20091109 biol1010 personalized medicine

Dumontier::BIOL1010:Towards Personalized Medicine

Towards Personalized

Medicine

Michel Dumontier, Ph.D.

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

Carleton University

Ottawa Institute for Systems BiologyOttawa-Carleton Institute for Biomedical Engineering

Nov 9, 2009


Outline

• Personalized Medicine

• Drug Discovery

• Role of Bioinformatics

• Current Research


“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


SNPs – a major source of variation

• Single Nucleotide Polymorphisms (SNPs)– Single base change in DNA

AAGCCTA

AAGCTTA– SNPs arise as a consequence of mistakes

during normal DNA replication

• Average frequency 1/1000bp


Human Variation• In human beings, 99.9 percent bases are same.• Remaining 0.1 percent makes a person unique.

– Different attributes / characteristics / traits • how a person looks, • diseases he or she develops.

• These variations can be:– Harmless (change in phenotype)– Harmful (diabetes, cancer, heart disease, Huntington's

disease, and hemophilia )– Latent (variations found in coding and regulatory

regions, are not harmful on their own, and the change in each gene only becomes apparent under certain conditions e.g. susceptibility to lung cancer)


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 patients showed best overall benefit– BiDil approved solely for use in African-descent patients.

Controversial!


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


PGx• 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

• Pharmacokinetics and pharmacodynamics are essential to assess the drug efficacy.


PGx + genetics/genomics

• 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


Cytochrome P450 EnzymesIn bacteria, fungi, insects, plants, fish, mammalsCatalyze monooxygenation reaction:

RH + 2H+ +O2 + NADPH ROH + H2O + NADP+

Act on:– Endogenous substrates (cholesterol, steroids,

fatty acids)– Exogenous (drugs, food additives,

environmental toxins)Involved in

– Production of steroids– Metabolism of fatty acids, prostaglandins,

leukotrienes, retinoids– Activation or inactivation of therapeutic agents– Enzyme activation/inhibition resulting in drug-

drug interactions, adverse events


CYP enzymes are involved in the metabolism of 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::BIOL1010:Towards Personalized MedicineS. 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

2A6; 2C9,19; 2D6;


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

Dumontier::BIOL1010:Towards Personalized MedicineWeinshilboum, R. N Engl J Med 2003;348:529-537

Nortriptyline (anti-depressant) Pharmacogenetics

Dumontier::BIOL1010:Towards Personalized MedicineWeinshilboum, 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


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:

– 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


Codeine Metabolism

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

• 80% codeine normally converted to glucuronide, eliminated by kidney.

• 5-10% codeine is metabolized into morphine by CYP2D6

• inhibition of CYP3A4 or rapid metabolic variants of CYP2D6 during renal failure would show toxicity– 7% of caucasians have a

nonfunctional CYP2D6 variant

– <2% are CYP2D6 ultrarapid metabolizers which may suffer from opioid intoxication


Known side effects

Unavoidable Avoidable

Medicationerrors

Product qualitydefects

Preventableadverseevents

Injuryor death

Remaininguncertainties

• Unexpected side effects• Unstudied uses• Unstudied populations

drug-drug interactions are mostly unavoidable


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


Known side effects

Unavoidable Avoidable

Medicationerrors

Product qualitydefects

Preventableadverseevents

Injuryor death

Remaininguncertainties

• Unexpected side effects• Unstudied uses• Unstudied populations

Medication errors are a significant source of adverse events

• 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


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

Many factors contribute to drug recalls


Treatment for Acute Pain

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

VIOXX: Unknown Side Effects


Diagnostics

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


But wait a minute…


There is still lots to figure out…

• Science still early. Limited data in public domain.• Many variations not clinically significant• Expensive to test for genotype (currently)

• Ethical issues in testing individual genotype• Unclear how to deliver information to the

practitioner


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 insurance premiums be affected?


Personalied Medicine:What’s your take?


Outline


• Drug Discovery

• Role of Bioinformatics



What is a drug?• A drug Compound of definite composition and

having a pharmacological effect

• Natural products – plant extracts – animal fluids (e.g., snake venoms)– isolated products (biological)– chimeric / recombinant products (biological)

• Synthetic chemicals– derived from medicinal chemistry– derived from combinatorial chemistry


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

• Discovery: – finding a lead compound (KD < 1μM)

– target, assay, chemical screening, hit identification, mechanism of action, lead identification, lead optimization

– in vivo proof of concept in animals and demonstration of therapeutic value

• Development: – Evaluate its effectiveness– begins when the decision is made to put a

molecule into clinical trials


Barriers that a drug must overcome to reach intended target

– 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


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


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


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


What disease would you try to treat with a drug?


Outline


• Drug Discovery

• Bioinformatics



What is Bioinformatics?“Using computers to solve problems in biology”

• Bioinformatics is a scientific discipline that encompasses all aspects of biological information acquisition, processing, storage, distribution, analysis and interpretation.

• Bioinformatics combines the tools of Biology, Chemistry, Mathematics, Statistics and Computer Science to understand and model biological processes.


Bioinformatics For Knowledge Discovery

Experimental Data– Sequence – Structure – Function– Expression– Regulation – Interactions – Pathways– Disease– Genetics– Taxonomy– Small molecules– Kinetics– Dynamics

model

validate

knowledge

simulate


Bioinformatics & Drug Discovery

• Knowledge Discovery

• Identification of potential drug targets– Genomics– Proteomics

• Cheminformatics– Drug target modeling– Drug optimization

• Simulating drug effects on pathways

• Estimating toxicological effects


Quick Survey of Bioinformatics Applications in Drug Discovery

• Tissue profiling

• Drug Screening


Gene Expression• A gene is expressed

when it is transcribed from DNA to RNA and then possibly translated into a protein

• By measuring the products of transcription,we can assay gene expression


• Differentiation: All cells in a body have the same genome. Expression is what differentiates one tissue from another, e.g. brain from liver.

• Physiology: Cells do their business (dividing, sending signals, digesting, etc.) largely via changes in expression

• Response to stimuli: Environmental changes (like drugs or disease) often cause changes in expression

• Disease markers and drug targets: changes in expression associated with disease can be diagnostic markers and/or suggest novel pharmaceutical approaches.

Importance of Gene Expression


Microarrays Can Be Used To Determine Relative Gene Expression


Distinct types of B-

cell lymphoma identified by gene

expression profiling


Drug Screening

• If we have a target, how do we find some compounds that might bind to it?

• Combinatorial chemistry

• 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


synthesisof compound

↓

manipulation of structure to get

better drug(greater efficacy, fewer side effects)Aspirin


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


How to discover a drug


Cancer Therapy

• Matrix Metallo Proteinases (MMP)• Degrade proteins in the extracellular

matrix • Levels increased in areas surrounding

tumor• Makes it easier for cancer cells to

become metastatic

• MMP Inhibitors – Stop MMPs from working– Can block tumor growth


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

“metallo” in MMP = zinc

→ catalytic domain contains 2 zinc atoms

MMP catalysis


Peptidic hydroxamate inhibitors

• Specific for MMPs

• Better binding

• But poor oral bioavailability

(how much gets into the bloodstream)


Drug Discovery by Agouron Pharmaceuticals

• Designed a new inhibitor

• Used structure of human MMPs bound to various inhibitors in silico

• Determined key residues, ligand substituents needed for binding Gelatinase A


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


Outline

• Personalized Medicine?

• Drug Discovery

• Bioinformatics



Goals

• Integrate pharmacogenomics knowledge• Improve our understanding of how genetic variations affect drug responses.• Deduce the biochemical mechanisms that underlie disease phenotypes• Predict side-effects from drug

interactions due to unexpected

cellular interactions


How do we find this knowledge?


PHARMGKB

+Role of genes, gene variants , drugs

+pharmacokinetics +pharmacodynamics

+ clinical outcomes.

+ Links to publications

- Natural language descriptions

- Variant details in publications


Surface web:167 terabytes

Deep web:91,000 terabytes

545-to-one


How do we integrate these resources?


Data silos – not made for sharingData silos – not made for sharing


The Semantic Web will expose The Semantic Web will expose data and link knowledgedata and link knowledge


Bio2RDF is building the linked data web for biological data


Bio2RDF provides the Bio2RDF provides the methodology to create methodology to create and glue these different and glue these different databases.databases.


Resource Description Framework (RDF)

• Allows one to express propositions, and reason about them

• Uniform Resource Identifier (URI) are entity names

• i.e P05067

is a name for Amyloid precursor protein APP

Protein

is a

• A RDF statement consists of:– Subject: resource identified by a URI

– Predicate: resource identified by a URI

– Object: resource or literal


Now Link Data!

APP

Protein

is a

Alzheimer’s

Disease

is a

is involved in


something you can lookup or search for with rich

descriptions


Ontology as

Strategy


APP

Protein

Is a

Molecule

is a

is a

Semantic Knowledge Base

fact

ontology

Knowledge base


Ontologies

• Shared conceptualization

• Tell computers what we believe

• Allows computer programs called reasoners to make inferences


Semantic Query Answering

http://smart.dumontierlab.com

ISWC Semantic Web Challenge: CS Honors: Alex De Leon


Build aBuild aknowledge baseknowledge basefrom a series of questionsfrom a series of questions


Cell Simulation

Molecules Interactions (metabolic/signaling) Compartments

Cell Simulation

+ +


3D Particle Simulation

GridCell - Dr. Warren Gross & Laurier Boulianne, PhD Candidate Engineering


3D Tetris or Science at Work?


Cellular Visions: The Inner Life of a Cell


Learn more and Get involved!

BIOC 3008 [0.5 credit]: BioinformaticsBIOC 4008 [0.5 credit]: Metabolic Modeling and Simulation

BIOC 2400 [0.5 credit]: Independent Research IBIOC 3400 [0.5 credit]: Independent Research IIBIOC 4906 [1.0 credit]: Interdisciplinary Research

BIOL 4900 [1.0 credit]: Biology Directed Special Studies BIOL 4901 [0.5 credit]: Biology Directed Special StudiesBIOL 4908 [1.0 credit]: Biology Research ThesisBIOC 4907 [1.0 credit]: Biochemistry Essay and Research ProposalBIOC 4908 [1.0 credit]: Biochemistry Research ProjectCHEM 4908 [1.0 credit]: Chemistry Research Project and SeminarCMPS 4909 [1.0 credit]: Computational Science Research ThesisCOMP 4901 [0.5 credit]: Computer Science Directed StudiesCOMP 4905 [0.5 credit]: Computer Science Research ThesisSYSC 4907 [0.5 credit]: Engineering Project


Learn more and Get involved!

Faculty• Biology - Jim Cheetham, Ashkan Golshani, Myron Smith,

Bill Willmore, Iain Lambert, Susan Aitken, John Vierula• Computer Science - Frank Dehne• Systems and Computer Engineering - Jim Green,

Gabriel Wainer

Programs• BSc – Bioinformatics (Honours), Computational

Biochemistry (Honours), Computational Biology (Honours)

• BCSc – stream in Bioinformatics• Master’s Specialization in Bioinformatics


[email protected]

20091109 biol1010 personalized medicine

Health & Medicine