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Europeanization and Globalization Nada Bodiroga-Vukobrat Daniel Rukavina Krešimir Pavelić Gerald G Sander Editors Personalized Medicine A New Medical and Social Challenge Europeanization and Globalization Volume Series editors Nada Bodiroga-Vukobrat Rijeka, Croatia Sinisˇa Rodin Luxembourg, Luxembourg Gerald G Sander Ludwigsburg, Germany More information about this series at http://www.springer.com/series/13467 Nada Bodiroga-Vukobrat • Daniel Rukavina • Kresˇimir Pavelic´ • Gerald G Sander Editors Personalized Medicine A New Medical and Social Challenge Editors Nada Bodiroga-Vukobrat Jean Monnet Department of European Public Law University of Rijeka Rijeka Croatia Kresˇimir Pavelic´ Department of Biotechnology University of Rijeka Rijeka Croatia Daniel Rukavina Croatian Academy of Sciences and Arts Rijeka Croatia Gerald G Sander University of Applied Sciences ¨ ffentliche Verwaltung Hochschule f€ ur O und Finanzen Ludwigsburg Ludwigsburg Germany ISSN 2366-0953 ISSN 2366-0961 (electronic) Europeanization and Globalization ISBN 978-3-319-39347-6 ISBN 978-3-319-39349-0 (eBook) DOI 10.1007/978-3-319-39349-0 Library of Congress Control Number: 2016956105 © Springer International Publishing Switzerland 2016 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland Preface When we use the term personalized medicine, it implies the systematic use of information about the individual patient with the goal of choosing optimal prevention and/or welfare therapy The main focus of personalized medicine in current medical treatment is to generate innovative treatments and drugs while reducing negative side effects Recent achievements in life science have created novel opportunities to monitor and assess the progression of each individual patient’s condition The merit of these new capabilities lies mainly in the development and application of high-throughput technologies that provide global insights into the genomic-proteomic profile of diseases New accomplishments in high-throughput technologies such as transcriptomics that provides an entire insight into gene activity in an organism, proteomics that gathers knowledge on global protein profiles, or metabolomics that provides information on metabolite status, will dramatically change molecular medicine and life science At the same time, it should be noted that genes and proteins cannot explain everything One needs to consider other complex elements, including molecular pathways, protein structure, secondary protein modifications, epigenetics, and many others New methods to provide some novel insights into biological mechanisms could include lipidomics, glycomics, metabolomics, nutrinomics, and even complex structural genomics methodologies and approaches The use of these methods in medicine may allow an individualized service for each patient and boost the progression in medicine from the traditional focus on discovering new drugs to a new and more preemptive approach This change will bring about substantial social shifts that will change socio-humanistic relationships and raise a whole series of important questions: moral-ethical, legal, and socio-economic These issues will result from current challenges in medicine and humanity that are both faced with multiple processes of globalization and fast changes in society Some of the current issues relate to new severe and fast-spreading infectious diseases, changes in the “behavior pattern” of certain diseases, demographic change resulting from an aging population, and fast and dramatic climate changes v vi Preface This book offers comprehensive coverage of the various aspects of personalized medicine as an original approach to classifying, understanding, treating, and preventing disease based on individual biological differences In the introductory section, it defines personalized medicine as a way toward new medical practices and addresses the question: what can personalized medicine offer citizens, medical professionals and reimbursement bodies, and stakeholders? Subsequent chapters discuss the technological aspects of personalized medicine: data collection, comprehensive integration and handling of data, together with key enabling factors in developing the requisite technological support for personalized medicine Lastly, the book explores the main issues shaping the implementation and development of personalized medicine—education, stakeholder participation, infrastructure, a revised approach to the classification of disease and medical tests, regulatory frameworks, and new reimbursement models—together with ethical, legal, and social issues Ultimately, the book calls for interdisciplinarity and a radical change in the way we approach the health and well-being of individuals Target groups are medical doctors and researchers in the field of biomedicine, as well as experts from social sciences dealing with legal, economic, and social aspects of health system issues in general The primary beneficiaries are therefore from these groups of professional experts, but the presented content may attract the widest possible readership as it deals with the issue of paradigm change in one of the major society pillars—the health system We express our thanks to the University of Rijeka for their helpful support that was essential for this enterprise This publication is supported by the Croatian Science Foundation project No 5709 “Perspectives of maintaining the social state: towards the transformation of social security systems for individuals in personalized medicine” and the University of Rijeka project No 13.08.1.2.03 “Social security and market competition.” Finally, we owe our sincere gratitude to the Springer Verlag for recognizing the value of our efforts and for its continuous support to our scientific endeavors Rijeka, Croatia Rijeka, Croatia Rijeka, Croatia Ludwigsburg, Germany 10 March 2016 Nada Bodiroga-Vukobrat Daniel Rukavina Kresˇimir Pavelic´ Gerald G Sander Contents Personalized Medicine: The Path to New Medicine Kresˇimir Pavelic´, Sandra Kraljevic´ Pavelic´, and Mirela Sedic´ Legal Aspects of Personalized Medicine Ulrich Becker 21 Challenges of Personalized Medicine: Socio-Legal Disputes and Possible Solutions Nada Bodiroga-Vukobrat and Hana Horak 31 Embryonic Stem Cell Patents and Personalized Medicine in the European Union Jasmina Mutabžija 53 Personalised Medicine and Public Health Vladimir Mic´ovic´, Iva Sorta-Bilajac Turina, and Ðulija Malatestinic´ 81 Personalized Medicine and Technology Transfer Petra Karanikic 95 Economic Evaluations of Personalized Health Technologies: An Overview of Emerging Issues 107 Ana Bobinac and Maja Vehovec Computational Methods for Integration of Biological Data 137 Vladimir Gligorijevic´ and Natasˇa Pržulj The Role of Proteomics in Personalized Medicine 179 Djuro Josic´ and Urosˇ Andjelkovic´ The Role of Radiology in Personalized Medicine 219 D Miletic´, P Valkovic´-Zujic´, and R Antulov vii viii Contents Implantation of Toric Intraocular Lenses: Personalized Surgery on the Lens 231 Iva Dekaris, Nikica Gabric´, Ante Barisˇic´, and Alma Bisˇcˇevic´ Personalized Medicine of Central Nervous System Diseases and Disorders: Looking Toward the Future 241 Miranda Mladinic´ Pejatovic´ and Srđan Anzic´ Personalized Medicine in Gastroenterology 257 Davor Sˇtimac and Neven Franjic´ Personalized Medicine in Clinical Pharmacology 265 Dinko Vitezic´, Nada Božina, Jasenka Mrsˇic´-Pelcˇic´, Viktorija Erdeljic´ Turk, and Igor Francetic´ Personalized Medicine: The Path to New Medicine Kresˇimir Pavelic´, Sandra Kraljevic´ Pavelic´, and Mirela Sedic´ Abstract Personalised medicine is a new paradigm that represents a shift from current simplified consideration of the patient as a member of the population sharing common fate of disease towards the view that each patient is a unique individual Every person has specific genomic/proteomic and metabolic signature that could account for specific clinical features of disease, response to treatment and disease severity Therefore, disease and the treatment itself should be considered individually Due to a number of reasons for introduction of new paradigm in medicine, implementation of personalised medicine is envisaged in several consecutive steps where projections of the levels of technology, medicine and integration need to be coordinated Introduction Modern medicine faces great challenges, including rapid social changes resulting from globalization, emerging new infectious diseases that spread quickly, alterations in clinical patterns of some diseases (e.g., drug-resistant tuberculosis), and abrupt climate and demographic changes (i.e., aging) These are only some of the issues that traditional medicine is likely to cope with great difficulties Professor Kresˇimir Pavelic´, M.D Ph.D., Head of Laboratory for High-Throughput Analytics, University Centre for High-Throughput Technologies, Department of Biotechnology, University of Rijeka, Rijeka, Croatia Professor Sandra Kraljevic´ Pavelic´, Ph.D., University Centre for High-Throughput Technologies, Department of Biotechnology, University of Rijeka, Rijeka, Croatia Assistant Professor Mirela Sedic´, Ph.D., University Centre for High-Throughput Technologies, Department of Biotechnology, University of Rijeka, Rijeka, Croatia K Pavelic´, M.D., Ph.D (*) Laboratory for High-Throughput Analytics, Department of Biotechnology, University Centre for High-Throughput Technologies, University of Rijeka, Rijeka, Croatia e-mail: pavelic@biotech.uniri.hr S Kraljevic´ Pavelic´, Ph.D • M Sedic´, Ph.D Department of Biotechnology, University Centre for High-Throughput Technologies, University of Rijeka, Rijeka, Croatia © Springer International Publishing Switzerland 2016 N Bodiroga-Vukobrat et al (eds.), Personalized Medicine, Europeanization and Globalization 2, DOI 10.1007/978-3-319-39349-0_1 264 D Sˇtimac and N Franjic´ Ramchandani R, Wang Y, Booth BP et al (2007) The role of SN-38 exposure UGT1A1*28 polymorphism, and baseline bilirubin level in predicting severe irinotecan activity J Clin Pharmacol 47:78–86 Saito YA, Camilleri M (2006) Clinical application of pharmacogenetics in gastrointestinal diseases Expert Opin Pharmacother 7:1857–1869 Schmalfuss F, Kolominsky-Rabas PL (2013) Personalized medicine in screening for malignant disease: a review of methods and applications Biomark Insights 8:9–14 Somma V, Ababneh H, Ababneh A et al (2013) The novel Crohn’s disease marker anti-GP2 antibody is associated with ileocolonic location of disease Gastroenterol Res Pract 2013:683824 doi:10.1155/2013/683824 Tesˇija Kuna A (2013) Serological markers of inflammatory bowel disease Biochem Med (Zagreb) 23(1):28–42 Weinshilboum RM, Sladek SL (1980) Mercaptopurine pharmacogenetics: monogenic inheritance of erythrocyte thiopurine methyltransferase activity Am J Hum Genet 32(5):651–662 Wen S, Velin D, Pan-Hammarstr€ om Q et al (2007) Expression of Helicobacter pylori virulence factors and associated expression profiles of inflammatory genes in the human gastric mucosa Infect Immun 75:5118–5126 Yen JL, McLeod HL (2007) Should DPD analysis be required prior to prescribing fluorpyrimidines? Eur J Cancer 43:1011–1016 Personalized Medicine in Clinical Pharmacology Dinko Vitezic´, Nada Božina, Jasenka Mršić-Pelčić, Viktorija Erdeljić Turk, and Igor Francetić Abstract Clinical pharmacology includes the principles of personalized medicine as tailoring of medical treatment to the individual characteristics of each patient In this chapter, three different areas of clinical pharmacology that are important in the individualization of the therapy (therapeutic drug monitoring, individualization in patients with renal and liver dysfunction, and pharmacogenetics/pharmacogenomics) have been presented The main goal of therapeutic drug monitoring is to use drug concentrations to manage a patient’s medication regimen and optimize the outcome of the treatment Proper dosage adjustment is of utmost importance in patients with liver or kidney dysfunction (main organs involved in the processes of metabolization and elimination of drugs) The recognition that a part of interindividual variability in drug response is inherited, and therefore predictable, created the field of pharmacogenetics/pharmacogenomics Therefore, it is important to take into consideration all these specific fields, and the result will be adequate dosage for individual patients This personalized therapy would maximize therapeutic efficacy, minimize drug toxicity, and can have an important economic impact on the health system We presume, in the future, that personalized medicine will probably lose this adjective “personalized” since it is a unique medicine that uses all the tools we have at disposal in order to use drugs optimally for individual patients In this approach, clinical pharmacologists certainly have a particularly important place Professor Dinko Vitezic´, M.D., Ph.D., University of Rijeka Medical School and University Hospital Centre Rijeka, Rijeka, Croatia Assistant Professor Nada Božina, M.D., Ph.D., University of Zagreb Medical School and University Hospital Centre Zagreb, Zagreb, Croatia Professor Jasenka Mrsˇic´-Pelcˇic´, M.D., Ph.D., University of Rijeka Medical School, Rijeka, Croatia Viktorija Erdeljic´ Turk, M.D., Ph.D., University of Zagreb Medical School and University Hospital Centre Zagreb, Zagreb, Croatia Professor Igor Francetic´, M.D., Ph.D., University of Zagreb Medical School and University Hospital Centre Zagreb, Zagreb, Croatia D Vitezic´, M.D., Ph.D (*) • J Mrsˇic´-Pelcˇic´, M.D., Ph.D University of Rijeka Medical School and University Hospital Centre Rijeka, Rijeka, Croatia e-mail: dinko.vitezic@medri.uniri.hr N Božina, M.D., Ph.D • V.E Turk, M.D., Ph.D • I Francetic´, M.D., Ph.D University of Zagreb Medical School and University Hospital Centre Zagreb, Zagreb, Croatia © Springer International Publishing Switzerland 2016 N Bodiroga-Vukobrat et al (eds.), Personalized Medicine, Europeanization and Globalization 2, DOI 10.1007/978-3-319-39349-0_14 265 266 D Vitezic´ et al Introduction Clinical pharmacology could be defined as a translational discipline between basic pharmacology and applied pharmacology and how they are used in drug discovery and development and in solving practical therapeutic problems in individuals and populations.1 One of the basic principles of clinical pharmacology and pharmacotherapy in general could be synthetized in the phrase “the right drug for the right patient.” This phrase aligns with the broader definition of personalized medicine, e.g., tailoring of medical treatment to the individual characteristics of each patient.2 This individual patient’s characteristics include interindividual variability in drug response as a consequence of multiple factors, such as gender, age, and/or concomitant illness and medication, genomics, epigenomics, and the environment.3 This chapter therefore includes three different areas of clinical pharmacology that are important in the individualization of the therapy such as therapeutic drug monitoring, individualization in patients with renal and liver dysfunction, and pharmacogenetics/pharmacogenomics In the broader definition of personalized medicine, we have to take into account the specifics of drug therapy in the elderly, pregnancy, lactation, and children as special populations, but it would exceed the extent of this chapter Therapeutic Drug Monitoring Therapeutic drug monitoring (TDM) is a branch of clinical chemistry and clinical pharmacology that specializes in the measurement of medication concentrations in blood.4 To ensure that best practice in TDM is achieved, accurate and clinically meaningful drug concentrations can only be obtained by close collaboration between the prescribing physician, the laboratory specialist, the clinical pharmacologist, and the patient TDM has been often identified with a simple drug measuring However, it is only one part of TDM that provides expert clinical interpretation, as well as the concentration to ensure full clinical benefit Its main focus is on drugs with a narrow therapeutic range, i.e., drugs that can easily be under- or overdosed TDM can be based on a priori pharmacogenetic, demographic, and clinical information and/or on the a posteriori measurement of blood concentrations of drugs (pharmacokinetic monitoring) or biological surrogate or end-point markers of effect (pharmacodynamic monitoring).5 There are numerous variables that influence the interpretation of drug concentration data: time, route and dose of drug given, time of blood sampling, handling Aronson (2010) Bates (2010) Schwab and Schaeffeler (2012) Marshall and Bangert (2008) IATDMCT Executive Committee (2011) Personalized Medicine in Clinical Pharmacology 267 and storage conditions, precision and accuracy of the analytical method, validity of pharmacokinetic models and assumptions, comedications and clinical status of the patient (i.e., disease, renal/hepatic status, biologic tolerance to drug therapy, etc.).6 The importance of the clinical interpretation of the drug concentration measured and its contribution to individualization of a drug dosage regimen is crucial Just relating a drug concentration to a published therapeutic range is not an adequate interpretation, e.g., a digoxin concentration must be interpreted in light of the creatinine and potassium concentrations, concomitant drug therapy, patients’ compliance, as well as the patient’s clinical state Clinical pharmacologist is ideally placed to fulfill this function in cooperation with other members of the TDM team By the definition of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology, a priori TDM consists of determining the initial dose regimen to be given to a patient based on clinical end point and on established population pharmacokinetic–pharmacodynamic (PK/PD) relationships (see footnote 5) These relationships help to identify subpopulations of patients with different dosage requirements by utilizing demographic data, clinical findings, clinical chemistry results, and/or, when appropriate, pharmacogenetic characteristics A posteriori TDM is most often based on the specific, accurate, precise, and timely determinations of the active and/or toxic forms of drugs in biological samples collected at the appropriate times in the correct containers (PK monitoring) or can employ the measurement of a biological perimeter as a surrogate or end-point marker of effect (PD monitoring), e.g., concentration of an endogenous compound, enzymatic activity, gene expression, etc., either as a complement to PK monitoring or as the main TDM (see footnote 5) It requires interpretation of the results, taking into account preanalytical conditions, clinical information, and the clinical efficiency of the current dosage regimen In pharmacotherapy, many medications are used without monitoring of blood levels as their dosage can generally be varied according to the clinical response that a patient gets to that substance In the small group of drugs, this is impossible as insufficient levels will lead to undertreatment or resistance and excessive levels can lead to toxicity and tissue damage Drug assays are costly, so the reason for monitoring and the additional information to be gained should be carefully considered Routine monitoring is not advocated for most drugs Only clinically meaningful tests should be performed Indications for therapeutic drug monitoring include the following: • • • • • narrow target range, significant pharmacokinetic variability, a reasonable relationship between plasma concentrations and clinical effects, established target concentration range, availability of cost-effective drug assay Burton et al (2006) 268 D Vitezic´ et al Examples of drugs suitable for therapeutic drug monitoring include (see footnote 4) the following:7 • digoxin (target range: 0.8–2 μg/L), • lithium (target range-acute mania: 0.8–1.2 mmol/L, maintenance: 0.4–1.0 mmol/L), • phenytoin (target range: 10–20 mg/L), • cyclosporine [target range: 50–125 μg/L (serum or plasma), 150–400 μg/L (whole blood), concentrations differ for various clinical settings], • tacrolimus [target range: 5–20 μg/L (whole blood)], • sirolimus [target range: 5–15 μg/L (whole blood)] Although TDM services have usually been set up within large hospitals, the principles of TDM best practice could be applied to the community setting and should be increasingly easy to incorporate as a result of the continual improvement of information technology in general practice.8 Only a limited number of articles have been published that demonstrate the costeffectiveness of therapeutic drug monitoring, and there continues to be a debate as to whether these services make a cost-effective contribution to patient care.9,10 It surely cannot be seen as cost-effective if it is used as an unthinking routine in patients rather than as an aid in resolving clinical problems TDM has to be applied rationally, starting from a valid indication to blood sampling and ending with a sound dosage adaptation decision Due to the upswing in individualization of drug therapy and thereby in TDM, which is foundational to the concept of personalized medicine, the need for improvement in current deficiencies in the provision of TDM services became evident This includes assay selection, laboratory variability in reporting, accessibility, validity of suggested target ranges, and both quality and quantity of postanalytical advice Continuing work in ensuring the best practice guidelines and professional standards of practice in TDM are needed, supported by an active program of professional development.11 Ghiculescu (2008) Gross (2001) Eadie (1995) 10 Eadie (1997) 11 Norris et al (2010) Personalized Medicine in Clinical Pharmacology 269 Drug Therapy Individualization in Patients with Renal and Liver Dysfunction The liver and kidneys are the main organs involved in the processes of elimination of drugs and their metabolites Hence, proper dosage adjustment is of utmost importance in patients with liver or kidney dysfunction It would maximize therapeutic efficacy, minimize drug toxicity, and can have an important economic impact on the health system It was shown that dosing errors and the risk of toxicity are common among patients with chronic kidney disease (CKD).12 CKD is defined as the presence of kidney damage or a reduction in the glomerular filtration rate (GFR) for months or longer.13 Incidence of CKD significantly increased over the last decade, either as complication of hypertension and/or diabetes as two major causative factors of this illness or because of increasing number of older population Indeed, kidney function decreases with age, and older patients constitute the most rapidly expanding patient group linked with CKD.14 The degree of renal insufficiency and the severity of kidney disease are generally reflected in the decline of glomerular filtration rate (GFR) The evaluation of GFR is the most reliable index and surrogate marker of overall kidney function The Kidney Disease Outcomes Quality Initiative (K/DOQI) of the National Kidney Foundation (NKF) established a classification of CKD based on GFR that has been accepted and used worldwide (see footnote 12) The five stages of classification, along with a description of each stage, are shown in Table GFR below 60 ml/min requires dosage adjustment for certain drugs Direct measurement of GFR using exogenous filtration markers is more accurate but the most costly option The estimation of creatinine clearance has been extensively used even though creatinine is a crude index of kidney function Several formulas have been developed for estimating GFR based on serum creatinine clearance data, all of which have advantages and/or limitations (Table 2) The most commonly used are the Cockcroft-Gault and the 4-variable Modification of Diet in Renal Disease (MDRD4) formulas The NKF, however, is now recommending the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation Cockcroft and Gault equation depends on serum creatinine concentrations and associated measurements limitations, including tubular secretion of creatinine that results in overestimation of GFR by up to 20 % Despite these limitations, this equation remains the most appropriate method to determine drug dosage individualization based on kidney function Many have considered that an advantage of this equation for individual drug dose adjustment is that the body weight is considered (see footnote 14) The abbreviated version of Modification of Diet in Renal Disease 12 Verbeeck and Musuamba (2009) Hartmann et al (2010) 14 Matzke et al (2011) 13 D Vitezic´ et al 270 Table Chronic kidney disease staging Stage Description Kidney damage with normal or increased GFR Kidney damage with a mild decrease in GFR Moderate decrease in GFR Severe decrease in GFR Kidney failure GFR (ml/min/1.73 m2) !90 60–89 30–59 15–29 control) Encephalopathy (grade) Ascites point 3.5 3 6 or Moderate Points should be summed, and total score is classified according to the severity: 5–6 points, group A (mild); 7–9 points, group B (moderate); 10–15 points, group C (severe) 16 17 Dourakis (2008) Peria´~nez-Pa´rraga et al (2012) 272 D Vitezic´ et al Personalized Medicine and Pharmacogenomics The recognition that a part of interindividual variability in drug response is inherited, and therefore predictable, created the field of pharmacogenetics/ pharmacogenomics Genetic variation is considered an important source of variability in drug response and contributes to 25–50 % of inappropriate drug responses.18 It has the potential to negatively impact effectiveness of drug therapy (drug efficacy) and increases the risk for adverse drug reactions (ADRs) One type of genetic variation is the single nucleotide polymorphisms (SNPs) Knowing the types of SNPs/genetic variations can help predict the associated drug response This can help physicians to improve effectiveness of the drug, decrease the chance of negative side effects, and save health care costs Associations of SNPs to drug treatment outcome are continuously being discovered, with a recent focus on genome-wide association (GWA) studies being conducted in many different ethnic groups Interindividual differences in drug disposition are important causes for ADRs and lack of drug response There are major interindividual differences in the capacity to metabolize and detoxify drugs and other xenobiotics Biotransformation occurs through phase I and phase II drug-metabolizing enzymes (DMEs), i.e., enzymes catalyzing oxidation and conjugation reactions, respectively, with the important role of drug transporters, named phase III reactions The majority of phase I and phase II DMEs and phase III drug transporters are polymorphic and constitute essential factors for the outcome of drug therapy In the terms of drug metabolism, there are four specific phenotypes that can be determined by either phenotyping or genotyping: a poor metabolizer (PM), intermediate metabolizer (IM), extensive metabolizer (EM), and ultrarapid metabolizer (UM) A poor metabolizer lacks active allele and may experience more adverse events at usual doses due to reduced metabolism and increased drug concentration If individuals lacking the active allele receive a prodrug, they may not respond due to a lowerthan-expected concentration of the active metabolite Individuals with intermediate metabolic phenotype are homozygous for two reduced activity alleles or are heterozygous for an inactive allele They may experience some, or a lesser degree of, consequences of a poor metabolizer Extensive metabolizer has two fully active alleles and shows expected response to a standard dose Ultraextensive metabolizers are individuals with more than two copies of active gene They may not reach therapeutic concentrations at usual, recommended drug doses due to increased metabolism When a prodrug is administered, they may experience adverse effects due to higher-than-expected concentrations of active metabolite Clinically, the most important polymorphisms in phase I are of the CYP2C9, CYP2C19, CYP2D6 and CYP3A4/5 genes.19 Phase II biotransformation processes also show high interindividual variability Polymorphisms of the thiopurine methyltransferase (TPMT), UDP-glucuronosyltransferase 18 19 Spear et al (2001) Johansson and Ingelman-Sundberg (2011) Personalized Medicine in Clinical Pharmacology 273 (UGT1A1) N-Acetyltransferase (NAT2), and glutathion S-transferase (GST) have been demonstrated to be of great importance for clinical practice.20,21 Genetic variation also plays a crucial role in drug–drug interactions Presence of a second drug may induce (enhance) or inhibit the metabolic activity of a certain enzyme responsible for drug metabolism Such unwanted drug–drug interactions can influence the activity of the enzyme and reduce bioavailability of the primary drug being taken If this occurs in a patient with low initial level of enzyme activity due to genetic variation, drug–drug interaction can result in poor efficacy and dangerous side effects.22 Pharmacogenomics promote the development of targeted therapies There are very good examples of important applications of pharmacogenomics for cancer therapy like cetuximab/panitumumab and KRAS, vemurafenib and BRAF, gefitinib/ erlotinib and EGFR, crizotinib and EML4-ALK, imatinib and KIT (c-KIT).23 Drug hypersensitivity remains an important clinical issue It is consisted of a variety of phenotypes, mainly the cutaneous adverse reactions that range from milder skin reactions (e.g., exanthem, urticaria, and angioedema) to severe cutaneous adverse reactions (SCARs) SCARs are life threatening, including StevensJohnson syndrome (SJS), toxic epidermal necrolysis (TEN), and drug reaction with eosinophilia and systemic symptoms (DRESS) or drug-induced hypersensitivity syndrome (DIHS) Associations between human leukocyte antigen (HLA) alleles and specific drug hypersensitivity syndromes such as abacavir hypersensitivity have accelerated the widespread use of a pharmacogenetic test in clinical practice to prevent the development of specific life-threatening drug toxicity.24 Genetic predisposition to drug-induced liver injury (DILI) may be due to variation in both pharmacokinetic and pharmacodynamic pathways GWAS have identified, in the HLA alleles, strong genetic factors that predispose to liver injury on exposure to any of several drugs.25 A clear role in drug toxicity and efficacy has been established for some gene– drug combinations, yet the implementation of pharmacogenomic tests in clinical practice lags behind this knowledge It is partly due to the lack of specific guidelines on how to adjust medications on the basis of genetic test results To overcome this problem, in recent years, the Pharmacogenetics Implementation Consortia were established The main goal of the Consortia is to provide peer-reviewed, updated, evidence-based, freely accessible guidelines for gene/drug pairs (http://www pharmgkb.org) These guidelines will facilitate the translation of pharmacogenomic knowledge from bench to bedside (Table 4).26,27 20 Sim et al (2013) Stingl et al (2014) 22 Cascorbi and Tyndale (2014) 23 Ong et al (2012) 24 Kaniwa and Saito (2013) 25 Alfirevic and Pirmohamed (2012) 26 Caudle et al (2014) 27 Swen et al (2011) 21 D Vitezic´ et al 274 Table Guidelines and recommendations for drug dosing according to genotype Drug Abacavir Gene HLA-B Allopurinol HLA-B Carbamazepine HLA-B Amitriptyline CYP2C19 CYP2D6 Azathioprine TPMT Boceprevir, peginterferon alfa-2a, peginterferon alfa2b, ribavirin, telaprevir IFNL3 Recommendation In individuals with the HLA-B*57:01 variant allele, abacavir is not recommended and should be considered only under exceptional circumstances Allopurinol is contraindicated in individuals with the HLA-B*58:01 allele due to significantly increased risk of SCAR Carbamazepine is not recommended for carbamazepine-naive individuals who have at least one copy of the HLA-B*15:02 allele The variant allele is associated with an increased risk of SJS and TEN in response to carbamazepine treatment Dosing Guideline for amitriptyline recommends an alternative drug for CYP2D6 or CYP2C19 ultrarapid metabolizers and for CYP2D6 poor metabolizers Consider a 50 % dose reduction for CYP2C19 poor metabolizers and a 25 % dose reduction for CYP2D6 intermediate metabolizers Tricyclic antidepressants have comparable pharmacokinetic properties; it may be reasonable to apply the Dosing Guideline for amitriptyline and CYP2C19, CYP2D6 to other tricyclics, including clomipramine, imipramine Consider an alternate agent or extreme dose reduction of azathioprine for patients with low or deficient TPMT activity Start at 30–70 % of target dose for patients with intermediate enzyme activity IFNL3 (IL28B) variation (rs12979860) is the strongest baseline predictor of response to PEG-interferon-alpha-containing regimens in HCV genotype patients Patients with the favourable response genotype (rs12979860 CC) have increased likelihood of response (higher SVR rate) to PEG-interferon-alpha- Guidelines by CPIC CPIC CPIC CPIC CPIC CPIC (continued) Personalized Medicine in Clinical Pharmacology 275 Table (continued) Drug Gene Capecitabine, fluorouracil, tegafur DPYD Clopidogrel CYP2C19 Codeine CYP2D6 Haloperidol CYP2D6 Irinotecan UGT1A1 Ivacaftor CFTR Recommendation containing regimens as compared to patients with unfavorable response genotype (rs12979860 CT or TT) Consider implications before initiating PEG-IFN alpha and RBV containing regimens Dosing Guideline for fluoropyrimidines (i.e., 5-fluorouracil, capecitabine, or tegafur) recommends an alternative drug for patients who are homozygous for DPYD nonfunctional variants (*2A rs3918290, *13 rs55886062, and rs67376798) as these patients are typically DPD deficient Consider a 50 % reduction in starting dose for heterozygous patients (intermediate activity) Dosing Guideline for clopidogrel recommends an alternative antiplatelet therapy (e.g., prasugrel, ticagrelor) for CYP2C19 poor or intermediate metabolizers if there is no contraindication Alternate analgesics are recommended for CYP2D6 ultrarapid and poor metabolizers (not tramadol, oxycodone) A label recommended age- or weightspecific codeine dose is warranted for CYP2D6 extensive and intermediate metabolizers Reduce haloperidol dose by 50 %, or select an alternative drug for CYP2D6 poor metabolizer genotype patients Reduce the starting dose of irinotecan for UGT1A1*28 homozygous patients receiving more than 250 mg/m^2 Ivacaftor treatment is recommended only in CF patients who are either homozygous or heterozygous for the G551D-CFTR variant (rs75527207 genotype AA or AG) In patients who are homozygous for F508delCFTR (F508del/F508del, rs113993960 or rs199826652 Guidelines by CPIC CPIC CPIC DPWG DPWG CPIC (continued) D Vitezic´ et al 276 Table (continued) Drug Gene Simvastatin SLCO1B1 Tamoxifen CYP2D6 Warfarin CYP2C9 VKORC1 Recommendation genotype del/del), ivacaftor is not recommended See full guideline for disclaimers, further details, and supporting evidence In the amended FDA-approved ivacaftor drug label, the indication has been changed to include additional CFTR variants The clinical trial to support this data is not yet published The FDA recommends against 80 mg daily simvastatin dosage In patients with the C allele at SLCO1B1 rs4149056, there are modest increases in myopathy risk even at lower simvastatin doses (40 mg daily); if optimal efficacy is not achieved with a lower dose, alternate agents should be considered The association of rs4149056 with myopathy has been less compelling for other statins Guideline is focused on simvastatin For CYP2D6 poor and intermediate metabolizers, consider using aromatase inhibitors for postmenopausal women due to increased risk for relapse of breast cancer with tamoxifen For intermediate metabolizers, avoid concomitant CYP2D6 inhibitor use The best way to estimate the anticipated stable dose of warfarin is to use the algorithms available on http://www.warfarindosing.org Guidelines by CPIC DPWG CPIC The Clinical Pharmacogenetics Implementation Consortium (CPIC) of the National Institutes of Health Pharmacogenomics Research Network develops peer-reviewed gene–drug guidelines that are published and updated periodically on http://www.pharmgkb.org based on new developments in the field These dosing guidelines take into consideration patient genotype and have been published by the *Clinical Pharmacogenetics Implementation Consortium CPIC*, the *Royal Dutch Association for the Advancement of Pharmacy-Pharmacogenetics Working Group DPWG *(manually curated by PharmGKB), or other professional society PRO (manually curated by PharmGKB) Personalized Medicine in Clinical Pharmacology 277 Conclusion In spite of limitations of this chapter, which not cover all aspects or fields in which clinical pharmacology is directly involved in the individualization of the therapy, it could be concluded that contribution of this clinical discipline for personalization of therapy is exceptionally large It is also important to emphasize that personalized medicine will probably lose, in the future, this adjective “personalized” since it is a unique medicine that uses all the tools we have at disposal in order to use drugs optimally for individual patients In this approach, clinical pharmacologists certainly have a particularly important place References Alfirevic A, Pirmohamed M (2012) Predictive genetic testing for drug-induced liver injury: considerations of clinical utility Clin Pharmacol Ther 92(3):376–380 doi:10.1038/clpt.2012 107 Aronson JK (2010) A manifesto for clinical pharmacology from principles to practice Br J Clin Pharmacol 70:3–13 Bates S (2010) Progress towards personalized medicine Drug Discov Today 15:115–120 Burton ME, Shaw LM, Shentag JJ, Evans WE (2006) Applied pharmacokinetics & pharmacodynamics, 4th edn Lippincott Williams & Wilkins, Baltimore, Philadelphia Cascorbi I, Tyndale R (2014) Progress in pharmacogenomics: bridging the gap from research to practice Clin Pharmacol Ther 95(3):231–235 doi:10.1038/clpt.2013.235 Caudle KE, Klein TE, Hoffman JM et al (2014) Incorporation of pharmacogenomics into routine clinical practice: the clinical pharmacogenetics implementation consortium (CPIC) guideline development process Curr Drug Metab 15(2):209–217 Dourakis SP (2008) Drug therapy in liver diseases Ann Gastroenterol 21(4):215–217 Eadie MJ (1995) The role of therapeutic drug monitoring in improving the cost effectiveness of anticonvulsant therapy Clin Pharmacokinet 29:29–35 Eadie MJ (1997) Indications for plasma drug monitoring in patients with epilepsy Pharmacoeconomics 11:343–349 Ghiculescu RA (2008) Therapeutic drug monitoring: which drugs, why, when and how to it? Aust Prescr 31:42–44 Gross AS (2001) Best practice in therapeutic drug monitoring Br J Clin Pharmacol 52(Suppl 1):5–10 Hartmann B, Czock D, Keller K (2010) Drug therapy in patients with chronic renal failure Dtsch Arztebl Int 107(37):647–656 IATDMCT Executive Committee (2011) Definition of TDM&CT http://www.iatdmct.org/aboutus/about-association/about-definitions-tdm-ct.html Accessed 12 Apr 2014 Johansson I, Ingelman-Sundberg M (2011) Genetic polymorphism and toxicology- with emphasis on cytochrome p450 Toxicol Sci 120(1):1–13 doi:10.1093/toxsci/kfq374 Kaniwa N, Saito Y (2013) Pharmacogenomics of severe cutaneous adverse reactions and druginduced liver injury J Hum Genet 58(6):317–326 doi:10.1038/jhg.2013.37 Marshall WJ, Bangert SK (2008) Clinical chemistry, 6th edn Mosby Elsevier, Edinburgh, London Matzke GR, Aronoff GR, Atkinson AJ, Bennett WM, Decker BS, Eckardt KU, Golper T, Grabe DW, Kasiske B, Keller F, Kielstein JT, Mehta R, Mueller BA, Pasko DA, Schaefer F, Sica DA, Inker LA, Umans JG, Murray P (2011) Drug dosing consideration in patients with acute and 278 D Vitezic´ et al chronic kidney disease A clinical update from kidney disease: improving global outcomes (KDIGO) Kidney Int 80(11):1122–1137 Norris RL, Martin JH, Thompson E et al (2010) Current status of therapeutic drug monitoring in Australia and New Zealand: a need for improved assay evaluation, best practice guidelines, and professional development Ther Drug Monit 32(5):615–623 Ong FS, Das K, Wang J et al (2012) Personalized medicine and pharmacogenetic biomarkers: progress in molecular oncology testing Expert Rev Mol Diagn 12(6):593–602 doi:10.1586/ erm.12.59 Peria´~nez-Pa´rraga L, Martı´nez-Lo´pez I, Ventayol-Bosch P, Puigvento´s-Latorre F, DelgadoSa´nchez O (2012) Drug dosage recommendations in patients with chronic liver disease Rev Esp Enferm Dig 104(4):165–184 Schwab M, Schaeffeler E (2012) Pharmacogenomics: a key component of personalized therapy Genome Med 4(11):93 doi:10.1186/gm394 Sim SC, Kacevska M, Ingelman-Sundberg M (2013) Pharmacogenomics of drug-metabolizing enzymes: a recent update on clinical implications and endogenous effects Pharmacogenomics J 13(1):1–11 doi:10.1038/tpj.2012.45 Spear BB, Heath-Chiozzi M, Huff J (2001) Clinical application of pharmacogenetics Trends Mol Med 7(5):201–204 Stingl JC, Bartels H, Viviani R et al (2014) Relevance of UDP-glucuronosyltransferase polymorphisms for drug dosing: a quantitative systematic review Pharmacol Ther 141(1):92–116 doi:10.1016/j.pharmthera.2013.09.002 Swen JJ, Nijenhuis M, de Boer A et al (2011) Pharmacogenetics: from bench to byte—an update of guidelines Clin Pharmacol Ther 89(5):662–673 doi:10.1038/clpt.2011.34 Verbeeck RK (2008) Pharmacokinetics and dosage adjustment in patients with hepatic dysfunction Eur J Clin Pharmacol 64(12):1147–1161 Verbeeck RK, Musuamba FT (2009) Pharmacokinetics and dosage adjustment in patients with renal dysfunction Eur J Clin Pharmacol 65(8):757–773 ... procedures, data collection, and manipulation Quality assurance protocols for laboratories have to be developed and made available at all levels Harmonization represents a decent basis for data management... series at http://www.springer.com/series/13467 Nada Bodiroga-Vukobrat • Daniel Rukavina • Kresˇimir Pavelic´ • Gerald G Sander Editors Personalized Medicine A New Medical and Social Challenge. .. 241 Miranda Mladinic´ Pejatovic´ and Srđan Anzic´ Personalized Medicine in Gastroenterology 257 Davor Sˇtimac and Neven Franjic´ Personalized Medicine in Clinical Pharmacology

Ngày đăng: 14/05/2018, 15:14

Mục lục

  • Preface

  • Contents

  • Personalized Medicine: The Path to New Medicine

    • 1 Introduction

    • 2 Definition and Elements of Personalized Medicine

    • 3 Difference Between Traditional and Personalized Medicine

    • 4 What Personalized Medicine Has to Offer?

    • 5 Influence of Personalized Medicine on Participants

    • 6 Technological and Infrastructural Presumptions

    • 7 The Impact of Personalized Medicine and Implementation

    • 8 Personalized Preventive Medicine and Diet

    • 9 Studies Indispensable for the Development of Personalized Medicine

    • 10 Timeline for the Development and Implementation of Personalized Medicine

    • References

  • Legal Aspects of Personalized Medicine

    • 1 Introduction

    • 2 Concept and Appearance of Personalized Medicine

    • 3 Access to Health Care Systems

    • 4 Data Protection

    • 5 Final Observations

    • References

  • Challenges of Personalized Medicine: Socio-Legal Disputes and Possible Solutions

    • 1 Introduction

    • 2 Personalized Medicine and the Resulting Challenges

    • 3 The Right to Health: Level of Access and Level of Participation

    • 4 How to Understand Personalized Medicine in the Social and Legal Context

    • 5 The Principle of Solidarity in Health Care Systems

    • 6 Health Insurance and Personalized Medicine

    • 7 Regulation at the EU Level

    • 8 Issues Surrounding the Legal Nature in the Implementation of Personalized Medicine: The Regulatory Framework in the United S...

      • 8.1 Regulatory Framework in the United States

        • 8.1.1 Genetic Privacy and Nondiscrimination

        • 8.1.2 Further Development of Regulatory Framework for the Pharmaceutical and Diagnostic Industry

    • 9 Conclusion

    • References

  • Embryonic Stem Cell Patents and Personalized Medicine in the European Union

    • 1 Introduction

    • 2 The Basic Science of Embryonic Stem Cells and Their Potential in Medicine

    • 3 The Legality of Embryonic Stem Cell Research in the EU

    • 4 Embryonic Stem Cell Patents in the EU

      • 4.1 Legal Analysis of the Relevant Provisions of the Directive on Patents in Biotechnology

        • 4.1.1 Human Body and Its Elements

        • 4.1.2 Processes for Cloning Human Beings and Uses of Human Embryos for Industrial and Commercial Purposes

      • 4.2 Decisions of the CJEU Regarding the Interpretation of Article 6 of the Directive

        • 4.2.1 CJEU Decision in Oliver Brüstle

        • 4.2.2 CJEU Decision in International Stem Cell Corporation

    • 5 Conclusion

    • References

  • Personalised Medicine and Public Health

    • 1 Introduction

    • 2 Personalised Medicine in Public Health

    • 3 Personalised Medicine vs. Public Health

    • 4 Personalised Medicine and Public Health

      • 4.1 Redefining the Definition

      • 4.2 Medical Data

      • 4.3 New Taxonomy of Health and Disease

      • 4.4 Health Literacy

      • 4.5 A Glimpse into the Future of Public Health: From Proactive P4 Medicine to Personalised Preventive Medicine

    • 5 Conclusion

    • References

  • Personalized Medicine and Technology Transfer

    • 1 Introduction

    • 2 Technology Transfer Concept in the Personalized Medicine Approach

    • 3 Role of Marketing in Personalized Medicine Concept

    • 4 Personalized Medicine and Process Management Implementation

    • 5 Conclusion

    • References

  • Economic Evaluations of Personalized Health Technologies: An Overview of Emerging Issues

    • 1 Introduction

    • 2 Economic Evaluations in a Nutshell

      • 2.1 QALY as a Measure of Health Benefits

      • 2.2 The Measure of Costs

      • 2.3 Decision Rule for CUA

      • 2.4 Uncertainty

    • 3 Economic Evaluations of Companion Diagnostics

      • 3.1 The Differences Between the Economic Evaluations of Drugs and Diagnostics

      • 3.2 Assessments of Companion Diagnostics: Some Applications

    • 4 Methodological Challenges for Economic Evaluations of Companion Diagnostics

      • 4.1 Complexity of Personalized Medicine

      • 4.2 Available Evidence

      • 4.3 The Value of Personalized Medicine

    • 5 Concluding Remarks

    • References

  • Computational Methods for Integration of Biological Data

    • 1 Introduction

    • 2 Biological Problems

      • 2.1 Protein Function Prediction

      • 2.2 Drug Repurposing

      • 2.3 Disease Classification and Disease-Disease Association Prediction

      • 2.4 Prioritization of Disease Genes

    • 3 Biological Data and Their Network Representation

      • 3.1 Biological Networks

        • 3.1.1 Protein-Protein Interaction (PPI) Networks

        • 3.1.2 Metabolic Networks

        • 3.1.3 Gene Coexpression (Co-Ex) Networks

        • 3.1.4 Genetic Interaction (GI) Networks

        • 3.1.5 Signal-Transduction (ST) Networks

        • 3.1.6 Gene-Disease Association (GDA) Bipartite Network

        • 3.1.7 Drug-Target Interaction (DTI) Bipartite Network

        • 3.1.8 Drug Interaction Networks

        • 3.1.9 Ontology Data

      • 3.2 Network Representations

    • 4 Integration Methods

      • 4.1 Bayesian Networks for Data Integration

      • 4.2 Kernel-Based Data Integration

      • 4.3 Matrix Factorization-Based Data Integration

    • 5 Conclusion

    • References

  • The Role of Proteomics in Personalized Medicine

    • 1 Introduction

    • 2 Personal Patient Profiling by Use of Integrated Omics

    • 3 Targeted Biomarker Discovery

    • 4 Posttranslational Modifications as Potential Theranostic Biomarkers

    • 5 Application of Proteomics for Early Disease Diagnosis, Treatment and Follow-Up of the Recovery Process

      • 5.1 Cancer

      • 5.2 Cardiovascular Diseases

      • 5.3 Urological Diseases

      • 5.4 Neurodegenerative Diseases

      • 5.5 Diabetes Mellitus

      • 5.6 Allergy

      • 5.7 Proteomics in Space Medicine

    • 6 Concluding Remarks

    • References

  • The Role of Radiology in Personalized Medicine

    • References

  • Implantation of Toric Intraocular Lenses: Personalized Surgery on the Lens

    • 1 Introduction

    • 2 Refractive Errors

    • 3 Premium Intraocular Lenses

    • 4 Toric Intraocular Lenses

    • 5 Multifocal Intraocular Lenses

    • 6 Conclusion

    • References

  • Personalized Medicine of Central Nervous System Diseases and Disorders: Looking Toward the Future

    • 1 Introduction

    • 2 Stroke

      • 2.1 The Scale of the Problem

      • 2.2 Genetic Predisposition to Stroke

      • 2.3 Recombinant DNA Biotechnology Methods in the Detection of ``Stroke Genes´´

      • 2.4 Can Identifying Genes for Stroke Help Patients?

    • 3 Schizophrenia

      • 3.1 Personalized Medicine in Psychiatry

      • 3.2 Genetic Predisposition to Schizophrenia

      • 3.3 The Role of Environmental Exposures and Epigenetics in Predisposition to Schizophrenia

    • 4 Role of Stem Cell Therapy in Personalized Medicine of CNS Diseases

    • 5 Conclusion

    • References

  • Personalized Medicine in Gastroenterology

    • 1 Personalized Medicine

    • 2 Personalized Medicine in Gastroenterology

    • 3 The Potential of Personalized Medicine

    • 4 Conclusion

    • References

  • Personalized Medicine in Clinical Pharmacology

    • 1 Introduction

    • 2 Therapeutic Drug Monitoring

    • 3 Drug Therapy Individualization in Patients with Renal and Liver Dysfunction

    • 4 Personalized Medicine and Pharmacogenomics

    • 5 Conclusion

    • References

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