Combinatorial parameter space experiment design

• US 6,983,233 B1
• Filed: 04/19/2001
• Issued: 01/03/2006
• Est. Priority Date: 04/19/2000
• Status: Active Grant

• Current Assignee: Unchained Labs Inc.
• Original Assignee: Symyx Technologies Incorporated (Dassault Systemes SA)
• Inventors: Wang, Youqi, Falcioni, Marco, Ramberg, C. Eric
• Primary Examiner(s): Allen, Marianne P.
• Application Number:
  US09/840,003
• Time in Patent Office: 1,720 Days
• Field of Search: 703/6, 703/11, 703/12, 703/13, 703/17, 703/22, 702/19, 702/20
• US Class Current: 703/12
• CPC Class Codes: G16B 35/00 ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
• CPC Class Codes: G16C 20/60 In silico combinatorial chemistry

Abstract

Methods and apparatus, including computer program apparatus, implementing techniques for designing sets of combinatorial experiments. A set of experimental parameters, sampling patterns, and constraints defines a set of experiments that is limited to a volume of a hyperspace defined by the set of experimental parameters. Parameters can be grouped by type such that grouped parameters are constrained to perform a common role in the set of experiments. The practicability of the experiment design can be estimated based on the number of experiments in the set of experiments. The experiment design can be used to prepare one or more combinatorial libraries.

Claims

1. A computer program product on a computer-readable medium for designing a set of experiments, the program comprising instructions operable to cause a programmable processor to:

receive input defining a set of experimental parameters, one or more sampling patterns defining a sampling for each parameter of the set of experimental parameters, and one or more constraints limiting the set of experiments to a particular volume or volumes of a hyperspace defined by the set of experimental parameters, at least a plurality of the set of parameters being grouped according to a parameter type such that the grouped parameters are constrained to perform a common role in the set of experiments;

generate a first estimate of the practicability of a first set of experiments defined by the parameters, the sampling patterns and the constraints, the first estimate including a count of the set of experiments defined by the set of experimental parameters, the sampling patterns and the constraints, and provide the first estimate to a user;

receive input modifying at least one of the set of parameters, the sampling patterns or the constraints in response to the first estimate;

in response to the input modifying at least one of the set of parameters, the sampling patterns or the constraints, generate a second estimate of the practicability of a second set of experiments defined by the set of experimental parameters defined by the parameters, the sampling patterns and the constraints, including the modified parameters, sampling patterns or constraints, the second estimate including a count of the second set of experiments, and provide the second estimate to the user, and

in response to input approving of the second estimate, generate an experiment design defined by the parameters, the sampling patterns and the constraints, the experiment design including data representing a final set of experiments, the data including a plurality of sets of coordinates in the hyperspace defined by the set of experimental parameters, each of the sets of coordinates defining an experiment in the final set of experiments.

2. The computer program product of claim 1, wherein:

the sampling patterns include at least a first sampling pattern defined for a first parameter of the set of experimental parameters and a second sampling pattern defined for a second parameter of the set of experimental parameters, wherein the first sampling pattern is different from the second sampling pattern.

3. The computer program product of claim 2, wherein:

at least one of the first and second sampling patterns includes a gradient of parameter values defined by a minimum parameter value, a maximum parameter value and a step size.

4. The computer program product of claim 3, wherein:

the first and second sampling patterns are defined by first and second gradients.

5. The computer program product of claim 1, wherein:

the set of experimental parameters includes a plurality of component materials to be used in the set of experiments.

6. The computer program product of claim 5, wherein:

the set of experimental parameters includes at least one process condition to be varied in the set of experiments.

7. The computer program product of claim 5, wherein:

the constraints include a mixture constraint limiting the fractional contribution of at least a plurality of the component materials to a total composition in one or more of the experiments in the set of experiments.

8. The computer program product of claim 7, wherein:

the mixture constraint specifics a minimum number of component materials to be included in one or more of the experiments in the set of experiments.

9. The computer program product of claim 8, wherein:

the mixture constraint specifies a maximum number of component materials to be included in one or more of the experiments in the set of experiments.

10. The computer program product of claim 5, wherein:

the constraints include a type constraint limiting the total number of parameters of a specified type to be included in one or more of the experiments in the set of experiments.

11. The computer program product of claim 5, wherein:

the constraints include a sum constraint limiting the sum of a contribution of parameters of a specified type to one or more of the experiments in the set of experiments.

12. The computer program of claim 5, wherein:

the constraints include a balance constraint limiting the contribution of at least one parameter to a plurality of experiments of the set of experiments based on the contribution of one or more other parameters to one or more of the experiments in the set of experiments.

13. The computer program product of claim 5, wherein:

the constraints include a list constraint identifying a list of one or more starting compositions to be used to generate the set of experiments.

14. The computer program product of claim 13, wherein:

each of the starting compositions is represented as a point in the hyperspace defined by the set of experimental parameters; and

the list constraint specifies a distance criterion specifying an acceptable distance in the hyperspace from the points corresponding to the starting compositions.

15. The computer program product of claim 13, wherein:

the one or more starting compositions are derived from results of a previous experiment.

16. The computer program product of claim 5, wherein:

the constraints include a synthesis constraint specifying an order in which a plurality of component materials are to be added in a synthesis to be performed in one or more of the experiments in the set of experiments.

17. The computer program product of claim 16, wherein:

the synthesis constraint specifies that the order in which component materials are to be added is to vary between a plurality of experiments in the set of experiments.

18. The computer program product of claim 5, wherein:

the constraints include a process constraint specifying an order in which a plurality of process steps are to be performed in one or more of the experiments in the set of experiments.

19. The computer program product of claim 18, wherein:

the process constraint specifies that the order in which process steps are to be performed is to vary between a plurality of experiments in the set of experiments.

20. The computer program product of claim 1, wherein:

the constraints include a project constraint specifying the order in which individual experiments in the set of experiments are to be performed.

21. The computer program product of claim 20, wherein:

the project constraint includes a priority value assigned to one or more of the set of experiment parameters, the priority value representing a relative priority attached to the corresponding parameter.

22. The computer program product of claim 5, wherein:

the constraints include one or more chemistry-specific constraints selected from balance constraints, electron-counting constraints, atomic size constraints, ionic size constraints, atomic packing constraints, ionic packing constraints, heat of formation constraints, or entropy constraints.

23. The computer program product of claim 1, wherein:

at least one of the constraints includes one or more tolerance values representing an amount by which the corresponding constraint can be relaxed during generation of the experiment design.

24. The computer program product of claim 1, wherein the instructions operable to generate the experiment design include instructions operable to cause a programmable processor to:

identify a plurality of points in the hyperspace defined by the set of experimental parameters corresponding to candidate materials by counting through parameter space points defined by the sampling pattern and applying the experimental constraints to the parameter space points.

25. The computer program product of claim 1, wherein:

the set of experimental parameters includes at least four experimental parameters.

26. The computer program product of claim 1, wherein:

the set of experimental parameters includes at least six experimental parameters.

27. The computer program product of claim 1, wherein:

the set of experimental parameters includes at least ten experimental parameters.

28. The computer program product of claim 1, wherein:

the set of experimental parameters includes at least fifty experimental parameters.

29. The computer program product of claim 1, wherein:

the final set of experiments includes at least 48 experiments.

30. The computer program product of claim 1, wherein:

the final set of experiments includes at least 96 experiments.

31. The computer program product of claim 1, wherein:

the final set of experiments includes at least 1,000 experiments.

32. The computer program product of claim 1, wherein:

the final set of experiments includes at least 10,000 experiments.

33. The computer program product of claim 1, wherein:

the final set of experiments includes at least 50,000 experiments.

34. The computer program product of claim 1, wherein:

the final set of experiments includes at least 100,000 experiments.

35. The computer program product of claim 5, wherein:

each of the component materials has an associated set of material properties describing the component material; and

the instructions operable to cause a programmable processor to receive input defining the set of experimental parameters include instructions operable to cause a programmable processor to receive for each of the component materials a set of values for one or more of the material properties associated with the component material.

36. The computer program product of claim 35, wherein:

at least one of the material properties is selected from the group consisting of molecular weight, equivalents, density and concentration.

37. The computer program product of claim 35, wherein:

at least one of the material properties is a type describing a class of chemicals to be used in generating the experiment design.

38. A computer-implemented method for designing a set of experiments, comprising:

receiving input defining a set of experimental parameters, one or more sampling pattern defining a sampling for each parameter of the set of experimental parameters, and one or more constraints limiting the set of experiments to a particular volume or volumes of a hyperspace defined by the set of experimental parameters, at least a plurality of the set of parameters being grouped according to a parameter type such that the grouped parameters arc constrained to perform a common role in the set of experiments;

generating a first estimate of the practicability of a first set of experiments defined by the parameters, the sampling patterns and the constraints, the first estimate including a count of the set of experiments defined by the set of experimental parameters, the sampling patterns and the constraints, and providing the first estimate to a user;

receiving input modifying at least one of the set of parameters, the sampling patterns or the constraints in response to the first estimate;

in response to the input modifying at least one of the set of parameters, the sampling patterns or the constraints, generating a second estimate of the practicability of a second set of experiments defined by the parameters, the sampling patterns and the constraints, including the modified parameters, sampling patterns or constraints, the second estimate including a count of the second set of experiments, and providing the second estimate to the user; and

in response to input approving of the second estimate, generating an experiment design defined by the parameters, the sampling patterns and the constraints, the experiment design including data representing a final set of experiments, the data including a plurality of sets of coordinates in the hyperspace defined by the set of experimental parameters, each of the sets of coordinates defining an experiment in the final set of experiments.

39. The method of claim 38, further comprising:

using the experiment design to synthesize one or more combinatorial libraries including a plurality of compositions defined by the coordinates of the experiment design.

40. The method of claim 38, wherein:

the sampling patterns include at least a first sampling pattern defined for a first parameter of the set of experimental parameters and a second sampling pattern defined for a second parameter of the set of experimental parameters, wherein the first sampling pattern is different from the second sampling pattern.

41. The method of claim 38, wherein:

the set of experimental parameters includes a plurality of component materials to be used in the set of experiments.

42. The method of claim 41, wherein:

the set of experimental parameters includes at least one process condition to be varied in the set of experiments.

43. The method of claim 41, wherein:

the constraints include a mixture constraint limiting the fractional contribution of at least a plurality of the component materials to a total composition in one or more of the experiments in the set of experiments.

44. The method of claim 41, wherein:

the constraints include a type constraint limiting the total number of parameters of a specified type to be included in one or more of the experiments in the set of experiments.

45. The method of claim 41, wherein:

the constraints include a sun constraint limiting the sum of a contribution of parameters of a specified type to one or more of the experiments in the set of experiments.

46. The method of claim 41, wherein:

the constraints include a balance constraint limiting the contribution of at least one parameter to a plurality of experiments of the set of experiments based on the contribution of one or more other parameters to one or more of the experiments in the set of experiments.

47. The method of claim 41, wherein:

the constraints include a list constraint identifying a list of one or more starting compositions to be used to generate the set of experiments.

48. The method of claim 41, wherein:

the constraints include a synthesis constraint specifying an order in which a plurality of component materials are to be added in a synthesis to be performed in one or more of the experiments in the set of experiments.

49. The method of claim 48, wherein:

the synthesis constraint specifies that the order in which component materials are to be added is to vary between a plurality of experiments in the set of experiments.

50. The method of claim 41, wherein;

the constraints include a process constraint specifying an order in which a plurality of process steps are to be performed in one or more of the experiments in the set of experiments.

51. The method of claim 50, wherein:

the process constraint specifies that the order in which process steps are to be performed is to vary between a plurality of experiments in the set of experiments.

52. The method of claim 41, wherein:

each of the component materials has an associated set of material properties describing the component material; and

receiving input defining the set of experimental parameters includes receiving for each of the component materials a set of values for one or more of the material properties associated with the component material.

53. The method of claim 52, wherein:

at least one of the material properties is selected from the group consisting of molecular weight, equivalents, density and concentration.

54. The method of claim 52, wherein:

at least one of the material properties is a type describing a class of chemicals to be used in generating the experiment design.

55. The method of claim 38, wherein:

the constraints include a project constraint specifying the order in which individual experiments in the set of experiments are to be performed.

56. The method of claim 38, wherein:

at least one of the constraints includes one or more tolerance values representing an amount by which the corresponding constraint can be relaxed during generation of the experiment design.

57. The method of claim 38, wherein:

generating the experiment design includes identifying a plurality of points in the hyperspace defined by the set of experimental parameters corresponding to candidate materials by counting through parameter space points defined by the sampling pattern and applying the experimental constraints to the parameter space points.

58. The method of claim 38, wherein:

the set of experimental parameters includes at least four experimental parameters.

59. The method of claim 38, wherein:

the set of experimental parameters includes at least six experimental parameters.

60. The method of claim 38, wherein:

the set of experimental parameters includes at least ten experimental parameters.

61. The method of claim 38, wherein:

the set of experimental parameters includes at least fifty experimental parameters.

62. The method of claim 38, wherein:

the final set of experiments includes at least 48 experiments.

63. The method of claim 38, wherein:

the final set of experiments includes at least 96 experiments.

64. The method of claim 38, wherein:

the final set of experiments includes at least 1,000 experiments.

65. The method of claim 38, wherein:

the final set of experiments includes at least 10,000 experiments.

66. The method of claim 38, wherein:

the final set of experiments includes at least 50,000 experiments.

67. The method of claim 38, wherein:

the final set of experiments includes at least 100,000 experiments.

68. A computer-implemented experiment design system, comprising:

means for defining a set of experimental parameters, one or more sampling patterns defining a sampling for each parameter of the set of experimental parameters, and one or more constraints limiting the set of experiments to a particular volume or volumes of a hyperspace defined by the set of experimental parameters, at least a plurality of the set of parameters being grouped according to a parameter type such that the grouped parameters are constrained to perform a common role in the set of experiments;

means for generating an estimate of the practicability of a set of experiments defined by the parameters, the sampling patterns and the constraints, the estimate including a count of the set of experiments defined by the set of experimental parameters, the sampling patterns and the constraints;

means for generating, in response to a user input approving of the estimate, an experiment design defined by the parameters, the sampling patterns and the constraints, the experiment design including data representing a final set of experiments, the data including a plurality of sets of coordinates in the hyperspace defined by the set of experimental parameters, each of the sets of coordinates defining an experiment in the final set of experiments.

69. The experiment design system of claim 68, further comprising:

means for synthesizing based on the experiment design one or more combinatorial libraries including a plurality of compositions defined by the coordinates of the experiment design.

70. The experiment design system of claim 69, wherein:

the set of experimental parameters includes at least ten experimental parameters.

71. The experiment design system of claim 69, wherein:

the final set of experiments includes at least 1,000 experiments.

72. A computer program product on a computer-readable medium for designing a set of experiments, the program comprising instructions operable to cause a programmable processor to:

receive input defining a set of experimental parameters, one or more sampling patterns defining a sampling of each parameter of the set of experimental parameters, and one or more constraints limiting the set of experiments to a particular volume or volumes of a hyperspace defined by the set of experimental parameters, at least a plurality of the set of parameters being mixture parameters defining a plurality of component materials to be used in the set of experiments to generate a mixture, the sampling patterns defined for the mixture parameters defining a non-uniform sampling of the mixture parameters; and

generate an experiment design defined by the parameters, the sampling patterns and the constraints, the experiment design including data representing a final set of experiments, the data including a plurality of sets of coordinates in the hyperspace defined by the set of experimental parameters, each of the sets of coordinates defining an experiment in the final set of experiments.

73. A computer program product on a computer-readable medium for designing a set of experiments, the program comprising instructions operable to cause a programmable processor to:

receive input defining a set of experimental parameters, one or more sampling patterns defining a sampling of each parameter of the set of experimental parameters, and one or more constraints limiting the set of experiments to a particular volume or volumes of a hyperspace defined by the set of experimental parameters, at least a plurality of the set of parameters being mixture parameters defining a plurality of component materials to be used in the set of experiments to generate a mixture, the constraints including a mixture constraint limiting the fractional contribution of at least a plurality of the component materials to a total composition in one or more of the experiments in the set of experiments, the mixture constraint including one or more tolerance values representing an amount by which the mixture constraint can be relaxed during generation of an experiment design; and

generate an experiment design defined by the parameters, the sampling patterns and the constraints, the experiment design including data representing a final set of experiments, the data including a plurality of sets of coordinates in the hyperspace defined by the set of experimental parameters, each of the sets of coordinates defining an experiment in the final set of experiments.

74. A computer program product on a computer-readable medium for designing a set of experiments, the program comprising instructions operable to cause a programmable processor to:

receive input defining a set of experimental parameters, one or more sampling patterns defining a sampling of each parameter of the set of experimental parameters, and one or more constraints limiting the set of experiments to a particular volume or volumes of a hyperspace defined by the set of experimental parameters, at least a plurality of the set of parameters being mixture parameters defining a plurality of component materials to be used in the set of experiments to generate a mixture, the constraints including a balance constraint limiting the contribution of at least one of the mixture parameters to the experiment design based on the contribution of a plurality of other mixture parameters to one or more of the experiments in the set of experiments; and

generate an experiment design defined by the parameters, the sampling patterns and the constraints, the experiment design including data representing a final set of experiments, the data including a plurality of sets of coordinates in the hyperspace defined by the set of experimental parameters, each of the sets of coordinates defining an experiment in the final set of experiments.