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Miscio G, Paroni G, Bisceglia P, Gravina C, Urbano M, Lozupone M, Piccininni C, Prisciandaro M, Ciavarella G, Daniele A, Bellomo A, Panza F, Di Mauro L, Greco A, Seripa D. Pharmacogenetics in the clinical analysis laboratory: clinical practice, research, and drug development pipeline. Expert Opin Drug Metab Toxicol 2019; 15:751-765. [PMID: 31512953 DOI: 10.1080/17425255.2019.1658742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Introduction: Over the last decade, the spread of next-generation sequencing technology along with the rising cost in health management in national health systems has led to widespread use/abuse of pharmacogenetic tests (PGx) in the practice of many clinical disciplines. However, given their clinical significance, it is important to standardize these tests for having an interaction with the clinical analysis laboratory (CAL), in which a PGx service can meet these requirements. Areas covered: A diagnostic test must meet the criteria of reproducibility and validity for its utility in the clinical routine. This present review mainly describes the utility of introducing PGx tests in the CAL routine to produce correct results useful for setting up personalized drug treatments. Expert opinion: With a PGx service, CALs can provide the right tool to help clinicians to make better choices about different categories of drugs and their dosage and to manage the economic impact both in hospital-based settings and in National Health Services, throughout electronic health records. Advances in PGx also allow a new approach for pharmaceutical companies in order to improve drug development and clinical trials. As a result, CALs can achieve a powerful source of epidemiological, clinical, and research findings from PGx tests.
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Affiliation(s)
- Giuseppe Miscio
- Clinical Laboratory Analysis and Transfusional Medicine, Laboratory and Transfusional Diagnostics, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Giulia Paroni
- Research Laboratory, Complex Structure of Geriatrics, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Paola Bisceglia
- Research Laboratory, Complex Structure of Geriatrics, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Carolina Gravina
- Research Laboratory, Complex Structure of Geriatrics, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Maria Urbano
- Research Laboratory, Complex Structure of Geriatrics, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Madia Lozupone
- Neurodegenerative Disease Unit, Department of Basic Medical Sciences, Neuroscience, and Sense Organs, University of Bari Aldo Moro , Bari , Italy
| | - Carla Piccininni
- Psychiatric Unit, Department of Clinical and Experimental Medicine, University of Foggia , Foggia , Italy
| | - Michele Prisciandaro
- Clinical Laboratory Analysis and Transfusional Medicine, Laboratory and Transfusional Diagnostics, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Grazia Ciavarella
- Clinical Laboratory Analysis and Transfusional Medicine, Laboratory and Transfusional Diagnostics, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Antonio Daniele
- Institute of Neurology, Catholic University of Sacred Heart , Rome , Italy.,Institute of Neurology, Fondazione Policlinico Universitario A. Gemelli IRCCS , Rome , Italy
| | - Antonello Bellomo
- Psychiatric Unit, Department of Clinical and Experimental Medicine, University of Foggia , Foggia , Italy
| | - Francesco Panza
- Research Laboratory, Complex Structure of Geriatrics, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy.,Neurodegenerative Disease Unit, Department of Basic Medical Sciences, Neuroscience, and Sense Organs, University of Bari Aldo Moro , Bari , Italy
| | - Lazzaro Di Mauro
- Clinical Laboratory Analysis and Transfusional Medicine, Laboratory and Transfusional Diagnostics, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Antonio Greco
- Research Laboratory, Complex Structure of Geriatrics, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
| | - Davide Seripa
- Research Laboratory, Complex Structure of Geriatrics, Department of Medical Sciences, Fondazione IRCCS Casa Sollievo della Sofferenza , Foggia , Italy
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Abstract
This article introduces fundamental principles of pharmacogenetics as applied to personalized and precision medicine. Pharmacogenetics establishes relationships between pharmacology and genetics by connecting phenotypes and genotypes in predicting the response of therapeutics in individual patients. We describe differences between precision and personalized medicine and relate principles of pharmacokinetics and pharmacodynamics to applications in laboratory medicine. We also review basic principles of pharmacogenetics, including its evolution, how it enables the practice of personalized therapeutics, and the role of the clinical laboratory. These fundamentals are a segue for understanding specific clinical applications of pharmacogenetics described in subsequent articles in this issue.
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Affiliation(s)
- Roland Valdes
- Department of Pathology and Laboratory Medicine, University of Louisville School of Medicine, MDR Building, Room 222, 511 South Floyd Street, Louisville, KY 40202, USA; Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, HSC-A Building, Louisville, KY 40202, USA.
| | - DeLu Tyler Yin
- Department of Pathology and Laboratory Medicine, University of Louisville School of Medicine, MDR Building, Room 218, 511 South Floyd Street, Louisville, KY 40202, USA
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Andreev VP. Pharmacoproteomics of obesity: definitions, role and a case study of dynamics of human plasma proteome. Pharmacogenomics 2011; 12:1363-5. [DOI: 10.2217/pgs.11.101] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Affiliation(s)
- Victor P Andreev
- Department of Psychiatry & Behavioral Sciences, University of Miami Miller School of Medicine, 1120 NW 14th Street, Room 1476, Miami, FL 33136, USA and Center for Computational Sciences, University of Miami, Miami, FL, USA
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Matteson S, Paulauskis J, Foisy S, Hall S, Duval M. Opening the gate for genomics data into clinical research: a use case in managing patients' DNA samples from the bench to drug development. Pharmacogenomics 2010; 11:1603-12. [PMID: 21121778 DOI: 10.2217/pgs.10.151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The use of human genetic polymorphism data in drug development is not a recent event. Typically, the detection of patients' genetic variations in drug-metabolizing enzymes has become common practice in clinical laboratories. What is new is the scale and diversity of genomics data that has entered into the drug research and development decision-making process. At least three concurrent events contribute to this paradigm shift: first the growing body of evidence that establishes that interindividual variation in both therapeutic response and adverse events are attributable to a genetic component; second the technological progress that enables the consistent and reproducible detection of human genomic quantities; third the expectation that the productivity of new drug development will be increased by identifying which patients would benefit from candidate therapies early in the clinical process. This influx of human genomics data into clinical laboratories requires some logistical adjustment in terms of data management. The major specifications of an information solution system intended for a clinical genomic laboratory are its compliance with regulatory procedures, regarding the handling of human genetic data and its subsequent integration into an existing clinical data management system from the hosting institution. The purpose of this article is to inform the community of the challenges in setting up a center for genomics data that ensures accurate, traceable and integrated data for laboratory management. This is by no means the only way to accomplish the same goal, and is simply presented as one way that Pfizer chose to solve these issues.
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Abstract
The notion that developing countries must wait for the developed world to make advances in science and technology that they later import at great cost is being challenged. We have previously argued that developing countries can harness human genetic variation to benefit their populations and economies. Based on our empirical studies of large-scale population genotyping projects in Mexico, India and Thailand, we describe how these resources are being adopted to improve public health and create knowledge-based economies. A significant additional benefit is building the capacity for scientific research and internalizing advances in technology, whatever their source.
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Stallings SC, Huse D, Finkelstein SN, Crown WH, Witt WP, Maguire J, Hiller AJ, Sinskey AJ, Ginsburg GS. A framework to evaluate the economic impact of pharmacogenomics. Pharmacogenomics 2006; 7:853-62. [PMID: 16981846 DOI: 10.2217/14622416.7.6.853] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
INTRODUCTION Pharmacogenomics and personalized medicine promise to improve healthcare by increasing drug efficacy and minimizing side effects. There may also be substantial savings realized by eliminating costs associated with failed treatment. This paper describes a framework using health claims data for analyzing the potential value of pharmacogenomic testing in clinical practice. METHODS We evaluated a model of alternate clinical strategies using asthma patients' data from a retrospective health claims database to determine a potential cost offset. We estimated the likely cost impact of using a hypothetical pharmacogenomic test to determine a preferred initial therapy. We compared the annualized per patient costs distributions under two clinical strategies: testing all patients for a nonresponse genotype prior to treating and testing none. RESULTS In the Test All strategy, more patients fall into lower cost ranges of the distribution. In our base case (15% phenotype prevalence, 200 US dollars test, 74% overall first-line treatment efficacy and 60% second-line therapy efficacy) the cost savings per patient for a typical run of the testing strategy simulation ranged from 200 US dollars to 767 US dollars (5th and 95th percentile). Genetic variant prevalence, test cost and the cost of choosing the wrong treatment are key parameters in the economic viability of pharmacogenomics in clinical practice. CONCLUSIONS A general tool for predicting the impact of pharmacogenomic-based diagnostic tests on healthcare costs in asthma patients suggests that upfront testing costs are likely offset by avoided nonresponse costs. We suggest that similar analyses for decision making could be undertaken using claims data in which a population can be stratified by response to a drug.
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Affiliation(s)
- Sarah C Stallings
- Massachusetts Institute of Technology Program on the Pharmaceutical Industry (MIT POPI) and Department of Biology, USA
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Yengi LG. Systems biology in drug safety and metabolism: integration of microarray, real-time PCR and enzyme approaches. Pharmacogenomics 2006; 6:185-92. [PMID: 15882137 DOI: 10.1517/14622416.6.2.185] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
The last decade has seen a rapid expansion in the field of functional genomics, due mainly to the global gene expression profiling capabilities provided by techniques, such as microarray analysis. Application of these technologies in fields as diverse as plant research, to public health and environmental sciences, forensic science and drug research, shows the versatility of these tools and the promise they hold for revolutionizing research in the life sciences. In drug discovery, attempts have been made to use functional genomics in target identification and validation, lead selection and optimization, and in preclinical studies to predict clinical outcome. These studies have provided a plethora of data and undoubtedly expanded our understanding of genetic alterations in diseased and non-diseased states, but the benefits that these technologies hold have not yet been fully realized. This review discusses how a comprehensive approach to gene regulation studies, a 'systems biology' approach, is being applied in a drug development setting to address mechanism-based questions and issues raised by regulatory authorities.
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Affiliation(s)
- Lilian G Yengi
- Wyeth Research, Drug Metabolism Division, Drug Safety and Metabolism, 500 Arcola Road, Collegeville, PA 19426, USA.
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Phillips KA, Van Bebber SL. Regulatory perspectives on pharmacogenomics: a review of the literature on key issues faced by the United States Food and Drug Administration. Med Care Res Rev 2006; 63:301-26. [PMID: 16651395 DOI: 10.1177/1077558706287020] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Pharmacogenomics (PGx), the use of genetic information to individualize drug therapy, is an immediate and important application of the Human Genome Project. The advent of PGx presents challenges to the U.S. Food and Drug Administration (FDA) in pursuing its mandate of protecting public health and safety. The authors conducted a review of academic, industry, and government literature using a technology diffusion framework to identify issues faced by the FDA relevant to the application of PGx. Two hundred and ten articles were reviewed. Key issues were categorized as rationale and structure for PGx regulation, regulation of PGx-based testing technologies, regulation of applications in clinical settings, regulation of data, and regulation of product life cycles. This review identifies issues faced by the FDA with respect to PGx, which the FDA is addressing through several initiatives. It also illustrates the complex issues involved in developing, implementing, and adopting new technologies.
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