Design of Experiments talk given at University of Puerto Rico

1. Design of Experiments (DOE): A “New” Approach to Reaction Optimization Dr. Steven Weissman Merck & Co. Feb 4, 2008/UPR

10. Automated Synthesis Cycle Design Experiment Analysis Informatics

11. Automated Synthesis Cycle Design Experiment Analysis Informatics Design of Experiments

14. Example of OFAT (11/07)

15. 21 Reactions

19. DoE Introduction Core Knowledge (Engineering, Chemistry, Biology,…) Statistical Knowledge Develop Solutions DOE is NOT a replacement for process knowledge

25. High Throughput Screening = 96 x Discreet variables- ‘The what” What is the best ligand/catalyst combination ? What is the best solvent ?

26. High Throughput Screening = 96 x Can we do OPTIMIZATION this way too ??

27. High Throughput Optimization ?? = 96 x If so,………………….. Which reactions do we run ? How do assess the data ?

28. High Throughput Optimization ?? = 96 x Statistical Design of Experiments (DOE)

29. HTS Reaction Vials

31. DOE Design (N=27) 64 0.25 1.85 0.875 4 100 20 58 0.25 1.85 0.875 2 100 19 66 0.25 1.85 0.875 3 115 18 64 0.25 1.85 0.875 3 85 17 76 0.4 2.5 1.5 4 115 16 80 0.1 2.5 1.5 4 85 15 65 0.1 2.5 1.5 2 115 14 79 0.4 2.5 1.5 2 85 13 76 0.1 2.5 0.25 4 115 12 88 0.4 2.5 0.25 4 85 11 63 0.4 2.5 0.25 2 115 10 48 0.1 2.5 0.25 2 85 9 54 0.1 1.2 1.5 4 115 8 39 0.4 1.2 1.5 4 85 7 55 0.4 1.2 1.5 2 115 6 45 0.1 1.2 1.5 2 85 5 55 0.4 1.2 0.25 4 115 4 43 0.1 1.2 0.25 4 85 3 49 0.1 1.2 0.25 2 115 2 45 0.4 1.2 0.25 2 85 1 Yield E:Conc D:Boron/Br C:Cu B:P/Pd A:temp Rxn # Response 1 Factor 5 Factor 4 Factor 3 Factor 2 Factor 1

32. DOE Creates a Design Space Design-Expert® Software Yield X1 = A: temp X2 = B: P/Pd X3 = C: Cu load Actual Factors D: Boron/Br = 2.50 E: Conc = 0.40 Cube Yield A: temp B: P/Pd C: Cu load A-: 85.00 A+: 115.00 B-: 2.00 B+: 4.00 C-: 0.25 C+: 1.50 63.7936 74.1825 86.3492 83.738 59.9047 70.2936 82.4603 79.8492

33. DOE Expts: How Many ? screening optimaztion 29 9 11 9 5 27 10 7 10 4 17 5 7 5 3 35 16 3 16 5 19 8 3 8 4 11 4 3 4 3 factors Total rxns Lo Med HI rxns factors

34. DOE Case Studies

35. MK-0518 First-in-Class Oral HIV-1 Integrase Inhibitor Approved by FDA October-12-2007

36. MK-0518

37. MK-0518 Challenge: to reduce manufacture cost by 20%

38. MK-518: Problem step Peter Maligres Existing Conditions : 4 eq Mg(OMe) 2 / 4 eq MeI @ 0.5 M (68% isolated yield) 18 solvents, 8 bases screened 78 22

39. MK-518: DOE Optimization Peter Maligres DOE Optimzation Design Factors : Mg(OMe) 2 equiv: 1.0 and 3.0 MeI equiv: 2.5 and 5.0 Conc: 0.25 and 1.0 M Temperature: 30 and 65 o C 19 reactions Responses (4 and 20 h): Assay yield Selectivity

40. MK-518 Optimization Peter Maligres DOE Optimal Settings Base equiv: 1.0 and 3.0 MeI equiv: 2.5 and 5.0 Temperature: 30 and 65 o C Conc: 0.25 and 1.0 M Time: 4 and 20 h 99 1

41. MK 518: Surface Model

42. Effect of Temp & Conc

43. Effect of Base and Conc

44. MK518-In Situ Demethylation 99/1 80/20 N vs O 99% 95% Conv 20 h 4 h

46. MK-518 Optimization Peter Maligres Yield =90% Selectivity = >99.9 % Safer, more economical reagents Incorporated best practices from DOE: HI Temp/HI Concentration/Longer reaction times

47. MK-518 Summary 78 22 > 99 < 1 DOE Goal of 20% reduction in drug inventory cost was achieved Higher Yield cascades back to allow fewer RM/solvents to be used Submitted for 2008 Presidential Green Chemistry Award

49. Case Study 2- Suzuki DOE Factors : Ligand/Pd ratio: 1.0 and 3.0 Catalyst load: 0.1 and 0.5 mole% Molarity boronic acid: 0.5 and 1.5 Temperature: 60 and 80 o C 27 Reactions in 96-well plate format, 2 days to plan/setup/execute/assay 0.65 g material (24 mg/rxn) !!

50. Case Study 2- Suzuki DOE Optimal Settings : Ligand/Pd ratio: 1.0 and 3.0 Catalyst load: 0.1 and 0.5 mole% Molarity boronic acid : 0.5 and 1.5 Temperature: 60 and 80 o C ( 65 o C )

51. Effect of Temp and Pd Loading Lig/ catalyst ratio fixed at 3:1; Triol M fixed at 1.5 M Overall LCAP

52. Optimized Conditions Optimized Experiment: -increased LCAP by 1% -decreased DesBr impurity (50%) -decreased Pd by 75% -decreased Lig by 70% Spencer Dreher

53. Case Study #3 Dave Pollard Goal: to reduce cost by increasing productivity 100 g/L

54. Screening Design Dave Pollard Factors Octanol: 40 and 60 % NADP equiv: 0.1 and 0.5 % Concentration: 50 and 150 g/L Temp: 25 and 35 o C Enzyme load: 0.3 to 1.0 g/L 19 experiments

55. DOE Factors Plot

56. Interaction: Conc and NAD

57. Screening Result Dave Pollard Factor Preferred Setting Octanol: 40 and 60 % No impact NADP equiv: 0.1 and 0.5 % No impact- increase more ? Concentration: 50 and 150 g/L 50 g/L- undesirable setting Temp: 25 and 35 o C minimal effect- set at 30 o C Enzyme load: 0.3 to 1.0 g/L 1.0 g/L- increase more

58. Optimization Design Dave Pollard Factor NADP equiv: 0.5 and 1.5 % Concentration: 100 and 200 g/L Enzyme load: 0.5 to 3.0 g/L 19 experiments

59. Optimization Design Factor Preferred setting NADP equiv: 0.5 and 1.5 % No effect Concentration: 100 and 200 g/L 200 Enzyme load: 0.5 to 3.0 g/L 3.0

60. Optimization Design Factor Preferred setting NADP equiv: 0.5 and 1.5 % No effect Concentration: 100 and 200 g/L 200 Enzyme load: 0.5 to 3.0 g/L 3.0 Confirming experiment at 200 g/L NADP= 0.5 g/L and enzyme at 3 g/L gave 100% conversion Goal achieved

61. Case Study #4-Sonogashira S. Krska/A. Northrup Medicinal Chemistry conditions

62. HTS Result Screened: ligands and Pd sources 32 reactions (HTS-96 well plate format) – 1.5 days- 125 mg of substrate

65. DOE Optimization Cu/Pd = 2

68. DOE Summary

69. Case Study # 5 Mark Weisel 10% loading Pearlman’s catalyst 25 o C/45 psi/EtOAc 88 A% Goal: to minimize formation of impurities/maximize desired product 12 A%

70. Case Study # 5 Mark Weisel 88 A% 12 A% DOE design: 4 Factors (19 reactions) Temp (25 and 55 o C) Pressure (30 and 60 psi) Pd(OH) 2 loading (5 and 15 wt%) Volume EtOAc (6 and 10 ml/g)

71. Factors

72. Effect of Pd and Temp

77. QUESTIONS ?