Personalized Medicine Overview

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This is a brief overview of the current state of personalized medicine and its scientific and clinical challenges.

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  • The presentation focused on the scientific and clinical challenges posed by personalized medicine
  • Personalized Medicine Overview

    1. 1. Personalized Medicine:Scientific and Clinical Challenges<br />Andrew Helicher and Tieming Lang<br />INS 497C<br />April 30, 2010<br />
    2. 2. Agenda<br /><ul><li>Personalized Medicine Overview
    3. 3. Scientific Challenges
    4. 4. Clinical Challenges</li></ul>2<br />
    5. 5. Agenda<br /><ul><li>Personalized Medicine Overview
    6. 6. Scientific Challenges
    7. 7. Clinical Challenges</li></ul>3<br />
    8. 8. Definition<br />4<br />“Use of molecular or genetic characteristics to customize therapy for individuals”<br />But how well does individual resemble various sub-populations?<br />Patient<br />Sub-Populations<br />A Patient’s resemblance to a sub-population is probabilistic vs. deterministic. <br />This is not a perfect science, but benefits can be achieved. <br />Kohane, 2009, p. 1<br />
    9. 9. Categories and Benefits<br />Ginsburg, 2009, p. 1<br />Aspinall, 2007, p. 1 <br />5<br />
    10. 10. Challenges<br />6<br />Aspinall, 2007<br />Davis, 2010<br />
    11. 11. Agenda<br /><ul><li>Personalized Medicine Overview
    12. 12. Scientific Challenges
    13. 13. Clinical Challenges</li></ul>7<br />
    14. 14. Scientific Challenges<br />8<br /><ul><li>The molecular mechanisms of diseases
    15. 15. Finding the right marker
    16. 16. Statistical nature</li></li></ul><li>Scientific Challenges<br />9<br /><ul><li> The molecular mechanisms of diseases
    17. 17. Finding the right marker
    18. 18. Statistical nature</li></li></ul><li>The Molecular Mechanisms of Diseases<br /><ul><li>One gene, one enzyme theory
    19. 19. Since one gene codes for one protein, mal-function of a protein can be traced back to mutation of one gene
    20. 20. If we can know the gene that is responsible for a disease, finding a mutation can certainly predict disease
    21. 21. Problem:
    22. 22. We don’t know the root genes of many diseases</li></ul>10<br />
    23. 23. <ul><li>One gene, multiple diseases; multiple genes, one diseases
    24. 24. Many genes have multiple functions and participate in multiple cellular pathways.
    25. 25. Many diseases are result of disruption of a particular cellular pathway or function, which often involves many genes
    26. 26. Problem:
    27. 27. Which gene(s) can be used as diagnostic marker?</li></ul>11<br />The Molecular Mechanisms of Diseases<br />
    28. 28. <ul><li>The case of cancer:
    29. 29. Cancer cells are usually genetically heterogeneous
    30. 30. Disruption of many cellular pathways can contribute to cancer
    31. 31. Most cancer cells are result of accumulation of mutations on multiple genes
    32. 32. Cancer stem cells may be the root cause of resistance and malignancy
    33. 33. Problems:
    34. 34. Marker to which gene to use?
    35. 35. What’s the utility of marker if the associated gene is not the root cause of cancer?</li></ul>12<br />The Molecular Mechanisms of Diseases<br />
    36. 36. Scientific Challenges<br />13<br /><ul><li>The molecular mechanisms of diseases
    37. 37. Finding the right marker
    38. 38. Statistical nature</li></li></ul><li><ul><li>Which mutation to use for diagnosis?
    39. 39. Types of mutation:
    40. 40. Single nucleotide mutations
    41. 41. Deletions and insertions
    42. 42. Change of repetition numbers
    43. 43. Epigenetics
    44. 44. For complex genes, such as BRCA1 and BRCA2, there are thousands of known polymorphisms and mutations
    45. 45. Many mutations, although change protein activity, do not result in diseases</li></ul>14<br />Finding the Right Marker<br />
    46. 46. What type of marker to use?<br /><ul><li>Single nucleotide mutation
    47. 47. Deletion and insertion
    48. 48. Single nucleotide polymorphism (SNP)
    49. 49. Microarrays
    50. 50. Associated marker
    51. 51. Expression profile
    52. 52. metabolites</li></ul>15<br />Finding the Right Marker<br />
    53. 53. Scientific Challenges<br />16<br /><ul><li> The molecular mechanisms of diseases
    54. 54. Finding the right marker
    55. 55. Statistical nature</li></li></ul><li>Statistical Nature<br />Most studies are conducted on relatively small population:<br /><ul><li>Not representative of general population.
    56. 56. Participants are more likely to have disease.
    57. 57. Investigators are biased toward positive results.</li></ul>17<br />
    58. 58. Statistical Nature<br />Determinants:<br /><ul><li>Mutation of a gene will cause a disease
    59. 59. Relatively rare</li></ul>Susceptibility:<br /><ul><li>Mutation of a gene will only confer a small increase of disease risk.
    60. 60. Gene complementation/ redundancy
    61. 61. Mutation of DNA repair genes
    62. 62. How to interpret testing results?</li></ul>18<br />
    63. 63. Statistical Nature<br />19<br /><ul><li>Known biomarkers may only have limited effect on disease risk
    64. 64. Companies disagree on which are the strong effect markers</li></ul>Probabilistic results based on different inputs are hard for patients and physicians to interpret and act upon.<br /><ul><li>Companies measure populations differently
    65. 65. Patient responses may be inaccurate (i.e. what is your race?)</li></ul>1/3 of disease risk predictions differ between genetic testing companies 23andMe and Navigenics1<br />Ng, 2009, p. 1-3<br />
    66. 66. Agenda<br /><ul><li>Personalized Medicine Overview
    67. 67. Scientific Challenges
    68. 68. Clinical Challenges</li></ul>20<br />
    69. 69. Challenges to Clinical Adoption<br />Aspinal, 2007, p. 1<br />Ginsburg, 2009, p. 25-26<br />Kalota, 2010, p. 1<br />Downing, 2009, p. 3<br />21<br />
    70. 70. Pre-Requisites to Clinical Adoption<br />22<br />Genomics incorporated into medical education4<br />FDA clarifies genomic regulatory requirements1<br />Pharma produces robust clinical guidance on genomic drugs5<br />Payers create CPT codes and reimburse genomic drugs/diagnostics2<br />Increased Clinical Adoption<br />Scientific advances improve accuracy and clarify of genomic tests<br />Providers are reimbursed for genomic tests3<br />Genomics incorporated into EHR/CDS systems6<br />Ratain, 2007<br />Apinall, 2007<br />Davis, 2010, p. 8<br />Ginsburg, 2009<br />Woodcock, 2007, p. 3<br />Downing, 2009<br />
    71. 71. Questions?<br />23<br />
    72. 72. References<br />24<br />Aspinall, M. & Hamermesh, R. (2007) Realizing the Promise of Personalized Medicine. Harvard Business Review. October, 2007.<br />David, J., Ma, P. & Sufaria, S. (2010) The Microeconomics of Personalized Medicine. McKinsey Quarterly. Retrieved from http://www.mckinseyquarterly.com/The_microeconomics_of_personalized_medicine_2527. February, 2010. <br />Downing, G., Boyle, S., Brinner, K. & Osheroff, J. (2009) Information Management to Enable Personalized Medicine: Stakeholder Roles in Building Clinical Decision Support. BMC Medical Informatics and Decision Making. Retrieved from http://www.biomedcentral.com/content/pdf/1472-6947-9-44.pdf. October 8, 2009. <br />Ginsburg, G. & McCarthy, J. (2009) Transforming the Practice of Medicine Using Genomics. Clinical Cases in Bone Metabolism. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2781216/pdf/ClinicalCases-6-0025.pdf, April 28, 2010. <br />Kohane, I. (2009) The Twin Questions of Personalized Medicine: Who Are You and Whom Do You Resemble? Genome Medicine. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2651581/pdf/gm4.pdf. January 20, 2009. <br />Ng., P., Murray, S., Levy, S. & Venter, J. (2009) An Agenda for Personalized Medicine. Nature. Vol. 461. October 8, 2009. <br />Ratain, M. (2007) Personalized Medicine: Building the GPS to Take Us There. Clinical and Pharmacology Therapeutics. Volume 81, Number 3. March, 2007. <br />Woodcock, J. (2007) Molecular Medicine: How, What, and When? Nature. Volume 82, Number 4. October, 2007. <br />

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