1. Generic Prices Forecasting and Mega Trends

3. How do companies forecast generic prices?

4. Some just react to market changes

5. Fitting trends to prices

6. But reality was different

7. Same Therapeutic Cat Same Therapeutic Category, But Different Decay Rates Selective Serotonin Re-Uptake Inhibitors

8. Same Market Value Same Value, But Different Decay Rates £450,000 - £550,000

9. Same molecule Same Molecule But No Uniformity Fluconazole Caps

10. But actual patterns are very complex

11. Sophisticated Wild Ass Guesses SWAGs

13. Data Collection Wavedata founded in 2000 60,000 hours of data entry 160 wholesalers and suppliers Thousands of generic products 2 years of analysis

14. Trend in average generic price

15. Each product follows a pattern

16. Patterns & Relationships £ ?  Generic Price Volume Market Share Value Brand Generic Spilt No of Manufacturers Reimbursement 

17. Statisticians found each product can be modelled

18. Multiple models were produced, one for each product

19. Each with its own formula

20. First Model (2005) 80 products analysed Linear dynamic model 3 forecast models A, B and C Based on statistical coefficients

21. Further development (2006) Another year of modelling 120 products analysed Non-linear polynomial model Adding Reimbursement arguments Including Tariff M

22. Works for 99% of products No therapeutic adjustment needed No strength adjustment needed Integrated into a web site Current model completed (2007)

24. Can generic prices really be forecast? Before During Actuality Does it work?

32. Model can be adapted for new markets Different coefficients for each market USA EU States Other Markets

33. USA

34. USA vs UK

35. Other Products

37. The ‘Dead Cat Bounce’

38. Cost of goods Manufacturer withdrawal Short or long residual life Holiday link? Bounces are visible side of seasonality? Disease timings – ie hay fever Key Bounce factors

39. 282 products analysed 42 products bounced once 6 products bounced twice 4 products bounced three times  18% of products bounced How often bounces happen

40. Bounces after generic launch

41. Bounces – the real picture

42. Bounce frequency

43. Seasonality – Omeprazole Apr 02- Mar 06

44. Seasonality - Omeprazole Oct 02- Sep 06

45. Seasonality - Ciprofloxacin Jan 03 – Dec 05

46. Seasonality - Levothyroxine Oct 00-Sep 06

47. Seasonality - Atenolol Oct 00-Sep 06 Jan 01- Dec 05

48. Seasonality - Simvastatin Oct 03-Sep 06

49. Seasonality - Lisinopril Jan 01 – Dec 05

50. Clusters 8 Clusters seen so far Some product specific Some not

51. Clusters 1 - 4

52. Clusters 5 - 8

53. Low price point ▪ February ▪ June ▪ November High price points ▪ April ▪ August ▪ December Highs and Lows

54. Highs ▪ When commercial people are on holiday Lows ▪ When commercial people are all working But what about the others? Possible reasons

55. Natural decline √ Reimbursement √ Seasonality √ UK √ Other Markets ? Summary

56. Many Thanks www.wavedata.biz