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Data Mining & Signal Detection In Pv


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Data Mining & Signal Detection In Pv

  1. 1. Dr. Bhaswat S. Chakraborty Senior VP, R&D, Cadila Pharmaceuticals January 22, 2009 Presented at Pharmacovigilance 2010, January 21-22, 2010
  2. 2. Risk Management and Pharmacovigilance <ul><li>Increased focus on safety and risk management is a global issue with diminishing boundaries </li></ul><ul><li>Knowledge and experience of the drug and its life-cycle further develops as we understand its use and hazards </li></ul><ul><li>Development of global risk management plan rather than individual region or country Risk </li></ul><ul><li>Management plans would be an important step forward to more effectively and accurately assess the safety of pharmaceutical drug products </li></ul><ul><li>An early risk management planning between company, regulator and healthcare professionals is key for successful product life cycle management </li></ul><ul><li>Risk Communication Plan between Company, Regulator, Healthcare Professionals and Patients is getting more transparent </li></ul>
  3. 3. And Yet… <ul><li>Despite these models of risk management, stakeholders use traditional methods for PV </li></ul><ul><li>Conservative methods do not capture many SAEs and USAEs that are possible to capture from huge databases without further experimentation </li></ul><ul><li>Data mining is one such approach </li></ul><ul><li>Data mining can help find unrecognized toxic signals </li></ul>
  4. 4. Two categories of approved drug <ul><li>Category 1 </li></ul><ul><ul><li>Those who are unequivocally superior to existing drugs of that class in efficacy </li></ul></ul><ul><ul><li>May or may not be superior in safety </li></ul></ul><ul><li>Category 2 </li></ul><ul><ul><li>Those who are not superior to existing drugs of that class in efficacy </li></ul></ul><ul><ul><li>Non-inferior </li></ul></ul><ul><ul><li>Superior to placebo but inferior to existing standard care </li></ul></ul><ul><ul><li>May or may not be superior in safety </li></ul></ul>
  5. 5. Premature Approval? <ul><li>Many Category 2 drugs whose complete safety profile is still unknown were approved </li></ul><ul><li>In some cases, drugs are approved despite identification of SAEs in premarketing trials </li></ul><ul><ul><li>Alosetron hydrochloride – ischemic colitis </li></ul></ul><ul><ul><li>Grepafloxacin hydrochloride – QT prolongation and deaths </li></ul></ul><ul><ul><li>Rofecoxib – heart attack and stroke (long-term, high-dosage use) </li></ul></ul><ul><li>They were all subsequently withdrawn from the market because of these SAEs </li></ul>
  6. 6. Market Uptake and Sales Volume <ul><li>Many drugs whose complete safety profile is still unknown actually have/had a rapid market and very high sales volume through increased Rx. </li></ul><ul><li>Promotion of early use of new drugs by sponsors </li></ul><ul><li>Physicians' adoption of such drugs </li></ul><ul><li>Direct-to-consumer drug advertising </li></ul><ul><li>Pharma companies concern for patent life, a desire to mold prescribing habits prior to the market entry of competitors </li></ul><ul><li>“ Ramp-up&quot; in sales encourages investors and increase stock prices. </li></ul><ul><li>New drug safety may be further compromised by the failure to conduct postmarketing studies </li></ul>
  7. 9. J. Herson. In Data and Safety Monitoring Committees in Clinical Trials
  8. 10. Having an Adverse Events Database <ul><li>Is not a bad idea </li></ul><ul><li>All good pharma companies have AE database </li></ul><ul><li>Almost all developed country regulatory agencies have AE database </li></ul><ul><li>The WHO Uppsala Monitoring Centre (UMC) now receive >1,000,000 reports per year </li></ul><ul><li>Such databses can really help in bringing down drug induced morbidity </li></ul>
  9. 11. Desirable Attributes of AE Database Software <ul><li>Should be well integrated with Clinical data management software </li></ul><ul><li>User friendly </li></ul><ul><li>Individual reports management features </li></ul><ul><li>Easy for query </li></ul><ul><li>Line listing of the entire database or part is possible and easy </li></ul><ul><li>Data extraction is easy, with desirable filters </li></ul><ul><li>May also keep track of postmarketing Rx utility and complaints data </li></ul>
  10. 12. Gavali, Kulkarni, Kumar and Chakraborty (2009), Ind J Pharmacol , 41, 162-166 or any comprehensive database Collection of ICSRs from CADRMP Conversion of free text to structured information Data cleaning and duplicate detection Applying quantitative or statistical methods Computing an accurate measure for SD
  11. 13. Targeted Event Y All other events Total Targeted Drug X A B A+B All other drugs C D C+D Total A+C B+D A+B+C+D
  12. 14. Criteria for a Toxic Disproportional ADR <ul><li>ROR = </li></ul><ul><li> χ 2 = </li></ul>Significant disproportional Signal is detected when  2 is ≥ 4.0 and the rest ≥ 2.0
  13. 15. Casestudy Example: Propranolol-Bradycardia <ul><li>PRR = 2.51 </li></ul><ul><li>ROR = 2.58 </li></ul><ul><li>χ 2 = 3.26 </li></ul><ul><li>Therefore, bradycardia is not a significant disproportional signal (Serious Adverse Event) associated with Proprano lol </li></ul>Gavali, Kulkarni, Kumar and Chakraborty (2009), Ind J Pharmacol , 41, 162-166 Bradycardia Not Bradycardia Propranolol HCL 4 82 Not Propranolol HCL 52 2749
  14. 16. Casestudy Examples – Significant Signals <ul><li>Association </li></ul><ul><ul><li>Bupropion – seizures </li></ul></ul><ul><ul><li>Olanzapine – thrombosis </li></ul></ul><ul><ul><li>Pergolide – increased libido </li></ul></ul><ul><ul><li>Risperidon – diabetes mellitus </li></ul></ul><ul><ul><li>Terbinafine – stomatistis </li></ul></ul><ul><ul><li>Rosiglitazone – liver function abnormalities </li></ul></ul><ul><li>Dis-association </li></ul><ul><ul><li>Isotretinoine– suicide </li></ul></ul>Source: LAREB
  15. 17. Thank You Very Much Acknowledgment: Sharwan Singhal