DETAILED ACTION
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 action is responsive to communication filed on 11/22/2023.
Claims 1-26 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. A subject matter eligibility analysis is set forth below. See MPEP 2106.
Under Step 1 of the analysis, claim 1, belongs to a statutory category namely a method. Likely claims 12, 25 and 26 , belongs to a statutory category, namely it is a method.
Under Step 2A, prong 1: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
The claim(s) 1, 12, 25, and 26 recite(s) concepts related to mathematical algorithms/concepts, and mental processes and concepts performed in the human mind e.g. observation, evaluation, judgment, opinion and mere data characterization to “predict a first freezing profile of an at- scale volume of the solution subjected to first freezing operating conditions, wherein the first freezing profile includes predicted average temperatures of the solution during freezing and total freeze time”; “… fit a transient temperature boundary equation to the first freezing profile”; “predict a set-temperature sequence that produces a predicted second freezing profile of the scaled-down volume of the solution”; and “wherein: (i) the transient temperature boundary equation is a condition for predicting the set-temperature sequence; and (ii) the second freezing profile includes predicted average temperatures of the solution during freezing and total freeze time” (claim 1); “…predict a first thawing profile of an at-scale volume of the solution subjected to first thawing operating conditions, wherein the first thawing profile includes predicted average temperatures of the solution during thawing and total thaw time”; “…fit a transient temperature boundary equation to the first thawing profile”; “predict a set-temperature sequence that produces a predicted second thawing profile of the scaled-down volume of the solution”; “ wherein: (i) the transient temperature boundary equation is a condition for predicting the set-temperature sequence; and (ii) the second thawing profile includes predicted average temperatures of the solution during thawing and total thaw time” (claim 12); “…predict a freezing profile of the at-scale solution subjected to freezing operating conditions”; “…determining freezing will occur within a necessary period of time” (claim 25); “..predict a thawing profile of the at-scale solution subjected to first thawing operating conditions”;”…determining thawing will occur within a necessary period of time” (claim 26).
The concepts discussed above can be considered to describe mental processes, namely concepts performed in the human mind or with pen and paper, and/or mathematical concepts, namely a series of calculations leading to one or more numerical results or answers. Although, the claim does not spell out any particular equation or formula being used, the lack of specific equations for individual steps merely points out that the claim would monopolize all possible calculations in performing the steps. These steps recited by the claims, therefore amount to a series of mental or mathematical steps, making these limitations amount to an abstract idea.
Step 2A, prong 2 of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
This judicial exception is not integrated into a practical application because the abstract idea is not performed by using any particular device and mere gathering recited at high level of generality and the results of the algorithm are merely output/stored as part of insignificant post-solution activity, i.e. freezing/thawing the scaled-down volume using the set-temperature sequence (claims 1 and 12); freezing/thawing the at-scale volume of the solution using the thawing operation conditions (claims 25 and 26) which is a field of use and not a particular transformation and because the results are not used in any particular matter as to integrate the abstract idea in a practical application.
Under Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as described above with respect to Step 2A Prong 2, merely amount to mere data gathering/output recited at a high level of generality and insignificant extra-solution activity (i.e. freezing/thawing the at-scale volume) that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II) (Freezing and thawing cells, Rapid Litig. Mgmt. 827 F.3d at 1051, 119 USPQ2d at 1375), where freezing/thawing process is claimed at a high level of generality and is insignificant extra-solution activity; and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore, claims 1, 12, 25 and 26 are rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Dependent claims 2-11 merely expand on the abstract idea by appending additional steps to the mathematical algorithm on their respective independent claim 1.
Dependent claims 13-24 merely expand on the abstract idea by appending additional steps to the mathematical algorithm on their respective independent claim 12.
Dependent claims 2-11 and 13-24 merely expands on the abstract idea by reciting additional steps related to mathematical algorithms/concepts, and mental processes and concepts performed in the human mind e.g. observation, evaluation, judgment, opinion and mere characterization of the data acquired (6-7, 17-18) and applied for performing the abstract idea, i.e. determining at least one quality attribute of said scaled-down volume of the solution after freezing (claim 2); “using said computational fluid dynamics model to produce said set-temperature sequence for freezing said scaled-down volume” (claim 4); “determining at least one quality attribute of said scaled-down volume of the solution after thawing”(claim 13); “using said computational fluid dynamics model to produce said set-temperature sequence for thawing said scaled-down volume” (claim 15).
This judicial exception is not integrated into a practical application in claims 2-11 and 13-24 because the abstract idea is not performed by using any particular device and because the “a temperature regulation system” recited in claims 4 and 15 and amounts to the recitation of a general purpose computer used to apply the abstract idea; and because the recitation of “measuring a temperature of at least one point of interest in said scaled-down volume throughout freezing” recited in claim 5, and “measuring a temperature of at least one point of interest in said scaled-down volume throughout thawing” recited in claim 16, amounts to mere data gathering recited at a high level of generality, the limitations merely add further details as to the type of data generally linking the abstract idea to a field of use (claims 3, 6-11, 14, 17-24), the means of collecting data being received/input/stored and used with the mental process and/or math steps recited in the independent claims, also further calculations and math, so they are properly viewed as part of the recited abstract idea; insignificant post solution activities (i.e. scaled-scale volume being in a scale-down container with a particular chosen volume, claims 8-11, and 19-22) and the results are not used in any particular matter as to integrate the abstract idea in a practical application.
The claim(s) claims 2-11 and 13-24 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are general purpose computer used to apply the abstract idea and mere data gathering/output recited at a high level of generality and insignificant extra-solution activity that when further analyzed under Step 2B is found to be well-understood, routine and conventional activities as evidenced by MPEP 2106.05(d)(II); and because the data of performing the algorithm must necessarily be “obtained” and the use of a general purpose computer to implement the abstract idea for performing the algorithm does not amount to significantly more than the recitation of the abstract idea itself.
Therefore claims 1-26 are rejected under 35 USC 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 25 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bluemel Oliver et al. 2020 publication “Cryoconcentration and 3D Temperature Profiles During Freezing of mAb Solutions in Large-Scale PET Bottles and a Novel Scale-Down Device” (hereinafter Bluemel).
Regarding claim 25, Bluemel disclose a method for freezing a solution, comprising:
(a) using a computational fluid dynamics model (see abstract, pages 2-3, wherein the simulations are performed using “computational fluid dynamics (CFD)” is discussed) to predict a freezing profile of the at-scale solution subjected to freezing operating conditions (see Results section “3D freezing profiles in the SDD were comparable to large-scale bottles. The SDD accurately predicted cryoconcentration of both mAb and histidine of large-scale freezing”; Fig. 4a and page 5 Results and Discussion section on page 5 right column, “Figure 4(a) shows the calculated and the experimentally determined temperature profiles of a 2 L bottle at the geometrical centre and at half of the centre’s width at same height. The experimental and simulated temperatures were congruent for most of the freezing period, showing that the model is correctly predicting the solution’s thermal history”);
(b) determining freezing will occur within a necessary period of time (see Results and Discussion Section, wherein a Matching Thermal History Between a 2L bottle and scale-down containers is discussed and wherein “2 L freezing experiment was simulated by implementing in the model’s boundary conditions the heat transfer coefficient and temperature imposed by the gas-flow, measured during the experiment”, “[t]he experimental and simulated temperatures were congruent for most of the freezing period, showing that the model is correctly predicting the solution’s thermal history”, see Figs. 4(a) and 4(b), where stress time distribution of SSD that was closest to the stress time distribution of the 2L bottle is shown).
(c) freezing the at-scale volume of the solution using the freezing operating conditions (see page 5, left column Analysis of Cryoconcentration section, where 125mL and 2L bottles as well as the 2L SDD were compared after freezing and where the applied freezing setup for temperature mapping were also used for the experiments; see page 5 Results and Discussion Section, wherein a Matching Thermal History Between a 2L bottle and scale-down containers is discussed and wherein “2 L freezing experiment was simulated by implementing in the model’s boundary conditions the heat transfer coefficient and temperature imposed by the gas-flow, measured during the experiment”, “[t]he experimental and simulated temperatures were congruent for most of the freezing period, showing that the model is correctly predicting the solution’s thermal history”, see Figs. 4(a) and 4(b), where stress time distribution of SSD that was closest to the stress time distribution of the 2L bottle is shown, therefore the freezing the at-scale volume of the solution is taking place during the experimental phase).
Claim(s) 26 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bluemel Oliver et al. 2022 publication “Evaluation of Two Novel Scale-Down Devices for Testing Monoclonal Antibody Aggregation During Large-Scale Freezing” (hereinafter Bluemel).
Regarding claim 26, Bluemel disclose a method for thawing a solution (abstract), comprising:
(a) using a computational fluid dynamics model (see page 1974, second left column, where a scale-down device (SDD) enables to mimic FT of 2L bottles utilizing 125ml bottles by using computational fluid dynamics (CFD) modeling, to predict a thawing profile of the at-scale solution subjected to first thawing operating conditions (see abstract, “Both an unshielded 125 mL bottle and the SDD can be used to predict aggregation during FT in 2 L bottles”; see page 1974, left column, p. 1975, left column, where mSDD can generate temperature profiles to mimic FT under a user-selected average heat transfer coefficient where coefficient during FT was set to 27W/(m2K) and where calculated temperature profile is shown in Fig. 5; see page 1980 left column, wherein “The heat exchange coefficient depends on the freezer and thawer and is estimated based on simulations”);
(b) determining thawing will occur within a necessary period of time (see page 1974, left column, where “heat exchange is controlled to match the cumulative stress time of a 2L bottle”, right column, “same CFD based approach of matching stress time was realized in a micro SDD (mSDD) to scale the volume further down”); and
c) thawing the at-scale volume of the solution using the thawing operating conditions (see page 1976 left column where “[t]hree different mAb solutions were frozen and thawed repeatedly to compare stress in the SDD to the large-scale 2 L bottle and an unshielded 125 mL bottle.”; p. 1976, Results and Discussion section where freeze-thaw cycles were conducted to compare stress SDD to the large-scale 2L bottle and unshielded 125mL bottle).
Discussion of Relevant Prior Art
The prior art made of record cited in form PTOL-892 and not relied upon is considered pertinent to applicant's disclosure.
a. Bluemel Oliver et al. 2020 publication “Cryoconcentration and 3D Temperature Profiles During Freezing of mAb Solutions in Large-Scale PET Bottles and a Novel Scale-Down Device” (hereinafter Bluemel) disclose a method for freezing a solution (see abstract, introduction section “small-scale models that simulate large-scale freezing of substance of biopharmaceuticals” and conclusion section, “SSD gives details insight into large scale freezing of mAb solutions”), comprising:
(a) using a computational fluid dynamics model (see abstract, pages 2-3, wherein the simulations are performed using “computational fluid dynamics (CFD)” is discussed) to predict a first freezing profile of an at-scale volume of the solution subjected to first freezing operating conditions (see Results section “3D freezing profiles in the SDD were comparable to large-scale bottles. The SDD accurately predicted cryoconcentration of both mAb and histidine of large-scale freezing”; Fig. 4a and page 5 Results and Discussion section on page 5 right column, “Figure 4(a) shows the calculated and the experimentally determined temperature profiles of a 2 L bottle at the geometrical centre and at half of the centre’s width at same height. The experimental and simulated temperatures were congruent for most of the freezing period, showing that the model is correctly predicting the solution’s thermal history”), wherein the first freezing profile includes predicted average temperatures of the solution during freezing and total freeze time (see Fig. 4(a), page 3 Section “Development of a Scale-Down Device Assisted by CFD “The freezing simulations were carried out using a solver program…The mathematical model assumes that the biomixture is an aqueous solution of an osmolyte (sucrose) and a protein (BSA). When the ice crystallizes, the model assumes that the matrix of ice dendrites in equilibrium with interstitial concentrated liquid solution constitutes a continuous slushy region of ice, with an average volumetric ice fraction”; p. 5, Results and Discussion section “Matching Thermal History Between a 2L Bottle and Scale-Down Containers” discusses with respect to Fig. 4a, the total freezing time, wherein Fig. 4(a), on page 6, shows that the calculated and experimentally determined temperature profiles of a 2L bottle and scale down containers and further discuss the total freezing time being different from matching stress-time distribution and further discuss “the freezing time at the last point to freeze, inferred from Fig. 4(a), was slightly differing”);
(b) using the computational fluid dynamics model to carry out the thermal history analysis and wherein the freezing simulations were carried out using a solver program using CFD (see page 3, left column second and third paragraphs, wherein the computational fluid dynamics (CFD) model is used to carry out the thermal history analysis and wherein the freezing simulations were carried out using a solver program using CFD), the stress-time distribution of SDD that was closest to the stress-time distribution of the 2L bottle shown in Figure 4(b) which and a simulated temperature profile for 2L center and 2L half distance which is modeling a transient temperature shown in Figure 4(a).
b. Olivier Bluemel March 2022 Publication “Computational fluid dynamic simulations of temperature, cryoconcentration, and stress time during large-scale freezing and thawing of monoclonal antibody solutions” (hereinafter Bluemel 2022) disclose Large-scale freezing and thawing experiments of monoclonal antibody (mAb) solutions are time and material consuming. Computational Fluid Dynamic (CFD) modeling of temperature for which Temperature profiles at six positions were recorded during freezing and thawing of a 2 L rectangular bottle and compared to CFD simulations via OpenFOAM. Furthermore, cryoconcentration upon freezing and concentration gradients upon thawing of a mAb solution were predicted and the stress time calculated (abstract, section 3.1, 3.3, 4).
c. Bahari et al. WO 2018104935 A1 disclose Method for cryopreserving a biological sample adhered to a substrate, involves (a) (i) adding a freezing solution to the biological sample, (ii) directionally freezing the sample by moving it along a temperature gradient, and (iii) gradually cooling the sample to at least -20 degrees C, -30 degrees C, -60 degrees C or -80 degrees C, or (b) (i) adding freezing solution to the biological sample, (ii) directionally freezing the sample by moving the sample along a temperature gradient on a precooled motorized translational cryostage at a velocity of 30 mu m/sec, thus the temperature of the biological sample is reduced from 4 degrees C to -2.5 degrees C, (iii) gradually cooling the sample on the translational cryostage to -80 degrees C at a rate of -0.5 degrees C/minute to -1.2 degrees C/minute, and optionally (iv) deep cooling of the sample to -196 degrees C. (see abstract, p. 1 second paragraph; p. 3 summary of the invention section).
d. Zhou et al. US2024/0050566A1 disclose a method of cryopreserving and thawing cells that results in the thawed cells having high cellular viability and functionality post-thawing.
With respect to independent claims 1 and 12 currently rejected under 35 USC 101, the closest prior art of record Bluemel, Bluemel 2022, Bahari an Zhou and either in singularly or in combination fails to expressly or explicitly disclose the limitations of “using the computational fluid dynamics model to fit a transient temperature boundary equation to the first freezing profile, using the computational fluid dynamics model to predict a set-temperature sequence that produces a predicted second freezing profile of the scaled-down volume of the solution, wherein: (i) the transient temperature boundary equation is a condition for predicting the set-temperature sequence; and (ii) the second freezing profile includes predicted average temperatures of the solution during freezing and total freeze time; and (d) freezing the scaled-down volume of the solution using the set-temperature sequence” set forth by independent claim 1 in combination with the limitations set forth by the claim without the use of impermissible hindsight; and the limitations of “(b) using the computational fluid dynamics model to fit a transient temperature boundary equation to the first thawing profile; (c) using the computational fluid dynamics model to predict a set-temperature sequence that produces a predicted second thawing profile of the scaled-down volume of the solution, wherein: (i) the transient temperature boundary equation is a condition for predicting the set- temperature sequence; and (ii) the second thawing profile includes predicted average temperatures of the solution during thawing and total thaw time; and (d) thawing the scaled-down volume of the solution using the set-temperature sequence” recited by claim 12 in combination with the limitations set forth by the claim without the use of impermissible hindsight.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YARITZA H PEREZ BERMUDEZ whose telephone number is (571)270-1520. The examiner can normally be reached Monday-Friday.
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/YARITZA H. PEREZ BERMUDEZ/
Examiner
Art Unit 2857
/SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857
Prosecution Insights