towards personalized medicine

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

Towards Personalized

Medicine

Michel Dumontier, Ph.D.

Assistant Professor of BioinformaticsDepartment of Biology, Institute of Biochemistry, School of Computer Science

Carleton University

Ottawa Institute for Systems BiologyOttawa-Carleton Institute for Biomedical Engineering


Drug Development Life Cycle

Years

0 2 4 6 8 10 12 14 16

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


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


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


Known side effects

Unavoidable Avoidable

Medicationerrors

Product qualitydefects

Preventableadverseevents

Injuryor death

Remaininguncertainties

• Unexpected side effects• Unstudied uses• Unstudied populations

Adverse Drug Reactions

• 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


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


Treatment for Acute Pain

increased risk of heart attack and stroke(after 18 months)

VIOXX: Unknown Side Effects


Drug Recalls

191

226

248

352

354

254

60 53 34 88 72 156

83 88248

316

176

72

0

200

400

1995 1996 1997 1998 1999 2000 2001 2002 2003

Fiscal year

Nu

mb

er

Prescription Over-the-counter

FDA: Center for Drug Evaluation and Research 2003 - Report to the Nation


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 anti-TB 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


Drug Development & Costs

• Discovery• Pre-Clinical• Phase I• Phase II • Phase III• FDA

COST # Drugs %Total

$100M 2000 100%

$0.5M 100 5%

$0.5M 20 1%

$5M 3 0.15%

$50M 2 0.10%

1 0.05%

~$156M


R&D Spending and New Medicines

PhRMA Annual Report 2005-2006

• 38 new medicines in 2004 – Cancer– Infectious diseases– Parkinson’s therapy– Radiation

contamination– Pain alleviation from

made from a synthetic form of a sea-snail venom.


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.


Most drugs approved are only slightly modified

NME35%

Other11%

IMD54%


Less innovative than you think


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.


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

7.2%

7.5%

8.2%

9.3%

9.5%

10.7%

14.0%

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

Consumer Food Products

Apparel

Publishing, Printing

Food Services

Medical Products & Equipment

Household Products

Pharmaceuticals

Source: Fortune Magazine, April 14, 2003


• 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

The Drug Business


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


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.


Whittaker et al. Chem. Rev. 1999, 99, 2735-2776

“metallo” in MMP = zinc

→ catalytic domain contains 2 zinc atoms

MMP catalysis


Peptidic hydroxamate inhibitors

• Specificity for MMPs over other MPs

• Better binding

• But poor oral bioavailability


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!


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


combinatorial synthesis of non-peptide drugs

R

NH2

+OOH

NH2Bead

ONH

NH2Bead

R

ONH

NH2Bead

R

Cl

O

R+

ONH

NH

Bead

R

O

R

1)

2)

RXN 1

RXN 2


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


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.


Structural bioinformatics to design nonpeptidic hydroxylates

oral bioavailabitybinding

anti-growth

anti-metastasis

repeat…


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


“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


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


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


Personalized MedicineThe 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


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


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.


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


Codeine Metabolism

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

• 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


Drug-Metabolizing Enzymes

Pharmacogenomics: Translating Functional Genomics into Rational Therapeutics. Evans and Relling Science 1999

Most DME have clinically relevant polymorphismsThose with changes in drug effects are separated from pie.

Phase I: modification of functional groups Phase II: conjugation with endogenous substitutents


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)


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 17-Estradiol, Testosterone

2B6 Cyclophosphamide, Erythromycin, Testosterone

2C-family Acetaminophen, Tolbutamide (2C9); Hexobarbital, S- Warfarin (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 R-Warfarin, Phenytoin, Testosterone, Halothane, Zidovudine

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

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008S. Rendic Drug Metab Rev 34: 83-448, 2002

Red indicates enzymes important in drug metabolism

Factors Influencing Activity and Level of CYP Enzymes

Nutrition 1A1;1A2; 1B1, 2A6, 2B6, 2C8,9,19; 2D6, 3A4,5

Smoking 1A1;1A2, 2E1

Alcohol 2E1

Drugs 1A1,1A2; 2A6; 2B6; 2C; 2D6; 3A3, 3A4,5

Environment 1A1,1A2; 2A6; 1B; 2E1; 3A3, 3A4,5

Genetic Polymorphism

1A; 2A6; 2C9,19; 2D6; 2E1

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008Weinshilboum, R. N Engl J Med 2003;348:529-537

Pharmacogenetics: number of genes affects drug potency

Nortryptyline:

Anti-depressant

Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008Weinshilboum, R. N Engl J Med 2003;348:529-537

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

Antihypertensive debrisoquin decreases blood pressure


Diagnostics

AmpliChip CYP450: Range of drug metabolism phenotypes is observed for individuals based upon the cytochrome P-450 genes


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


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:

– 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)

5mg tablet with juice


Wilson. PXR, CAR, and drug metabolism. Nat Rev Drug Disc 2002

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


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


3D QSAR for CYP3A4


3D QSAR for CYP3A4 with known substrates


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.


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)

over 200 genes not associated with disease

• Molecular Mechanism?

SNP

DNA

Gene

Protein

Ligand Binding

Disease

Daniel Oropeza, 2006 Honours Thesis


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.


Qualitative Functional Inference


Genomic Medicine:Predictive, personalized, and

pre-emptive


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?


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?


Michel Dumontier

[email protected]

http://dumontierlab.com