Components of the Precision Medicine Approach

Precision Medicine encompasses several subareas that contribute to the whole range of activities from drug discovery, development, and use, through to disease prediction and monitoring. These areas include pharmacogenetics/pharmacoge- nomics, biomarkers, drug metabolism and metabolomics, and these are discussed in more detail below.

Pharmacogenetics and Pharmacogenomics

Pharmacogenomics is the study of the influence of genetic variation on drug response by attempting to correlate singlenucleotide polymorphisms (SNPs) or gene expression with an agent’s efficacy or toxicity. The aim is to develop a rational approach to optimize drug therapy for individual patients by maximizing efficacy and minimizing side effects. The terms pharmacogenomics and pharmacogenetics are often used interchangeably and attempts to agree precise definitions have failed. However, pharmacogenetics is usually regarded as the study or clinical testing of genetic variation that gives rise to differing responses to drugs, while pharmacogenomics is the broader, whole genome, application of genomic technologies to new drug discovery and the further characterization of older drugs. In other words, pharmacogenomics is the application of pharmacogenetics, which examines single-gene interactions with drugs.

Metabolism and Its Effect on Drug Efficacy and Toxicity

Another application of biomarkers is for the prediction of metabolism and thus drug exposure in individual patients. Most of the validated markers recommended for testing, such as thiopurine methyltransferase (TPMT) or UDP- glucuronosyltransferase 1A1 (UGT1 Al), are used to assess susceptibility to toxicity. An application of this can be seen in the AmpliChip CYP450, produced through a partnership between DNAVision and Roche, a diagnostic test to genotype patients based on two CYP450 enzymes (2C9 and 2D6).

Based in Belgium, DNAVision is one of the leading providers of Precision Medicine diagnostic services to physicians in Europe. The company genotypes genes encoding drug metabolism enzymes, targets, transporters, and receptors, and provides this information before treatment is started so that a physician can make the best treatment choices. This can avoid unresponsiveness to a drug, adverse drug reactions, and medication withdrawals. Most studies have been carried out with antidepressants, neuroleptics, and oncology agents. In particular, DNA Vision provides genotyping results (validated and ISO17025 accredited by the Belgium authorities) relating to drugs which carry a warning about pharmacogenetics in their labeling such as those shown below in Table 11.3.


Metabonomics (also known as metabolomics) is the profiling of endogenous metabolites in biofluids (/.

TABLE 11.3

Examples of Metabolizing Enzymes That Can Be Monitored to Predict the Outcome of Treatment in a Precision Medicine Approach


Metabolizing Enzymes



Acenocoumarol (Sintrom™)

Atomoxetine (Strattera™)


Irinotecan (Camptosar™)


Omeprazole (Losec™/Logastric™)


Tamoxifen CYP2D6 CYP2C9/VKORC1

Warfarin (Coumarin™)


A “biomarker” has been defined by a US National Institute of Health (NIH) Working Group as a “characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathological processes or responses (pharmacological or otherwise) to a therapeutic intervention”. Thus, biomarkers can range from patient performance status through to measurements of gene and/or protein expression profiles, with the latter, more complex measurements gaining pace as more advanced analytical technologies are developed. The parameter measured in practice can vary widely depending on context, available technologies, authority guidelines, and ethical aspects. Examples of the main categories and subcategories of biomarkers are shown in Figure 11.2.

Physiological parameters, including patient performance status, are well-known biomarkers that have been used since the dawn of medicine to follow disease progression and treatment benefit. These could include other items of patient information such as medical or family background, or even behavioral tests in the case of neurological or psychiatric diseases. It could also include simple palpation in the case of a tumor to gauge size, or patient appearance in the case of other diseases (e.g., jaundice). Since the discovery of X-Rays, imaging techniques have also been used as biomarkers, and today’s sophisticated imaging technologies include Computer Assisted Tomography (CAT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET). Biochemical biomarkers are chemical entities, usually proteins, that can be detected in biological fluids or on cell surfaces, and these have rapidly gained in importance in the last decade.

Main Categories:

Biomarker Type



• Predisposition

• Am 1 going to get cancer?

• See below

• Screening

• Have 1 got cancer?


• Diagnostic

• What kind of cancer is it?

• NMP22 and BTAstat

• Prognostic

• How aggressive is my cancer?

• MammaPrint™

• Predictive

• What is the best treatment?

• Her2/Herceptin™


• Will 1 have side effects to treatment?

• UGTIAl/lrinotecan

• Pharmacological

• Is the drug hitting the right target?

• See below

• Surrogate Response

• Is the treatment working?

• MRI, X-ray, PET, PSA

Biomarker Sub-Categories:

Biomarker Type




• Do 1 have DNA sequences predisposing me to cancer?


aCarcinogen involvement

• Have 1 been exposed to any carcinogens that might promote cancer?

• Aflatoxin-DNA Adducts

• Pharmacokinetic

• Is the drug getting to the target?

• Blood/tissue analysis

• Pharmacodynamic

• Does the drug work through the intended mechanism?

• Caspase, DNA cross-links

FIGURE 11.2 The main categories and subcategories of biomarkers in oncology.

Well-known examples include PSA (Prostate Serum Antigen) in the blood that can be used as an aid to predict the risk and progress of prostate cancer, and cell-surface receptors such as Her-2 that can be used to determine best treatment for breast cancer (i.e., Herceptin™).

Cell-based biomarkers include either whole cells or cell fragments (e.g., cell membranes) in biological fluids such as blood, lymph, urine, or saliva. This approach has been used to detect circulating cancer cells in blood for most forms of leukemia for many decades. However, more recently, sensitive analytical techniques have been developed capable of detecting circulating cancer cells (CCTs) released into the blood stream, urine or saliva by some solid tumors (see “Emerging Technologies”, Section 11.5.3),

At the gene level, various technologies allow genetic mutations (e.g., SNPs) to be measured in the DNA of cells, and this has led to the recognition of well-known biomarkers such as the BRCA1 and BRCA2 mutations associated with inherited breast cancer. In the last two decades, more sophisticated analytical methods based on “Genomic Profiling” (i.e., Transcriptone Analysis) and “Protein Expression Profiling” (i.e., Proteome Analysis) have been developed which are starting to be used in the oncology area to predict the risk of a cancer occurring, the aggressiveness of tumors, the risk of the disease returning after treatment, and to suggest the best treatments. These genotype profiling techniques include the detection of mutations, methylations (i.e., epigenetics), loss of heterozygosis [LOH], quantitative trait locus [QTL], perturbations in gene expression patterns, and changes to protein levels. A related approach known as “metabonomics” profiles a patient’s biological fluids for the presence and range of a variety of metabolites, the pattern of which can indicate the presence and/or progress of a disease and suggest the likely response to therapy (see Section 11.4.3).

In terms of the clinical usefulness of the various types of biomarkers described above, two well-known researchers in this area (Marrer and Dieterle) have commented that that metabonomic measurements indicate “what has happened”, proteomic measurements represent “what is happening now”, and genetic and genomic measurements suggest “what could happen”. A history of the development of biomarker technologies is summarized in Figure 11.3.

Finally, biomarkers are now important in every phase of drug development from drug discovery through to approval, and this is discussed further in Section 11.6.7. Until recently, traditional and well-established clinical tests such as serum creatinine levels to monitor kidney function were the mainstay of regulatory decision-making. However, in the so-called “Critical Path Initiative” based on a 2004 FDA “White Paper”, there was a call for efforts to modernize the tools and methods used for the discovery and development of drugs to enhance both efficacy and safety. This resulted in regulatory bodies such as the FDA, MHRA and EMA viewing biomarkers as a critical component of the drug discovery and development process, and biomarkers are now becoming important for labeling requirements on drug products.


Epigenetics is an area of rapidly growing importance, and has been discussed in some detail in Chapter 5 in relation to nucleic acid-based therapeutics. The term essentially refers to the presence or absence of patterns of methylation on genes

Summary of the development of biomarker technologies

FIGURE 11.3 Summary of the development of biomarker technologies.

and patterns of methylation and acetylation or deacetylation on histone proteins. These chemical changes to the DNA helix and its associated histone proteins are now understood to directly influence the expression of individual genes and are remarkable in that they can be modified during the lifetime of an individual and can then be passed on to the next generation. New therapeutic strategies are beginning to emerge based on reversing the DNA methylation process and inhibiting histone deacetylation. These approaches are being supported by the development of novel methodologies to rapidly screen and evaluate DNA methylation and histone acetylation patterns in the human genome (see Section

In the cancer area, there is growing evidence that tumor cells find ways to alter methylation and histone acetylation patterns throughout their genome to benefit their survival. It is now thought that identifying epigenetic alterations in a pre- cancerous lesion could lead to the discovery of biomarkers that may add to knowledge of risk assessment and early detection, and potentially provide molecular targets for chemopreventive intervention. An important distinction between genetic and epigenetic changes in cancer cells is that the latter might be more easily reversible through therapeutic intervention. Examples of current approaches to new therapies include the inhibition of DNA methylation and histone deacetylation as described in Chapter 5.

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