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Patient-Centered Care
Precision Medicine
Lecture a
This material (Comp 25 Unit 8) was developed by the University of Alabama at Birmingham, funded by the
Department of Health and Human Services, Office of the National Coordinator for Health Information
Technology under Award Number 90WT0007.
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
License. To view a copy of this license, visit http://creativecommons.org.
Precision Medicine
Learning Objectives
• Define precision medicine and key concepts associated
with it
• Describe the major current applications in the practice of
precision medicine
• Discuss national initiatives including the NIH Precision
Medicine Initiative
• Describe the activities of national research networks
focused on precision medicine
What is Precision Medicine?
• Precision Medicine
– “an emerging approach for disease treatment
and prevention that takes into account
individual variability in genes, environment,
and lifestyle for each person.”
• Personalized Medicine
• P4 Medicine
– predictive, personalized, preventive,
participatory
Source: (NIH, 2016, The Precision Medicine Initiative
Hood and Friend, 2011.)
Key Concepts
• Genetics: study of individual genes and role in
hereditary traits
• Genomics: study of all genetic material and
relationship with environment
• Genetic variation:
– SNPs (single nucleotide polymorphisms)
– INDEL (insertion / deletion)
• GWAS
– Scan of SNPs association with single phenotype
– Linking genomic variants with disease
Source (The Jackson Laboratory, 2016)
Key Concepts 2
• Genotype and Phenotype
• PheWAS
– Scan of phenotypes to determine association
with single gene variant
• Germline and somatic mutations
• Other “-omics”
– Proteomics
– Metabolomics
Source: (Denny et al 2010)
Key Concepts 3
• Exposome
– Individual exposures
o Environmental
o Internal
• Precision Medicine
– Genomics
– Other –omics
– Environment
– Lifestyle
Source: (Martin-Sanchez et al, 2014)
Analysis of Genetic Data
• Family Trees
• GWAS
• PheWAS
• Candidate gene association studies
Applications in Practice
• Pharmacogenomics
– Predict response to medications
– Tailored drug selection
– Adjust dosages
Source: (Denny, Wylie, Peterson, 2016)
Applications in Practice 2
• Oncology
– Diagnosis
– Therapy
– Prognosis
• Gene-disease associations
– Increased knowledge due to research on
germline testing
National Initiatives
• Precision Medicine Initiative
– National research cohort of >1 million people
• Research Networks
– eMERGE
– PGRN
– PCORnet
– IGNITE
Source: (Precision medicine cohort initiative, 2015; eMERGE network, 2014; PGRN 2016;
Pcornet, 2015; NIH, 2016)
eMERGE Network
• Electronic Medical Records and Genomics
• Integration of genomic data into the EHR
• Using the EHR to identify phenotypes
• Developing clinical decision support
• Integrating knowledge resources into EHR
Source: (Gottesman, et al. 2013)
Pharmacogenomics Research
Network (PGRN)
• Research on response to medications based on
genomics
• Research on tailoring medications to individuals
• Collaboration with eMERGE Network
Source: (Pharmacogenomics Research Network, 2016)
PCORnet
• Patient Centered Clinical Research Network
– Clinical Data Research Networks (CDRNs)
– Patient Powered Research Networks
(PPRNs)
• Funded by the Patient Centered Outcomes
Research Institute (PCORI)
Source: (Collins et al. 2014)
IGNITE
• Implementing GeNomics In PracTicE
• Funded by the NIH National Human Genome
Research Institute
• Demonstration projects
• Exploration of strategies to implement genomics
in clinical care
Source: (NIH, 2016)
Discovery Efforts in Precision
Medicine
• Geisinger
– Rural Pennsylvania
– Large data repository for quality improvement
and research
– Biorepository with over 45,000 individuals
– Opt-in genomic testing
Source: (Wade et al, 2014)
Discovery Efforts in Precision
Medicine 2
• Vanderbilt
– Biorepository (BioVU)
o Originally ‘Opt-out’
– Over 200,000 de-identified samples
– Transitioning to ‘Opt-in’ consent process
– Researchers use de-identified and identified
samples
Source: (Denny, Wylie, Peterson, 2016)
Implementation in Practice
• Pre-emptive vs reactive testing
– Test in advance and have data available
o Provide clinical decision support when needed
– Test when patient actually has disease
Source: (Denny, Wylie, Peterson, 2016)
Precision Medicine
Summary – lecture a
• Basic definitions
• National initiatives
• Examples of use of precision medicine in
clinical practice and research
Precision Medicine
References – lecture a
References
Collins, F. S., Hudson, K. L., Briggs, J. P., & Lauer, M. S. (2014). PCORnet: turning a dream into
reality. Journal of the American Medical Informatics Association : JAMIA, 21(4), 576–577.
www.ncbi.nlm.nih.gov
Denny, J. C., Ritchie, M. D., Basford, M. A., Pulley, J. M., Bastarache, L., Brown-Gentry, K., &
Crawford, D. C. (2010). PheWAS: demonstrating the feasibility of a pheonme-wide scan to
discover gene-disease associations. Bioinformatics, 26(9), 1205-1210. www.ncbi.nlm.nih.gov
Denny, J. C., Wiley, L. K., & Peterson, J. F. (2016). Use of Clinical Decision Support to Tailor Drug
Therapy Based on Genomics. In E. S. Berner, Clinical Decision Support Systems (Third ed.).
Springer. Forthcoming.
Gottesman, O., Kuivaniemi, H., Tromp, G., Faucett, W. A., Li, R., Manolio, T. A., … and The eMERGE
Network. (2013). The Electronic Medical Records and Genomics (eMERGE) Network: past,
present, and future. Genetics in Medicine, 15(10), 761–771. www.ncbi.nlm.nih.gov
Hood, L., & Friend, S. H. (2011). Predictive, personalized, preventive, participatory (P4) cancer
medicine. Nat Rev Clin Oncol, 8(3), 184-7. www.nature.com
The Jackson Laboratory. (2016). The Difference Between Genetics and Genomics. Retrieved April 27,
2016, from The Jackson Laboratory: www.jax.org
Martin Sanchez, F., Gray, K., Bellazzi, R., Lopez-Campos, G., & Martin Sanchez, F. (2014, May).
Exposome informatics: considerations for the design of future biomedical research information
systems. J Am Med Inform Assoc, 21(3), 386-390. www.ncbi.nlm.nih.gov
19
Precision Medicine
References 2 – lecture a
References
National Human Genome Research Institute. (2014). eMERGE NETWORK - Electronic Medical
Records and Genomics. Retrieved April 26, 2016, from eMERGE NETWORK:
emerge.mc.vanderbilt.edu
National Institutes of Health. (2016). IGNITE - Implementing GeNomics In PracTicE. Retrieved April
27, 2016, from Implementing GeNomics In PracTicE (IGNITE) Network: www.ignite-genomics.org
National Institutes of Health. (n.d.). Precision Medicine Initiative Cohort Program. Retrieved April 27,
2016, from Precision Medicine Initiative: www.nih.gov
Pharmacogenomics Research Network. (2016, April 26). Retrieved from PGRN: http://www.pgrn.org/
The National Patient-Centered Clinical Research Network. (2015). pcornet. Retrieved April 26, 2016,
from The National Patient-Centered Clinical Research Network: pcornet.org
Wade, J. E., Ledbetter, D. H., & Williams, M. S. (2014, March). Implementation of genomic medicine in
a health care delivery system: a value proposition? Am J Med Genet C Semin Med Genet, 112-6.
onlinelibrary.wiley.com
20
Patient-Centered Care
Precision Medicine
lecture a
This material was developed by the
University of Alabama at Birmingham,
funded by the Department of Health and
Human Services, Office of the National
Coordinator for Health Information
Technology under Award Number
90WT0007.
21

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Patient Centered Care | Unit 8a Lecture

  • 1. Patient-Centered Care Precision Medicine Lecture a This material (Comp 25 Unit 8) was developed by the University of Alabama at Birmingham, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number 90WT0007. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org.
  • 2. Precision Medicine Learning Objectives • Define precision medicine and key concepts associated with it • Describe the major current applications in the practice of precision medicine • Discuss national initiatives including the NIH Precision Medicine Initiative • Describe the activities of national research networks focused on precision medicine
  • 3. What is Precision Medicine? • Precision Medicine – “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” • Personalized Medicine • P4 Medicine – predictive, personalized, preventive, participatory Source: (NIH, 2016, The Precision Medicine Initiative Hood and Friend, 2011.)
  • 4. Key Concepts • Genetics: study of individual genes and role in hereditary traits • Genomics: study of all genetic material and relationship with environment • Genetic variation: – SNPs (single nucleotide polymorphisms) – INDEL (insertion / deletion) • GWAS – Scan of SNPs association with single phenotype – Linking genomic variants with disease Source (The Jackson Laboratory, 2016)
  • 5. Key Concepts 2 • Genotype and Phenotype • PheWAS – Scan of phenotypes to determine association with single gene variant • Germline and somatic mutations • Other “-omics” – Proteomics – Metabolomics Source: (Denny et al 2010)
  • 6. Key Concepts 3 • Exposome – Individual exposures o Environmental o Internal • Precision Medicine – Genomics – Other –omics – Environment – Lifestyle Source: (Martin-Sanchez et al, 2014)
  • 7. Analysis of Genetic Data • Family Trees • GWAS • PheWAS • Candidate gene association studies
  • 8. Applications in Practice • Pharmacogenomics – Predict response to medications – Tailored drug selection – Adjust dosages Source: (Denny, Wylie, Peterson, 2016)
  • 9. Applications in Practice 2 • Oncology – Diagnosis – Therapy – Prognosis • Gene-disease associations – Increased knowledge due to research on germline testing
  • 10. National Initiatives • Precision Medicine Initiative – National research cohort of >1 million people • Research Networks – eMERGE – PGRN – PCORnet – IGNITE Source: (Precision medicine cohort initiative, 2015; eMERGE network, 2014; PGRN 2016; Pcornet, 2015; NIH, 2016)
  • 11. eMERGE Network • Electronic Medical Records and Genomics • Integration of genomic data into the EHR • Using the EHR to identify phenotypes • Developing clinical decision support • Integrating knowledge resources into EHR Source: (Gottesman, et al. 2013)
  • 12. Pharmacogenomics Research Network (PGRN) • Research on response to medications based on genomics • Research on tailoring medications to individuals • Collaboration with eMERGE Network Source: (Pharmacogenomics Research Network, 2016)
  • 13. PCORnet • Patient Centered Clinical Research Network – Clinical Data Research Networks (CDRNs) – Patient Powered Research Networks (PPRNs) • Funded by the Patient Centered Outcomes Research Institute (PCORI) Source: (Collins et al. 2014)
  • 14. IGNITE • Implementing GeNomics In PracTicE • Funded by the NIH National Human Genome Research Institute • Demonstration projects • Exploration of strategies to implement genomics in clinical care Source: (NIH, 2016)
  • 15. Discovery Efforts in Precision Medicine • Geisinger – Rural Pennsylvania – Large data repository for quality improvement and research – Biorepository with over 45,000 individuals – Opt-in genomic testing Source: (Wade et al, 2014)
  • 16. Discovery Efforts in Precision Medicine 2 • Vanderbilt – Biorepository (BioVU) o Originally ‘Opt-out’ – Over 200,000 de-identified samples – Transitioning to ‘Opt-in’ consent process – Researchers use de-identified and identified samples Source: (Denny, Wylie, Peterson, 2016)
  • 17. Implementation in Practice • Pre-emptive vs reactive testing – Test in advance and have data available o Provide clinical decision support when needed – Test when patient actually has disease Source: (Denny, Wylie, Peterson, 2016)
  • 18. Precision Medicine Summary – lecture a • Basic definitions • National initiatives • Examples of use of precision medicine in clinical practice and research
  • 19. Precision Medicine References – lecture a References Collins, F. S., Hudson, K. L., Briggs, J. P., & Lauer, M. S. (2014). PCORnet: turning a dream into reality. Journal of the American Medical Informatics Association : JAMIA, 21(4), 576–577. www.ncbi.nlm.nih.gov Denny, J. C., Ritchie, M. D., Basford, M. A., Pulley, J. M., Bastarache, L., Brown-Gentry, K., & Crawford, D. C. (2010). PheWAS: demonstrating the feasibility of a pheonme-wide scan to discover gene-disease associations. Bioinformatics, 26(9), 1205-1210. www.ncbi.nlm.nih.gov Denny, J. C., Wiley, L. K., & Peterson, J. F. (2016). Use of Clinical Decision Support to Tailor Drug Therapy Based on Genomics. In E. S. Berner, Clinical Decision Support Systems (Third ed.). Springer. Forthcoming. Gottesman, O., Kuivaniemi, H., Tromp, G., Faucett, W. A., Li, R., Manolio, T. A., … and The eMERGE Network. (2013). The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future. Genetics in Medicine, 15(10), 761–771. www.ncbi.nlm.nih.gov Hood, L., & Friend, S. H. (2011). Predictive, personalized, preventive, participatory (P4) cancer medicine. Nat Rev Clin Oncol, 8(3), 184-7. www.nature.com The Jackson Laboratory. (2016). The Difference Between Genetics and Genomics. Retrieved April 27, 2016, from The Jackson Laboratory: www.jax.org Martin Sanchez, F., Gray, K., Bellazzi, R., Lopez-Campos, G., & Martin Sanchez, F. (2014, May). Exposome informatics: considerations for the design of future biomedical research information systems. J Am Med Inform Assoc, 21(3), 386-390. www.ncbi.nlm.nih.gov 19
  • 20. Precision Medicine References 2 – lecture a References National Human Genome Research Institute. (2014). eMERGE NETWORK - Electronic Medical Records and Genomics. Retrieved April 26, 2016, from eMERGE NETWORK: emerge.mc.vanderbilt.edu National Institutes of Health. (2016). IGNITE - Implementing GeNomics In PracTicE. Retrieved April 27, 2016, from Implementing GeNomics In PracTicE (IGNITE) Network: www.ignite-genomics.org National Institutes of Health. (n.d.). Precision Medicine Initiative Cohort Program. Retrieved April 27, 2016, from Precision Medicine Initiative: www.nih.gov Pharmacogenomics Research Network. (2016, April 26). Retrieved from PGRN: http://www.pgrn.org/ The National Patient-Centered Clinical Research Network. (2015). pcornet. Retrieved April 26, 2016, from The National Patient-Centered Clinical Research Network: pcornet.org Wade, J. E., Ledbetter, D. H., & Williams, M. S. (2014, March). Implementation of genomic medicine in a health care delivery system: a value proposition? Am J Med Genet C Semin Med Genet, 112-6. onlinelibrary.wiley.com 20
  • 21. Patient-Centered Care Precision Medicine lecture a This material was developed by the University of Alabama at Birmingham, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number 90WT0007. 21

Editor's Notes

  1. Welcome to Patient Centered Care, Precision Medicine. This is lecture A. Patient-centered care is broadly considered as attending to the unique values and needs of the individual patient, communicating about diagnosis and treatment in a way that the patient can understand, and engaging and involving patients in their own care.  The idea behind precision medicine is that a patient’s care should be crafted based on the unique characteristics of each patient—their genetics, their environment and their lifestyle.  Aspects of precision medicine are just beginning to be implemented in a few places, but are likely to exponentially expand over the coming years.  While precise definitions vary, precision medicine involves incorporating the use of biological and environmental data into clinical care to make both diagnosis and treatment more precise and effective.  While there are many types of ‘-omics’ (pronounced OH-micks) data, genomics is closest to broad adoption or translation into clinical practice and will be the focus of this unit.  This lecture will examine the basic concepts and some of the current initiatives in precision medicine.
  2. The objectives for this unit, Precision Medicine, are to: Define precision medicine and key concepts associated with it; Describe the major current applications in the practice of precision medicine; Discuss national initiatives including the NIH Precision Medicine Initiative; and Describe the activities of national research networks focused on precision medicine.
  3. According to NIH, precision Medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” It is called precision medicine because the assumption is with this additional information, we can be more precise about risks of disease or benefits of treatments for a given individual and can design treatments that are better tailored to the unique genetic, environmental, and lifestyle makeup of the individual. As an example, we have known for a long time that the anticoagulant clopidogrel (pronounced clo-PID-uh-grel), or Plavix, works for most patients, but not all. If we know that an individual has a gene that decreases clopidogrel’s effectiveness, we can develop a different treatment plan immediately, rather than waiting to see how the individual responds to the standard drug regimen. Not only is this less risky for the patient, it is likely to save costs as well. Although precision medicine is a relatively new term, older similar terms that are still used are personalized medicine and what has been called P4 medicine. P4 stands for “predictive, personalized, preventive, participatory”, a term coined by Leroy Hood.
  4. According to the Jackson Laboratory, which is an institution that breeds mice with certain characteristics so they can be used for research on diseases , Genetics “is the study of heredity, or how characteristics of living organisms are transmitted from one generation to the next.” Jackson Laboratory defines genomics as the “study of the entirety of an organisms’ genes—called the genome.” Research in genetics involves known genes, and often single genes known to cause a specific disease; genomic research often involves discovery of new associations, frequently of multiple genes by looking at whole genomes of individuals with or without some complex diseases. Scientists look for variants in what are called SNPs (pronounced snips) between these two groups. These genome-wide association studies, or GWAS (pronounced G-wass) discover associations that can form the basis for hypotheses for further genomic research.
  5. The genotype of an individual describes the specific genes in their body that were inherited from their parents. The phenotype describes an individual’s physical or clinical characteristics. PheWAS (pronounced fee-wass) are phenome-wide association studies, that scan the clinical record to determine phenotypes associated with a single gene variant. While the genotype remains stable over the course of a person’s life, there can be changes in individual cells of the body that are called mutations. If these mutations occur in the sperm or egg cells, they are called germline mutations and can be passed on to offspring. If they occur in other cells of the body, such as when cancer develops, they are known as somatic mutations. In addition to genomics, there are other –omics (pronounced OH-micks) that refer to “the studies of the roles, relationships and actions of the various types of molecules that make up the cells of an organism.” Examples include proteomics (pronounced Pro-T-omics) the study of proteins, and metabolomics (pronounced met-TAB-o-lomics), the study of cellular metabolism.
  6. Another concept that has not yet become very widespread is the idea of the “exposome” (pronounced expo-zome). The exposome refers to a detailed description, quantified if possible, of all of an individual’s exposures, both environmental and internal. Precision medicine will ultimately involve both genomic, other omics, as well as environmental and lifestyle data, but to date, most of the focus has been on genomic data and that is the focus of this presentation as well.
  7. For many years we have incorporated genetic data into clinical care by collecting data on family trees and using that data to identify genetic diseases. With genome-wide association studies we have generated many hypotheses to test specific associations of a variety of genes with specific clinical conditions. Conversely, with the increased availability of clinical data in electronic form we have moved to PheWAS studies, looking at phenotypes associated with specific gene variants. Finally, in using these data we can identify candidate genes for specific association studies. These studies are adding to our knowledge that bring us closer to widespread application to clinical care.
  8. While geneticists and genetic counselors use a variety of genomic analyses in their work, there are two areas where genomics has already found its way beyond the researchers and genetic specialists into other areas of clinical practice. One of these areas is pharmacogenomics (pronounced FARM-uh-co-GEN-o-micks) which uses genomic data to make prescribing more precise. The example we gave earlier of clopidogrel prescribing is an example of using genomics to predict responses to medication and select the most appropriate medication. Other uses have been to assist with dosing, where genomics is used to identify individuals who have increased or decreased sensitivity to a given medication. Warfarin dosing informed by genomic testing can prevent dangerous side effects of this potent medication.
  9. Oncology is another area that has made use of genomic data for more precise diagnosis of the type of cancer and more precise therapy. In addition to genetic testing to determine if a patient has mutations in a specific gene such as BRCA 1 or 2 (pronounced B-R-C-A) that would increase the risk of breast cancer, analysis of the genome of the cancer tumor itself can provide information on sensitivities of the tumor to various types of treatments. For oncology, prognosis is also highly altered by tumor gene molecular subtypes. For example, if a patient has what is known as “triple-negative breast cancer” there is no target for therapy. The type of testing involved in the oncology applications is somatic testing that examines characteristics of the tumor cell, but the research on germline testing has led to more knowledge about gene-disease associations.
  10. There are several national initiatives that promise to dramatically increase the knowledge we will have for incorporating precision medicine into clinical practice. NIH’s Precision Medicine initiative that was announced by President Obama in the 2015 State of the Union address involves increasing NIH funding to build a “national research cohort of one million or more Americans” who will provide both genomic and clinical data for research. This cohort will cover a broad range of diseases, in fact, NIH says “all diseases.” There is additional funding specifically targeting precision medicine in oncology. This new effort and funding will supplement some existing research networks that themselves have developed large cohorts of patients. Three networks that have been ongoing include the eMERGE (pronounced emerge) Network, the Pharmacogenomics Research Network or PGRN (pronounced P-G-R-N), and PCORnet (pronounced P-Core-net).
  11. The NIH-funded eMERGE Network as of the end of 2015 consists of nine institutions. EMERGE stands for “Electronic Medical Records and Genomics.” Each of the 9 institutions obtains both clinical and genomic data from individuals, but they also use the electronic health record to identify phenotypes for different diseases. They have a library of phenotypes that others with EHRs can use. Current foci (pronounced foe-sigh) for eMERGE are integrating genomic data into the EHR and integrating clinical decision support and knowledge resources for precision medicine into the EHR.
  12. The Pharmacogenomics Research network or PGRN does research on identifying how individuals respond to medication based on their genetic characteristics and studies the impact of tailoring medications to an individual’s unique genetic make-up. They have collaborated with the EMERGE network on studying several medications including warfarin and clopidogrel.
  13. PCORnet consists of two types of research networks, although both of them are collecting both clinical and genomic data on individuals. The CDRNs (pronounced C-D-R-Ns) are building the infrastructure to extract data from EHRs for research. Each CDRN consists of multiple institutions who will be conducting research using the data in their EHR systems. The second type of network is the PPRN. Each PPRN (pronounced P-P-R-N) is engaging patients with a particular disease to contribute data for research. The PPRNs are particularly interested in comparative effectiveness research related to their disease. The two networks obviously can work together with the PPRN enriching what is already the EHRs that can be shared over the PCORnet infrastructure.
  14. Another research network is the IGNITE consortium. Ignite stands for implementing genomics in practice, an acronym that is a bit of a reach but does sound better than IGNIP or IGIP. The aim of the consortium, which involves six academic institutions, some of which are also eMERGE or PGRN sites, is to conduct demonstration projects and study strategies for effective implementation and sustainability. These national initiatives will greatly increase the evidence base for precision medicine, but they will do more than that. The engagement of large numbers of people in research that supports precision medicine will also educate them and make it easier to translate this research into practice. The use of precision medicine in practice, however, has already begun.
  15. As an example, several large healthcare systems have made precision medicine a priority. Both Geisinger (pronounced Guy-singer) Health System and Vanderbilt University are part of the eMERGE Network, but their work to build genomic repositories predated their participation in the eMERGE Network. Geisinger, a large integrated delivery system in rural Pennsylvania has had an electronic health record since 1995 that includes a data repository for research and quality improvement. They started a biorepository in 2007 and have consented over 45,000 individuals. Individuals have to opt in to have their data included in the biorepository.
  16. Until recently, Vanderbilt had one of the few opt-out biorepositories. When patients signed the consent for care forms, they were told that leftover blood or other tissue samples may be used for research, including genomic research. Patients could opt out of having their samples in the data repository, but few did. Vanderbilt’s repository has over 200,000 unique individuals, but they have now transitioned to an opt-in model like Geisinger’s. Vanderbilt’s basic biorepository, called BioVU (pronounced bio-view) is de-identified, but some projects have used identified data as well.
  17. Both Geisinger and Vanderbilt have incorporated genomic data into their Electronic Health Records by using what is known as pre-emptive genetic testing. That is, they test the patient’s blood samples for known disease associated genetic variants, such as those that lead to decreased sensitivity to clopidogrel, and then provide clinical decision support so that the information is available to physicians when they have a patient for whom they would ordinarily prescribe clopidogrel. The alternative to pre-emptive testing is reactive testing, which is testing done only when the patient has a condition that needs the test. There is debate over which approach is best.
  18. This concludes Precision Medicine, Lecture a. In summary, we have defined some of the basic concepts that underlie the new model of person-centered care known as precision medicine. We discussed national initiatives and gave examples of its use in clinical practice and research, including pharmacogenomics and cancer care.
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