This document discusses various approaches to personalized and precision medicine, including stratified medicine, personalized medicine, and precision medicine. It also discusses the role of biomarkers, pharmacogenomics, genetic testing, biobanking, and examples of individualized cancer treatments. Key points include the use of targeted medicines based on disease stage or individual information, and ensuring best outcomes while reducing side effects. The goal of precision medicine is to integrate genomic data to guide health and disease prevention.

1. Medhavi Vashisth
2018BS09D (Dept. of MBB&B)
medhavi3868@gmail.com
CCS Haryana Agricultural University, Hisar

2. Personalized Medicine
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3. Different Approaches
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• Stratified medicine – It is the use of medicine that is targeted at a patient
sub-population (a group of patients eg. having a particular disease stage),
instead of use one medicine to treat all patients with the disease.
• Personalized medicine – It aims to use targeted medicines taking into
account the other individual information to tailor the treatment and
management of the patient to their particular situation. It is used to
ensure the best outcome and reduce the risk of side effects.
• Precision medicine - Precision medicine describes a model for health care
delivery that relies heavily on data, analytics, and information.
Mathur, S., & Sutton, J. (2017). Personalized medicine could transform healthcare. Biomedical
reports, 7(1), 3–5. doi:10.3892/br.2017.922

4. Role of Precision/Personalized Medicine
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5. 3/14/2023 5

6. Translational Genomics Research Model
T0-T4 research Model
• T0 (Initial discovery) - Genomic discovery research including new genomic
variants, biomarkers and other basic science discoveries.
• T1 - Research encompasses the development of new diagnostic tests or
interventions in the clinical setting but in a limited fashion. ( Eg.-
evaluating the function of genomic variants.)
• T2 - Research evaluates the clinical utility of candidate genomic
applications in clinical practice.
• T3 - Research includes studies that assess implementation and integration
of genomics into routine clinical practice.
• T4 - Research evaluates population health impact of genomic medicine.
Khoury M.J., Gwinn M., Yoon P.W., Dowling N., Moore C.A., Bradley L. The continuum of translation research in
genomic medicine: how can we accelerate the appropriate integration of human genome discoveries into health care
and disease prevention? Genet. Med. 2007 Oct;9(10):665–674
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7. Integrating Translational Genomics
with Personalized Medicine
Molidor, R. (2003). New trends in bioinformatics: from genome sequence to personalized medicine. Experimental
Gerontology, 38(10), 1031–1036. doi:10.1016/s0531-5565(03)00168-2 7

8. Paving the way forward
Genome sequencing
• Copy number variation
• Transcriptional readouts
• Comprehensive measurements of:
• micro RNA, ncRNA, lncRNA
• Proteins
• Metabolite levels (Systems approach)
Biomedical assays/tests
Computational biology
• Bioinformatics
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9. Timeline of Sequencing technologies
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10. Pharmacogenomics
• Pharmacogenetics (the study of inherited
variation in a single gene and associated
effects on drug disposition, metabolism,
toxicity, and response)
• Pharmacogenomics (the study of inherited
variation across many different genes that
determine drug disposition, metabolism,
toxicity, and response).
Samuel G. Johnson. 2017. Genomic Medicine in Primary Care. Genomic and Precision Medicine. Doi:
http://dx.doi.org/10.1016/B978-0-12-800685-6.00001-1 10

11. • Pharmacokinetics (PK) is concerned with the processes that govern a
drug’s path through the body and its resulting concentration in different
body compartments. (ADMET)
• Pharmacodynamics (PD), in contrast, is concerned with the physiological
and behavioral consequences produced by that subset of drug molecules
that find and occupy receptors during their journey through the body.
• N-of-1 trials
• Umbrella trials
• P4 medicine - predictive, personalized, preventive,
and participatory medicine.
Negus, S. S., & Banks, M. L. (2018). Pharmacokinetic-Pharmacodynamic (PKPD) Analysis with Drug
Discrimination. Current topics in behavioral neurosciences, 39, 245–259. doi:10.1007/7854_2016_36 11

12. BIOMARKERS
Drucker, Elisabeth & Krapfenbauer, Kurt. (2013). Pitfalls and limitations in translation from biomarker discovery to
clinical utility in personalised medicine. The EPMA journal. 4. 7. 10.1186/1878-5085-4-7
Naylor S. (2003). Biomarkers: Current perspectives and future prospects. Expert Rev Mol Diagn. 3(5):525-9.
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Biomarkers
Stratification Efficacy Differentiation Toxicity Screening Prognosis
Biological characteristics that can be objectively measured and evaluated as an
indicator of normal biological processes, pathogenic processes, or pharmacological
responses to a therapeutic intervention. (Naylor S. 2003)

13. Companion Diagnostics
• Pharmaceutical companies are increasingly looking
to develop a drug and diagnostic test simultaneously,
in a process referred to as drug-diagnostic-co-
development so-called companion diagnostic (CDx),
to better define the appropriate patient population
for treatment. CDx are increasingly important tools in
drug development:
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14. Drug Labelling
Pharmacogenomics can play an important role in identifying responders and non-
responders to medications, avoiding adverse events, and optimizing drug dose.
Drug labelling may contain information on genomic biomarkers and can describe:
• Indications and usage
• Dosage and administration
• Contraindications
• Warning and Precautions – Hypersensitivity
• Adverse reactions
• Drug interactions
• Use in specific populations
• Clinical Pharmacology
• Patient Counselling information
• Clinical Trials
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15. Genetic Testing
Genetic diagnosis-
• >3000 Mendelian disease genes have been identified and catalouged in OMIM
Genetic Testing Registry-
• >31,000 marker tests for 5800 conditions relating to 3900 genes
Genotype-Phenotype causation
Various testing procedures-
• Single gene sequencing
• Exome sequencing
• Genome sequencing
• Oligonucleotide microarray
• Karyotype
Thomas Morgan. 2017. Genetic Testing for Rare and Undiagnosed Diseases. Genomic and Precision Medicine.
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16. Advantages of Biomarkers
• Objective assessment
• Precision
• Reliable; validity can be established
• Less biased than conventional diagnostics
• Disease mechanisms often studied
• Homogeneity of risk or disease
• Delineation of events between exposure and disease
• Establishment of dose-response
• Identification of early events in the natural history
• Identification of mechanisms by which exposure and disease are related
• Reduction in misclassification of exposures or risk factors and disease
• Establishment of variability and effect modification
• Enhanced individual and group risk assessments
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17. Limitations
• Majority stopped at the first phase of biomarker discovery
• Phase I - preclinical exploratory studies to identify potentially useful markers
• Phase II - clinical assay development for clinical disease
• Phase III - retrospective longitudinal repository studies
• Phase IV - prospective screening studies
• Phase V - control studies
• Lack in study
• Lack in execution
• Insufficient validation
• Most of them do not possess the required sensitivity and specificity
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18. Biobanking
• In many respects, genomic research is at its most useful when conducted
at scale. In order to identify patterns in populations in a reliable and
repeatable manner, researchers must have access to large volumes of
patient data.
• Biobanking, or the act of collecting and storing samples of DNA from
groups of individuals (typically blood, saliva, and/or urine), allows
researchers to access larger pools of potential subjects who have already
signalled a willingness to participate in studies or trials.
• Contain clinical specimens and a range of data for the purposes of
• Large-scale genetic epidemiology studies
• Biobanks have proliferated in recent years as healthcare provider systems
and government agencies recognize the need to have as much data
available for research as possible.
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19. Examples of invidualized treatments
• Examples for individualized treatments of cancer include HER2 (Human Epidermal
Growth factor receptor2)/neu-positive breast cancers that are treated with the
monoclonal antibody trastuzumab (Herceptin™) and poly(ADP-ribose) polymerase
(PARP-) inhibitors used in clinical trials to treat patients with BRCA1- or BRCA2-
deficient breast cancers.
• The inhibition of poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP) is a
potential synthetic lethal therapeutic strategy for the treatment of cancers with
specific DNA-repair defects, including those arising in carriers of a BRCA1 or BRCA2
mutation
Fong P.C. et al. 2009. Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation. JSN Engl J Med.
2009 Jul 9; 361(2):123-34. 19

20. Blood Pressure gene Discovery
• Elevated blood pressure (BP) or hypertension [≥140 mmHg (SBP) and/or ≥ 90
mmHg (DBP)] is estimated to cause 9.4 million deaths, and 7% of disease burden in
global population.
• Hypertension is a major risk factor for cardiovascular disease (CVD), and if left
uncontrolled, it causes myocardial infarction, stroke, cardiac failure, and renal
failure.
• Causes- Lifestyle and Genetic
• Evidence for a genetic component comes from studies of families and twins, and a
recent study in twins suggests that the heritability (the fraction of BP variance
contributed by genetic factors) for both SBP and DBP is approx 50%.
• Recent advances in human genetics offer the opportunity to discover hitherto-
unknown mechanisms and pathways affecting BP, which could in principle be
targeted by novel therapeutic approaches and thus improve treatment of
hypertension and prevention of CVD.
Menni C, et al. Heritability analyses show visit-to-visit blood pressure variability reflects different pathological
phenotypes in younger and older adults: evidence from UK twins. J Hypertens 2013;31(12):2356–61.
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21. Timeline for discovery of BP associated loci
3/14/2023 21

22. Treatment of NSCLC
• Drugs that target cells with EGFR gene changes
• Epidermal growth factor receptor (EGFR) is a protein on the surface of cells. It
normally helps the cells grow and divide. Some NSCLC cells have too much EGFR,
which makes them grow faster. Drugs called EGFR inhibitors can block the signal
from EGFR that tells the cells to grow. Some of these drugs can be used to treat
advanced NSCLC (Non Small Cell Lung Carcinoma).
• EGFR inhibitors that target cells with the T790M mutation
• Drugs that target cells with ALK (anaplastic lymphoma kinase) gene changes
• Drugs that target cells with ROS1 (Tyrosine receptor Kinase Proto oncogne)gene
changes
• Drugs that target cells with BRAF (Rapidly Accelerated Fibro Sarcoma)gene
changes
• Drugs that target cells with MEK (Mitogen-activated Protein/Extracellular Signal-
regulated Kinase Kinase) gene changes
• Drugs that target cells with NTRK (Neurotrophic tyrosine receptor kinase) gene
changes
https://www.cancer.org/content/cancer/en/cancer/lung-cancer/treating-non-small-cell/targeted-
therapies.html
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23. Jerry, John & Herrington, David. (2005). Maintenance warfarin dose varies according to two haplotypes of the
vitamin K epoxide reductase gene. Future cardiology. 2. 29-32. 10.2217/14796678.2.1.29. 23

24. Warfarin
• Anticoagulant of choice for cardivascular disease, thromboembolic
disease, and prophylactic post-surgery application.
• 15th most prescribed drug and 1st in category of accidents and adverse
reactions (bleeding)
• Very narrow therapeutic index and individualized dosing mandatory.
Effective daily dose 0.5 to 80mg.
• When initiating warfarin therapy, clinicians assess risks of thrombosis and
hemorrhage due to under- and over-anticoagulation, respectively.
• Mechanism-
• Activation of coagulation factors II, VII, IX and X by carboxylation requires
vitamin K
• VitK generated by vitK-epoxide-reductase (VKORC).
• Warfarin (and other oral anticoagulants) inhibits this enzyme complex.
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25. Methods
• Patients of European ancestry in anticoagulation clinics had their charts
retrospectively analyzed for variation in mean maintenance warfarin dose.
Single nucleotide polymorphisms (SNPs) in the VKORC1 gene were
identified in 186 patients, with five major haplotypes being inferred.
Multiple linear regression analysis was used to determine the association
with warfarin dose.
• The association between VKORC1 haplotype and warfarin dose was
replicated in a larger secondary population of 368 patients.
• Haplotype frequencies of VKORC1 were evaluated in diversity population
samples of human DNA obtained from cell repositories of individuals of
European, Asian and African ancestry.
• VKORC1 mRNA expression was obtained from human liver samples of
patients with European ancestry and correlated with haplotype.
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26. Results
• Ten common SNPs of the VKORC1 gene were identified. Five major
haplotypes were inferred from these SNPs and separated into a low-dose
group (A) and a high-dose group (B). Mean doses of maintenance warfarin
dose were 2.7 mg for A/A, 4.9 mg for A/B, and 6.2 mg for B/B haplotype
group combinations, which were statistically significant at the p < 0.05
level when haplotype combinations A/B and B/B were compared with A/A.
These associations persisted in a larger replication population.
• These haplotype groups explained 25% of the variance in warfarin dose.
• In the diversity samples of DNA, Asians had a higher proportion of low-
dose haplotypes, while African–Americans had a higher proportion of
high-dose haplotypes.
• High-dose haplotype groups of the VKORC1 gene expressed relatively
higher amounts of mRNA when compared with low-dose haplotypes
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27. Significance
• Haplotypes of the VKORC1 gene are associated with inter-individual
variations in mean maintenance warfarin dose in patients of European
ancestry. The putative mechanism for this association may be haplotype-
associated differences in transcriptional regulation of vitamin K epoxide
reductase production.
• Future research regarding adjustment of warfarin dose based on
knowledge of VKORC1 haplotype and its relation to clinical outcomes are
necessary.
• As genetic testing becomes more available, clinicians will likely incorporate
clinical variables as well as patient genotype in determining appropriate
pharmacotherapy for patients.
• Knowledge of VKORC1 haplotype and other environmental factors may be
useful to prospectively estimate an individual’s maintenance warfarin
dose.
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28. Precision Medicine Initiative
• What is the Precision Medicine Initiative?
• The Precision Medicine Initiative is a long-term research endeavor, involving the
National Institutes of Health (NIH) and multiple other research centers, which aims
to understand how a person's genetics, environment, and lifestyle can help
determine the best approach to prevent or treat disease.
• The Precision Medicine Initiative has both short-term and long-term goals. The
short-term goals involve expanding precision medicine in the area of cancer
research. Researchers at the National Cancer Institute (NCI) hope to use an
increased knowledge of the genetics and biology of cancer to find new, more
effective treatments for various forms of this disease. The long-term goals of the
Precision Medicine Initiative focus on bringing precision medicine to all areas of
health and healthcare on a large scale.
https://ghr.nlm.nih.gov/primer/precisionmedicine/initiative
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29. 1000 Genomes Project
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30. Auton A. et. al. (2015). A global reference for human genetic variation. Nature. 526. 68.
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31. The HapMap Project
International HapMap Consortium (2005). A haplotype map of the human genome. Nature, 437(7063), 1299–1320.
doi:10.1038/nature04226
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32. Cost of sequencing the genome over years
$1000 Genome
https://www.genome.gov/about-genomics/fact-sheets/DNA-Sequencing-Costs-Data
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33. Private companies Year Cost of genome sequencing
Knome 2007 $350,000
Illumina 2008 $100,000
Applied Biosystems $60,000
Helicos Biosciences 2009 $48,000
Complete Genomics 2010 $5000
Illumina (HiSeq X Ten
Sequencer)
2014 $1000
Veritas Genetics 2015 $1000
Dante Labs 2017 $900
Beijing Genomics Institute 2017 $600
Dante Labs 2018 (Sale!!!) $200
Veritas Genetics 2018(Black
Friday)
$199
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34. 3/14/2023 34

35. Project Baseline
3/14/2023 35

36. 36

37. Translational Informatics
• It is true that significant breakthroughs and advancement of deep
sequencing and other analytical technologies have greatly expanded the
pool of available biological data, but integrating this data into medically
meaningful knowledge via translational informatics remains an area of
opportunity that is far from being fully realized
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38. Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level
classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118.
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39. Benefits from Personalized Medicine
• Proactive and preventive
approach as opposed to the
current model in health care
that is reactive & episodic.
• Improved disease - risk
assessment
• Precise selection of drug
therapy
• Diagnosis and prognosis
• Maximizing health benefits
• Minimize unnecessary harms
• Reduction of healthcare costs.
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40. Limitations
• New medical discoveries often outpace an individual specialist practitioner’s ability
to master it as well.
• Scientific challenges (a poor understanding of molecular mechanisms or a lack of
molecular markers associated with some diseases, for example)
• Genomic literacy: education and counseling
• Economic aspects
• Operational issues in public healthcare systems
• Ethical aspects
• Medical insurance policies
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41. Health care today versus the
precision medicine ideal
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42. SYMBOL OF TRUST