Personalized Medicine

Towards Personalized Medicine Michel Dumontier, Ph.D. Assistant Professor of Bioinformatics Department of Biology, Institute of Biochemistry, School of Computer Science

Carleton University Ottawa Institute for Systems Biology Ottawa-Carleton Institute for Biomedical Engineering Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Drug Development Life Cycle Discovery

Preclinical Testing (Lab and Animal Testing)

Phase I (20-30 Healthy Volunteers used to check for safety and dosage)

Phase II (100-300 Patient Volunteers used to check for efficacy and side effects)

Phase III (1000-5000 Patient Volunteers used to monitor reactions to long-term drug use)

FDA Review & Approval Post-Marketing Testing

Years

0

2

4

6

8

10

12

14

16

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Drug Discovery aims to identify a lead compound • Discovery: – – – – –

Identify the molecular target Design an assay for regulation of activity Identify hits with chemical screening Determine mechanism of action Identify a lead compound with strong binding affinity, KD < 1μM

– Demonstrate therapeutic value with in vivo proof of concept in animals/cell cultures

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

The development phase evaluates drug effectiveness • Drugs must overcome numerous challenges – chemically stable in stomach (pH 1) – not digested by gastrointestinal enzymes – absorbed into the bloodstream • pass through series of cell membranes

– – – – –

not bind tightly to other substances survive xenobiotic detoxification by liver enzymes avoid excretion by kidneys brain: cross blood-brain barrier (blocks polar substances) intracellular receptor: pass through cell membrane

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Adverse Drug Reactions Known side effects Unavoidable

Avoidable

Medication errors

Product quality defects

Preventable adverse events Remaining uncertainties Injury or death

• • •

• Unexpected side effects • Unstudied uses • Unstudied populations

ADR is one of the leading causes of hospitalization and death 6.7% of hospitalized patients have serious ADRs 0.3% of hospitalized patients have fatal ADRs Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

LIPITOR: Known Side Effects • Lipitor blocks the production of cholesterol in the body. • May reduce risk of hardening of the arteries, which can lead to heart attacks, stroke, and peripheral vascular disease

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

VIOXX: Unknown Side Effects

Treatment for Acute Pain increased risk of heart attack and stroke (after 18 months) Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Drug Recalls

248 34

176 88

352 72

316 156

248 72

354 83

254 88

0

226 53

200

191 60

Number

400

1995

1996

1997

1998

1999

2000

2001

2002

2003

Fiscal year FDA: Center for Drug Evaluation and Prescription Over-the-counter Research 2003 - Report to the Nation Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Cost of developing drugs • Global Alliance for Tuberculosis Drug Development – www.tballiance.org – "The Economics of TB Drug Development"

• Costs to discover and develop a new antiTB drug range from $115 million to $240 million. – $40 million to $125 million for discovery – $76 million to $115 million for preclinical development through Phase III trials Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Drug Development & Costs • • • • • •

Discovery Pre-Clinical Phase I Phase II Phase III FDA

COST $100M $0.5M $0.5M $5M $50M

# Drugs 2000 100 20 3 2 1

%Total 100% 5% 1% 0.15% 0.10% 0.05%

~$156M

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

R&D Spending and New Medicines • 38 new medicines in 2004 – – – – –

PhRMA Annual Report 2005-2006

Cancer Infectious diseases Parkinson’s therapy Radiation contamination Pain alleviation from made from a synthetic form of a sea-snail venom.

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

An Analysis • National Institute for Health Care Management – Changing Patterns of Pharmaceutical Innovation, May 2002

• Quality of pharmaceutical innovation varies widely. – Breakthrough treatments for life threatening diseases TO – Minor modifications of drugs that have been on the market for some time. Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Most drugs approved are only slightly modified Other 11%

IMD 54% NME 35%

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Less innovative than you think

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The Hatch-Waxman Act (1984) • Drug Price Competition and Patent Term Restoration Act • Open the market to generics immediately after patent expiry, but new tactics to protect – Easier for generics to obtain FDA marketing approval

• Drug Company – 30-month stay against generic manufactures that challenge their patents. – Additional period (< 5 yrs) of marketing exclusivity in addition to 20 year patent exclusivity – Easy patents for drug variants • keep generics off the market by protecting their drugs with extra patents of poor quality, filing lawsuits to protect the patents even when the lawsuit will be lost, but getting the extra market exclusivity anyway.

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Profits as a Percentage of Assets, 2002 Top 7 of Fortune 500 Industries 14.0%

Pharmaceuticals Household Products M edical Products & Equipment Food Services Publishing, Printing Apparel Consumer Food Products

10.7% 9.5% 9.3% 8.2% 7.5% 7.2%

0% 2% 4% 6% 8% 10% 12% 14% 16%

Source: Fortune Magazine, April 14, 2003 Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

The Drug Business • Drug development has been and still is costly, risky, and lengthy • R&D costs have increased, but the industry remains one of the most profitable • Pharmaceutical innovation is targeted towards protecting interests • The payoffs for improvements in the process are significant

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Agouron Pharmaceuticals • Designed a non-peptidic hydroxamate inhibitor • Used structure of recombinant human MMPs bound to various inhibitors • Determined key residues, ligand substituents needed for binding

Gelatinase A

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

MMPI in Cancer Therapy • Design of inhibitors • Matrix Metallo Proteinase Inhibitors (MMPI) are a class of cancer therapeutics – MMP levels are increased in areas surrounding tumor – Degrade extracellular matrix proteins and can lead to spread of cancer – Inhibitors • can prevent metastasis • may also play role in blocking tumor growth

Melissa Passino. Structural Bioinformatics in Drug Discovery. Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

MMP catalysis “metallo” in MMP = zinc

→ catalytic domain contains 2 zinc atoms

Whittaker et al. Chem. Rev. 1999, 99, 2735-2776 Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Peptidic hydroxamate inhibitors • Specificity for MMPs over other MPs • Better binding • But poor oral bioavailability

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Finding drug leads • If we have a target, how do we find some compounds that might bind to it? • Classic: exhaustive screening • Modern: computational screening!

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Combinatorial Chemistry • Parallel synthetic approach – Build on previous products – Generate diversity by adding R groups – Recover most active compounds

• Solid phase synthesis – Wash away excess reagants & other products – Can recover the main product

• Parallel testing

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

combinatorial synthesis of non-peptide drugs 1)

HO

O

+

2)

NH2

R

H N

R NH2

Bead

O

R

O

+ Bead

O

RXN 1

NH2

Bead

H N

R

NH2

Cl

H N

O

RXN 2

O

R Bead

N H

R

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Structure-Based Docking Methods

• Need 3D structure • Scan a virtual library of small molecules and “dock” them to a site of interest on a protein structure • Predict binding energy • Filters thousands of compounds relatively quickly • Top hits can be used for more rigorous computational/experimental characterization and optimization Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Importance of Structural Bioinformatics • Provides a framework for understanding general macromolecular features – Automatic identification of binding pockets. – Measurement size of surface binding pockets.

• Speeds up key steps in drug discovery – Understand molecular basis for disease – Determine potential interactors – Identify potential targets which bind small molecules. Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Structural bioinformatics to design nonpeptidic hydroxylates

binding

oral bioavailabity

antigrowth

antimetastasis

repeat… Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Prinomastat • Good oral bioavailability • Selective for specific MMPs • Evidence showing prevention of lung cancer metastasis in rat and mice models • Clinical trials – cell lung cancer – prostate cancer

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

“If it were not for the great variability among individuals, medicine might as well be a science and not an art” Sir William Osler, 1892

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Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Major sources of variation • Single Nucleotide Polymorphisms (SNPs) – Single base change in DNA

AAGCCTA AAGCTTA – Average frequency 1/1000bp – SNPs arise as a consequence of mistakes during normal DNA replication

• Genomic rearrangements – Duplications, insertions, deletions Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Genetics as the basis for variability in drug response • Pharmacogenetics – The effect of genetic variation on drug response.

• Pharmacogenomics – The application of genomics to the study of human variability in drug response. • Pharmacogenetics and pharmacogenomics are expected to play an important role in the development of better medicines for populations and targeted therapies with improved benefit/risk ratios for individuals

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Personalized Medicine The ability to offer • The Right Drug • To The Right Patient • For The Right Disease • At The Right Time • With The Right Dosage Genetic and metabolic data will allow drugs to be tailored to patient subgroups

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Benefits of Personalized Medicine • Better matching patients to drugs instead of “trial and error • Customized pharmaceuticals may eliminate life-threatening adverse reactions • Reduce costs of clinical trials by – Quickly identifying total failures – Favourable responses for particular backgrounds

• Improved efficacy of drugs

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Personalized Medicine : BiDil • Combination pill containing two medications for heart failure, cardiovascular disease, and/or diabetes. • Clinical trials did not show overall benefit across entire population. • Subgroup of African-descent patients showed benefit – BiDil approved for use in African-descent patients.

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Pharmacokinetics and pharmacodynamics are essential to assess the drug efficacy. • Pharmacokinetics – What the body does to the drug – dose, dosage regimen, delivery form – Drug fate: Absorption, distribution, metabolism, and elimination of drugs (ADME)

• Pharmacodynamics – What the drug does to the body – Biochemical and physiological effects of drugs – mechanism of drug action – relationship between drug concentration and effect

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

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Codeine Metabolism •

5-10% codeine is metabolized into morphine by CYP2D6 – 7% of caucasians have a nonfunctional CYP2D6 variant – <2% are CYP2D6 ultrarapid metabolizers which may suffer from opioid intoxication

•

•

80% codeine normally converted to glucuronide, eliminated by kidney. inhibition of CYP3A4 or rapid metabolic variants of CYP2D6 during renal failure would show toxicity

Gasche Y et al. Codeine intoxication associated with ultrarapid CYP2D6 metabolism. NEJM 2004

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Drug-Metabolizing Enzymes

Phase II: conjugation with endogenous substitutents

Phase I: modification of functional groups

Most DME have clinically relevant polymorphisms Those with changes in drug effects are separated from pie. Pharmacogenomics: Translating Functional Genomics into Rational

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Cytochrome P450 Enzymes • Expressed mainly in liver • Act on: – Endogenous substrates – Xenobiotics including plant and fungal products, pollution, chemicals – Drugs (metabolize 50-60%) • Typical reaction: – Oxidation – RH + O2 + NADPH + H+  ROH + H2O + NADP+ • Sequence diversity: – 18 families – 43 subfamilies – ~60 genes – ~100 allelic variants (isoforms)

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Participation of the CYP Enzymes in Metabolism of Some Clinically Important Drugs CYP Enzyme Examples of substrates 1A1

Caffeine, Testosterone, R-Warfarin

1A2

Acetaminophen, Caffeine, Phenacetin, R-Warfarin

2A6

17β -Estradiol, Testosterone

2B6

Cyclophosphamide, Erythromycin, Testosterone

2C-family

Acetaminophen, Tolbutamide (2C9); Hexobarbital, SWarfarin (2C9,19); Phenytoin, Testosterone, R- Warfarin, Zidovudine (2C8,9,19);

2E1

Acetaminophen, Caffeine, Chlorzoxazone, Halothane

2D6

Acetaminophen, Codeine, Debrisoquine

3A4

Acetaminophen, Caffeine, Carbamazepine, Codeine, Cortisol, Erythromycin, Cyclophosphamide, S- and RWarfarin, Phenytoin, Testosterone, Halothane, Zidovudine

S. Rendic Drug Metab Rev 34: 83-448, 2002

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Factors Influencing Activity and Level of CYP Enzymes

Nutrition Red indicates enzymes important in drug metabolism S. Rendic Drug Metab Rev 34: 83-448, 2002

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Pharmacogenetics: number of genes affects drug potency

Weinshilboum, R. N Engl J Med 2003;348:529-537

Nortryptyline: Anti-depressant

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Use of probe drugs to determine metabolic activity due to CYP2D6 variants

Antihypertensive debrisoquin decreases blood pressure Weinshilboum, R. N Engl J Med 2003;348:529-537

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Diagnostics

AmpliChip CYP450: Range of drug metabolism phenotypes is observed for individuals based upon the cytochrome P-450 genes Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Is pharmacogenetics in routine use? NO • Science still early. Limited data in public domain. • Fragmentation of drug markets is not attractive to drug companies. • Many variations not clinically significant • Expensive to test for genotype • Significantly more challenging to track drug drug interactions

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

CYP3A4 •

Abundant in liver and intestines and accounts for nearly 50% of CYP450 enzymes.

•

Activity can vary markedly among members of a population – Constitutive variability is ~5-fold but can increase to 400-fold through induction and inhibition

•

Activity affected by other drugs: 5mg tablet with juice

– St Johns wort is an inducer, grapefruit juice is an inhibitor – Felodipine is a calcium channel blocker (calcium antagonist), a drug used to control hypertension (high blood pressure)

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

CYP3A4 mediated Drug-Drug Interaction

PXR: pregnane X receptor; • • •

RXR: retinoid X receptor

Protect against xenobiotics Diverse drugs activate through heterodimer complex Cause drug-drug interactions

Wilson. PXR, CAR, and drug metabolism. Nat Rev Drug Disc 2002 Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

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Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Quantitative Structure-Activity Relationship (QSAR) • find consistent relationship between biological activity and molecular properties, so that these “rules” can be used to evaluate the activity of new compounds. • extract features (hydrophobicity, pK, van der Waals radii, hydrogen bonding energy, conformation) • build mathematical relationship f(activity|features) • automatically assesses the contribution of each feature • can be used to make predictions on a new molecule

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

3D QSAR for CYP3A4

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

3D QSAR for CYP3A4 with known substrates

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Drug Metabolic Fate

What are the potential by-products of a drug? Going beyond QSAR to de novo predictions Quantify differences in binding due to natural variation. Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

nsSNPs in Ligand Sites of Proteins involved in Disease • Of 9.7M SNPs, 778 nsSNPs were located in the predicted binding sites of 484 proteins 611 nsSNPs in 351 disease causing genes (OMIM)

SNP DNA

Gene Protein

over 200 genes not associated with disease • Molecular Mechanism?

Ligand Binding Disease Daniel Oropeza, 2006 Honours Thesis

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

GTP binding site of S. cerevisiae Homolog 2. The ASP 137 ASN mutation has been shown to cause a decrease in the affinity for GDP (Jones, B et al . 2003). This mutation has been associated with Chylomicron retention disease. Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Qualitative Functional Inference

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Genomic Medicine: Predictive, personalized, and pre-emptive

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Things to Consider • Does my doctor know enough about genomic medicine to be advising me? – Are there genetic counselors available?

• Will the test only be for this condition? – What if I am susceptible to another disease?

• Who will know about this? – Doctors… insurance companies?

• How exactly will the results be kept secure and in confidence? Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

How much will this cost? • More drugs may succeed in clinical trials due to positive outcome for smaller subset – Will pharma attempt to recoup costs with a pricier drug?

• Will public health cover the costs of genetic testing? – Reduce overall health cost due to fewer ADRs – Should we determine clinically validated genes or should we sequence the genome?

• How will my insurance premiums be affected?

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008

Michel Dumontier [email protected] http://dumontierlab.com

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008