20091109 Biol1010 Personalized Medicine


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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. I highlight some bioinformatic roles in the drug discovery process, and discuss the use of semantic web technologies for data integration and knowledge discovery..

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  • Excess amounts can lead to bone marrow toxicity, reducing the normal amounts of white and red blood cells
  • 6-MP ribonucleotide inhibits purine nucleotide synthesis and metabolism. This alters the synthesis and function of RNA and DNA.
  • congestive heart failure—the progressive weakening of the heart muscle to the point where it can no longer pump blood efficiently
  • Most drug-metabolizing enzymes exhibit clinically relevant genetic polymorphisms . Essentially all of the major human enzymes responsible for modification of functional groups [classified as phase I reactions ( left )] or conjugation with endogenous substituents [classified as phase II reactions ( right )] exhibit common polymorphisms at the genomic level; Those enzyme polymorphisms that have already been associated with changes in drug effects are separated from the corresponding pie charts. The percentage of phase I and phase II metabolism of drugs that each enzyme contributes is estimated by the relative size of each section of the corresponding chart. ADH, alcohol dehydrogenase; ALDH, aldehyde dehydrogenase; CYP, cytochrome P450; DPD, dihydropyrimidine dehydrogenase; NQO1, NADPH:quinone oxidoreductase or DT diaphorase; COMT, catechol O -methyltransferase; GST, glutathione S -transferase; HMT, histamine methyltransferase; NAT, N -acetyltransferase; STs, sulfotransferases; TPMT, thiopurine methyltransferase; UGTs, uridine 5'-triphosphate glucuronosyltransferases.
  • Figure 4. Pharmacogenetics of Nortriptyline. Mean plasma concentrations of nortriptyline after a single 25-mg oral dose are shown in subjects with 0, 1, 2, 3, or 13 functional CYP2D6 genes. In addition, some subjects with ultrarapid metabolism have been shown to have multiple copies of the CYP2D6 gene. 18 Such subjects can have an inadequate therapeutic response to standard doses of the drugs metabolized by CYP2D6. Although the occurrence of multiple copies of the CYP2D6 gene is relatively infrequent among northern Europeans, in East African populations, the allele frequency can be as high as 29 percent. 22 The effect of the number of copies of the CYP2D6 gene — ranging from 0 to 13 — on the pharmacokinetics of the antidepressant drug nortriptyline is shown in Figure 4. 23 There could hardly be a more striking illustration of how genetics influences the metabolism of a drug.
  • Approximately 5 to 10 percent of white subjects were found to have a relative deficiency in their ability to oxidize the antihypertensive drug debrisoquin. They also had an impaired ability to metabolize the antiarrhythmic and oxytocic drug sparteine. Subjects with poor metabolism of these two drugs had lower urinary concentrations of metabolites and higher plasma concentrations of the parent drug than did subjects with extensive metabolism A plot of the ratio of urinary debrisoquin to 4-hydroxydebrisoquin — a so-called metabolic ratio — is shown in Figure 3. The higher the metabolic ratio, the less metabolite was excreted. Therefore, subjects with poor metabolism are shown, counterintuitively, at the far right of the graph, with a few subjects at the far left of the frequency distribution who are now classified as having ultrarapid metabolism. As described subsequently, suchsubjects may have multiple copies of the gene for CYP2D6. Therefore, debrisoquin and sparteine represented “probe drugs” — compounds that could be used to classify subjects as having either poor metabolism or extensive metabolism. That strategy, the administration of a probe compound metabolized by a genetically polymorphic enzyme, became a standard technique used in many pharmacogenetic studies.
  • Drug ミ drug interactions. The molecular basis of a drug - drug interaction. The orphan nuclear receptor PXR is a transcription factor that regulates the expression of the CYP3A gene (yellow) in the liver and intestine. It functions as a heterodimer with the nuclear receptor RXR. Drug A binds to PXR and induces expression of the CYP3A enzyme (pink), accelerating the metabolism of drug B, which is a substrate for CYP3A. CYP, cytochrome P450; OH, hydroxyl group; PXR, pregnane X receptor; RXR, retinoid X receptor.
  • Figure 1. The Incidence-Rate Ratio for Sudden Death from Cardiac Causes According to the Current Use of the Study Antibiotic Medications and CYP3A Inhibitors. The bars indicate 95 percent confidence intervals. The reference group for the incidence-rate ratio associated with the concurrent use of erythromycin and CYP3A inhibitors and with the use of CYP3A inhibitors alone is the patients who used none of these medications; that for the incidence-rate ratio associated with the use of erythromycin and use of amoxicillin, regardless of the use of CYP3A inhibitors, is the patients who used neither of these antibiotic medications.
  • Life-threatening opioid intoxication developed in a patient after he was given small doses of codeine for the treatment of a cough associated with bilateral pneumonia. Codeine is bioactivated by CYP2D6 into morphine, which then undergoes further glucuronidation. CYP2D6 genotyping showed that the patient had three or more functional alleles, a finding consistent with ultrarapid metabolism of codeine. We attribute the toxicity to this genotype, in combination with inhibition of CYP3A4 activity by other medications and a transient reduction in renal function. Figure 1. Metabolic Pathways of Codeine Biotransformation. The conversion of codeine into norcodeine by CYP3A4 and into codeine-6-glucuronide by glucuronidation usually represents 80 percent of codeine clearance, and conversion of codeine into morphine by CYP2D6 represents only 10 percent of codeine clearance (blue arrows). Morphine is further metabolized into morphine-6-glucuronide and into morphine-3-glucuronide. Morphine and morphine-6-glucuronide have opioid activity (green arrows). Glucuronides are eliminated by the kidney and are thus susceptible to accumulation in cases of acute renal failure. The patient (red arrows) had ultrarapid CYP2D6 metabolism, inhibition of CYP3A4 as a result of treatment with clarithromycin and voriconazole, and glucuronide accumulation due to acute renal failure. Red arrows with dotted lines indicate low levels of drug conversion or elimination, green arrows with dotted lines indicate low levels of brain penetration, and thick arrows indicate high levels.
  • Research – that’s what brought you here Skils – marketable in whatever you choose to do thereafter Knowledeable – where the field has been and where it is going Improve oral and written scientific communication skills Research – tell people what you’ve been doing Track progress – develop a sense of progress
  • Can’t answer questions that require background knowledge
  • Transcription factor
  • What inspires you?
  • Reality: No formal training, peer networks? EDC training Human dynamic
  • Reality: No formal training, peer networks? EDC training Human dynamic
  • Thanks – CWV Hogue, Hogue Lab, Blueprint Team, Collaborators Funding – Carleton, NSERC, CFI, Health Canada Slides - Scott Brinker @ Chief Marketing Technologies
  • 20091109 Biol1010 Personalized Medicine

    1. 1. Towards Personalized Medicine Michel Dumontier, Ph.D. Associate 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 Nov 9, 2009
    2. 2. Outline <ul><li>Personalized Medicine </li></ul><ul><li>Drug Discovery </li></ul><ul><li>Role of Bioinformatics </li></ul><ul><li>Current Research </li></ul>
    3. 3. <ul><li>“ If it were not for the great variability among individuals , medicine might as well be a science and not an art ” </li></ul><ul><li>Sir William Osler, 1892 </li></ul>
    4. 5. SNPs – a major source of variation <ul><li>Single Nucleotide Polymorphisms (SNPs) </li></ul><ul><ul><li>Single base change in DNA </li></ul></ul><ul><li>AAGC C TA </li></ul><ul><li>AAGC T TA </li></ul><ul><ul><li>SNPs arise as a consequence of mistakes during normal DNA replication </li></ul></ul><ul><li>Average frequency 1/1000bp </li></ul>
    5. 6. Human Variation <ul><li>In human beings, 99.9 percent bases are same. </li></ul><ul><li>Remaining 0.1 percent makes a person unique. </li></ul><ul><ul><li>Different attributes / characteristics / traits </li></ul></ul><ul><ul><ul><li>how a person looks, </li></ul></ul></ul><ul><ul><ul><li>diseases he or she develops. </li></ul></ul></ul><ul><li>These variations can be: </li></ul><ul><ul><li>Harmless (change in phenotype) </li></ul></ul><ul><ul><li>Harmful (diabetes, cancer, heart disease, Huntington's disease, and hemophilia ) </li></ul></ul><ul><ul><li>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) </li></ul></ul>
    6. 9. Personalized Medicine : BiDil <ul><li>Combination pill containing two medications for heart failure, cardiovascular disease, and/or diabetes. </li></ul><ul><li>Clinical trials did not show overall benefit across entire population. </li></ul><ul><li>Subgroup of patients showed best overall benefit </li></ul><ul><ul><li>BiDil approved solely for use in African-descent patients. </li></ul></ul><ul><li>Controversial! </li></ul>
    7. 10. Personalized Medicine <ul><li>The ability to offer </li></ul><ul><li>The Right Drug </li></ul><ul><li>To The Right Patient </li></ul><ul><li>For The Right Disease </li></ul><ul><li>At The Right Time </li></ul><ul><li>With The Right Dosage </li></ul><ul><li>Genetic and metabolic data will allow drugs to be tailored to patient subgroups </li></ul>
    8. 11. Benefits of Personalized Medicine <ul><li>Better matching patients to drugs instead of “trial and error </li></ul><ul><li>Customized pharmaceuticals may eliminate life-threatening adverse reactions </li></ul><ul><li>Reduce costs of clinical trials by </li></ul><ul><ul><li>Quickly identifying total failures </li></ul></ul><ul><ul><li>Favourable responses for particular backgrounds </li></ul></ul><ul><li>Improved efficacy of drugs </li></ul>
    9. 12. PGx <ul><li>Pharmacokinetics </li></ul><ul><ul><li>What the body does to the drug </li></ul></ul><ul><ul><li>dose, dosage regimen, delivery form </li></ul></ul><ul><ul><li>Drug fate: Absorption, distribution, metabolism, and elimination of drugs (ADME) </li></ul></ul><ul><li>Pharmacodynamics </li></ul><ul><ul><li>What the drug does to the body </li></ul></ul><ul><ul><li>Biochemical and physiological effects of drugs </li></ul></ul><ul><ul><li>mechanism of drug action </li></ul></ul><ul><ul><li>relationship between drug concentration and effect </li></ul></ul><ul><li>Pharmacokinetics and pharmacodynamics are essential to assess the drug efficacy. </li></ul>
    10. 14. PGx + genetics/genomics <ul><li>Pharmacogenetics </li></ul><ul><ul><li>The effect of genetic variation on drug response. </li></ul></ul><ul><li>Pharmacogenomics </li></ul><ul><ul><li>The application of genomics to the study of human variability in drug response. </li></ul></ul><ul><li>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 </li></ul>
    11. 15. Cytochrome P450 Enzymes <ul><li>In bacteria, fungi, insects, plants, fish, mammals </li></ul><ul><li>Catalyze monooxygenation reaction: </li></ul><ul><ul><li>RH + 2H + +O 2 + NADPH </li></ul></ul><ul><ul><li> ROH + H 2 O + NADP + </li></ul></ul><ul><li>Act on: </li></ul><ul><ul><li>Endogenous substrates (cholesterol, steroids, fatty acids) </li></ul></ul><ul><ul><li>Exogenous (drugs, food additives, environmental toxins) </li></ul></ul><ul><li>Involved in </li></ul><ul><ul><li>Production of steroids </li></ul></ul><ul><ul><li>Metabolism of fatty acids, prostaglandins, leukotrienes, retinoids </li></ul></ul><ul><ul><li>Activation or inactivation of therapeutic agents </li></ul></ul><ul><ul><li>Enzyme activation/inhibition resulting in drug-drug interactions, adverse events </li></ul></ul>
    12. 16. CYP enzymes are involved in the metabolism of clinically important drugs S. Rendic Drug Metab Rev 34: 83-448, 2002 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
    13. 17. Factors Influencing Activity and Level of CYP Enzymes S. Rendic Drug Metab Rev 34: 83-448, 2002 Red indicates enzymes important in drug metabolism
    14. 18. Drug-Metabolizing Enzymes Pharmacogenomics: Translating Functional Genomics into Rational Therapeutics. Evans and Relling Science 1999 Most DME have clinically relevant polymorphisms Those with changes in drug effects are separated from pie. Phase I: modification of functional groups Phase II: conjugation with endogenous substitutents
    15. 19. Nortriptyline (anti-depressant) Pharmacogenetics Weinshilboum, R. N Engl J Med 2003;348:529-537
    16. 20. Weinshilboum, 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
    17. 21. CYP3A4 <ul><li>Abundant in liver and intestines and accounts for nearly 50% of CYP450 enzymes. </li></ul><ul><li>Activity can vary markedly among members of a population </li></ul><ul><ul><li>Constitutive variability is ~5-fold but can increase to 400-fold through induction and inhibition </li></ul></ul><ul><li>Activity affected by other drugs: </li></ul><ul><ul><li>Grapefruit juice is an inhibitor </li></ul></ul><ul><ul><li>Felodipine is a calcium channel blocker (calcium antagonist), a drug used to control hypertension (high blood pressure) </li></ul></ul>5mg tablet with juice
    18. 23. Wilson. PXR, CAR, and drug metabolism. Nat Rev Drug Disc 2002 CYP3A4 mediated Drug-Drug Interaction PXR: pregnane X receptor; RXR: retinoid X receptor <ul><li>Protect against xenobiotics </li></ul><ul><li>Diverse drugs activate through heterodimer complex </li></ul><ul><li>Cause drug-drug interactions </li></ul>
    19. 25. Codeine Metabolism <ul><li>80% codeine normally converted to glucuronide, eliminated by kidney. </li></ul><ul><li>5-10% codeine is metabolized into morphine by CYP2D6 </li></ul><ul><li>inhibition of CYP3A4 or rapid metabolic variants of CYP2D6 during renal failure would show toxicity </li></ul><ul><ul><li>7% of caucasians have a nonfunctional CYP2D6 variant </li></ul></ul><ul><ul><li><2% are CYP2D6 ultrarapid metabolizers which may suffer from opioid intoxication </li></ul></ul>Gasche Y et al. Codeine intoxication associated with ultrarapid CYP2D6 metabolism. NEJM 2004
    20. 26. drug-drug interactions are mostly unavoidable Known side effects Unavoidable Avoidable Medication errors Product quality defects Preventable adverse events Injury or death <ul><li>Remaining uncertainties </li></ul><ul><li>Unexpected side effects </li></ul><ul><li>Unstudied uses </li></ul><ul><li>Unstudied populations </li></ul>
    21. 27. LIPITOR: Known Side Effects <ul><li>Lipitor blocks the production of cholesterol in the body. </li></ul><ul><li>May reduce risk of hardening of the arteries, which can lead to heart attacks, stroke, and peripheral vascular disease </li></ul>
    22. 28. Medication errors are a significant source of adverse events <ul><li>ADR is one of the leading causes of hospitalization and death </li></ul><ul><li>6.7% of hospitalized patients have serious ADRs </li></ul><ul><li>0.3% of hospitalized patients have fatal ADRs </li></ul>Known side effects Unavoidable Avoidable Medication errors Product quality defects Preventable adverse events Injury or death <ul><li>Remaining uncertainties </li></ul><ul><li>Unexpected side effects </li></ul><ul><li>Unstudied uses </li></ul><ul><li>Unstudied populations </li></ul>
    23. 29. Many factors contribute to drug recalls FDA: Center for Drug Evaluation and Research 2003 - Report to the Nation
    24. 30. VIOXX: Unknown Side Effects Treatment for Acute Pain increased risk of heart attack and stroke (after 18 months)
    25. 31. Diagnostics AmpliChip CYP450: Range of drug metabolism phenotypes is observed for individuals based upon the cytochrome P-450 genes
    26. 33. But wait a minute…
    27. 34. There is still lots to figure out… <ul><li>Science still early. Limited data in public domain. </li></ul><ul><li>Many variations not clinically significant </li></ul><ul><li>Expensive to test for genotype (currently) </li></ul><ul><li>Ethical issues in testing individual genotype </li></ul><ul><li>Unclear how to deliver information to the practitioner </li></ul>
    28. 36. Things to Consider <ul><li>Does my doctor know enough about genomic medicine to be advising me? </li></ul><ul><ul><li>Are there genetic counselors available? </li></ul></ul><ul><li>Will the test only be for this condition? </li></ul><ul><ul><li>What if I am susceptible to another disease ? </li></ul></ul><ul><li>Who will know about this? </li></ul><ul><ul><li>Doctors… insurance companies ? </li></ul></ul><ul><li>How exactly will the results be kept secure and in confidence? </li></ul>
    29. 37. How much will this cost? <ul><li>More drugs may succeed in clinical trials due to positive outcome for smaller subset </li></ul><ul><ul><li>Will pharma attempt to recoup costs with a pricier drug? </li></ul></ul><ul><li>Will public health cover the costs of genetic testing? </li></ul><ul><ul><li>Reduce overall health cost due to fewer ADRs </li></ul></ul><ul><ul><li>Should we determine clinically validated genes or should we sequence the genome? </li></ul></ul><ul><li>How will insurance premiums be affected? </li></ul>
    30. 39. Personalied Medicine: What’s your take?
    31. 40. Outline <ul><li>Personalized Medicine </li></ul><ul><li>Drug Discovery </li></ul><ul><li>Role of Bioinformatics </li></ul><ul><li>Current Research </li></ul>
    32. 41. What is a drug? <ul><li>A drug Compound of definite composition and having a pharmacological effect </li></ul><ul><li>Natural products </li></ul><ul><ul><li>plant extracts </li></ul></ul><ul><ul><li>animal fluids (e.g., snake venoms) </li></ul></ul><ul><ul><li>isolated products (biological) </li></ul></ul><ul><ul><li>chimeric / recombinant products (biological) </li></ul></ul><ul><li>Synthetic chemicals </li></ul><ul><ul><li>derived from medicinal chemistry </li></ul></ul><ul><ul><li>derived from combinatorial chemistry </li></ul></ul>
    33. 42. 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
    34. 43. Drug Discovery <ul><li>Discovery: </li></ul><ul><ul><li>finding a lead compound (K D < 1 μ M) </li></ul></ul><ul><ul><li>target, assay, chemical screening, hit identification, mechanism of action, lead identification, lead optimization </li></ul></ul><ul><ul><li>in vivo proof of concept in animals and demonstration of therapeutic value </li></ul></ul><ul><li>Development: </li></ul><ul><ul><li>Evaluate its effectiveness </li></ul></ul><ul><ul><li>begins when the decision is made to put a molecule into clinical trials </li></ul></ul>
    35. 44. Barriers that a drug must overcome to reach intended target <ul><ul><li>chemically stable in stomach (pH 1) </li></ul></ul><ul><ul><li>not digested by gastrointestinal enzymes </li></ul></ul><ul><ul><li>absorbed into the bloodstream </li></ul></ul><ul><ul><ul><li>pass through series of cell membranes </li></ul></ul></ul><ul><ul><li>not bind tightly to other substances </li></ul></ul><ul><ul><li>survive xenobiotic detoxification by liver enzymes </li></ul></ul><ul><ul><li>avoid excretion by kidneys </li></ul></ul><ul><ul><li>brain: cross blood-brain barrier (blocks polar substances) </li></ul></ul><ul><ul><li>intracellular receptor: pass through cell membrane </li></ul></ul>
    36. 45. R&D Spending and New Medicines <ul><li>38 new medicines in 2004 </li></ul><ul><ul><li>Cancer </li></ul></ul><ul><ul><li>Infectious diseases </li></ul></ul><ul><ul><li>Parkinson’s therapy </li></ul></ul><ul><ul><li>Radiation contamination </li></ul></ul><ul><ul><li>Pain alleviation from made from a synthetic form of a sea-snail venom. </li></ul></ul>PhRMA Annual Report 2005-2006
    37. 46. An Analysis <ul><li>National Institute for Health Care Management </li></ul><ul><ul><li>Changing Patterns of Pharmaceutical Innovation, May 2002 </li></ul></ul><ul><li>Quality of pharmaceutical innovation varies widely. </li></ul><ul><ul><li>Breakthrough treatments for life threatening diseases </li></ul></ul><ul><ul><li>TO </li></ul></ul><ul><ul><li>Minor modifications of drugs that have been on the market for some time. </li></ul></ul>
    38. 47. Most drugs approved are only slightly modified
    39. 48. Less innovative than you think
    40. 49. Cost of developing drugs <ul><li>Global Alliance for Tuberculosis Drug Development </li></ul><ul><ul><li>www.tballiance.org </li></ul></ul><ul><ul><li>&quot;The Economics of TB Drug Development&quot; </li></ul></ul><ul><li>Costs to discover and develop a new anti-TB drug range from $115 million to $240 million. </li></ul><ul><ul><li>$40 million to $125 million for discovery </li></ul></ul><ul><ul><li>$76 million to $115 million for preclinical development through Phase III trials </li></ul></ul>
    41. 50. Profits as a Percentage of Assets, 2002 Top 7 of Fortune 500 Industries Source: Fortune Magazine, April 14, 2003
    42. 51. <ul><li>Drug development has been and still is costly, risky, and lengthy </li></ul><ul><li>R&D costs have increased , but the industry remains one of the most profitable </li></ul><ul><li>Pharmaceutical innovation is targeted towards protecting interests </li></ul><ul><li>The payoffs for improvements in the process are significant </li></ul>The Drug Business
    43. 52. <ul><li>What disease would you try to treat with a drug? </li></ul>
    44. 53. Outline <ul><li>Personalized Medicine </li></ul><ul><li>Drug Discovery </li></ul><ul><li>Bioinformatics </li></ul><ul><li>Current Research </li></ul>
    45. 54. What is Bioinformatics? <ul><li>“ Using computers to solve problems in biology ” </li></ul><ul><li>Bioinformatics is a scientific discipline that encompasses all aspects of biological information acquisition, processing, storage, distribution, analysis and interpretation . </li></ul><ul><li>Bioinformatics combines the tools of Biology, Chemistry, Mathematics, Statistics and Computer Science to understand and model biological processes. </li></ul>
    46. 55. Bioinformatics For Knowledge Discovery <ul><li>Experimental Data </li></ul><ul><ul><li>Sequence </li></ul></ul><ul><ul><li>Structure </li></ul></ul><ul><ul><li>Function </li></ul></ul><ul><ul><li>Expression </li></ul></ul><ul><ul><li>Regulation </li></ul></ul><ul><ul><li>Interactions </li></ul></ul><ul><ul><li>Pathways </li></ul></ul><ul><ul><li>Disease </li></ul></ul><ul><ul><li>Genetics </li></ul></ul><ul><ul><li>Taxonomy </li></ul></ul><ul><ul><li>Small molecules </li></ul></ul><ul><ul><li>Kinetics </li></ul></ul><ul><ul><li>Dynamics </li></ul></ul>model validate knowledge simulate
    47. 63. Bioinformatics & Drug Discovery <ul><li>Knowledge Discovery </li></ul><ul><li>Identification of potential drug targets </li></ul><ul><ul><li>Genomics </li></ul></ul><ul><ul><li>Proteomics </li></ul></ul><ul><li>Cheminformatics </li></ul><ul><ul><li>Drug target modeling </li></ul></ul><ul><ul><li>Drug optimization </li></ul></ul><ul><li>Simulating drug effects on pathways </li></ul><ul><li>Estimating toxicological effects </li></ul>
    48. 64. Quick Survey of Bioinformatics Applications in Drug Discovery <ul><li>Tissue profiling </li></ul><ul><li>Drug Screening </li></ul>
    49. 65. Gene Expression <ul><li>A gene is expressed when it is transcribed from DNA to RNA and then possibly translated into a protein </li></ul><ul><li>By measuring the products of transcription, we can assay gene expression </li></ul>
    50. 66. <ul><li>Differentiation : All cells in a body have the same genome. Expression is what differentiates one tissue from another, e.g. brain from liver. </li></ul><ul><li>Physiology : Cells do their business (dividing, sending signals, digesting, etc.) largely via changes in expression </li></ul><ul><li>Response to stimuli : Environmental changes (like drugs or disease) often cause changes in expression </li></ul><ul><li>Disease markers and drug targets : changes in expression associated with disease can be diagnostic markers and/or suggest novel pharmaceutical approaches. </li></ul>Importance of Gene Expression
    51. 67. Microarrays Can Be Used To Determine Relative Gene Expression
    52. 68. <ul><li>Distinct types of B-cell lymphoma identified by gene expression profiling </li></ul>
    53. 69. Drug Screening <ul><li>If we have a target , how do we find some compounds that might bind to it? </li></ul><ul><li>Combinatorial chemistry </li></ul><ul><li>Computational screening </li></ul>
    54. 70. Combinatorial Chemistry <ul><li>Parallel synthetic approach </li></ul><ul><ul><li>Build on previous products </li></ul></ul><ul><ul><li>Generate diversity by adding R groups </li></ul></ul><ul><ul><li>Recover most active compounds </li></ul></ul><ul><li>Solid phase synthesis </li></ul><ul><ul><li>Wash away excess reagants & other products </li></ul></ul><ul><ul><li>Can recover the main product </li></ul></ul><ul><li>Parallel testing </li></ul>
    55. 71. combinatorial synthesis of non-peptide drugs + 1) 2) RXN 1 RXN 2
    56. 72. Structure-Based Docking Methods <ul><li>Need 3D structure </li></ul><ul><li>Scan a virtual library of small molecules and “dock” them to a site of interest on a protein structure </li></ul><ul><li>Predict binding energy </li></ul><ul><li>Filters thousands of compounds relatively quickly </li></ul><ul><li>Top hits can be used for more rigorous computational/experimental characterization and optimization </li></ul>
    57. 73. <ul><li>synthesis </li></ul><ul><li>of compound </li></ul><ul><li>↓ </li></ul><ul><li>manipulation of structure to get better drug </li></ul><ul><li>(greater efficacy, </li></ul><ul><li>fewer side effects) </li></ul>Aspirin
    58. 74. Quantitative Structure-Activity Relationship (QSAR) <ul><li>find consistent relationship between biological activity and molecular properties, so that these “rules” can be used to evaluate the activity of new compounds. </li></ul><ul><li>extract features (hydrophobicity, pK, van der Waals radii, hydrogen bonding energy, conformation) </li></ul><ul><li>build mathematical relationship f(activity|features) </li></ul><ul><li>automatically assesses the contribution of each feature </li></ul><ul><li>can be used to make predictions on a new molecule </li></ul>
    59. 75. 3D QSAR for CYP3A4
    60. 76. 3D QSAR for CYP3A4 with known substrates
    61. 77. How to discover a drug
    62. 78. Cancer Therapy <ul><li>Matrix Metallo Proteinases (MMP) </li></ul><ul><ul><ul><li>Degrade proteins in the extracellular matrix </li></ul></ul></ul><ul><ul><ul><li>Levels increased in areas surrounding tumor </li></ul></ul></ul><ul><ul><ul><li>Makes it easier for cancer cells to become metastatic </li></ul></ul></ul><ul><li>MMP Inhibitors </li></ul><ul><ul><li>Stop MMPs from working </li></ul></ul><ul><ul><li>Can block tumor growth </li></ul></ul>
    63. 79. <ul><li>“ metallo” in MMP = zinc </li></ul><ul><ul><li>-> catalytic domain contains 2 zinc atoms </li></ul></ul>MMP catalysis Whittaker et al. Chem. Rev. 1999 , 99 , 2735-2776
    64. 80. Peptidic hydroxamate inhibitors <ul><li>Specific for MMPs </li></ul><ul><li>Better binding </li></ul><ul><li>But poor oral bioavailability </li></ul><ul><li>(how much gets into the bloodstream) </li></ul>
    65. 81. Drug Discovery by Agouron Pharmaceuticals <ul><li>Designed a new inhibitor </li></ul><ul><li>Used structure of human MMPs bound to various inhibitors in silico </li></ul><ul><li>Determined key residues, ligand substituents needed for binding </li></ul>Gelatinase A
    66. 82. Structural bioinformatics to design nonpeptidic hydroxylates oral bioavailabity binding anti-growth anti-metastasis repeat…
    67. 83. Prinomastat <ul><li>Good oral bioavailability </li></ul><ul><li>Selective for specific MMPs </li></ul><ul><li>Evidence showing prevention of lung cancer metastasis in rat and mice models </li></ul><ul><li>Clinical trials </li></ul><ul><ul><li>cell lung cancer </li></ul></ul><ul><ul><li>prostate cancer </li></ul></ul>
    68. 85. Outline <ul><li>Personalized Medicine? </li></ul><ul><li>Drug Discovery </li></ul><ul><li>Bioinformatics </li></ul><ul><li>Current Research </li></ul>
    69. 86. <ul><li>Goals </li></ul><ul><li>Integrate pharmacogenomics knowledge </li></ul><ul><li>Improve our understanding of how genetic variations affect drug responses. </li></ul><ul><li>Deduce the biochemical mechanisms that underlie disease phenotypes </li></ul><ul><li>Predict side-effects from drug </li></ul><ul><li>interactions due to unexpected </li></ul><ul><li>cellular interactions </li></ul>
    70. 87. How do we find this knowledge?
    71. 88. <ul><li>PHARMGKB </li></ul><ul><li>+ Role of genes, gene variants , drugs </li></ul><ul><li>+pharmacokinetics +pharmacodynamics </li></ul><ul><li>+ clinical outcomes. </li></ul><ul><li>+ Links to publications </li></ul><ul><li>- Natural language descriptions </li></ul><ul><li>- Variant details in publications </li></ul>
    72. 89. Surface web: 167 terabytes Deep web: 91,000 terabytes 545-to-one
    73. 90. How do we integrate these resources?
    74. 91. Data silos – not made for sharing
    75. 92. The Semantic Web will expose data and link knowledge
    76. 93. Bio2RDF is building the linked data web for biological data
    77. 94. Bio2RDF provides the methodology to create and glue these different databases.
    78. 95. Resource Description Framework (RDF) <ul><li>Allows one to express propositions, and reason about them </li></ul><ul><li>Uniform Resource Identifier (URI) are entity names </li></ul><ul><ul><li>i.e P05067 </li></ul></ul><ul><ul><li>is a name for Amyloid precursor protein </li></ul></ul>APP Protein is a <ul><li>A RDF statement consists of: </li></ul><ul><ul><li>Subject : resource identified by a URI </li></ul></ul><ul><ul><li>Predicate : resource identified by a URI </li></ul></ul><ul><ul><li>Object : resource or literal </li></ul></ul>
    79. 96. Now Link Data! APP Protein is a Alzheimer’s Disease is a is involved in
    80. 97. something you can lookup or search for with rich descriptions
    81. 98. Ontology as Strategy
    82. 99. Semantic Knowledge Base APP Protein Is a Molecule is a is a fact ontology Knowledge base
    83. 100. Ontologies <ul><li>Shared conceptualization </li></ul><ul><li>Tell computers what we believe </li></ul><ul><li>Allows computer programs called reasoners to make inferences </li></ul>
    84. 101. Semantic Query Answering http://smart.dumontierlab.com ISWC Semantic Web Challenge: CS Honors: Alex De Leon
    85. 102. Build a knowledge base from a series of questions
    86. 103. Cell Simulation Molecules Interactions (metabolic/signaling) Compartments Cell Simulation + +
    87. 104. 3D Particle Simulation GridCell - Dr. Warren Gross & Laurier Boulianne, PhD Candidate Engineering
    88. 105. 3D Tetris or Science at Work?
    89. 106. Cellular Visions: The Inner Life of a Cell
    90. 107. Learn more and Get involved! BIOC 3008 [0.5 credit]: Bioinformatics BIOC 4008 [0.5 credit]: Metabolic Modeling and Simulation BIOC 2400 [0.5 credit]: Independent Research I BIOC 3400 [0.5 credit]: Independent Research II BIOC 4906 [1.0 credit]: Interdisciplinary Research BIOL 4900 [1.0 credit]: Biology Directed Special Studies BIOL 4901 [0.5 credit]: Biology Directed Special Studies BIOL 4908 [1.0 credit]: Biology Research Thesis BIOC 4907 [1.0 credit]: Biochemistry Essay and Research Proposal BIOC 4908 [1.0 credit]: Biochemistry Research Project CHEM 4908 [1.0 credit]: Chemistry Research Project and Seminar CMPS 4909 [1.0 credit]: Computational Science Research Thesis COMP 4901 [0.5 credit]: Computer Science Directed Studies COMP 4905 [0.5 credit]: Computer Science Research Thesis SYSC 4907 [0.5 credit]: Engineering Project
    91. 108. Learn more and Get involved! <ul><li>Faculty </li></ul><ul><li>Biology - Jim Cheetham, Ashkan Golshani, Myron Smith, Bill Willmore, Iain Lambert, Susan Aitken, John Vierula </li></ul><ul><li>Computer Science - Frank Dehne </li></ul><ul><li>Systems and Computer Engineering - Jim Green, Gabriel Wainer </li></ul><ul><li>Programs </li></ul><ul><li>BSc – Bioinformatics (Honours), Computational Biochemistry (Honours), Computational Biology (Honours) </li></ul><ul><li>BCSc – stream in Bioinformatics </li></ul><ul><li>Master’s Specialization in Bioinformatics </li></ul>
    92. 109. dumontierlab.com [email_address]