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`UNITED STATES PATENT AND TRADEMARK OFFICE
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`____________________________________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
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`____________________________________________
`
`FOUNDATION MEDICINE, INC.,
`Petitioner,
`v.
`
`GUARDANT HEALTH, INC.,
`Patent Owner.
`
`_____________________
`
`Case No. IPR2019-00634
`U.S. Patent No. 9,840,743
`_____________________
`
`DECLARATION OF DR. STACEY GABRIEL
`IN SUPPORT OF PETITIONER’S OPPOSITION TO
`PATENT OWNER’S MOTION TO AMEND
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`FOUNDATION EXHIBIT 1060
`IPR2019-00634
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`TABLE OF CONTENTS
`INTRODUCTION ........................................................................................... 1 
`I. 
`BACKGROUND AND QUALIFICATIONS ................................................. 1 
`II. 
`III.  MATERIALS REVIEWED AND CONSIDERED ........................................ 2 
`IV.  LEGAL PRINCIPLES ..................................................................................... 2 
`V. 
`EX1002 ............................................................................................................ 4 
`VI.  CLAIM CONSTRUCTION ............................................................................ 4 
`VII.  PRIOR ART ..................................................................................................... 6 
`A. 
`Rava (EX1055) ...................................................................................... 6 
`B. 
`Hyland (EX1061) ................................................................................ 10 
`VIII.  EXPLANATION OF GROUNDS FOR UNPATENTABILITY ................. 15 
`A.  Ground 1: Rava Anticipates Substitute Claims 27 and 37-41 ............ 15 
`1. 
`Substitute Claim 27 ........................................................ 15 
`2. 
`Substitute Claims 37-41 .................................................. 28 
`Ground 2: Substitute Claims 28-36 Are Obvious Over Rava ............. 29 
`1. 
`Substitute Claim 28 ........................................................ 30 
`2. 
`Substitute Claim 29 ........................................................ 31 
`3. 
`Substitute Claim 30 ........................................................ 32 
`4. 
`Substitute Claim 31-33 ................................................... 33 
`5. 
`Substitute Claim 34 ........................................................ 36 
`6. 
`Substitute Claim 35 ........................................................ 37 
`7. 
`Substitute Claim 36 ........................................................ 37 
`Ground 3: Substitute Claim 27 is Obvious in view of Hyland .......... 39 
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`C. 
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`B. 
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`Substitute Claim 27 ........................................................ 39 
`1. 
`Substitute Claims 37-41 .................................................. 47 
`2. 
`SUMMARY ........................................................................................ 48 
`D. 
`IX.  COMPENSATION; AVAILABILITY FOR CROSS-EXAMINATION ..... 48 
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`I, Stacey Gabriel, Ph.D., declare as follows.
`I.
`INTRODUCTION
`1.
`I have been retained as an expert in this proceeding by Petitioner
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`Foundation Medicine, Inc. (“Petitioner”). I previously submitted a declaration in
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`support of Petitioner’s Petition for Inter Partes Review of U.S. Patent No. 9,840,743
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`(“the '743 patent”) (EX1001). My prior declaration is filed as Exhibit 1002 in this
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`matter (IPR2019-00634).
`
`2.
`
`I have been informed and understand that Patent Owner has filed a
`
`Motion To Amend (“Motion”) the claims of the '743 patent with the United States
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`Patent and Trademark Office in this proceeding (IPR2019-00634).
`
`3.
`
`I have been informed and understand that Petitioner is filing an
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`Opposition to Patent Owner’s Motion to Amend (“Opposition”) in IPR2019-00634.
`
`4.
`
`I have been asked to review Substitute Claims 27-41 (“Substitute
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`Claims”) of the '743 patent presented in the Motion and the references identified in
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`the Opposition, and to evaluate whether the cited references alone or in combination
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`render the Substitute Claims unpatentable.
`
`II. BACKGROUND AND QUALIFICATIONS
`5. My background and qualifications are set out more fully in my prior
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`declaration (EX1002), and in my curriculum vitae (CV). EX1003.
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`III. MATERIALS REVIEWED AND CONSIDERED
`6. Materials I have reviewed in preparation of this Declaration are cited
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`herein. I have also relied upon my scientific knowledge and experience as of
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`September 4, 2012, which I have been informed and understand is when the earliest
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`application to which the '743 patent could claim priority was filed. I have been
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`instructed to use the “priority date” of September 4, 2012, for the purposes of my
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`analysis; I have, however, not been asked to opine and, thus, do not have an opinion,
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`on whether this priority date is proper.
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`IV. LEGAL PRINCIPLES
`7.
`I am not an attorney, but counsel has informed me about certain aspects
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`of the law that are relevant to my analyses and opinions. These aspects are described
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`below.
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`8.
`
`I have been informed that in order to render a patent claim unpatentable
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`as anticipated under 35 U.S.C. § 102(a)(1), it must be shown by a preponderance of
`
`the evidence that a prior art disclosure that was patented, described in a printed
`
`publication, or in public use, on sale or otherwise available to the public before the
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`priority date of the claimed invention discloses every element of a claim. I have been
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`informed that in order to render a patent claim unpatentable as anticipated under 35
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`U.S.C. § 102(a)(2), it must be shown by a preponderance of the evidence that a prior
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`art disclosure was described in a patent, or in an application for patent published or
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`deemed published, in which the patent or application, as the case may be, names
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`another inventor and was effectively filed before the effective filing date of the
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`claimed invention.
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`9.
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`I have been informed and understand that in order to invalidate a patent
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`claim as obvious in the context of an inter partes review, it must be shown by a
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`preponderance of the evidence that the claim would have been obvious to a person of
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`ordinary skill in the art as of the priority date.
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`10.
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`I have been informed and understand that factors relevant to the
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`determination of obviousness include the scope and content of the prior art, the level
`
`of ordinary skill in the art as of the priority date, differences between the claimed
`
`invention and the prior art, and, to the extent they exist, “secondary considerations”
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`or objective evidence of non-obviousness.
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`11.
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`I have been informed and understand that obviousness can be
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`established by combining or modifying the teachings of the prior art to produce the
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`claimed invention where there is some teaching, suggestion, or motivation to do so;
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`and that a reasonable expectation of success in achieving the subject matter of the
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`claim at issue must also be shown. Further, I have been informed and understand that
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`the teaching, suggestion, or motivation test is flexible and that an explicit suggestion
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`to combine the prior art is not necessary – the motivation to combine may be implicit
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`and may be found in the knowledge of one of ordinary skill in the art, from the nature
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`of the problem to be solved, market demand, or common sense.
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`12.
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`I have been informed that hindsight reasoning is not an appropriate basis
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`for combining references to form an obviousness combination.
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`13.
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`In undertaking an obviousness analysis, I have been informed and
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`understand that I may take into account the inferences and creative steps that a person
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`of ordinary skill would have employed in reviewing the prior art as of the priority
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`date. If the claimed invention combines elements known in the prior art and the
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`combination yields results that would have been predictable to a person of ordinary
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`skill as of the priority date, then this evidence would make it more likely that the
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`claim was obvious.
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`V. EX1002
`14. As mentioned above, I previously submitted a declaration, which I
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`understand is Exhibit 1002 in IPR2019-00634. In EX1002, I provided an overview
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`of technology relevant to the '743 patent. EX1002, ¶¶17-63. I also provided my
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`understanding of a person of ordinary skill in the art (“POSA”). Id., ¶¶64-66. For
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`this declaration, I have not repeated those positions, but instead incorporate those
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`positions by reference to EX1002 here.
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`VI. CLAIM CONSTRUCTION
`15.
`I understand that for purposes of the Opposition, additional claim
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`construction is not necessary. The meaning I have given to the terms of the Substitute
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`Claims addressed herein reflect the plain and ordinary meaning the terms would have
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`had to a POSA in light of the specification.
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`16.
`
` I previously set forth particular claim terms in my 2019 Declaration.
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`Id., ¶67. For convenience, I am setting forth the specific constructions I provided in
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`my 2019 Declaration below:
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`The term “barcode” refers to “a nucleotide or sequence of nucleotides used as
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`an identifier.”
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`The term “control” refers to “any object or system in an experiment that is
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`used as a standard of comparison.”
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`The term “fixed sequence” refers to “a sequence that is predetermined as
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`opposed to random.”
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`The term “mapping score” refers to “a metric used to indicate whether a
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`sequence read maps to a single location in the genome or multiple locations in the
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`genome.”
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`The term “mappable base position” refers to a position on the genome to
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`which sequence reads can confidently be mapped.
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`The term “normalization” refers to “methods of adjusting data that allow for
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`comparison of data from different sources.”
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`The term “processing a number of reads in the plurality of defined regions
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`with numbers obtained from a control sample” refers to comparing read counts or
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`normalized read counts from a test sample to read counts or normalized read counts
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`from a control sample.
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`The term “processing the ratio with a similarly derived number from a
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`reference sample” refers to “comparing a ratio derived from a test sample with a
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`ratio derived from a reference sample.”
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`The term “reference sample” refers to any sample that is similar to a test
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`sample and can readily be compared to the test sample.
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`The term “selective enrichment” refers to “selecting and/or enriching
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`particular portions of genomic regions of interest for analysis.”
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`The
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`term “wherein each barcode attached to the extracellular
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`polynucleotides or fragments therefor prior to sequencing is not unique” means
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`that “that the number of barcodes is fewer than the number of polynucleotides.”
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`VII. PRIOR ART
`17. Below, I address the specific prior art references that, in my opinion,
`
`anticipate certain Substitute Claims and/or render the Substitute Claims obvious.
`
`A. Rava (EX1055)
`18. U.S. Patent No. 9,323,888 (“Rava”) is entitled “Detecting and
`
`Classifying Copy Number Variation.” EX1055. From the first page of Rava, I
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`understand that Rava was filed as U.S. Patent Application No. 13/600,043 on August
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`30, 2012. Id., Page 1. I have been informed that Rava is therefore prior art to the
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`'743 patent pursuant to 35 U.S.C. §102(a)(2).
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`19.
`
`In its Background section, Rava describes:
`
`One of the critical endeavors in human medical research is the discovery
`of genetic abnormalities that produce adverse health consequences. In
`many cases, specific genes and/or critical diagnostic markers have been
`identified in portions of the genome that are present at abnormal copy
`numbers. For example, in prenatal diagnosis, extra or missing copies of
`whole chromosomes are frequently occurring genetic lesions. In cancer,
`deletion or multiplication of copies of whole chromosomes or
`chromosomal segments, and higher level amplifications of specific
`regions of the genome, are common occurrences.
`
`Id., 1:54-64.
`
`20. Rava describes that conventional procedures for detecting genetic
`
`abnormalities, and in particular CNVs, have presented challenges. Id., 1:65-2:22.
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`Rava explains, for example, that:
`
`the limitations of the existing methods, which include insufficient
`sensitivity stemming from the limited levels of cfDNA, and the
`sequencing bias of the technology stemming from the inherent nature of
`genomic information, underlie the continuing need for noninvasive
`methods that would provide any or all of the specificity, sensitivity, and
`applicability, to reliably diagnose copy number changes in a variety of
`clinical settings.
`
`Id., 2:14-22.
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`21. To address the limitations associated with prior techniques, Rava
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`discloses “a method for determining copy number variations (CNV) of a sequence of
`
`interest in a test sample that comprises a mixture of nucleic acids that are known or
`
`are suspected to differ in the amount of one or more sequence of interest.” EX1055,
`
`Abstract, 2:31-35. Rava states that its methods “fulfill some of the above needs and
`
`in particular offer[ ] an advantage in providing a reliable method that is applicable at
`
`least to the practice of noninvasive prenatal diagnostics, and to the diagnosis and
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`monitoring of metastatic progression in cancer patients.” Id., 2:23-27. Specifically,
`
`Rava discloses its “method is applicable to determining CNV of any fetal aneuploidy,
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`and CNVs known or suspected to be associated with a variety of medical conditions.”
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`Id., 2:38-48. For example, Rava describes that copy number variants (“CNVs”) that
`
`can be determined include “trisomies and monosomies of any one or more of
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`chromosomes 1-22, X and Y, other chromosomal polysomies, and deletions and/or
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`duplications of segments of any one or more of the chromosomes.” Id. Rava teaches
`
`that such “[s]equences of interest include genomic segment sequences ranging from,
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`e.g., kilobases (kb) to megabases (Mb) to entire chromosomes that are known or are
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`suspected to be associated with a genetic or a disease condition.” Id., 27:65-28:1.
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`22. Because Rava is interested in providing a reliable method that is
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`applicable at least to the practice of noninvasive prenatal diagnostics, and to the
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`diagnosis and monitoring of metastatic progression in cancer patients, Rava describes
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`analyzing cell-free nucleic acid molecules in test samples, such as “maternal
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`sample[s],” which include “a mixture of fetal and maternal cell-free DNA
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`molecules,” and fluid samples from cancer patients, which a POSA would have
`
`understood includes a mixture of DNA molecules from the tumor and the normal
`
`genome of an individual. EX1055, 2:23-27, 9:8-10, 10:35-43.
`
`23. Rava’s methods “may employ next generation sequencing technology
`
`(NGS)” to obtain quantitative information, such as where “each sequence read is a
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`countable “sequence tag” representing an individual clonal DNA template or a single
`
`DNA molecule.” Id., 38:62-64, 39:2-5 (emphasis added). Rava uses generated
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`sequencing data in a series of steps, including, for example, to perform the following:
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`align the reads to portions of a reference sequence/genome and
`determine the amount of DNA (e.g., the number of reads) that map to
`defined portions [of] the reference sequence (e.g., to defined
`chromosomes or chromosome segments); calculate a dose of one or
`more of the defined portions by normalizing the amount of DNA
`mapping to the defined portions with an amount of DNA mapping to
`one or more normalizing chromosomes or chromosome segments
`selected for the defined portion; determining whether the dose indicates
`that the defined portion is “affected[.]”
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`Id., 32-33.
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`B. Hyland (EX1061)
`24. U.S. Patent Application Publication No. 2012/0046877 (“Hyland”) is
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`entitled “Systems and Methods to Detect Copy Number Variation.” EX1061. From
`
`the first page of Hyland, I understand that Hyland was published on February 23,
`
`2012. Id., Page 1. I have been informed that Hyland is therefore prior art to the '743
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`patent pursuant to 35 U.S.C. §102(a)(1).
`
`25. Hyland “relates to the field of nucleic acid sequencing including systems
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`and methods for identifying genomic variants using nucleic acid sequencing data.”
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`Id., [0002]. As Hyland explains, amongst genomic variants, CNVs were “[o]f
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`particular interest” in the field, having been “observed in mammalian germline DNA
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`and in tumor genomes.” Id., [0006]. Hyland observes that “CNVs are being
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`increasingly implicated as contributing factors in common disease states (for
`
`example, mental retardation and schizophrenia) and in cancer progression,” and the
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`significance of CNVs could not be overlooked because “[i]n humans, more total
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`nucleotides exhibit variation due to alterations in copy number than due to single
`
`nucleotide diversity.” Id., [0006].
`
`26. To address the need in the field for technologies capable of detecting
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`CNVs, Hyland provides “[s]ystems, methods, software and computer-usable media
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`for copy number variation determination from analyzing biomolecule-related
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`sequence reads.” EX1061, Title, [0007]. Hyland recognizes that sequencing and
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`mapping technology had been developed. See, e.g., id., [0003]-[0005]. Hyland,
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`therefore, seeks methods to improve data analyses utilizing mapped sequence reads
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`in order to detecting CNVs. Id., [0006]-[0009]. Hyland’s methods are best
`
`understood by looking at a combination of Figs. 3 and 5, or Figs. 3 and 7.
`
`27. Fig. 3 of Hyland shows a sequencing analysis pipeline and is reproduced
`
`below. Id., [0018]. In particular, Fig. 3 of Hyland shows method steps, including (a)
`
`sequencing polynucleotides to generate sequence reads, (b) mapping the sequence
`
`reads to a reference genome, (c) quantifying the sequence reads in a plurality of
`
`windows, and (d) performing data analysis to detect copy number variations. See
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`below.
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`28. Figs. 5 and 7 of Hyland show exemplary flowcharts for methods of
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`identifying CNVs, and provide the details of the steps of quantifying the sequence
`
`reads in a plurality of windows, and performing data analysis to detect copy number
`
`variations, shown in Fig. 3. Id., [0020], [0023]. Fig. 5, reproduced below, shows an
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`exemplary flowchart for methods of identifying CNVs using a single sample
`
`approach. Id., [0020]. See below.
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`Following quantification of the sequence reads in a plurality of windows, Fig. 5
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`shows an exemplary method of Hyland includes (a) “normaliz[ing] the nucleic acid
`
`sequence read coverage determined for each window region to correct bias,” (b)
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`“convert[ing] the normalized nucleic acid sequence read coverage for each window
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`region to discrete copy number states,” and (c) “utiliz[ing] the discrete copy number
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`states of each window region to identify copy number variation in the chromosomal
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`regions.” See above. Taking Figs. 3 and 5 together, Hyland illustrates an exemplary
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`method of detecting CNVs in a single sample. See also EX1061, [0061]-[0100].
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`29. Fig. 7, reproduced below, shows an exemplary flowchart for methods of
`
`identifying CNVs using a paired sample approach. Id., [0020]. See below.
`
`
`Following quantification of the sequence reads in a plurality of windows, Fig. 7
`
`shows an exemplary method of Hyland includes (a) “determin[ing] nucleic acid
`
`sequence read coverage ratios for each window region of the test sample by dividing
`
`the read coverage of each window region of the test sample with the read coverage
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`of corresponding window region of the control sample,” (b) “normaliz[ing] nucleic
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`acid sequence read coverage ratios for each window region of the test sample,” (c)
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`“convert[ing] the normalized nucleic acid sequence read coverage ratios for each
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`window region of the test sample to discrete copy number states,” (d) utiliz[ing] the
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`discrete copy number states of each window region of the test sample to identify copy
`
`number variation in the chromosomal regions of the test sample.” Together, Figs. 3
`
`and 7 illustrate an exemplary method of Hyland for detecting CNVs in a paired
`
`sample. See also id., [0101]-[0114].
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`VIII. EXPLANATION OF GROUNDS FOR UNPATENTABILITY
`A. Ground 1: Rava Anticipates Substitute Claims 27 and 37-41
`1.
`Substitute Claim 27
`
`30. As discussed above, Rava describes methods “for determining copy
`
`number variations (CNV) of a sequence of interest in a test sample that comprises a
`
`mixture of nucleic acids that are known or are suspected to differ in the amount of
`
`one or more sequence [sic] of interest.” EX1055, 2:31-35. Throughout its disclosure,
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`Rava provides methods including the features recited in Substitute Claims 27 and 37-
`
`41, as set forth in detail below. In my view, Example 20 of Rava is particularly
`
`relevant to the Substitute Claims, as Example 20 discloses a method including each
`
`and every limitation of Substitute Claims 27 and 37-41. Therefore, in my opinion,
`
`Rava anticipates Substitute Claims 27 and 37-41. For ease of reference, Substitute
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`Claim 27 is reproduced below in its entirety:
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`27. A method for detecting sub-chromosomal copy number
`variation, comprising:
`a) sequencing extracellular polynucleotides from a bodily sample
`from a subject, wherein each of the extracellular polynucleotides
`generates a plurality of sequence reads;
`b) filtering out reads that fail to meet a set accuracy, quality score,
`or mapping score threshold;
`c) mapping the plurality of sequence reads to a reference
`sequence;
`d) quantifying mapped reads or unique sequence reads in a
`plurality of predefined regions of the reference sequence; and
`e) determining sub-chromosomal copy number variation in one or
`more of the plurality of predefined regions by:
`i) normalizing a number of reads in the plurality of
`predefined regions to each other, or a number of unique sequence
`reads in the plurality of predefined regions to each other; and/or
`ii) processing a number of reads in the plurality of
`predefined regions or a number of unique sequence reads in the
`plurality of predefined regions with numbers obtained from a
`control sample,
`wherein each of the predefined regions is up to 100 kb.
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`A method for detecting copy number variation, comprising:
`31. Rava is entitled, “Detecting and Classifying Copy Number Variation.”
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`As such, it is evident from the very beginning of Rava that it is directed to methods
`
`of detecting and classifying (CNV). See, e.g., EX1055, Title; see also id., Abstract,
`
`2:31-35, 27:60-64. Rava discloses its methods can detect CNVs that are
`
`subchromosomal. For example, Rava states that CNVs that can be determined
`
`include e.g., “deletions and/or duplications of segments of any one or more of the
`
`chromosomes.” Id., 2:31-48 (emphasis added); see also id., 220:63-65 (“In order to
`
`detect any sub-chromosomal differences, … .”). Rava also teaches that “[s]equences
`
`of interest include genomic segment sequences ranging from, e.g., kilobases (kb) to
`
`megabases (Mb) to entire chromosomes that are known or are suspected to be
`
`associated with a genetic or a disease condition.” Id., 27:65-28:5. This indicates that
`
`Rava’s methods can be used to detect sub-chromosomal CNVs, and also that Rava’s
`
`methods are applicable to CNVs associated with diseases, such as cancer.
`
`32.
`
`In Example 20, Rava discloses a method of noninvasively detecting fetal
`
`sub-chromosomal abnormalities (id., 218:45-47). The method includes, for example,
`
`sub-chromosomal CNVs in Chromosomes 6 (sub-chromosomal duplication) (id.,
`
`222:65-223:24) and Chromosome 7 (sub-chromosomal deletion) (id., 222:5-24),
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`using deep sequencing of maternal plasma. See also id., 218:43-224:47.
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`33.
`
`In view of the above disclosures, it is my opinion that Rava discloses a
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`method for detecting sub-chromosomal CNV.
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`(a) sequencing extracellular polynucleotides from a bodily
`sample from a subject, wherein each of the extracellular
`polynucleotides generates a plurality of sequence reads;
`34. Rava describes sequencing extracellular polynucleotides throughout its
`
`disclosure. In fact, Rava starts out by describing in its background that “[t]he advent
`
`of technologies that allow for sequencing entire genomes in relatively short time,”
`
`e.g., NGS, and “the discovery of circulating cell-free DNA (cfDNA) have provided
`
`the opportunity to compare genetic material originating from one chromosome to be
`
`compared to that of another without the risks associated with invasive sampling
`
`methods.” EX1055, 2:9-14. Rava discloses that its methods utilize this opportunity
`
`and leverage sequencing technologies as a part of “a reliable method that is applicable
`
`at least to the practice of noninvasive prenatal diagnostics, and to the diagnosis and
`
`monitoring of metastatic progression in cancer patients.” Id., 2:23-27.
`
`35. For example, Rava discloses that “[t]he methods and apparatus
`
`described herein may employ next generation sequencing technology (NGS), which
`
`is massively parallel sequencing.” Id., 32:32-35; 38:62-64. The sequencing
`
`performed by Rava provides multiple sequence reads, wherein “each sequence read
`
`is a countable “sequence tag” representing an individual clonal DNA template or a
`
`single DNA molecule.” Id., 39:3-5.
`
`36.
`
`In my opinion, a POSA would have known that each of the extracellular
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`polynucleotides sequenced in a method of Rava generates a plurality of sequence
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`reads. Rava refers to a process commonly known as deduplication, which removes
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`PCR duplicates. PCR duplicates obstruct an accurate count of DNA or RNA
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`molecules, they can bias many types of NGS experiments. For instance, Rava
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`discloses filtering out sequence reads when multiple sequence reads uniquely map to
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`the same “start and end coordinates,” i.e., when multiple sequence reads are
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`duplicates (not unique sequence reads). See, e.g., id., 166:60-64, 174:45-46.
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`Duplicates can arise in circumstances when the same DNA fragment is amplified and
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`sequence multiple times.
`
`37. Rava discloses that the polynucleotides sequenced in its method can be
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`cell free (i.e., extracellular). In fact, Rava states that its “samples contain nucleic
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`acids that are that are present in cells and/or nucleic acids that are “cell-free.”
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`EX1055, 53:57-59 (emphasis added); see also id., 19:17-20 (“In certain embodiments
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`the sequencing comprises sequencing cell free DNA from the test sample to provide
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`the sequence information.”); 10:44-11:14, 11:27-33, 12:10-14, 39:22-23 Rava
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`specifically discloses that:
`
`In any one of the embodiments, the test sample is may be plasma sample.
`The nucleic acid molecules of the maternal sample are a mixture of fetal
`and maternal cell-free DNA molecules. Sequencing of the nucleic acids
`can be performed using next generation sequencing (NGS).
`
`Id., 9:7-12 (emphasis added).
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`38.
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`In Example 20, Rava specifically discloses that maternal plasma
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`samples in the “MatErnal BLood IS Source to Accurately Diagnose Fetal Aneuploidy
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`(“MELISSA”)” study library, were sequenced using TruSeq v3 chemistry on an
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`Illumina HiSeq 2000 with single-end reads of 25 bp. It is my opinion that a POSA
`
`would have known that maternal plasma samples include cell-free DNA. Id., 9:7-10
`
`(“In any one of the embodiments, the test sample is may be plasma sample. The
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`nucleic acid molecules of the maternal sample are a mixture of fetal and maternal
`
`cell-free DNA molecules.”). In Example 20, each of the 11 maternal samples was
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`sequenced “utilizing an entire flow cell, resulting in 600x106 to 1.3x109 sequence
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`[reads] per sample.” Id., 219:34-44.
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`39.
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`In view of the above, it is my opinion that Rava discloses sequencing
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`extracellular polynucleotides from a bodily sample from a subject, where each of the
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`extracellular polynucleotides generates a plurality of sequence reads, as recited in
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`Substitute Claim 27, step a).
`
`(b) filtering out reads that fail to meet a set accuracy, quality
`score or mapping score threshold;
`40. Rava discloses “determining whether to include the read under
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`consideration in the number of sequence tags for a chromosome of interest or a
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`chromosome segment of interest.” EX1055, 11:15-26. Rava broadly describes that
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`“[v]arious criteria may be set for choosing when to disregard an identical tag from a
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`single sample.” Id., 51:29-50. Among the criteria for filtering reads that Rava
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`describes is a mapping score. Id., 33:36-51; see also id., 34:5-20, 50:58-62.
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`41.
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`In the context of Example 20, Rava specifically describes that only reads
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`with “up to two base mismatches during alignment” were allowed to be used in the
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`read count analysis. Id., 220:33-36. Moreover, “[o]nly reads that unambiguously
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`mapped to a single genomic location were included.” Id., 220:36-39. This step is,
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`therefore, filtering out read that meet a mapping score threshold, i.e., “a metric used
`
`to indicate whether a sequence read maps to a single location in the genome or
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`multiple locations in the genome.” See above Section VI.
`
`42.
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`In view of the above, it is my opinion that Rava discloses excluding
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`reads based on a mapping score threshold, and thus that Rava discloses filtering out
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`reads that fail to meet a set accuracy, quality score, or mapping score threshold, as
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`recited in Substitute Claim 27, step b).
`
`(c) mapping the plurality of sequence reads to a reference
`sequence;
`43. Rava discloses “aligning the sequence reads to one or more chromosome
`
`reference sequences using a computing apparatus and thereby providing sequence
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`tags corresponding to the sequence reads.” EX1055, 10:44-11:14; see also id., 12:5-
`
`34, 16:44-20:14, 39:17-36. Rava describes its aligning step as:
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`the process of comparing a read or tag to a reference sequence and
`thereby determining whether the reference sequence contains the read
`sequence. If the reference sequence contains the read, the read may be
`mapped to the reference sequence or, in certain embodiments, to a
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`particular location in the reference sequence.
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`Id., 33:52-34:4.
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`44. Example 20 describes the mapping step. Example 20 states that
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`“[s]equence reads were aligned to the human genome assembly hg19 obtained from
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`the UCSC database [ ].” Id., 220:31-43.
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`45.
`
`In view of the above, in my opinion, Rava discloses “mapping the
`
`plurality of sequence reads to a reference sequence,” as recited in Substitute Claim
`
`27, step c).
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`(d) quantifying mapped reads or unique sequence reads in a
`plurality of predefined regions of the reference sequence;
`46. Rava discloses quantifying (e.g., counting) mapped reads, e.g.,
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`“determin[ing] the amount of DNA (e.g., the number of reads) that map to defined
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`portions the reference sequence (e.g., to defined chromosomes or chromosome
`
`segments).” EX1055, 39:17-36.
`
`47. Rava also discloses that the reads it is quantifying are “unique sequence
`
`reads.” As set forth in my prior declaration, it is my opinion that a POSA would have
`
`understood that “unique sequence reads” are “sequence reads that can be mapped to
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`just one location.” See, e.g., EX1002, ¶84. Therefore, it is possible to determine a
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`particular extracellular polynucleotide to which a unique sequence read corresponds.
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`Id., ¶124. Rava discloses that the mapped sequence reads that are quantified can be
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`unique sequence reads:
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`The software reads the sequence data generated from the above
`procedure that uniquely aligned to the genome from Bowtie output
`(bowtieout.txt files). Sequence alignments with