Lecture 27- Genomics, Medicine and Pharmaconomics Copyright © 2010 Pearson Education Inc.

Lecture 27- Genomics, Medicine and

Pharmaconomics

Copyright © 2010 Pearson Education Inc.

Contents

1. Medical promise of genomics2. High-throughput methods for genotyping3. Cancer genomics4. The problem of variable drug response5. Polymorphisms affecting drug efficacy

a. In drug metabolismb. In drug transportersc. In drug targets

6. Pharmacogenomics in drug development© 2005 Prentice Hall Inc. / A Pearson Education Company / Upper Saddle River, New Jersey 07458

What can be gained from genomics applied to pharmacy

1. Drug, diagnostics, and prognostics development

2. Genotyping to predict patient susceptibility to disease

3. Personalized healthcare based on an individual’s genomic features

© 2005 Prentice Hall Inc. / A Pearson Education Company / Upper Saddle River, New Jersey 07458

decision support systems

genotype

molecular profile

patient history

knowledge base

drugs diagnostics prognostics

genome health

pharma R&D patient care


Long-term returns

1. Personalized genotype databases

a. Used to assess health risks throughout life

b. Prescribe adjustments to lifestyle and medical treatment

2. Simulated cells

a. Reduce the need for time-consuming experiments

b. Allow experiments that would otherwise be impossible

3. New frameworks for clinical trials

a. Pharmacogenomics

Short-term returns

1. Faster characterization of disease genes

2. Better disease diagnosis and prognosis with microarrays

3. Better methods for genotyping

4. More efficient drug and vaccine development


Advances in disease genetics

1. Detection of disease genes is most direct medical use of genomics information

2. Over 1,000 disease genes were characterized by 2000

3. How to exploit this information?

250

0

Year of discoveryD

ise

ase

gen

es

1981 2000


Preimplantation diagnosis

1. Couples with at least one child suffering from cystic fibrosis underwent preimplantation diagnosis

2. Biopsied cells from in vitro three-day-old embryos were genotyped

3. Implanted embryos (NN and ND) in one couple resulted in a healthy baby girl

BAD diagnosis

homoduplexheteroduplex

biopsied cell DNA added

1 2 3 4 5 6


Single-nucleotide polymorphisms (SNPs)

Benefits of characterizing SNPs High-density SNP map - disease genes and cancer SNPs as a diagnostic Millions of SNPs presently in public and private

databases

1. Cancer Genome Anatomy Project (CGAP)

2. Human Cancer Genome Project (HCGP)

3. Cancer Genome Project (CGP)


Microarrays and cancer

1. Classic Histology not always effective

2. Microarrays distinguish cancerous tissues on the basis of a gene expression profile

a. Use in diagnosis

i. Example: characterizing acute lymphoblastic leukemia

b. Use in prognosis

i. Example: assessing the likelihood of metastasis in medulloblastoma



Microarrays in the prognosis of metastasis

1. Identified 85 genes with different levels of expression in metastatic and nonmetastatic tumors

2. 72% accuracy in predicting metastasis

3. Identified genes induced in metastasis

a. Could serve as potential drug targets

M+M–

green = downregulated

red = upregulated

The social cost of drug variability

1. Adverse drug reactions affect roughly 2 million hospital patients every year

2. Approximately 100,000 fatalities per year - adverse drug effects

3. Ineffective


Causes of variability in drug response

1. Environment

a. Foods

b. Other drugs

c. Patient’s condition

2. Heredity

a. Inability of the body to metabolize drug

b. Drug receptor polymorphisms

3. Combination of environment and heredity

a. Example: drug allergies


Background

1. 1950s

a. Inherited differences in drug response observed

2. 1980s

a. CYP2D6 gene cloned

3. 1990s–present

a. Human genome sequenced

b. Microarray technology


Enzymatic deficiency in primaquine-sensitive blood cells

1. Primaquine causes adverse side effects in some patients

2. 1956 study found cause - blood enzyme deficiency

3. Test for this deficiency

Normalsubject

Primaquine-sensitivesubject

Hemolysate (ml)

Re

du

ced

glu

tath

ion

e,

GS

H (

mg

)

1 5 100.00

0.25

0.50

0.75

1.00


The CYP2D6 gene

1. Human CYP2D6 gene cloned in 1988

a. Shown to be involved in metabolism of a hypertension drug

2. Developments since 1988

a. More than 40 SNPs discovered

b. CYP2D6 found to be involved in the metabolism of 20% of all prescription drugs

promoter exon intron

CYP2D6 gene

known SNPs


Pharmacogenetics

1. Variations used since the 1950s

2. A classic genetics approach

a. Look for unusual drug response or metabolism phenotype

b. Conduct family studies to understand the pattern of inheritance

c. Clone the responsible gene

i. 1980s and 1990s


Pharmacogenomics

1. Since the late 1990s

2. Uses high-throughput sequencing methods

3. Takes advantage of human genome databases to identify candidate mutations

a. Especially single-nucleotide polymorphisms (SNPs)

4. Finally, looks for correlations between polymorphisms and drug-response phenotypes


Phenotype distribution depends on mutation type

1. Mutations accounting for typical variability

a. Minor a.a. substitutions

b. Promoter SNPs

c. Regulatory SNPs

2. Mutations accounting for atypical variability

a. Early stop codons

b. Exon skipping

c. Deletions

d. Major amino acid substitutions

Normal drug response

Abnormal drug

response

Enzyme activity or drug clearance

fre

qu

en

cy

1 10 100


Possible physiological barriers to drug efficacy

1. Drug metabolism

2. Drug disposition

3. Drug transport

4. Drug targets

5. Environmental and genetic factors can play a role in all of these aspects


The economics of drug development

Annual worldwide expenditures on pharmaceuticals in 2001 were over $300 billion.

Cost of drug development from discovery to approval estimated at $350–$500 million

Drug development costs are increasing faster than inflation


Overview of drug trial process

1. ~12 years for experimental drugs to reach the marketplace

2. Five out of 5,000 compounds that are preclinically tested make it to human trials

a. One of those five makes it to market

3. Clinical trials take 6 years

4. FDA review process

a. ~100,000 pages of trial data to analyze

b. Law requires process to be completed in 6 months

c. More typically, it takes 2.5 years


Clinical Trials

Phase PurposeAverage Duration

Test Population

IAssess safety and dosage in humans

1 year20–80 healthy volunteers

IISearch for side effects, determine drug efficacy

2 years100–300 patient volunteers

IIIVerify drug efficacy, study effects of long-term use

3 years1,000–3,000 patient volunteers


Using pharmacogenomics to improve clinical trials

1. Phase Ia. Genotype subjects to ensure sufficient diversityb. Identify genotypes of poor metabolizersc. Archive genotypes to assess patient risk in later

trials2. Phase II

a. Determine genotypes in patients experiencing toxicity

b. Exclude patients with toxicity risk from further trials, using pharmacogenomic markers

3. Phase IIIa. Excluding patients with at-risk genotypes allows

pharmaceutical companies to improve drug efficacy numbers and reduce the number of volunteers needed to show benefits of a new drug


Improving the effectiveness of treatments with pharmacogenomics

All patients with same diagnosis

1 Removetoxic and

nonresponders

TreatResponders and patientsnot predisposed to toxic

side effects

2


Lecture 27- Genomics, Medicine and Pharmaconomics Copyright © 2010 Pearson Education Inc.

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