View
4.714
Download
4
Category
Preview:
DESCRIPTION
Personalized medicine involves the prescription of specific therapeutics best suited for an individual based on their genetic or proteomic profile. This talk discusses current approaches in drug discovery/development, the role of genetics in drug metabolism, and lawful/ethical issues surrounding the deployment of new health technology.
Citation preview
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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
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
Treatment for Acute Pain
increased risk of heart attack and stroke(after 18 months)
VIOXX: Unknown Side Effects
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
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 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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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.
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
NME35%
Other11%
IMD54%
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
Less innovative than you think
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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, 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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
• 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
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
Whittaker et al. Chem. Rev. 1999, 99, 2735-2776
“metallo” in MMP = zinc
→ catalytic domain contains 2 zinc atoms
MMP catalysis
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
Peptidic hydroxamate inhibitors
• Specificity for MMPs over other MPs
• Better binding
• But poor oral bioavailability
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
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
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
oral bioavailabitybinding
anti-growth
anti-metastasis
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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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 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
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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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::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 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, 2008
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
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:
– 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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
Dumontier::BIOL4301:Towards Personalized Medicine:Nov 25, 2008
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)
over 200 genes not associated with disease
• Molecular Mechanism?
SNP
DNA
Gene
Protein
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
michel_dumontier@carleton.ca
http://dumontierlab.com
Recommended