasugamycin, oxytetracycline, streptomycin, resistome phyto.annualreviews.org https://doi.org/10.1146/annurev-phyto-080417- Abstract 045946 Antibiotics have been used for the management of relatively few bacterial Copyright c 2018 by Annual Reviews. plant diseases and are largely restricted to high-value fruit crops because of Access provided by INSEAD on 06/01/18. For personal use only. All rights reserved the expense involved. Antibiotic resistance in plant-pathogenic bacteria has Annu. Rev. Phytopathol. 2018.56. Downloaded from www.annualreviews.org become a problem in pathosystems where these antibiotics have been used for many years. Where the genetic basis for resistance has been examined, antibiotic resistance in plant pathogens has most often evolved through the acquisition of a resistance determinant via horizontal gene transfer. For ex- ample, the strAB streptomycin-resistance genes occur in Erwinia amylovora, Pseudomonas syringae,andXanthomonas campestris, and these genes have pre- sumably been acquired from nonpathogenic epiphytic bacteria colocated on plant hosts under antibiotic selection. We currently lack knowledge of the effect of the microbiome of commensal organisms on the potential of plant pathogens to evolve antibiotic resistance. -
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). -
Pharmacogenomic Biomarkers in Docetaxel Treatment of Prostate Cancer: from Discovery to Implementation
G C A T T A C G G C A T genes Review Pharmacogenomic Biomarkers in Docetaxel Treatment of Prostate Cancer: From Discovery to Implementation Reka Varnai 1,2, Leena M. Koskinen 3, Laura E. Mäntylä 3, Istvan Szabo 4,5, Liesel M. FitzGerald 6 and Csilla Sipeky 3,* 1 Department of Primary Health Care, University of Pécs, Rákóczi u 2, H-7623 Pécs, Hungary 2 Faculty of Health Sciences, Doctoral School of Health Sciences, University of Pécs, Vörösmarty u 4, H-7621 Pécs, Hungary 3 Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520 Turku, Finland 4 Institute of Sport Sciences and Physical Education, University of Pécs, Ifjúság útja 6, H-7624 Pécs, Hungary 5 Faculty of Sciences, Doctoral School of Biology and Sportbiology, University of Pécs, Ifjúság útja 6, H-7624 Pécs, Hungary 6 Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania 7000, Australia * Correspondence: csilla.sipeky@utu.fi Received: 17 June 2019; Accepted: 5 August 2019; Published: 8 August 2019 Abstract: Prostate cancer is the fifth leading cause of male cancer death worldwide. Although docetaxel chemotherapy has been used for more than fifteen years to treat metastatic castration resistant prostate cancer, the high inter-individual variability of treatment efficacy and toxicity is still not well understood. Since prostate cancer has a high heritability, inherited biomarkers of the genomic signature may be appropriate tools to guide treatment. In this review, we provide an extensive overview and discuss the current state of the art of pharmacogenomic biomarkers modulating docetaxel treatment of prostate cancer. This includes (1) research studies with a focus on germline genomic biomarkers, (2) clinical trials including a range of genetic signatures, and (3) their implementation in treatment guidelines.