Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is in response to claims filed on 04/14/2023.
Claims 1-18 are pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/23/2023 and 10/31/2024 are being considered by the examiner.
Claim Objections
Claims 14-17 are objected to because of the following informalities: Claims 14-17 recites the limitation "The user interface of claim 1", it should be “The user interface of claim 11”.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: a (first, second and third) input field for receiving, in claim 11 and a (first, send and third) input field configured to receive, in claim 18.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. The specification [51] disclose the input field being part of a UI (user interface).
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-18 are rejected under 35 U.S.C. 103 as being unpatentable over James Swarbrick, NPL “DRUGS AND THE PHARMACEUTICAL SCIENCES”, Published: 2005, (hereafter Swarbrick), in views of Jiri Kolar, NPL, “Optimization of Wurster fluid bed coating: Mathematical model validated against pharmaceutical production data”, Published: 29, March 2021 (hereafter Kolar).
Regarding claim 1. Swarbrick teaches a method for providing optimized process parameters for a fluid bed granulation process (Page 15, Fig 6, pharmaceutical granulation processes, batch fluid bed granulator) (Page 121, sec 4.1.2, fluid bed granulation) (Page 587, Fig 10, optimization algorithm) (Page 589, Par 1, optimal control strategies, start up and shut down operations), the method comprising:
receiving from a user a plurality of intrinsic properties of an input powder,
wherein the plurality of intrinsic properties comprises a bulk density of particles of the input powder and a threshold temperature value or a temperature range associated with degradation of an attribute of the input powder (Page 62, Fig 54, variables, mechanical transformation, density, chemical transformations, variable temperature) (Page 253, Par 1, typical range for air temperature);
receiving from the user granulation requirements for granules formed from the input powder during the fluid bed granulation process,
wherein the granulation requirements comprise a granule size distribution and a required granule density (Page 269, sec 6.2.1.1, particle properties, particle size) (Page 581, sec 5.1.3.2, granule size control system);
receiving from the user a plurality of operational capabilities of a fluid bed granulation system,
wherein the plurality of operational capabilities of the fluid bed granulation system comprises a minimum and a maximum volume capacity, a spray rate range, an inlet air flow range, an inlet air temperature range, and an inlet air dew point range (Page 274, sec 6.2.3, bowl capacity, spray rate, air velocity and volume, inlet air temperature) (Page 252, fig 4, Dewpoint, humidity);
modeling, using the plurality of intrinsic properties of the input powder, the granulation requirements, and the plurality of operational capabilities of the fluid bed granulation system, granulation of the input powder in the fluid bed granulation system to determine optimal process parameters for the fluid bed granulation system (Page 277, Table 3, process parameters, air temperature, air volume and pressure) (Page 580, Fig 5, control variables, model parameters, dynamic optimization); and
providing the optimal process parameters for the fluid bed granulation system on a user interface (Page 580, Fig 5, Dynamic optimization) (Page 252, Fig 4, Clear air prep window, user interface).
Swarbrick does not teach thermodynamically modeling, wherein the optimal process parameters comprise an inlet air temperature and an inlet air flow rate of air supplied into an inlet of the fluid bed granulation system.
Kolar teaches thermodynamically modeling (Page 517, sec 9, multi scale thermodynamic model) (Page 507, Thermodynamic quantities and single weight fraction for model purposes), wherein the optimal process parameters comprise an inlet air temperature and an inlet air flow rate of air supplied into an inlet of the fluid bed granulation system (Page 516, Fig 12 and 13, airflow, temperature, spray rate) (Page 517, sec 8, optimal approach inlet airflow, temperature).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Swarbrick to incorporate the teachings of Kolar to thermodynamically model and optimize the process parameter of air flow rate and air temperature because it reduces the need for experimentation and prevents undesired agglomeration (Kolar, Pag 505, abstract).
Regarding claim 2. Swarbrick and Kolar teach the method of claim 1, wherein thermodynamically modeling granulation of the input powder in the fluid bed granulation system comprises determining an absolute humidity of exhaust air expelled by the fluid bed granulation system using the threshold temperature value or the temperature range associated with degradation of the attribute of the input powder (Swarbrick, Page 252, fig 4, output temperature and dewpoint).
Regarding claim 3. Swarbrick and Kolar teach the method of claim 2, wherein thermodynamically modeling granulation of the input powder in the fluid bed granulation system comprises determining a specific enthalpy of exhaust air expelled by the fluid bed granulation system using the threshold temperature value or the temperature range associated with degradation of the attribute of the input powder and the absolute humidity of exhaust air (Swarbrick, Page 267, fig 21, enthalpy based on dry bulb temperature, humidity ratio) (Swarbrick, Page 267, fig 22, product temperatures, having different temperatures, wet bulb temp).
Regarding claim 4. Swarbrick and Kolar teach the method of claim 3, wherein thermodynamically modeling granulation of the input powder in the fluid bed granulation system comprises determining a specific enthalpy air at the inlet to the fluid bed granulation system based on the specific enthalpy of exhaust air expelled by the fluid bed granulation system (Swarbrick, Page 267, fig 21, enthalpy based on dry bulb temperature, humidity ratio) (Swarbrick, Page 267, fig 22, product temperatures, having different temperatures, dry bulb temp.).
Regarding claim 5. Swarbrick and Kolar teach the method of claim 4, wherein the inlet air temperature is determined based on the specific enthalpy air at the inlet to the fluid bed granulation system (Swarbrick, Page 267, fig 21, enthalpy based on humidity ratio).
Regarding claim 6. Swarbrick and Kolar teach the method of claim 5, wherein thermodynamically modeling granulation of the input powder in the fluid bed granulation system comprises determining an absolute humidity of air at the inlet to the fluid bed granulation system using the inlet air temperature (Swarbrick, Page 252, fig 4, inlet temp and humidity) (Swarbrick, Page 275, fig 24, temperature and humidity changes during the granulation process).
Regarding claim 7. Swarbrick and Kolar teach the method of claim 6, wherein thermodynamically modeling granulation of the input powder in the fluid bed granulation system comprises determining a wet-bulb temperature of air at the inlet to the fluid bed granulation system using the absolute humidity of air at the inlet to the fluid bed granulation system (Swarbrick, Page 252, fig 4, preheat, humidity, temperature and dewpoint) (Swarbrick, Page 267, fig 22, dry bulb temp, wet bulb temp, phase 1 and 2).
Regarding claim 8. Swarbrick and Kolar teach the method of claim 7, wherein thermodynamically modeling granulation of the input powder in the fluid bed granulation system comprises determining a drying capacity of the fluid bed granulation system and a drying rate of the fluid bed granulation system based on the absolute humidity of the inlet air at the dry-bulb temperature and at the wet-bulb temperature (Swarbrick, Page 142, fig 10, drying rate curve) (Swarbrick, Page 265, sec 5, drying rate is determined by the factors affecting the heat and mass transfer) (Swarbrick, Page 267, fig 22, product temperature changes during drying).
Regarding claim 9. Swarbrick and Kolar teach the method of claim 8, wherein the inlet air flow rate of air supplied into an inlet of the fluid bed granulation system is determined based on the drying capacity and the drying rate for the fluid bed granulation system (Swarbrick, Page 276, table 2, calculation of fluid bed spray rate).
Regarding claim 10. Swarbrick and Kolar teach the method of claim 1, comprising:
providing the optimal process parameters for the fluid bed granulation system to the fluid bed granulation system (Swarbrick, Page 580, Fig 5, Dynamic optimization) (Swarbrick, Page 252, Fig 4, Clear air prep window, user interface); and
granulating the input powder using the fluid bed granulation system (Swarbrick, Page 285, table 5, scale up process parameters) (Swarbrick, Page 286, fig 27, case study and resultant particle size distribution).
Regarding claim 11. Swarbrick teaches a user interface for providing optimal process parameters for a fluid bed granulation process (Page 252, Fig 4, Clear air prep window, user interface) (Page 15, Fig 6, pharmaceutical granulation processes, batch fluid bed granulator) (Page 121, sec 4.1.2, fluid bed granulation) (Page 587, Fig 10, optimization algorithm) (Page 589, Par 1, optimal control strategies, start up and shut down operations), the user interface comprising:
a first input field for receiving, from a user (Page 252, Fig 4, Clear air prep window, user interface) (Page 280, GUI, for user to input), a plurality of intrinsic properties of an input powder,
wherein the plurality of intrinsic properties comprises a bulk density of particles of the input powder and a threshold temperature value or a temperature range associated with degradation of an attribute of the input powder (Page 62, Fig 54, variables, mechanical transformation, density, chemical transformations, variable temperature) (Page 253, Par 1, typical range for air temperature);
a second input field for receiving, from the user (Page 252, Fig 4, Clear air prep window, user interface) (Page 280, GUI, for user to input), granulation requirements for granules formed from the input powder during the fluid bed granulation process,
wherein the granulation requirements comprise a granule size distribution and a required granule density (Page 269, sec 6.2.1.1, particle properties, particle size) (Page 581, sec 5.1.3.2, granule size control system);
a third input field for receiving, from the user (Page 252, Fig 4, Clear air prep window, user interface) (Page 280, GUI, for user to input), a plurality of operational capabilities of a fluid bed granulation system,
wherein the plurality of operational capabilities of the fluid bed granulation system comprises a minimum and a maximum volume capacity, a spray rate range, an inlet air flow range, an inlet air temperature range, and an inlet air dew point range (Page 274, sec 6.2.3, bowl capacity, spray rate, air velocity and volume, inlet air temperature) (Page 252, fig 4, Dewpoint, humidity);
an output field configured to provide optimal process parameters for the fluid bed granulation system, wherein the optimal process parameters are determined by modeling, using the plurality of intrinsic properties of the input powder, the granulation requirements, and the plurality of operational capabilities of the fluid bed granulation system, granulation of the input powder in the fluid bed granulation system (Page 277, Table 3, process parameters, air temperature, air volume and pressure) (Page 580, Fig 5, control variables, model parameters, dynamic optimization), and
Swarbrick does not teach thermodynamically modeling, wherein the optimal process parameters comprise an inlet air temperature and an inlet air flow rate of air supplied into an inlet of the fluid bed granulation system.
Kolar teaches thermodynamically modeling (Page 517, sec 9, multi scale thermodynamic model) (Page 507, Thermodynamic quantities and single weight fraction for model purposes), wherein the optimal process parameters comprise an inlet air temperature and an inlet air flow rate of air supplied into an inlet of the fluid bed granulation system (Page 516, Fig 12 and 13, airflow, temperature, spray rate) (Page 517, sec 8, optimal approach inlet airflow, temperature).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Swarbrick to incorporate the teachings of Kolar to thermodynamically model, and optimize the process parameter of air flow rate and air temperature because it reduces the need for experimentation and prevents undesired agglomeration (Kolar, Pag 505, abstract).
Regarding claim 12. Swarbrick and Kolar teach the user interface of claim 11, wherein the user interface is configured to display an information window comprising information associated with the first user input field, the second user input field, or the third user input field upon user request (Swarbrick, Page 252, Fig 4, Clear air prep window, user interface) (Swarbrick, Page 280, GUI, for user to input).
Regarding claim 13. Swarbrick and Kolar teach the user interface of claim 12, wherein the information associated with the first user input field, the second user input field, or the third user input field comprises information about a format of a requested user input or a description of a requested user input (Swarbrick, Page 499, Format of SUPAC guidance documents) (Swarbrick, Page 557, Inputs, u are variables that are manipulated to drive the system or maintain its condition in the face of changes from disturbances, thus providing information about how the input should be proper to enter).
Regarding claim 14. Swarbrick and Kolar teach the user interface of claim 1, wherein the user interface is configured to display a warning window indicating that a possible error has been detected when the user provides a value to the first user input field, the second user input field, or the third user input field that is outside of a predetermined range (Kolar, Page 512, Table 6, Error) (Kolar, Page 514, Sec 6.1, error was low, steady temperature, prediction is precise).
Regarding claim 15. Swarbrick and Kolar teach the user interface of claim 1, wherein the output field provides the optimal process parameters by displaying values of the optimal process parameters (Swarbrick, Page 252, Fig 4, Clear air prep window, user interface) (Swarbrick, Page 280, GUI, for user to input).
Regarding claim 16. Swarbrick and Kolar teach the user interface of claim 1, wherein the output field provides the optimal process parameters by providing a downloadable file comprising the optimal process parameters (Swarbrick, Page 280, Fig 26, PLC system, transfer file from computer to PLC system or pulling a file from the PLC to the computer).
Regarding claim 17. Swarbrick and Kolar teach the user interface of claim 1, wherein the user interface is configured to provide information about inputting the optimal process parameters into the fluid bed granulation system upon user request (Swarbrick, Page 252, Fig 4, Clear air prep window, user interface) (Swarbrick, Page 280, GUI, for user to input).
Regarding claim 18. Swarbrick teaches a system for providing optimal process parameters for a fluid bed granulation process (Page 15, Fig 6, pharmaceutical granulation processes, batch fluid bed granulator) (Page 121, sec 4.1.2, fluid bed granulation) (Page 587, Fig 10, optimization algorithm) (Page 589, Par 1, optimal control strategies, start up and shut down operations), the system comprising:
a fluid bed granulation system (Page 247, Batch fluid bed granulation);
a user interface (Page 252, Fig 4, Clear air prep window, user interface) (Page 280, GUI, for user to input) comprising:
a first input field configured to receive, from a user, a plurality of intrinsic properties of an input powder, wherein the plurality of intrinsic properties comprises a bulk density of particles of the input powder and a threshold temperature value or a temperature range associated with degradation of an attribute of the input powder (Page 62, Fig 54, variables, mechanical transformation, density, chemical transformations, variable temperature) (Page 253, Par 1, typical range for air temperature),
a second input field configured to receive, from the user, granulation requirements for granules formed from the input powder during the fluid bed granulation process, wherein the granulation requirements comprise a granule size distribution and a required granule density (Page 269, sec 6.2.1.1, particle properties, particle size) (Page 581, sec 5.1.3.2, granule size control system),
a third input field configured to receive, from the user, a plurality of operational capabilities of a fluid bed granulation system, wherein the plurality of operational capabilities of the fluid bed granulation system comprises a minimum and a maximum volume capacity, a spray rate range, an inlet air flow range, an inlet air temperature range, and an inlet air dew point range, and an output field (Page 274, sec 6.2.3, bowl capacity, spray rate, air velocity and volume, inlet air temperature) (Page 252, fig 4, Dewpoint, humidity); and
a computing system comprising one or more memories and one or more processors (Page 280, Fig 26, PLC system) configured to:
receive, from the user interface, the plurality of intrinsic properties of the input powder, the granulation requirements, and the plurality of operational capabilities of the fluid bed granulation system (Page 252, Fig 4, Clear air prep window, user interface) (Page 280, GUI, for user to input),
model, using the plurality of intrinsic properties of the input powder, the granulation requirements, and the plurality of operational capabilities of the fluid bed granulation system, granulation of the input powder in the fluid bed granulation system to determine optimal process parameters for the fluid bed granulation system (Page 277, Table 3, process parameters, air temperature, air volume and pressure) (Page 580, Fig 5, control variables, model parameters, dynamic optimization),
provide, using the output field of the user interface, the optimal process parameters for the fluid bed granulation system (Page 252, Fig 4, Clear air prep window, user interface) (Page 280, GUI, for user to input).
Swarbrick does not teach thermodynamically modeling, wherein the optimal process parameters comprise an inlet air temperature and an inlet air flow rate of air supplied into an inlet of the fluid bed granulation system.
Kolar teaches thermodynamically modeling (Page 517, sec 9, multi scale thermodynamic model) (Page 507, Thermodynamic quantities and single weight fraction for model purposes), wherein the optimal process parameters comprise an inlet air temperature and an inlet air flow rate of air supplied into an inlet of the fluid bed granulation system (Page 516, Fig 12 and 13, airflow, temperature, spray rate) (Page 517, sec 8, optimal approach inlet airflow, temperature).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Swarbrick to incorporate the teachings of Kolar to thermodynamically model, and optimize the process parameter of air flow rate and air temperature because it reduces the need for experimentation and prevents undesired agglomeration (Kolar, Pag 505, abstract).
Conclusion
The prior art made of record, listed on PTO-892, and not relied upon is considered pertinent to applicant's disclosure.
H.G. Wang, NPL, “Investigation of Batch Fluidized-Bed Drying by Mathematical Modeling, CFD Simulation and ECT Measurement”, discloses understanding the batch fluidized bed drying by having a mathematical model. Integrated into an online process control system for a batch fluidized-bed dying application in the pharmaceutical industry.
Maryam Askarishahi, NPL, “Challenges in the Simulation of Drying in Fluid Bed Granulation”, discloses the importance of drying and the associated challenges when modeling a granulation process.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANGEL JAVIER CALLE whose telephone number is (571)272-0463. The examiner can normally be reached Monday - Friday 7:30 a.m. - 5 p.m..
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/A.C./Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189
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