COMPUTERIZED CONTROL OF HIGH-THROUGHPUT EXPERIMENTAL PROCESSING AND DIGITAL ANALYSIS OF COMPARATIVE SAMPLES FOR A COMPOUND OF INTEREST

• US 20070020662A1
• Filed: 08/24/2006
• Published: 01/25/2007
• Est. Priority Date: 01/07/2000
• Status: Abandoned Application

• Current Assignee: TransForm Pharmaceuticals, Inc. (Johnson & Johnson)
• Original Assignee: TransForm Pharmaceuticals, Inc. (Johnson & Johnson)
• Inventors: Chin, Donovan, Almarsson, Orn, Chen, Hongming, Lemmo, Anthony, Cima, Michael, Gonzalez-Zugasti, Javier, McNulty, Christopher, Levinson, Douglas, Moore, Christopher, Johnson, Alasdair
• Application Number:
  US11/467,061
• Publication Number:
  US 20070020662A1
• Time in Patent Office: Days
• US Class Current: 435/6
• CPC Class Codes: B01J 2219/007 Simulation or vitual synthesis
• CPC Class Codes: B01J 2219/00756 Compositions, e.g. coatings, crystals, formulations
• CPC Class Codes: G16B 15/00 ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
• CPC Class Codes: G16B 35/00 ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
• CPC Class Codes: G16B 40/00 ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• CPC Class Codes: G16B 40/10 Signal processing, e.g. from mass spectrometry [MS] or from PCR
• CPC Class Codes: G16B 40/30 Unsupervised data analysis
• CPC Class Codes: G16C 20/60 In silico combinatorial chemistry
• CPC Class Codes: G16C 20/64 Screening of libraries

Abstract

The present invention relates to computer-controlled automated high-throughput systems and/or computer-program products to design, prepare, process, and analyze a large number of samples having experimental formulations each containing a compound of interest formulated with differing component combinations and varying concentrations and component identities. The computer-controlled methods of the present invention allow determination of the effects of additional or inactive components, such as excipients, carriers, enhancers, adhesives, additives, and the like, on the compound of interest, such as pharmaceuticals. The invention thus encompasses the computer systems, computer methods, and computer-program products for computer-controlled automated high-throughput testing of pharmaceutical compositions or formulations in order to determine the overall optimal composition or formulation for an intended use or purpose.

Claims

1. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest, a method of computer-aided design for determining an experimental formulation for each sample, each experimental formulation being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples for a compound of interest, the method comprising:

inputting into the computing system at least one compound of interest to be included in each of a plurality of experimental formulations that are to be designed for the array of samples;

inputting into the computer system additional components to be formulated with the at least one compound of interest in the experimental formulations;

inputting into the computing system at least one experimental variable to be varied as between at least some of the samples of the array; and

the computing system thereafter designing a plurality of unique experimental formulations that differ as between at least some samples of the array based on at least one experimental variable that is varied as between the at least some samples of the array, each experimental formulation being designed at least in part based on at least one experimental variable.

3. A method as in claims 1 or 2 wherein the at least one experimental variable to be varied as between at least some samples of the array is varied as to at least one of the following:

concentration of the compound of interest, concentration of components in the experimental formulations, identity of the components, combination of components, additive, solvent, antisolvent composition, temperature, temperature change, heating, cooling, nucleation seeds, supersaturation, pH, pH change, or time of crystallization reaction.

4. A method as in claims 1 or 2, further comprising inputting into the computing system at least one criteria for determining the effect of at least one experimental variable for each experimental formulation that is varied as to that experimental variable, wherein said effect is manifested by a change in one or more of the following for a compound of interest between different experimental formulations:

microstructure, crystallinity, amorphism, polymorphism, hydrate, solvate, isomorphic desolvate, packing order, ionic crystal, interstitial space, lattice, or habit.

5. A method as in claims 1 or 2, further comprising the computing system designing a process for processing the array of samples to determine an effect on the compound of interest of at least one experimental variable for each experimental formulation.

6. A method as in claim 5, wherein the processing of each experimental formulation includes a process consisting of at least one of the following:

mixing, agitating, heating, cooling, adjusting pressure, adding crystallization aids, adding nucleation promoters, adding nucleation inhibitors, adding acids, adding bases, stirring, milling, filtering, centrifuging, emulsifying, mechanically stimulating, introducing ultrasound energy to the experimental formulation, introducing laser energy to the experimental formulation, subjecting the experimental formulation to a temperature gradient, allowing the experimental formulation to set for a time, or heating to a first temperature then cooling to a second temperature.

7. A method as in claim 5, wherein the effect is at least one of causing crystallization, inhibiting crystallization, or formation of a solid form.

2. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest, a computer-program product for implementing a method of computer-aided design for determining an experimental formulation for each sample, each experimental formulation being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples for a compound of interest, the computer-program product comprising a computer-readable medium containing computer-executable instructions for causing the computing system to execute the method, and wherein the method is comprised of:

inputting into the computing system at least one compound of interest and any additional components to be included in each of a plurality of experimental formulations that are to be designed for the array of samples;

inputting into the computer system additional components to be formulated with the at least one compound of interest in the experimental formulations;

inputting into the computing system at least one experimental variable to be varied as between at least some of the samples of the array; and

the computing system thereafter designing a plurality of unique experimental formulations that differ as between at least some samples based on at least one experimental variable that is varied as between the at least some samples of the array, each experimental formulation being designed at least in part based on at least one experimental variable.

8. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest represented in the array, a method of computer-aided design for determining an experimental formulation for each sample, each experimental formulation being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples for the compound of interest, the method comprising:

inputting into the computing system a compound of interest to be included in each of a plurality of experimental formulations that are to be designed for the array of samples;

inputting into the computer system a plurality of additional components to be formulated with the compound of interest in the experimental formulations;

inputting into the computing system a plurality of experimental variables to be varied as between at least some of the samples of the array;

the computing system thereafter designing, for a first group of samples in the array, a first plurality of experimental formulations that are different as between at least some of the samples in the first group that are based on a first experimental variable that is varied among the first plurality of experimental formulations determined for the first group; and

the computing system also designing, for at least a second group of samples in the array, a second plurality of experimental formulations that are different as between at least some of the samples in the second group that are based on a second experimental variable that is varied as among the second plurality of experimental formulations determined for the second group.

10. A method as in claims 8 or 9, wherein the plurality of experimental variables to be varied as between at least some of the samples of the array include at least one of the following:

concentration of the compound of interest, concentration of components in the experimental formulations, identity of components, combination of components, additive, solvent, antisolvent composition, temperature, temperature change, heating, cooling, nucleation seeds, supersaturation, pH, pH change, or time of crystallization reaction;

11. A method as in claims 8 or 9, further comprising inputting into the computing system at least one criteria for determining the effect of at least one experimental variable for each experimental formulation that is varied as to that experimental variable, wherein said effect is manifested by a change in one or more of the following for a compound of interest between different experimental formulations:

microstructure, crystallinity, amorphism, polymorphism, hydrate, solvate, isomorphic desolvate, packing order, ionic crystal, interstitial space, lattice, or habit.

12. A method as in claims 8 or 9, further comprising the computing system designing a process for processing each of the experimental formulations in the array of samples to determine an effect on a compound of interest of at least one experimental variable for each experimental formulation.

13. A method as in claim 12, wherein the processing of each experimental formulation includes a process consisting of at least one of the following:

mixing, agitating, heating, cooling, adjusting pressure, adding crystallization aids, adding nucleation promoters, adding nucleation inhibitors, adding acids, adding bases, stirring, milling, filtering, centrifuging, emulsifying, mechanical stimulation, introducing ultrasound energy to the experimental formulation, introducing laser energy to the experimental formulation, subjecting the experimental formulation to a temperature gradient, allowing the experimental formulation to set for a time, or heating to a first temperature then cooling to a second temperature.

14. A method as in claim 12, wherein the effect is at least one of causing crystallization, inhibiting crystallization, or formation of a solid form.

9. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest represented in the array, a computer-program product for implementing a method of computer-aided design for determining an experimental formulation for each sample, each experimental formulation being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples for the compound of interest, the computer-program product comprising a computer-readable medium for containing computer-executable instructions for causing the computing system to execute the method, and wherein the method is comprised of:

inputting into the computing system a compound of interest to be included in each of a plurality of experimental formulations that are to be designed for the array of samples;

inputting into the computer system a plurality of additional components to be formulated with the compound of interest in the experimental formulations;

inputting into the computing system a plurality of experimental variables to be varied as between at least some of the samples of the array;

the computing system thereafter designing, for a first group of samples in the array a first plurality of experimental formulations that are different as between at least some of the samples in the first group that are based on a first experimental variable that is varied among the first plurality of experimental formulations determined for the first group; and

the computing system also designing, for at least a second group of samples in the array a second plurality of experimental formulations that are different as between at least some of the samples in the second group that are based on a second experimental variable that is varied as among the second plurality of experimental formulations determined for the second group.

15. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest, and wherein the computing system provides computer-aided design and processing of an experimental formulation for each sample, each experimental formulation having the compound of interest and being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples, a method of analyzing data from the large number of comparative samples comprising:

inputting into the computing system at least one compound of interest and any additional components to be included in a plurality of experimental formulations that are to be designed for the array of samples;

inputting into the computing system at least one selected experimental variable of interest that is to be varied as between at least some of the samples of the array;

the computing system thereafter designing a plurality of unique experimental formulations that differ as between at least some samples of the array based on the at least one selected experimental variable of interest that is varied as between the at least some samples of the array;

the computing system thereafter controlling a process by which an experimental formulation for each sample is prepared and tested in order to create changes across a large number of comparative samples for the at least one compound of interest in its chemical and/or physical properties;

inputting into the computing system detected changes across the large number of comparative samples for the at least one compound of interest; and

the computing system thereafter automatically screening the large number of samples by identifying those samples which contain chemical and/or physical properties likely to lead to an optimal formulation for a given use of a compound of interest.

17. A method as in claims 15 or 16, wherein the at least one selected experimental variable of interest that is to be varied as between at least some samples of the array is varied as to at least one of the following:

concentrations of the compound of interest, concentrations of components in the experimental formulations, identity of components, combination of components, additives, solvents, antisolvent compositions, temperatures, temperature changes, heating, cooling, nucleation seeds, supersaturation, pH, pH change, or time of crystallization reaction.

18. A method as in claims 15 or 16, the chemical and/or physical properties likely to lead to optimal formulation for a given use of a compound of interest being at least one of microstructure, crystallinity, amorphism, polymorphism, hydrate, solvate, isomorphic desolvate, packing order, ionic crystal, interstitial space, lattice, or habit.

19. A method as in claims 15 or 16, further comprising:

inputting into the computing system a data set, based on analyzing the preparation and processing of each of the experimental formulations in the array of sample, having experimental data for the changes across the large number of comparative samples for the at least one compound of interest; and

analyzing the data set to determine at least one optimal formulation for a given use of a compound of interest.

20. A method as in claims 15 or 16, wherein the computing system further determines a process for processing each of the experimental formulations in the array of samples.

21. A method as in claim 20, wherein the processing of each experimental formulation includes a process consisting of at least one of the following:

mixing, agitating, heating, cooling, adjusting pressure, adding crystallization aids, adding nucleation promoters, adding nucleation inhibitors, adding acids, adding bases, stirring, milling, filtering, centrifuging, emulsifying, mechanical stimulation, introducing ultrasound energy to the experimental formulation, introducing laser energy to the experimental formulation, subjecting the experimental formulation to a temperature gradient, allowing the experimental formulation to set for a time, or heating to a first temperature then cooling to a second temperature.

22. A method as in claims 15 or 16, wherein the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable causes at least one of crystallization, inhibiting crystallization, or formation of a solid form.

23. A method as in claims 15 or 16, further comprising:

inputting into the computer system information obtained by screening the chemical and/or physical properties of each of the experimental formulations in the array of samples for at least one desired property; and

the computing system identifying at least one experimental formulation having the at least one desired property based on the obtained information.

16. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest, and wherein the computing system provides computer-aided design and processing of an experimental formulation for each sample, each experimental formulation having the compound of interest and being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples, a computer-program product for implementing a method of analyzing data from the large number of comparative samples, the computer-program product comprising a computer-readable medium containing computer-executable instructions for causing the computing system to execute the method, and wherein the method is comprised of:

inputting into the computing system at least one compound of interest and any additional components to be included in a plurality of experimental formulations that are to be designed for the array of samples;

inputting into the computing system at least one selected experimental variable of interest that is to be varied as between at least some of the samples of the array;

the computing system thereafter designing a plurality of unique experimental formulations that differ as between at least some samples of the array based on the at least one selected experimental variable of interest that is varied as between the at least some samples of the array;

the computing system thereafter controlling a process by which an experimental formulation for each sample is prepared and tested in order to create changes across a large number of comparative samples for the at least one compound of interest in its chemical and/or physical properties;

inputting into the computing system detected changes across the large number of comparative samples for the at least one compound of interest; and

the computing system thereafter automatically screening the large number of samples by identifying those samples which contain chemical and/or physical properties likely to lead to an optimal formulation for a given use of a compound of interest.

24. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest, and wherein the computing system provides computer-aided design and processing of an experimental formulation for each sample, each experimental formulation having the compound of interest and being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples, a method of analyzing data from the large number of comparative samples comprising:

inputting into the computing system at least one compound of interest and any additional components to be included in a plurality of experimental formulations that are to be designed for a first array of samples;

inputting into the computing system at least one selected experimental variable of interest that is to be varied as between at least some samples of the first array;

the computing system thereafter designing a plurality of unique experimental formulations that differ as between at least some samples based on the at least one selected experimental variable of interest that is varied as between the at least some samples of the first array;

the computing system thereafter controlling a process by which an experimental formulation for each sample is prepared and tested in order to create changes in chemical and/or physical properties across a large number of comparative samples for the at least one compound of interest;

inputting into the computing system detected changes across the large number of comparative samples for the at least one compound of interest;

the computing system thereafter screening the large number of samples by identifying those samples which contain chemical and/or physical properties likely to lead to an optimal formulation for a given use of a compound of interest, and storing as a first data set information as to the experimental formulation and the resulting chemical and/or physical properties for each of the identified samples;

inputting to the computing system at least one other selected experimental variable of interest that is to be varied as between at least some identified samples of the first data set;

the computing system thereafter designing a plurality of further experimental formulations for a second array having a large number of samples that are different as between at least some of the identified samples of the first data set based on the at least one further selected experimental variable of interest that is to be varied as between the at least some identified samples of the first data set;

the computing system thereafter controlling a process by which the plurality of further experimental formulations in the second array of samples are prepared and tested in order to create further changes in chemical and/or physical properties across further comparative samples for the at least one compound of interest;

inputting into the computing system detected further changes across the further comparative samples of the first data set for the at least one compound of interest;

the computing system thereafter screening the further comparative samples by identifying changes in chemical and/or physical properties and storing as a second data set information as to the plurality of further experimental formulations and the resulting chemical and/or physical properties for each further comparative sample; and

the computing system thereafter selecting from the first and second data sets those samples which contain chemical and/or physical properties likely to lead to an optimal formulation for a given use of a compound of interest.

26. A method as in claims 24 or 25, wherein the at least one selected experimental variable of interest and the at least one further experimental variable interest that are to be varied as between at least some samples of the array are each varied as to at least one of the following:

concentration of the compound of interest, concentration of components in the experimental formulations, identity of components, combination of components, additive, solvent, antisolvent composition, temperature, temperature change, heating, cooling, nucleation seeds, supersaturation, pH, pH change, or time of crystallization reaction.

27. A method as in claims 24 or 25, the chemical and/or physical properties likely to lead to optimal formulation for a given use of a compound of interest being at least one of microstructure, crystallinity, amorphism, polymorphism, hydrate, solvate, isomorphic desolvate, packing order, ionic crystal, interstitial space, lattice, or habit.

28. A method as in claims 24 or 25, further comprising:

inputting into the computing system a data set, based on analyzing the preparation and processing of each of the experimental formulations in the array of sample, having experimental data for the changes across the large number of comparative samples or further comparative samples for the at least one compound of interest; and

analyzing the data set to determine at least one optimal formulation for a given use of a compound of interest.

29. A method as in claims 24 or 25, the computing system further determining a process for processing each of the experimental formulations in the first or second array of samples.

30. A method as in claim 29, wherein the processing of each experimental formulation includes a process consisting of at least one of the following:

mixing, agitating, heating, cooling, adjusting pressure, adding crystallization aids, adding nucleation promoters, adding nucleation inhibitors, adding acids, adding bases, stirring, milling, filtering, centrifuging, emulsifying, mechanical stimulation, introducing ultrasound energy to the experimental formulation, introducing laser energy to the experimental formulation, subjecting the experimental formulation to a temperature gradient, allowing the experimental formulation to set for a time, or heating to a first temperature then cooling to a second temperature.

31. A method as in claims 24 or 25, wherein the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable causes at least one of crystallization, inhibiting crystallization, or formation of a solid form.

32. A method as in claims 24 or 25, further comprising:

the computer system at least partially controlling or assisting in screening the chemical and/or physical properties of each of the experimental formulations in the array of samples for at least one desired property; and

the computer system at least partially controlling or assisting in identifying at least one experimental formulation having the at least one desired property.

33. A method as in claims 24 or 25, wherein each experimental formulation in the first array of samples has a different combination of any additional components.

34. A method as in claim 33, wherein a first set of the plurality of further experimental formulations in the second array of samples has a different concentration of at least one additional component in at least one experimental formulation of the first array of samples.

35. A method as in claims 24 or 25, wherein the at least one selected experimental variable of interest includes identity of any additional components.

36. A method as in claim 35, wherein the at least one further selected experimental variable of interest includes a concentration gradient for at least one selected additional component.

37. A method as in claim 35, wherein the at least one further selected experimental variable of interest includes a concentration gradient for the at least one compound of interest.

25. In a computing system designed for controlling automated high-throughput processing of an array having a large number of samples in order to identify chemical and/or physical properties leading to optimal formulation for a given use of a compound of interest, and wherein the computing system provides computer-aided design and processing of an experimental formulation for each sample, each experimental formulation being based on at least one experimental variable which is varied as to at least some samples so that the effect in terms of changes in the chemical and/or physical properties of the compound of interest due to at least one experimental variable can be identified across a large number of comparative samples for a compound of interest, a computer-program product for implementing a method of analyzing data from the large number of comparative samples, the computer-program product comprising a computer-readable medium containing computer-executable instructions for causing the computing system to execute the method, and wherein the method is comprised of:

inputting into the computing system at least one compound of interest and any additional components to be included in each of a plurality of experimental formulations that are to be designed for the array of samples;

inputting into the computing system at least one selected experimental variable of interest that is to be varied as between at least some samples of the array;

the computing system thereafter designing a plurality of unique experimental formulations that differ as between at least some samples based on the at least one selected experimental variable of interest that is varied as between the at least some samples of the array;

the computing system thereafter controlling a process by which an experimental formulation for each sample is tested in order to create changes in chemical and/or physical properties across a large number of comparative samples for the at least one compound of interest;

inputting into the computing system detected changes across the large number of comparative samples for the at least one compound of interest;

the computing system thereafter screening the large number of samples by identifying those samples which contain chemical and/or physical properties likely to lead to an optimal formulation for a given use of a compound of interest, and storing as a first data set information as to the experimental formulation and the resulting chemical and/or physical properties for each of the identified samples;

inputting to the computing system at least one other selected experimental variable of interest that is to be varied as between at least some identified samples of the first data set;

the computing system thereafter designing a plurality of further experimental formulations that for a second array having a large number of samples that are different as between at least some of the identified samples of the first data set based on the at least one further selected experimental variable of interest that is to be varied as between the at least some identified samples of the first data set;

the computing system thereafter controlling a process by which the plurality of further experimental formulations in the second array of samples are prepared and tested in order to create further changes in chemical and/or physical properties across further comparative samples for the at least one compound of interest;

inputting into the computing system detected further changes across the further comparative samples of the first data set for the at least one compound of interest;

the computing system thereafter screening the further comparative samples of the first data set by identifying changes in chemical and/or physical properties and storing as a second data set information as to the plurality of further experimental formulations and the resulting chemical and/or physical properties for each further comparative sample; and

the computing system thereafter selecting from the first and second data sets those samples which contain chemical and/or physical properties likely to lead to an optimal formulation for a given use of a compound of interest.