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 .
Priority
Acknowledgment is made of applicant’s claim for priority. Application is a 371 of
PCT/US2020/060784 and claims the benefit of U.S. Provisional Application 62/936,550 filed 11/17/2019. As such, the effective filing date of claims 1-15 is 11/17/2019.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 8/16/2022 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Status
It is noted that that the preliminary amendment filed 12/13/2022 is noncompliant because it does not include an listing of all claims, in compliance with 37 CFR 1.121(c)(1). It is interpreted based on the first line of the amended claims that claims 1-50 are now cancelled. Any future response should include “Claims 1-50 (cancelled).” to be compliant.
Claims 51-72 are pending.
Claims 51-72 are rejected.
Drawings
Color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO patent electronic filing system or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO patent electronic filing system, and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification:
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
Color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2).
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: “filter generation module” in claims 64 and 66. The specification provides no further description than paragraph [0393] of what a “filter generation module” is, which merely provides the simple word module.
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.
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 § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 64 and 66 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claims use the phrase “filter generation module”, which is not properly described within the specification (the only description being in paragraph [0393] which mere describes said element as a module). Both the drawings and claims are unclear as to whether this is a physical element of the microfluidic device or a user interface component, with claims 64 and 66 not resolving this lack of clarity.
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 51-72 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claims recite a method for analyzing biological samples and generating/displaying said analysis from microfluidic devices. This judicial exception is not integrated into a practical application because while claims 51-72 attempt to integrate the exception into a practical application, said practical application is a generically recited computer element that does not add meaningful limitations to the abstract idea as it is simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the computer elements only store and retrieve information in memory as well as perform basic calculations that are known to be well-understood, routine and conventional computer functions as recognized by the decisions listed in MPEP § 2106.05(d).
Framework with which to Analyze Subject Matter Eligibility:
Step 1: Are the claims directed to a category of statutory subject matter (a process, machine manufacture, or composition of matter)? [see MPEP § 2106.03]
Claims are directed to statutory subject matter, specifically methods (claims 51-70), a computer program product (claim 71), and a system (claim 72).
Step 2A Prong One: Do the claims recite a judicially recognized exception, i.e., an abstract idea, a law of nature, or a natural phenomenon? [see MPEP § 2106.04(a)]
The claims herein recite abstract ideas.
With respect to the Step 2A Prong One evaluation, the instant claims are found herein to recite abstract ideas that fall into the grouping of mental processes and mathematical concepts.
The following claims recite abstract ideas (mental processes and mathematical concepts):
Claims 51, 71, 72: Identifying an analysis of biological samples, identifying filtered regions by applying a filter, and determining multiple characteristics for the single biological samples in regions of interest are processes of isolating, pinpointing, comparing/contrasting, and designing that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 52: The biological samples comprising T cells is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 53: The analysis being used is a multiplex cytokine assay and the characteristics include cytokines secreted by T cells is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 54: Determining a gallery structure for analysis results, determining a first sequence of data correlated with a set of time points or periods, determining a second sequence of data correlated with the set of time points or periods, extracting a first value of at least the first characteristic, and extracting a second value of at least the first characteristic are processes of isolating, pinpointing, comparing/contrasting, and designing that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes. The first sequence of data corresponding to at least a first characteristic of the multiple characteristics is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 59: Determining a timeline based upon a pipeline or workflow of biological samples is a process of comparing/contrasting and calculating that can be done with pen and paper or within the human mind is therefore an abstract idea, specifically a mental process.
Claim 60: Determining a plurality of stages for the analysis based upon the timeline is a process of comparing/contrasting and selecting information that can be done with pen and paper or within the human mind is therefore, an abstract idea, specifically a mental process.
Claim 61: Determining a plurality of graphic representations for the plurality of stages based upon the plurality of timepoints/time-periods is a process of comparing/contrasting and selecting information that can be done with pen and paper or within the human mind is therefore, an abstract idea, specifically a mental process.
Claim 63: The first data comprises a first identifier of the microfluidic device is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 64: Determining a first filter type for a first filter is a process of comparing/contrasting and selecting information that can be done with pen and paper or within the human mind is therefore, an abstract idea, specifically a mental process.
Claim 65: Dynamically determining and displaying a first total number of regions of interest is a process of selecting and calculating that can be done with pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 66: Generating a filter module that is a logical combination of at least a first and second filter type is a process of selecting and calculating that can be done with pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 67: Generating a bioinformatics pipeline view by determining a sequencing dataset comparing/contrasting and selecting information that can be done with pen paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 70: The multiple characteristics corresponding to one or more attributes listed is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Step 2A Prong Two: If the claims recite a judicial exception under prong one, then is the judicial exception integrated into a practical application? [see MPEP § 2106.04(d)]
Because the claims do recite judicial exceptions, direction under Step 2A Prong Two provides that the claims must be examined further to determine whether they integrate the abstract ideas into a practical application.
The following claims recite the following additional elements in the form of non-abstract elements:
Claim 51: Arranging and rendering associated data in a user interface is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)]. A processor is a generically recited element of computers that does not improve upon the functioning of any computer herein [See MPEP § 2106.05(d)(I) & (II)].
Claim 55: Rendering a first interactive object and second interactive object is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 56: Rendering the timeline view and matching grid portion in the user interface is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 57: The timeline view comprising a respective progress of workflow tasks that indicates respective temporal durations of the tasks is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 58: Associating a first region of interest with one or more graphical elements, is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 62: Rendering a data control view by generating a microfluidic device data structure having multiple fields and chambers is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 65: Populating first data correlated into the data structure is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 68: Rendering a first sequencing view is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 69: Overlaying the first sequencing view with first information comprising one or more of those listed is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 71: A computer program product, non-transitory computer-readable media, instructions, computing devices, and computer program instructions are generically recited elements of computers that do not improve upon the functioning of any computer herein [See MPEP § 2106.05(d)(I) & (II)]. Arranging and rendering associated data in a user interface is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 72: A system, processors, memory, and instructions are generically recited elements of computers that do not improve upon the functioning of any computer herein [See MPEP § 2106.05(d)(I) & (II)]. Arranging and rendering associated data in a user interface is an insignificant extra solution activity, specifically necessary data outputting (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept? [see MPEP § 2106.05]
Because the additional claim elements do not integrate the abstract ideas into a practical application, the claims are further examined under Step 2B, which evaluates whether the additional elements, individually and in combination, amount to significantly more than the judicial exception itself by providing an inventive concept.
The claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exceptions because the claims recite additional elements that are generic, conventional, nonspecific, or insignificant extra solution activity. These additional elements include:
The additional elements of a computer program product, non-transitory computer-readable media, instructions, computing devices, computer program instructions, a system, processors, and memory are generically recited elements of computers that do not improve upon the functioning of any computer herein [See MPEP § 2106.05(d)(I) & (II)]. Therefore, taken both individually and as whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
The additional elements of arranging and rendering associated data in a user interface (Conventional: Electric Power Group, LLC v. Alstom S.A. – Page 2, Paragraphs 1-2 Displaying results is generic and conventional failing under 101), rendering a first interactive object and second interactive object (Conventional: Electric Power Group, LLC v. Alstom S.A. – Page 2, Paragraphs 1-2 Displaying results is generic and conventional failing under 101), rendering the timeline view and matching grid portion in the user interface (Conventional: Electric Power Group, LLC v. Alstom S.A. – Page 2, Paragraphs 1-2 Displaying results is generic and conventional failing under 101), rendering a data control view by generating a microfluidic device data structure having multiple fields and chambers (Conventional: Electric Power Group, LLC v. Alstom S.A. – Page 2, Paragraphs 1-2 Displaying results is generic and conventional failing under 101), rendering a first sequencing view (Conventional:), overlaying the first sequencing view with first information comprising one or more of those listed (Conventional: Electric Power Group, LLC v. Alstom S.A. – Page 2, Paragraphs 1-2 Displaying results is generic and conventional failing under 101), are insignificant extra solution activity, specifically necessary data gathering (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering), Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)]. Therefore, taken both individually and as whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
Therefore, claims 51-72, when the limitations are considered individually and as a whole, are
rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
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 51-55, 58-61, and 71-72 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu et al. (Lab on a Chip (2008) 2197-2205), Bedekar et al. (Clinical chemistry (2007) 2023-2026), and Faley et al. (Lab on a Chip (2008) 1700-1712).
Claim 51 is directed to a method for analyzing biological samples using a microfluidic device with multiple regions to select and determine specific cell components that are representative of cell characteristics and provide an analysis of the respective characteristics.
Claim 71 is directed to a CRM for analyzing biological samples using a microfluidic device with multiple regions to select and determine specific cell components that are representative of cell characteristics and provide an analysis of the respective characteristics.
Claim 72 is directed to a system for analyzing biological samples using a microfluidic device with multiple regions to select and determine specific cell components that are representative of cell characteristics and provide an analysis of the respective characteristics.
Zhu et al. teaches in the abstract “The goal of the present study was to develop a miniature device for detection of interleukin (IL)-2 and interferon (IFN)-g cytokines secreted by a small population of CD4 and CD8 T-cells. Microarrays of T-cell- and cytokine-specific Ab spots were printed onto poly(ethylene glycol) (PEG) hydrogel-coated glass slides and enclosed inside a microfluidic device, creating a miniature (~3 mL) immunoreaction chamber. Introduction of the red blood cell (RBC) depleted whole human blood into the microfluidic device followed by washing at a pre-defined shear stress resulted in isolation of pure CD4 and CD8 T-cells on their respective Ab spots. Importantly, the cells became localized next to anti-IL-2 and -IFN-g Ab spots. Mitogenic activation of the captured T-cells was followed by immunofluorescent staining (all steps carried out inside a microfluidic device), revealing concentration gradients of surface-bound cytokine molecules. A microarray scanner was then used to quantify the concentration of IFN-g and IL-2 near CD4 and CD8 T-cells”, Figure 1(A) teaches “The conceptual design of microarrays for detection of T-cell-secreted cytokines. Printing of cell- and cytokine-specific Ab spots side-by-side allowed one to capture T-cells next to IL-2 and IFN-g sensing regions. T-cell-secreted cytokines were detected on the adjacent anti-cytokine Ab spots”, Figure 1(B) teaches “A map of the 8 x 20 microarray for capturing T-cells and detecting T-cell-secreted IL-2 and IFN-g”, Figure 1(C) teaches the integration of the two (1(A) and 1(B)) into a single microfluidic device, Figure 2-5 describe rendered visual analysis of the microfluidic device including florescent imaging, intensity profiles, calibration curves, and flow cytometry, reading on identifying an analysis of biological samples in multiple regions of interest in a microfluidic device; identifying, by a processor, filtered regions of interest by applying a filter to reduce the multiple regions of interest to include single biological sample regions of interest that each have single biological samples disposed within and not include multiple biological sample regions of interest that each include more than one biological samples disposed within; determining, by the processor, multiple characteristics for the single biological samples in the filtered regions of interest, wherein the multiple characteristics respectively correspond to an attribute, a property, or a quantifiable metric for the single biological samples; and arranging and rendering, by the processor, associated data from the analysis that respectively correspond to the filtered regions of interest in a user interface for at least a portion of the biological samples based at least in part upon the multiple characteristics.
Zhu et al. does not teach the use of computers, computer readable media, or processors.
Bedekar et al. teaches on page 2024, column 2, paragraph 2 “Design-modeling tools are needed that rapidly simulate the complex underlying phenomena such as electroosmosis, electrophoresis, sample dispersion, mixing, and biochemical reactions without significantly compromising accuracy. In addition, these design tools must be easily usable by the microfluidic community, which comprises scientists and engineers from a variety of disciplines. To meet these challenges, we developed integrated design software that allows rapid layout of microfluidic channel networks, fast system performance simulation using a system solver, and the ability to easily reconfigure chip layout to meet specifications… The software design follows a modified form of the traditional client-server architecture. The user interacts witha graphical user interface (GUI) front-end (client). Fig. 1 shows a screenshot of the GUI. The microfluidic lab-on-a chip system is represented as a network of interconnected components that can be assembled from a component library. The sequence of operations required for the creation of the microfluidic network, analysis, and visualization of results using the GUI”.
Faley et al. teaches on page 1702, column 1, paragraph 2 “Cells are introduced into one of the inlet ports using computer-controlled microsyringe pumps”, on page 1703, column 1, paragraph 2 “The motorized microscope stage, image acquisition, focus, and filter settings were controlled using Metamorph software (Molecular Devices, Downington, PA, USA). Syringe pump flow rates were also under computer control, utilizing software developed by VIIBRE researchers”, which in view of Bedekar et al. reads on the use of a computer system, computer media, and processors for the analysis, visualization and control of microfluidic devices.
It would have been obvious at the time of first filing to have modified the teachings of Zhu et al. for the method of claim 51 with the use of a computer, processors, and computer media from Faley et al. as Zhu et al. is building a singular microfluidic device, while Faley et al. is building a microfluidic platform, both of which are directed to the examination of T cells. Furthermore, Bedekar et al. is designing a software for design, analysis and visualization of both the microfluidic device and the analysis and show “the application of the software to improve the design for an electrokinetic immunoassay chip”. One would have had a reasonable expectation of success given that all three are designed to work with the same cell line, perform similar analysis, and primary difference being between the use of computer aided technology or not with Bedekar et al. further linking through the incorporation of specific software for the analysis and visualization. Therefore, it would have been obvious at the time of first filing to have modified the teachings of each and to be successful.
Claim 52 is directed to the claim of 51 but further specifies the biological samples are T cells.
Zhu et al. teaches in the abstract “The goal of the present study was to develop a miniature device for detection of interleukin (IL)-2 and interferon (IFN)-g cytokines secreted by a small population of CD4 and CD8 T-cells”, reading on wherein the biological samples are T cells.
Claim 53 is directed to the method of claim 52 and thus 51, but further specifies that the analysis is a cytokine assay and the characteristics include cytokines from the T cells.
Zhu et al. teaches on page 2198, column 1-2, paragraphs 2 and 3 “The goal of the present study was to integrate multiplexed immunoassay for detection of secreted cytokines with captured T-cells. To achieve this goal, microarrays of cell and cytokine-specific Ab spots were printed side-by-side so as to position T-cells in the immediate vicinity of the immunosensors for IFN-g and IL-2…This microarray arrangement ensured that all cytokine immunoassay spots were exposed to the same cytokine concentration. In addition to capture Abs, cytokine immunoassay microarray included several negative and positive controls”, reading on wherein the analysis is a multiplex cytokine assay, and the multiple characteristics includes a plurality of cytokines secreted from the T cells.
Claim 54 is directed to the method of claim 53 and thus 51, but further specifies that there be a gallery structure in which time series data is rendered based on the characteristics under examination in a user interface.
Faley et al. teaches on page 1706, column 2, paragraph 1 “Another key strength of this platform is the ability to generate and study cell–cell interactions in real time”, Figure 3(A)-(D) describes examples of cytosolic calcium transients across timepoints, Figure 4(B)-(D) describes profiles of subgroups, average profiles and simulated FACS data over time, and page 1708, column 1, paragraph 1 teaches “In Fig. 4B, we created cluster profiles by plotting the 457 individual T cell time-series profiles according to their group assignment”, reading on wherein arranging and rendering the associated data comprises determining a gallery structure having a plurality of gallery sub-structures for the analysis results based at least in part upon an allocable space… for rendering the analysis results, and wherein determining the gallery structure comprises: determining, by the processor, a first sequence of data correlated with a set of time points or time periods for a first biological sample obtained from a first region of interest of the multiple regions of interest from the gallery structure stored in an addressable space in a non-transitory computer accessible storage medium, wherein the first sequence of data corresponds to at least a first characteristic of the multiple characteristics; determining, by the processor, a second sequence of data correlated with the set of time points or time periods for a second biological sample obtained from a second region of interest of the multiple regions of interest from the gallery structure, wherein the second sequence of data corresponds to at least a second characteristic of the multiple characteristics; in response to a selection of the at least the first characteristic from the multiple characteristics with a first selection widget in the user interface, extracting, by the processor, a first value of at least the first characteristic from a plurality of values for the first biological sample or for the analysis; and extracting, by the processor, a second value of at least the first characteristic from the plurality of values for the second biological sample or for the analysis.
Faley et al. does not teach the use of a user interface, however it would have been obvious at the time of first filing to have modified the teachings of Zhu et al. and Faley et al. for the method previously described with the use of a user interface as the use of computer assisted methods such as those described in Faley et al. would necessitate a user controller and the computer-generated images as those described in Faley et al. would necessitate a computer display of sort, the combination of which would render obvious the need for a user interface for display or generation of various analyses from the microfluidic device. One would have had a reasonable expectation of success given the use of computer software, and computer display for the analysis and presentation of data being an integral part of the invention. Therefore, it would have been obvious at the time of first filing to have modified the teachings of each and to be successful.
Claim 55 is directed to the method of claim 54 and thus 51, but further specifies the rendering of a first and second interactive object that correspond to and are representative of the first and second values of the first and second biological samples.
Zhu et al. teaches in Figure 4 “A) Flow cytometry analysis of IFN-g and IL-2 in CD4+ T-cell population points to robust production of both cytokines by this leukocyte subset. (B) Flow cytometry analysis showed that CD8+ T-cells robustly produced IFN-g but not IL-2”, and in Figure 5(B) and (E) “Concentration of IL-2 and IFN-gdetected from CD4 T-cells activated for different time periods. The concentration values correspond to fluorescence intensity scans shown in part (B)”, furthermore Faley et al. teaches in Figure 4(B)-(C) describes profiles of subgroups, and average profiles.
Bedekar et al. teaches on page 2024, column 2, paragraph 2 “Design-modeling tools are needed that rapidly simulate the complex underlying phenomena such as electroosmosis, electrophoresis, sample dispersion, mixing, and biochemical reactions without significantly compromising accuracy. In addition, these design tools must be easily usable by the microfluidic community, which comprises scientists and engineers from a variety of disciplines. To meet these challenges, we developed integrated design software that allows rapid layout of microfluidic channel networks, fast system performance simulation using a system solver, and the ability to easily reconfigure chip layout to meet specifications… The software design follows a modified form of the traditional client-server architecture. The user interacts witha graphical user interface (GUI) front-end (client). Fig. 1 shows a screenshot of the GUI. The microfluidic lab-on-a chip system is represented as a network of interconnected components that can be assembled from a component library. The sequence of operations required for the creation of the microfluidic network, analysis, and visualization of results using the GUI”, which in view of Faley et al. reads on wherein rendering the analysis results comprises: rendering, by the processor, a first interactive object and a second interactive object respectively corresponding to the first sequence of data and the second sequence of data into the gallery view, wherein the first interactive object is representative of the first value for the first biological sample or for the analysis, and the second interactive object is representative of the second value for the second biological sample or for the analysis.
Claim 58 is directed to the method of claim 51 but further specifies that a region of interest is associated with one or more graphical elements in a timeline view.
Faley et al. teaches in Figure 4(B)-(C) describes profiles of subgroups, and average profiles over time, thereby reading on further comprising: associating, by the processor, a first region of interest of the multiple regions of interest with one or more graphical elements illustrated in a timeline view.
Claim 59 is directed to the method of claim 58, but further specifies determining a timeline based on a pipeline or workflow for the analysis of the biological samples.
Faley et al. teaches on page 1706, column 2, paragraph 1 “Another key strength of this platform is the ability to generate and study cell–cell interactions in real time. Fig. 3D and the corresponding inset clearly show pulsing of calcium transients within the TN cells as they interacted with DCs within the device”, reading on wherein rendering the analysis results comprises: determining, by the processor, a timeline based at least in part upon a pipeline or a workflow comprising the multiple workflow tasks for the analysis of the biological samples.
Claim 60 is directed to the method of claim 59 and thus claim 51, but further specifies determining stages that correspond to a plurality of timepoints in the analysis of the biological samples.
Faley et al. teaches on page 1706, column 2, paragraph 1 “Another key strength of this platform is the ability to generate and study cell–cell interactions in real time”, Figure 3(A)-(D) describes examples of cytosolic calcium transients across timepoints, and it would be inherent that any data described in in a graphical rendering across specific time points would also represent a plurality of stages based upon said timepoints, such as those shown in Figure 3 (B)-(D), thereby reading on wherein rendering the analysis results comprises: determining, by the processor, a plurality of stages for the analysis based at least in part upon the timeline, wherein the plurality of stages respectively corresponds to a plurality of timepoints or time periods for the analysis of the biological samples.
Claim 61 is directed to the method of claim 60 and thus 51, but further specifies determining graphical representations for the stages based on the time points.
Faley et al. teaches on page 1706, column 2, paragraph 1 “Another key strength of this platform is the ability to generate and study cell–cell interactions in real time”, and Figure 3(C) illustrates “three typical calcium transient patterns observed when stimulating T cells with ionomycin” across time, reading on wherein rendering the analysis results comprises: respectively determining, by the processor, a plurality of graphic representations for the plurality of stages based at least in part upon the plurality of timepoints or time periods.
Claims 56-57, and 62-63 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu et al. (Lab on a Chip (2008) 2197-2205), Bedekar et al. (Clinical chemistry (2007) 2023-2026), and Faley et al. (Lab on a Chip (2008) 1700-1712) as applied to claims 51-55, 58-61, and 71-72 above, and further in view of Fobel et al. (Applied Physics Letters (2013) 1-6).
Claim 56 is directed to the method of claim 51 but further specifies the invocation of a timeline view in the user interface with a matching grid portion.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described.
Zhu et al. and Faley et al. do not teach the invocation of a timeline view in the user interface with a matching grid portion.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay”, showing a data structure with multiple fields an ID and duration for each of the steps used within the microfluidic device for the protocol steps reading on in response to an invocation of a timeline view through a timeline view activation interactive widget in the user interface based at least in part upon the timeline, rendering, by the processor, the timeline view and a matching grid portion in the user interface.
It would have been obvious at the time of first filing to modify the teachings of Zhu et al. and Faley et al. for the method of claim 51, with the teachings of Fobel et al. for an open-source instrument for digital microfluidics, as the latter specifies in the abstract “this system will enhance insight into failure modes and lead to new strategies for improved device reliability, and will be useful for the growing number of users who are adopting digital microfluidics for automated, miniaturized laboratory operation”. One would have had a reasonable expectation of success given that the latter is open source and directed to automated, computer aided microfluidics. Therefore, it would have been obvious at the time of first to have modified the teachings of each and to be successful.
Claim 57 is directed to the method of claim 56 and thus 51, but further specifies that the timeline view comprises a respective progress of multiple workflow tasks.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described.
Zhu et al. and Faley et al. do not teach the invocation of a timeline view in the user interface with a matching grid portion.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay”, showing a data structure with multiple fields an ID and duration for each of the steps used within the microfluidic device for the protocol steps, thereby showing the progress of each step within the overall workflow according to each duration, reading on the timeline view comprises a respective progress of multiple workflow tasks in the analysis of the biological samples, and the respective progress graphically indicates respective temporal durations of the multiple workflow tasks.
Claim 62 is directed to the method of claim 51 but further specifies a control view comprising a microfluidic device data structure which has a plurality of fields and plurality of chambers.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described.
Zhu et al. and Faley et al. do not teach a control view comprising a microfluidic device data structure which has a plurality of fields and plurality of chambers.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay”, showing a data structure with multiple fields and a device with multiple chambers that a user can control, thereby reading on a data control view in the user interface, rendering the data control view comprising: generating a microfluidic device data structure having a plurality of fields for the microfluidic device, wherein the microfluidic device has a plurality of chambers.
Claim 63 is directed to the method of claim 61 and thus 51, but further specifies populating a first data field with an identifier for the device.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described.
Zhu et al. and Faley et al. do not teach populating a first data field with an identifier for the device.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay”, showing a data structure with multiple fields and an initial data structure with a device ID, reading on wherein rendering the data control view comprises: populating first data correlated with the microfluidic device into a first field in the microfluidic device data structure, wherein the first data comprises a first identifier of the microfluidic device.
Claims 64-66 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu et al. (Lab on a Chip (2008) 2197-2205), Bedekar et al. (Clinical chemistry (2007) 2023-2026), and Faley et al. (Lab on a Chip (2008) 1700-1712) as applied to claims 51-55, 58-61, and 71-72 above, and further in view of Fobel et al. (Applied Physics Letters (2013) 1-6) and Santaniello et al. (Journal of Micromechanics and Microengineering (2015) 1-13).
Claim 64 is directed to the method of claim 51 but further specifies determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described. Furthermore Zhu et al. teaches the use of specific microarrays within the microfluidic device that function essentially as filters for the binding of specific cell elements.
Zhu et al. and Faley et al. do not teach determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay” and Figure 3(A) showing path selection/creation, allowing for the selection by the user of a path for the fluid within the microfluidic device.
Santaniello et al. teaches on page 3, column 2, paragraph 1 “The produced microdevice was developed employing a micro-fabrication approach which is suitable for further scale up manufacturing. The produced polymeric film is mechanically fastened between two thermoplastic microfluidic components to act as a dynamic filter for single cells”, which in view of the previous teachings read on a filter view in the user interface, wherein rendering the filter view comprises: determining a first filter type for a first filter based at least in part upon an execution of one or more instructions triggered by an interaction with a first filter selector switch in a filter generation module.
It would have been obvious at the time of first filing to have modified the teachings of Zhu et al. and Faley et al. for the method of claim 51, with the teachings of Fobel et al. for an open-source instrument for digital microfluidics, as the latter specifies in the abstract “this system will enhance insight into failure modes and lead to new strategies for improved device reliability, and will be useful for the growing number of users who are adopting digital microfluidics for automated, miniaturized laboratory operation”. Furthermore, it would have been obvious to have modified those teachings with the teachings of Santaniello et al. for the incorporation of dynamic filters as the dynamic filters allowed for the “label-free cell separation procedures”. One would have had a reasonable expectation of success given that the methods are all directed to the use of microfluidic devices for single cell analysis, with the exception of Fobel et al. which is merely presenting a UI control device for said microfluid devices and is open source. Therefore, it would have been obvious at the time of first filing to have modified the teachings of each and to be successful.
Claim 65 is directed to the method of claim 64 and thus 51, but further specifies dynamically determining and displaying a filter view of regions of interest for filtered regions.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described. Furthermore Zhu et al. teaches the use of specific microarrays within the microfluidic device that function essentially as filters for the binding of specific cell elements.
Zhu et al. and Faley et al. do not teach determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay” and Figure 3(A) showing path selection/creation, allowing for the selection by the user of a path for the fluid within the microfluidic device.
Santaniello et al. teaches on page 3, column 2, paragraph 1 “The produced microdevice was developed employing a micro-fabrication approach which is suitable for further scale up manufacturing. The produced polymeric film is mechanically fastened between two thermoplastic microfluidic components to act as a dynamic filter for single cells”, which in view of the previous teachings read on dynamically determining and displaying, by the processor, in the filter view for the microfluidic device, a first total number of regions of interest for a first set of filtered regions of interest that satisfies a first dynamic constraint of the first filter applied to the multiple regions of interest.
Claim 66 is directed to the method of claim 64 and thus 51, but further specifies generating a logical combination of multiple filters.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described. Furthermore Zhu et al. teaches the use of specific microarrays within the microfluidic device that function essentially as filters for the binding of specific cell elements.
Zhu et al. and Faley et al. do not teach determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay” and Figure 3(A) showing path selection/creation, allowing for the selection by the user of a path for the fluid within the microfluidic device.
Santaniello et al. teaches on page 3, column 2, paragraph 1 “The produced microdevice was developed employing a micro-fabrication approach which is suitable for further scale up manufacturing. The produced polymeric film is mechanically fastened between two thermoplastic microfluidic components to act as a dynamic filter for single cells”, which in view of the previous teachings read on generating, by the processor, at a filter generation module, a logical combination of at least a second filter of a second filter type and the first filter of the first filter type.
Claim 70 is directed to the method of claim 51 but further specifies an identifier for a region of interest based on one of the specified identifiers.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described. Furthermore Zhu et al. teaches the use of specific microarrays within the microfluidic device that function essentially as filters for the binding of specific cell elements.
Zhu et al. and Faley et al. do not teach determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay” and Figure 3(A) showing path selection/creation, allowing for the selection by the user of a path for the fluid within the microfluidic device.
Santaniello et al. teaches on page 3, column 2, paragraph 1 “The produced microdevice was developed employing a micro-fabrication approach which is suitable for further scale up manufacturing. The produced polymeric film is mechanically fastened between two thermoplastic microfluidic components to act as a dynamic filter for single cells”, which in view of the previous teachings read on wherein the multiple characteristics correspond to one or more attributes that further comprise at least one of an identifier of a region of interest in the microfluidic device, a size attribute of the biological samples, a maximum brightness attribute for the biological samples, a minimum brightness attribute for the biological samples, a first pixel count attribute in a first direction for a centroid of a first biological sample, a second pixel count attribute in a second direction for the centroid of the biological sample, a size attribute for the centroid of the biological sample, a time lapse index attribute, a device identifier for the microfluidic device, a biological sample count attribute, a verified biological sample count attribute, a biological sample type attribute, a score attribute of the plurality of regions of interest, a gate path index, an area pixel attribute, a background pixel attribute, or a median brightness attribute for the plurality of biological samples.
Claims 67-70 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu et al. (Lab on a Chip (2008) 2197-2205), Bedekar et al. (Clinical chemistry (2007) 2023-2026), and Faley et al. (Lab on a Chip (2008) 1700-1712) as applied to claims 51-55, 58-61, and 71-72 above, and further in view of Fobel et al. (Applied Physics Letters (2013) 1-6) and Chang et al. (Sensor and Actuators (2017) 215-224).
Claim 67 is directed to the method of claim 51 but further specifies a bioinformatics pipeline view including regions of interest, and biological samples.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described.
Zhu et al. and Faley et al. do not teach determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay” and Figure 3(A) showing path selection/creation, allowing for the selection by the user of a path for the fluid within the microfluidic device.
Chang et al. teaches in the abstract “A microfluidic device, which performs a primer extension technique onto microbeads, is demonstrated to genotype Single Nucleotide Polymorphism (SNP) on genomic DNA. The device has on-chip heaters and sensors to create a uniform and yet stable temperature gradient between 56◦C and 94◦C across an array of serpentine microchannels, where the microbeads carry allele-specific primers passing through for thermal cycling. As the primers on the beads is designed to be only extended when perfectly matched with the SNP site of the template, the mismatched samples will not be amplified. The SNP discrimination is achieved”, which in view of the previously cited prior and particularly Fobel et al.’s use of step/process/pipeline view, reads on generating, by the processor, a bioinformatics pipeline view, wherein generating the bioinformatics pipeline view comprises: determining a sequencing dataset for the biological samples in a plurality of chambers or the multiple regions of interest of the microfluidic device, wherein the biological samples each comprise a sequence of nucleotides or amino acids.
It would have been obvious at the time of first filing to have modified the teachings of Zhu et al. and Faley et al. for the method of claim 51, with the teachings of Fobel et al. for an open-source instrument for digital microfluidics, as the latter specifies in the abstract “this system will enhance insight into failure modes and lead to new strategies for improved device reliability, and will be useful for the growing number of users who are adopting digital microfluidics for automated, miniaturized laboratory operation”. Furthermore, it would have been obvious to have modified those teachings with the teachings of Chang et al. for a microfluidic device that focuses on bioinformatics, specifically sequencing, and then integrate the previously cited prior arts focus on user interface and analysis presentation within the bioinformatics device as the latter specifies within the abstract “the SNP genotyping procedures, which typically involves multiple steps in amplification and detection, were integrated onto a single chip” and “the microfluidic environment promote enhanced mass transport and better hybridization kinetics, the microbeads offer an advantage for faster thermal response and higher signal-to-noise ratio”. This would therefore render obvious the inclusion of information regarding sequence analysis into the user interface presentation, along with sequencing steps that would replace single cell analyses, or chemical analyses seen in other microfluidic devices. One would have had a reasonable expectation of success given Fobel et al. is merely presenting a UI control device for said microfluid devices and is open source, and Chang et al. is merely successfully changing the use of the microfluidic device. Therefore, it would have been obvious at the time of first filing to have modified the teachings of each and to be successful.
Claim 68 is directed to the method of claim 67 and thus 51, but further specifies the rendering of a sequencing view that illustrates distribution of an attribute of a sequence such as nucleotides, amino acids or macromolecules.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described.
Zhu et al. and Faley et al. do not teach determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay” and Figure 3(A) showing path selection/creation, allowing for the selection by the user of a path for the fluid within the microfluidic device.
Chang et al. teaches in the abstract “A microfluidic device, which performs a primer extension technique onto microbeads, is demonstrated to genotype Single Nucleotide Polymorphism (SNP) on genomic DNA. The device has on-chip heaters and sensors to create a uniform and yet stable temperature gradient between 56◦C and 94◦C across an array of serpentine microchannels, where the microbeads carry allele-specific primers passing through for thermal cycling. As the primers on the beads is designed to be only extended when perfectly matched with the SNP site of the template, the mismatched samples will not be amplified. The SNP discrimination is achieved”, which in view of the previously cited prior and particularly Fobel et al.’s use of step/process/pipeline view, reads on wherein generating the bioinformatics pipeline view further comprises: in response to a first interaction with a first sequencing view widget in the user interface, rendering, by the processor, a first sequencing view in the bioinformatics pipeline view that illustrates a distribution of an attribute of a sequence of first biological samples including at least one of a sequence of nucleotides, a sequence of amino acids, or a sequence of macromolecules in the plurality of chambers or the multiple regions of interest of the microfluidic device.
Claim 69 is directed to the method of claim 68 and thus 51, but further specifies overlaying sequencing and bioinformatics views to include statistical measures of the distribution of an attribute.
Zhu et al. and Faley et al. teach the method of claim 51 as previously described.
Zhu et al. and Faley et al. do not teach determining a filter type for the first filter based upon instructions between a filter selector and filter generator.
Fobel et al. teaches in Figure 1(C) “Screenshot from the custom PYTHON software demonstrating live video overlay” and Figure 3(A) showing path selection/creation, allowing for the selection by the user of a path for the fluid within the microfluidic device.
Chang et al. teaches in the abstract “A microfluidic device, which performs a primer extension technique onto microbeads, is demonstrated to genotype Single Nucleotide Polymorphism (SNP) on genomic DNA. The device has on-chip heaters and sensors to create a uniform and yet stable temperature gradient between 56◦C and 94◦C across an array of serpentine microchannels, where the microbeads carry allele-specific primers passing through for thermal cycling. As the primers on the beads is designed to be only extended when perfectly matched with the SNP site of the template, the mismatched samples will not be amplified. The SNP discrimination is achieved”, which in view of the previously cited prior and particularly Fobel et al.’s use of step/process/pipeline view and the focus on sequencing in the current prior art, reads on wherein generating the bioinformatics pipeline view further comprises: overlaying the first sequencing view with first information that comprises one or more statistical measures of the distribution of the attribute of multiple sequences of first biological samples, the multiple sequences of first biological samples including the sequence of first biological samples, wherein the user interface comprises a total number of the multiple sequences of first biological samples, a total number of regions of interest having the sequence of first biological samples, and a respective total number of one or more sequences of first biological samples in a respective region of interest of the array of regions of interest.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 51, 54, and 56-72 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-21 of U.S. Patent No. 11521709. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims recite limitations that are either similar in scope or describe similar limitations.
Application: 17/745,624
U.S. Patent No. US 11521709 B2
Claim 51: A method for analyzing biological samples, comprising: identifying an analysis of biological samples in multiple regions of interest in a microfluidic device; identifying, by a processor, filtered regions of interest by applying a filter to reduce the multiple regions of interest to include single biological sample regions of interest that each have single biological samples disposed within and not include multiple biological sample regions of interest that each include more than one biological samples disposed within; determining, by the processor, multiple characteristics for the single biological samples in the filtered regions of interest, wherein the multiple characteristics respectively correspond to an attribute, a property, or a quantifiable metric for the single biological samples; and arranging and rendering, by the processor, associated data from the analysis that respectively correspond to the filtered regions of interest in a user interface for at least a portion of the biological samples based at least in part upon the multiple characteristics.
Claim 1: A method for analyzing biological samples, comprising: identifying an analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis, wherein the timeline comprises information that is temporally aligned with at least one of a workflow or a pipeline of the analysis of the biological samples; determining one or more region-of-interest types for the multiple regions of interest, wherein the one or more region-of-interest types comprise a target-based type correlated with at least one biological sample of the biological samples or a structure-based type correlated with the microfluidic device; determining multiple characteristics for the biological samples based at least in part upon the one or more region-of-interest types, wherein the multiple characteristics respectively correspond to an attribute, a property, or a quantifiable metric for the biological samples or the analyses; arranging and rendering associated data from the analysis that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples based at least in part upon the multiple characteristics and the timeline; and generating a bioinformatics pipeline view, generating the bioinformatics pipeline view comprising: determining a sequencing dataset for the biological samples in a plurality of chambers or the multiple regions of interest of the microfluidic device, wherein a biological sample comprises a sequence of nucleotides or amino acids.
Claim 52: The method of claim 51, wherein the biological samples are T cells.
Claim 53: The method of claim 52, wherein the analysis is a multiplex cytokine assay, and the multiple characteristics includes a plurality of cytokines secreted from the T cells.
Claim 54: The method of claim 53, wherein arranging and rendering the associated data comprises determining a gallery structure having a plurality of gallery sub-structures for the analysis results based at least in part upon an allocable space in the user interface for rendering the analysis results, and wherein determining the gallery structure comprises: determining, by the processor, a first sequence of data correlated with a set of time points or time periods for a first biological sample obtained from a first region of interest of the multiple regions of interest from the gallery structure stored in an addressable space in a non-transitory computer accessible storage medium, wherein the first sequence of data corresponds to at least a first characteristic of the multiple characteristics; determining, by the processor, a second sequence of data correlated with the set of time points or time periods for a second biological sample obtained from a second region of interest of the multiple regions of interest from the gallery structure, wherein the second sequence of data corresponds to at least a second characteristic of the multiple characteristics; in response to a selection of the at least the first characteristic from the multiple characteristics with a first selection widget in the user interface, extracting, by the processor, a first value of at least the first characteristic from a plurality of values for the first biological sample or for the analysis; and extracting, by the processor, a second value of at least the first characteristic from the plurality of values for the second biological sample or for the analysis.
Claim 2: The method of claim 1, wherein arranging and rendering the associated data comprises: determining a gallery structure having a plurality of gallery sub-structures for the analysis results based at least in part upon an allocable space in the user interface for rendering the analysis results.
Claim 3: The method of claim 2, wherein arranging and rendering the analysis results comprises: populating the analysis results into the plurality of gallery sub-structures in a gallery structure based at least in part upon a characteristic of the multiple characteristics.
Claim 6: The method of claim 1, further comprising: in response to an invocation of a timeline view through a timeline view activation interactive widget in the user interface based at least in part upon the timeline, rendering the timeline view and a matching grid portion in the user interface.
Claim 10: The method of claim 9, wherein arranging and rendering the analysis results comprises: determining a plurality of stages for the analysis based at least in part upon the timeline, wherein the plurality of stages respectively corresponds to a plurality of timepoints or time periods for the analysis of the biological samples.
Claim 11: The method of claim 10, wherein rendering the respective analysis results comprises: respectively determining a plurality of graphic representations for the plurality of stages based at least in part upon the plurality of timepoints or time periods.
Claim 55: The method of claim 54, wherein rendering the analysis results comprises: rendering, by the processor, a first interactive object and a second interactive object respectively corresponding to the first sequence of data and the second sequence of data into the gallery view, wherein the first interactive object is representative of the first value for the first biological sample or for the analysis, and the second interactive object is representative of the second value for the second biological sample or for the analysis.
Claim 56: The method of claim 51, further comprising: in response to an invocation of a timeline view through a timeline view activation interactive widget in the user interface based at least in part upon the timeline, rendering, by the processor, the timeline view and a matching grid portion in the user interface.
Claim 6: The method of claim 1, further comprising: in response to an invocation of a timeline view through a timeline view activation interactive widget in the user interface based at least in part upon the timeline, rendering the timeline view and a matching grid portion in the user interface.
Claim 57: The method of claim 56, wherein: the timeline view comprises a respective progress of multiple workflow tasks in the analysis of the biological samples, and the respective progress graphically indicates respective temporal durations of the multiple workflow tasks.
Claim 7: The method of claim 6, wherein the timeline view comprises a respective progress of multiple workflow tasks in the analysis of the biological samples, and the respective progress graphically indicates respective temporal durations of the multiple workflow tasks.
Claim 58: The method of claim 51, further comprising: associating, by the processor, a first region of interest of the multiple regions of interest with one or more graphical elements illustrated in a timeline view.
Claim 8: The method of claim 1, further comprising: associating a first region of interest of the multiple regions of interest with one or more graphical elements illustrated in a timeline view.
Claim 59: The method of claim 58, wherein rendering the analysis results comprises: determining, by the processor, a timeline based at least in part upon a pipeline or a workflow comprising the multiple workflow tasks for the analysis of the biological samples.
Claim 9: The method of claim 8, wherein arranging and rendering the analysis results comprises: determining the timeline based at least in part upon the pipeline or the workflow for the analysis of the biological samples.
Claim 60: The method of claim 59, wherein rendering the analysis results comprises: determining, by the processor, a plurality of stages for the analysis based at least in part upon the timeline, wherein the plurality of stages respectively corresponds to a plurality of timepoints or time periods for the analysis of the biological samples.
Claim 10: The method of claim 9, wherein arranging and rendering the analysis results comprises: determining a plurality of stages for the analysis based at least in part upon the timeline, wherein the plurality of stages respectively corresponds to a plurality of timepoints or time periods for the analysis of the biological samples.
Claim 61: The method of claim 60, wherein rendering the analysis results comprises: respectively determining, by the processor, a plurality of graphic representations for the plurality of stages based at least in part upon the plurality of timepoints or time periods.
Claim 11: The method of claim 10, wherein rendering the respective analysis results comprises: respectively determining a plurality of graphic representations for the plurality of stages based at least in part upon the plurality of timepoints or time periods.
Claim 62: The method of claim 51, further comprising rendering, by the processor, a data control view in the user interface, rendering the data control view comprising: generating a microfluidic device data structure having a plurality of fields for the microfluidic device, wherein the microfluidic device has a plurality of chambers.
Claim 12: The method of claim 1, further comprising rendering a data control view in the user interface, rendering the data control view comprising: generating a microfluidic device data structure having a plurality of fields for the microfluidic device having a plurality of chambers.
Claim 63: The method of claim 62, wherein rendering the data control view comprises: populating first data correlated with the microfluidic device into a first field in Response to Notice to File Missing Parts Attorney Docket No. BL002814-US2 the microfluidic device data structure, wherein the first data comprises a first identifier of the microfluidic device.
Claim 13: The method of claim 12, rendering the data control view comprising: populating first data correlated with the microfluidic device into a first field in the microfluidic device data structure, wherein the first data comprises a first identifier of the microfluidic device.
Claim 64: The method of claim 51, further comprising rendering, by the processor, a filter view in the user interface, wherein rendering the filter view comprises: determining a first filter type for a first filter based at least in part upon an execution of one or more instructions triggered by an interaction with a first filter selector switch in a filter generation module.
Claim 14: The method of claim 1, further comprising rendering a filter view, wherein rendering the filter view comprises: determining a first filter type for a first filter based at least in part upon an execution of one or more instructions triggered by an interaction with a first filter selector switch in a filter generation module.
Claim 65: The method of claim 64, wherein rendering the filter view further comprises: dynamically determining and displaying, by the processor, in the filter view for the microfluidic device, a first total number of regions of interest for a first set of filtered regions of interest that satisfies a first dynamic constraint of the first filter applied to the multiple regions of interest.
Claim 15: The method of claim 14, rendering the filter view further comprising: dynamically determining and displaying, in the filter view for the microfluidic device, a first total number of regions of interest for a first set of filtered regions of interest that satisfies a first dynamic constraint of the first filter applied to the multiple regions of interest.
Claim 66: The method of claim 64, wherein rendering the filter view further comprises: generating, by the processor, at a filter generation module, a logical combination of at least a second filter of a second filter type and the first filter of the first filter type.
Claim 16: The method of claim 14, rendering the filter view further comprising: generating, at a filter generation module, a logical combination of at least a second filter of a second filter type and the first filter of the first filter type.
Claim 67: The method of claim 51, further comprising generating, by the processor, a bioinformatics pipeline view, wherein generating the bioinformatics pipeline view comprises: determining a sequencing dataset for the biological samples in a plurality of chambers or the multiple regions of interest of the microfluidic device, wherein the biological samples each comprise a sequence of nucleotides or amino acids.
Claim 17: The method of claim 1, generating the bioinformatics pipeline view further comprising: in response to a first interaction with a first sequencing view widget in the user interface, rendering a first sequencing view in the bioinformatics pipeline view that illustrates a distribution of an attribute of the sequence of first biological samples including at least one of a sequence of nucleotides, a sequence of amino acids, or a sequence of macromolecules in the plurality of chambers or the multiple regions of interest of the microfluidic device.
Claim 18: The method of claim 17, generating the bioinformatics pipeline view further comprising: overlaying the first sequencing view with first information that comprises one or more statistical measures of the distribution of the attribute of multiple sequences of first biological samples including the sequence of first biological samples, wherein the user interface comprises a total number of the multiple sequences of first biological samples, a total number of regions of interest having the sequence of first biological samples, and a respective total number of one or more sequences of first biological samples in a respective region of interest of the array of regions of interest.
Claim 68: The method of claim 67, wherein generating the bioinformatics pipeline view further comprises: in response to a first interaction with a first sequencing view widget in the user interface, rendering, by the processor, a first sequencing view in the bioinformatics pipeline view that illustrates a distribution of an attribute of a sequence of first biological samples including at least one of a sequence of nucleotides, a sequence of amino acids, or a sequence of macromolecules in the plurality of chambers or the multiple regions of interest of the microfluidic device.
Claim 69: The method of claim 68, wherein generating the bioinformatics pipeline view further comprises: overlaying the first sequencing view with first information that comprises one or more statistical measures of the distribution of the attribute of multiple sequences of first biological samples, the multiple sequences of first biological samples including the sequence of first biological samples, wherein the user interface comprises a total number of the multiple sequences of first biological samples, a total number of regions of interest having the sequence of first biological samples, and a respective total number of one or more sequences of first biological samples in a respective region of interest of the array of regions of interest.
Claim 70: The method of claim 51, wherein the multiple characteristics correspond to one or more attributes that further comprise at least one of an identifier of a region of interest in the microfluidic device, a size attribute of the biological samples, a maximum brightness attribute for the biological samples, a minimum brightness attribute for the biological samples, a first pixel count attribute in a first direction for a centroid of a first biological sample, a second pixel count attribute in a second direction for the centroid of the biological sample, a size attribute for the centroid of the biological sample, a time lapse index attribute, a device identifier for the microfluidic device, a biological sample count attribute, a verified biological sample count attribute, a biological sample type attribute, a score attribute of the plurality of regions of interest, a gate path index, an area pixel attribute, a background pixel attribute, or a median brightness attribute for the plurality of biological samples.
Claim 19: The method of claim 1, wherein the multiple characteristics correspond to one or more attributes that further comprise at least one of an identifier of a region of interest in the microfluidic device, a size attribute of the biological samples, a maximum brightness attribute for the biological samples, a minimum brightness attribute for the biological samples, a first pixel count attribute in a first direction for a centroid of a first biological sample, a second pixel count attribute in a second direction for the centroid of the biological sample, a size attribute for the centroid of the biological sample, a time lapse index attribute, a device identifier for the microfluidic device, a biological sample count attribute, a verified biological sample count attribute, a biological sample type attribute, a score attribute of the plurality of regions of interest, a gate path index, an area pixel attribute, a background pixel attribute, or a median brightness attribute for the plurality of biological samples.
Claim 71: A computer program product, comprising one or more non-transitory computer-readable media having computer program instructions stored therein, the computer program instructions being configured such that, when executed by one or more computing devices, the computer program instructions cause the one or more computing devices to: identify an analysis of biological samples in multiple regions of interest in a microfluidic device; identify filtered regions of interest by applying a filter to reduce the multiple regions of interest to include single biological sample regions of interest that each have single biological samples disposed within and not include multiple biological sample regions of interest that each include more than one biological samples disposed within; determine multiple characteristics for the single biological samples in the filtered regions of interest, wherein the multiple characteristics respectively correspond to an attribute, a property, or a quantifiable metric for the single biological samples; and arrange and render associated data from the analysis that respectively correspond to the filtered regions of interest in a user interface for at least a portion of the biological samples based at least in part upon the multiple characteristics.
Claim 1: Claim 1: A method for analyzing biological samples, comprising: identifying an analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis, wherein the timeline comprises information that is temporally aligned with at least one of a workflow or a pipeline of the analysis of the biological samples; determining one or more region-of-interest types for the multiple regions of interest, wherein the one or more region-of-interest types comprise a target-based type correlated with at least one biological sample of the biological samples or a structure-based type correlated with the microfluidic device; determining multiple characteristics for the biological samples based at least in part upon the one or more region-of-interest types, wherein the multiple characteristics respectively correspond to an attribute, a property, or a quantifiable metric for the biological samples or the analyses; arranging and rendering associated data from the analysis that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples based at least in part upon the multiple characteristics and the timeline; and generating a bioinformatics pipeline view, generating the bioinformatics pipeline view comprising: determining a sequencing dataset for the biological samples in a plurality of chambers or the multiple regions of interest of the microfluidic device, wherein a biological sample comprises a sequence of nucleotides or amino acids
Claim 20: An article of manufacture comprising a non-transitory machine accessible storage medium storing thereupon a sequence of instructions which, when executed by a processor, causes the process to perform the method of claim 1.
Claim 72: A system, comprising: one or more processors; a memory coupled with the one or more processors, wherein the memory is configured to provide the one or more processors with instructions which when executed cause the one or more processors to: identify an analysis of biological samples in multiple regions of interest in a microfluidic device; identify filtered regions of interest by applying a filter to reduce the multiple regions of interest to include single biological sample regions of interest that each have single biological samples disposed within and not include multiple biological sample regions of interest that each include more than one biological samples disposed within; determine multiple characteristics for the single biological samples in the filtered regions of interest, wherein the multiple characteristics respectively correspond to an attribute, a property, or a quantifiable metric for the single biological samples; and arrange and render associated data from the analysis that respectively correspond to the filtered regions of interest in a user interface for at least a portion of the biological samples based at least in part upon the multiple characteristics.
Claim 1: Claim 1: A method for analyzing biological samples, comprising: identifying an analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis, wherein the timeline comprises information that is temporally aligned with at least one of a workflow or a pipeline of the analysis of the biological samples; determining one or more region-of-interest types for the multiple regions of interest, wherein the one or more region-of-interest types comprise a target-based type correlated with at least one biological sample of the biological samples or a structure-based type correlated with the microfluidic device; determining multiple characteristics for the biological samples based at least in part upon the one or more region-of-interest types, wherein the multiple characteristics respectively correspond to an attribute, a property, or a quantifiable metric for the biological samples or the analyses; arranging and rendering associated data from the analysis that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples based at least in part upon the multiple characteristics and the timeline; and generating a bioinformatics pipeline view, generating the bioinformatics pipeline view comprising: determining a sequencing dataset for the biological samples in a plurality of chambers or the multiple regions of interest of the microfluidic device, wherein a biological sample comprises a sequence of nucleotides or amino acids.
Claim 21: A system, comprising: a processor; a user interface coupled to the processor for processing a plurality of molecular-biological samples that comprise a first molecular-biological sample and a second molecular-biological sample in a first molecular-biological device; a non-transitory computer accessible storage medium storing thereupon a sequence of instructions which, when executed by a processor, causes the processor to perform any of the method of claim 1.
Conclusion
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/K.N.A./Examiner, Art Unit 1687
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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