DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
The present application was filed as a proper National Stage (371) entry of PCT Application PCT/EP2019/058206, filed 04/01/2019. Acknowledgement is also made of applicant’s claim for foreign priority under 35 U.S.C. 119(a)-(d) to Application No GB1805466.8, filed 04/03/2018 in the UK.
Status of the Claims
Claims 58, 60-75,78-84, and 86-91 are pending. Claims 1-57, 59, 76-77, and 85 are cancelled. Claim 58 is amended, claims 88-91 are new and claims 78-81 are withdrawn. Claims 58, 60-75, 82-84, and 86-91 are examined below.
Withdrawn Rejection
After consideration of the arguments the rejection of claims 58, 60-75,78-84, and 86-91 under 35 U.S.C. 103 has been withdrawn (see in detail below).
See new grounds of rejection below.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 58, 60-64, 66-69, 71-75, 83, 86-91 are rejected under U.S.C. 103 as being unpatentable over Kitamura et al. State-of-the-art fluorescence fluctuation-based spectroscopic techniques for the study of protein aggregation. International journal of molecular sciences. 2018 Mar 23;19(4):964, in view of Tiiman et al. Heterogeneity and turnover of intermediates during amyloid-β (Aβ) peptide aggregation studied by fluorescence correlation spectroscopy. Biochemistry. 2015 Dec 15;54(49):7203-11 (see PTO-892, 04/26/2023), Henriksen et al. The future of blood-based biomarkers for Alzheimer's disease. Alzheimer's & dementia. 2014 Jan 1;10(1):115-31, Griffin et al., Thioflavin T fluorescence in human serum: Correlations with vascular health and cardiovascular risk factors. Clinical biochemistry. 2010 Feb 1;43(3):278-86 and Wyss et al. Molecular and dimensional profiling of highly purified extracellular vesicles by fluorescence fluctuation spectroscopy. Analytical chemistry. 2014 Aug 5;86(15):7229-33 as evidenced by Rigler R. Fluorescence correlations, single molecule detection and large number screening applications in biotechnology. Journal of biotechnology. 1995 Jul 31;41(2-3):177-86 and Kask et al. Fluorescence-intensity distribution analysis and its application in biomolecular detection technology. Proceedings of the National Academy of Sciences. 1999 Nov 23;96(24):13756-61.
Regarding claims 58, 60-63, and 88-91, Kitamura teaches that Fluorescence Correlation Spectroscopy (FCS) enables the determination of the diffusion coefficient and the number of molecules of fluorescent molecules passing through a detection volume in solution (concentration). Kitamura further teaches that Fluorescence Correlation Spectroscopy is widely used to detect aggregation and oligomers of neurodegenerative disease-associated proteins (Kitamura, page 3, see entire paragraph ‘2.1. Fluorescence Correlation Spectroscopy’). Kitamura further teaches that highly sensitive photo-detectors are widely adopted for the detection of molecular diffusion with a single molecule sensitivity (individual aggregates; single molecule resolution) and that the detection volume enters the sub-fL range (observation volume element is 1 µL or less; Kitamura, page 4, see entire 1st paragraph and Figure 1). Kitamura further teaches that Amyloid β (Aβ) have been classically and traditionally analyzed using Fluorescence Correlation Spectroscopy (Kitamura, page 5, 2nd paragraph, line 1). Kitamura further teaches that Fluorescence Correlation Spectroscopy is highly sensitive to changes in the diffusion state of molecules and that the diffusion is reciprocal of the volume/size of the molecule of interest, and hence the size change through aggregation directly influences the diffusion of resulting aggregates allowing for determination of the aggregation and oligomeric states of misfolded proteins (size of individual aggregates; Kitamura, page 5, see entire 1st paragraph). Kitamura further teaches that to detect accumulation of non-fluorescent amyloids in vitro, fluorescent dyes that bind to amyloid structure, such as thioflavin T are generally used (Kitamura, page 2, ‘1.3. Amyloid Beta/β-Amyloid peptide (Aβ)’, lines 10-12). Kitamura further teaches that Fluorescence Correlation Spectroscopy can be used to determine mobile aggregation and oligomers in solution (Kitamura, page 11, ‘3. Conclusion’, lines 3-4). Kitamura further teaches an overview of Fluorescence Correlation Spectroscopy measurement and analysis comprising <I1> and <I2> representing the average fluorescence intensity of monomers and oligomers/soluble aggregates over time (time-resolved; amyloid aggregates; Kitamura, page 4, see Figure 1).
Even though Kitamura references Tiiman as an example that Aβ has been classically and traditionally been analyzed using FCS, Kitamura does not explicitly teach a method that does not comprise amplification of individual amyloidal compounds.
Kitamura is silent on the sample type and does not teach obtaining a sample of a bodily fluid from a subject.
Kitamura does not teach fluorescence intensity fluctuation analysis (FIFA) nor determining the frequency of single event occurrence by calculating the average number of occurrences per unit of time which is proportional to the concentration .
Tiiman teaches a method of detecting Aβ aggregation by Fluorescence Correlation Spectroscopy using Thioflavin T detection, which is a standard method for amyloid detection by fluorescence microscopy (Tiiman, page 7203, 2nd column, lines 1-11). Tiiman further teaches preparing fresh Aβ solutions and diluting to the final concentration using a buffer containing ThT for fluorescence measurements or Fluorescence Correlation Spectroscopy (method does not comprise amplification of individual amyloidal compounds; does not use non-target amyloid molecules or mixing target amyloid molecules and on-target amyloid molecules; Tiiman, page 7204, 2nd column, ‘Sample Preparation’, lines 3-7). Tiiman further teaches that the method using ThT as a fluorescent marker does not monitor Aβ monomers but rather amyloid aggregates rich in Aβ-structure (Tiiman, page 7208, 2nd column, 2nd paragraph, lines 1-3). Tiiman further teaches that ThT in micromolar concentrations does not significantly affect the kinetics of Aβ aggregation (Tiiman, page 7208, 2nd column, lines 13-15). Tiiman further teaches that in fluorescence correlation spectroscopy intensity fluctuations over time are typically analyzed by temporal autocorrelation analysis and that the decay time of the autocorrelation curve reflects the diffusion of the fluorescent molecule and hence its size (Tiiman, page 7204, lines 3-10).
Henriksen teaches that blood-based biomarkers of Alzheimer’s disease provide a cost- and time effective way to enhance the utility of cerebrospinal fluid and imaging biomarkers, such as the first step in a screening and diagnostic process for recruitment into clinical trials (bodily fluid, claim 58; blood, claim 60; Henriksen, page 3, see entire 43rd paragraph). Henriksen teaches that blood-based biomarkers are attractive because not all laboratories have access to sophisticated techniques such as MRI and/or PET scanners and even CSF sampling is more complex than blood sampling and standardized blood-based tests are helpful in an environment that is not as controlled as the setting of clinical studies (Henriksen, page 3, see entire 3rd paragraph). Henriksen teaches that established biomarkers of Alzheimer’s disease from cerebrospinal fluid and neuroimaging are highly accurate and that Amyloid β peptide 42, total tau protein, and hyperphosphorylated tau protein levels in cerebrospinal fluid are well-characterized biomarkers of Alzheimer’s disease and can serve as diagnostic markers with a substantial sensitivity and specificity, but that cerebrospinal fluid sampling at multiple time points to monitor treatment efficacy, disease onset, or risk is limited and might impact biomarker levels (Hendriksen, page 2, ‘Introduction’, 2nd paragraph, line 1-page 3, lines 2). Henriksen further teaches that a major issue in relation to serum detection of brain derived proteins is the blood brain barrier which restricts movement of large proteins, but cerebrospinal fluid is absorbed into blood every day and some exchange of peptides occurs and that furthermore some degree of loss of integrity of the blood brain barrier is seen in Alzheimer’s disease, potentially allowing the crossing of additional molecules into the blood and allowing detection in serum or plasma (serum, claims 61-63; Henriksen, page 5, see entire 4th paragraph). Put another way, Henriksen teaches advantages of blood-based (including plasma and serum) biomarker detection for the diagnosis or monitoring of Alzheimer’s disease, including biomarkers known to be of diagnostic value when measured in the cerebrospinal fluid such as Amyloid β peptide.
Griffin teaches that amyloid deposition is implicated in neurodegenerative diseases as well as atherosclerosis and further teaches that amyloid fibrils display a characteristic morphology, increased β-structure relative to the non-fibrillar form and the ability to interact with and alter the spectral properties of the dye thioflavin T (Griffin, page 278, ‘Introduction’, lines 1-6). Griffin further teaches measuring ThT fluorescence in sera from 35 healthy subjects and 70 high cardiovascular risk patients (Griffin, page 278, ‘Abstract’, ‘Design, Methods, and Results’, lines 1-2) and determining ThT fluorescence of serum using a plate-reader equipped with 444/485 nm excitation/emission filters (Griffin, page 279, ‘ThT fluorescence measurements’, lines 1-5).
Wyss teaches a method of detecting and characterization of extracellular vesicles by fluorescence correlation spectroscopy (Wyss, page 7229, 2nd paragraph, lines 20-21). Wyss further teaches that fluorescence correlation spectroscopy enables one to decipher biomolecular interaction, monitor molecular diffusions on/in the plasma membrane, and investigate photochemical properties of fluorescent probes by applying various models to fit the autocorrelation function. Wyss further teaches a model free analysis of the fluorescence fluctuations that circumvent the distortion of the autocorrelation function by highly fluorescent species in heterogeneous solution by systematically measuring both duration and amplitude of each individual fluorescent event within the recorded time trace using single fluctuation analysis (fluorescence intensity fluctuation analysis). Wyss further teaches that the benefit of the method is to provide in-depth distribution profiles of both size and membrane protein expression level (Wyss, page 7230, lines 4-18 and Figure 3 C). Wyss further teaches that the autocorrelation function biases size estimation in highly heterogeneous samples and that to circumvent this problem each translocation of individual labeled extracellular vesicles is systematically analyzed through the confocal detection volume of the microscope by single fluctuation analysis (Wyss, page 7230, 2nd column, lines 12-16). Wyss further teaches measuring the translational diffusion of analytes through a diffraction-limited observation volume which generates spikes in the recorded fluorescence time trace and from the fluorescence intensity fluctuations over time (Wyss, page 7230, 2nd column, 2nd paragraph, lines 2-8). Wyss further teaches recording a time trace that contains distinct fluorescent spikes of individual targets diffusion through the observation volume and then analyzing the time trace with an autocorrelation function and analyzing the spikes individually and extracting maximal fluorescence intensity and translocation time (Wyss, page 7231, see Figure 2 (B), (C) and (D), figure legend).
Kask teaches Fluorescence-Intensity distribution analysis in which the fluorescence intensity of a sample with a heterogeneous brightness profile is monitored permitting simultaneous determination of concentrations and specific brightness values of a number of individual fluorescent species in solution (Kask, page 13756, Abstract, lines 1-10). Kask further teaches that the method is appropriate for florescence correlation spectroscopy (Kask, page 13765, see 3rd paragraph). Kask further teaches that fluorescent species with different specific brightnesses can be distinguished by collecting a statistical distribution of the number of photon counts at time intervals of given length. The distribution of photon count numbers is used to determine concentrations of molecules of heterogeneous brightness in the sample (Kask, page 13765, see 2nd paragraph). As such Kask teaches determining the concentration using by determining single events per unit time. Kask further teaches that the overall distribution P(n) depends not only on the mean count rate but on both the concentration and the specific brightness and that the method can separate the contributions of individual species unambiguously (Kask, page 13758, lines 4-6). Kask further teaches that the method enables the study of single molecules, the concept is simple and the associated calculations can be performed rapidly in real time. The system is suitable for high-throughput screening of biologically relevant assays.
Kitamura is silent as to their detailed method of detection and as such is silent as to whether it involves amplification, however Kitamura references Tiiman’s method of detection and as such it would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have applied the method of Kitamura of detecting Aβ amyloids by fluorescence correlation spectroscopy in the manner as taught by Tiiman, comprising diluting Aβ in buffer comprising ThT (without amplification).
The ordinary skilled artisan would have a reasonable expectation of success using unseeded fluorescence correlation spectroscopy to detect amyloid β aggregates as taught by Kitamura with the method of Tiiman, because even though Kitamura does not specifically state that the method is unseeded, it does teach a method comprising Thioflavin T and Tiiman teaches success using an unseeded method of detecting Aβ amyloids comprising Thioflavin T as the detection agent.
It would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have applied the method of Kitamura in view of Tiiman, namely a method of detecting Aβ amyloids by fluorescence correlation spectroscopy, to detect Aβ amyloids in blood-based samples, including serum as the sample, as an obvious matter of a simple substitution of one art recognized sample over another. The prior art contained the base invention (see as taught by Kitamura in view of Tiiman, the prior art recognized a method of analyzing Amyloid β (Aβ) using Fluorescence Correlation Spectroscopy using dyes such as Thioflavin T in a sample. As such, it would have been obvious to apply fluorescence correlation spectroscopy to bodily fluid such as blood, as the ordinarily skilled artisan would appreciate that it is possible to detect cerebrospinal fluid derived biomarkers in blood and serum and that blood-based biomarkers of Alzheimer’s disease provide a cost- and time effective way to enhance the utility of cerebrospinal fluid and imaging biomarkers, as taught by Henriksen.
The results of the modification would have been predictable, namely in that fluorescence correlation spectroscopy would be expected to be able to detect Thioflavin T labeled amyloid aggregates in serum because, as taught by Tiiman, Fluorescence Correlation Spectroscopy using Thioflavin T detection is a standard method for amyloid detection and because of the teaching of Griffin of detecting amyloid fibers in serum using Thioflavin T.
Furthermore, the modification is also considered an obvious matter to try, namely considering there was a finite number of identified sample types for detecting amyloids, see Kitamura in view of Tiiman teaches detecting amyloid aggregates in buffer and Henriksen teaches detecting amyloids in blood-based samples. One having ordinary skill in the art would have recognized that applying the known method of fluorescence correlation spectroscopy of Kitamura in view of Tiiman in a blood-based sample as described by Henriksen, using Thioflavin T which has been shown to result in detectable measurements in serum (see Griffin), would have predictably resulted in the detection of amyloids in blood-based samples, such as serum, one would have had a reasonable expectation of success (considering Kitamura in view of Tiiman teaches detection of amyloids by fluorescence correlation spectroscopy and Griffin teaches success detecting amyloids in serum using Thioflavin T labeling).
It would have further been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Kitamura in view of Tiiman by applying the single fluctuation analysis method of Wyss to the data generated by fluorescence correlation spectrometry, as taught by the method of Kitamura in view of Tiiman, because of the teaching of Wyss that this method circumvents the problem of size bias by highly fluorescent species in heterologous samples.
It would have further been prime facie obvious to one having ordinary skill in the art before the effective filing date of claimed invention to have modified the method of Kitamura in view of Tiiman by applying the data analysis method of Kask because the analysis is simple and the associated calculations can be performed rapidly in real time and suitable for high-throughput screening of biologically relevant assays.
The ordinary artisan would further have a reasonable expectation of success applying the analysis methods of Wyss and Kask to the fluorescence correlation spectroscopy data of Kitamura, because Wyss uses data generated by fluorescence correlation spectroscopy within a recorded time trace (as taught by Kitamura) and analyzes it using a single fluctuation analysis method as taught by Wyss or fluorescence-intensity distribution analysis as taught by Kask (i.e., one having ordinary skill would expect success because the measurement remains the same, the difference is merely the type of data analysis).
Regarding the limitation of the number of individual amyloid aggregates present in the observation volume element (below 1000 for claim 58, below 500 for claim 88, below 100 for claim 89, below 50 for claim 90 and below 25 for claim 91), the limitation does not comprise an active method step and therefore also fails to clearly result in a manipulative difference that would distinguish the claim from the prior art. Further, Rigler provides evidence that introducing the extremely small volume elements resulted in substantial improvements in the sensitivity of fluorescence correlation spectroscopy (Rigler, page 177, 2nd column, lines 1-3) and that the method has in principle no lower concentration limit and allows working concentrations between 10-9 M and 10-15 M and that detecting down to 10-18 M (1 molecule per microliter) is realistic (Rigler, page 178,lines 7-14).
Regarding claim 64, Kitamura and the cited art above teaches a method of detecting the concentration and/or size of individual amyloid aggregates substantially as claimed.
Kitamura teaches that Fluorescence Correlation Spectroscopy is highly sensitive to changes in the diffusion state of molecules and that the diffusion is reciprocal of the volume/size of the molecule of interest, and hence the size change through aggregation directly influences the diffusion of resulting aggregates allowing for determination of the aggregation and oligomeric states of misfolded proteins (Kitamura, page 5, see entire 1st paragraph). As such Kitamura teaches determining the size profile of amyloid molecules/particles/aggregates in each sample.
Regarding claims 66 and 67, Kitamura and the cited art as applied to claim 58 also applies to claims 66 and 67.
Kitamura teaches that to detect accumulation of non-fluorescent amyloids in vitro, fluorescent dyes that bind to amyloid structure, such as thioflavin T are generally used (claim 67; Kitamura, page 2, ‘1.3. Amyloid Beta/β-Amyloid peptide (A β)’, lines 10-12). Tiiman teaches that the ThT assay is based on specific properties for the ThT molecule which upon binding to amyloid fibrils undergoes a bathochromic shift in absorbance maximum and therefore in the presence of amyloid fibrils displays a strong increase in fluorescence quantum yield and the appearance of a fluorescence emission band with a maximum at 480 nm (claim 66; Tiiman, page 7203, 2nd paragraph, lines 3-12).
Regarding claims 68 and 83, Kitamura and the cited art above teaches a method of detecting the concentration and/or size of individual amyloid aggregates substantially as claimed.
Kitamura teaches that Fluorescence Correlation Spectroscopy is widely used to detect aggregation and oligomers of neurodegenerative disease-associated proteins (Kitamura, page 3, see entire paragraph ‘2.1. Fluorescence Correlation Spectroscopy’). Kitamura further teaches that to detect accumulation of non-fluorescent amyloids in vitro, fluorescent dyes that bind to amyloid structure, such as thioflavin T are generally used (Kitamura, page 2, ‘1.3. Amyloid Beta/β-Amyloid peptide (A β)’, lines 10-12). As such Kitamura teaches the detection of amyloid oligomers.
Regarding claims 69, 86, and 87, Kitamura and the cited art above as applied to claim 58 also applies to claims 69, 86, and 87.
Tiiman teaches that the smallest aggregates consist of 50-70 Aβ monomers (peptides; Tiiman, page 7206, 2nd paragraph, lines 12-15). As such the prior art reads on the claimed range because the prior art range lies inside those ranges claimed, see for example 50-70 lies inside aggregates comprising 20 or more, because 50-70 equals more than 20 aggregates and no upper limit is recited in the claim (claim 69), about 30 or more; about 40 or more; about 50 or more; about 60 or more; about 70 or more; (claim 86) or about 40 or more, because 50-70 equals more than 40 aggregates and there is no upper limit recited (claim 87).
Regarding claim 71, Kitamura and the cited art above teaches a method of detecting the concentration and/or size of individual amyloid aggregates substantially as claimed.
Wyss teaches that single fluctuation analysis is able to estimate size of the target in highly heterogeneous samples (Wyss, page 7230, 2nd column, lines 12-16). Further, since the combination of Kitamura as modified by Tiiman teach the method substantially as claimed, i.e., detecting Aβ aggregates by FCS using a fluorescent reporter, rather than seeding peptides and amplification in CSF, one having ordinary skill would expect the method as taught by the prior art to also be able to detect individual amyloid aggregates comprising more than 1,000,000 proteins or peptides.
Regarding claim 72, Kitamura, and the cited art as applied to claim 58 also applies to claim 72.
Tiiman teaches monitoring changes in distribution of aggregate sizes, where over time the number of small aggregates decreases and larger and larger aggregates appear (Tiiman et al., page 7207, 2nd paragraph, lines 9-12). Tiiman further teaches that during the course of Aβ aggregation, there is a transition from coil-dominant structure to β-sheet dominant population at the end (Tiiman et al., page 7207, 6th paragraph, lines 2-6). Put another way, the prior art teaches the method substantially as claimed, comprising the detection of Aβ aggregates comprising those of a β-sheet structure, which is the dominant population at the end and therefore it would be obvious that one performing the method as taught by the combination of the prior art would necessarily detect Aβ aggregates that comprise one or more β-sheets.
Regarding claims 73-75, Kitamura and the cited art above teaches a method of detecting the concentration and/or size of individual amyloid aggregates substantially as claimed.
Kitamura teaches that Aβ is a collective term for peptides that play a crucial role in the Alzheimer’s disease (Kitamura, page 2, ‘1.3. Amyloid Beta/β-Amyloid Peptide (Aβ)’, lines 1-2.
Claim 65 is rejected under 35 U.S.C. 103 as being unpatentable over Kitamura et al., in view of Tiiman et al., Henriksen et al., Griffin et al. and Wyss et al. as applied to claim 61 above, and further in view of Burch et al. Fluorometric measurements of riboflavin and its natural derivatives in small quantities of blood serum and cells. Journal of Biological Chemistry. 1948 Aug 1;175(1):457-70 (IDS 06/10/2021) and Schwille et al. Molecular dynamics in living cells observed by fluorescence correlation spectroscopy with one-and two-photon excitation. Biophysical journal. 1999 Oct 1;77(4):2251-65 (PTO-892, 04/26/2023).
Regarding claim 65, Kitamura in view of Tiiman, and the cited art above teaches a method of detecting the concentration and/or size of individual amyloid aggregates substantially as claimed.
However, the cited art does not teach that the blood sample does not comprise one or more of the group of: FAD enzymes, FAD lipopigments, and/or NADH enzymes or lipopigments.
Burch et al. teaches that FAD is completely hydrolyzed in 5% trichloroacetic acid in 20h (Burch et al., page 458, ‘Principles of the Methods’, (3)) in serum before measuring fluorescence in a sample (Burch et al., page 459, ‘Procedure’, lines 1-12). Burch et al. further teaches that FAD autofluoresces (Burch et al, page 458, ‘Principles of the Methods’, (2)). Schwille et al. teaches that autofluorescence is often considered one of the major problems in FCS and that known intrinsic biological autofluorescent molecules include NADH and FAD (Schwille et al. page 2262, 2nd paragraph, lines 1-6) and that FCS within living cells is feasible if the signal is considerably higher than the autofluorescent background signal (Schwille et al., page 2263, 5th paragraph, lines 1-7).
It would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Kitamura and the cited art, namely the method detecting aggregated Aβ by FCS in a serum blood sample, by depleting the sample of NAD by applying the method of Burch et al., because of the teaching of Schwille et al., to deplete the sample of NAD because Schwille et al. teach that intrinsic biological autofluorescent molecules such as NADH and FAD are a major problem in FCS and that FCS is feasible if the signal is considerably high than the background. As such, one would be motivated to deplete NAD in order to eliminate any intrinsic, interfering autofluorescence, thereby improving the detection by FCS.
The ordinarily skilled artisan would have had a reasonable expectation of success in doing so because of the teaching of Burch et al. that NAD can be depleted in serum samples before measuring fluorescence and the teaching of Schwille et al. that by if the signal is considerably higher than the background (autofluorescence) the dynamics of molecules at nM concentrations can easily be investigated.
Claim 70 are rejected under 35 U.S.C. 103 as being unpatentable over Kitamura et al. in view of Tiiman et al., Henriksen et al., Griffin et al., and Wyss et al. as applied to claim 68 above, and further in view of Nichols et al. Biophysical comparison of soluble amyloid-β (1–42) protofibrils, oligomers, and protofilaments. Biochemistry. 2015 Apr 7;54(13):2193-204 (IDS, 06/10/2021).
Regarding claim 70, Kitamura and the cited art above teaches a method of detecting the concentration and/or size of individual amyloid aggregates in bodily fluid substantially as claimed, but fails to teach nano-aggregates comprising about 20 to 100 000 peptides.
The specification of the present invention recites amyloid nano-aggregates as aggregates that comprise higher numbers of peptides than dimers and trimers, but which have not yet formed amyloid fibrils or senile amyloid aggregates (Specification, page 9, lines 31-33 to page 10, lines 1-2).
Nichols teaches distinct oligomers (nano-aggregates) from 50-657 monomers (Nichols, page 2196, lines 10-13 and page 2195, 4th paragraph, lines 25-26) that are distinct from protofibrils (see Nichols et al., Abstract). Nichols further teaches assessing Aβ solutions by Thioflavin T Fluorescence (Nichols, page 2194, ‘Thioflavin T Fluorescence’, lines 1-2).
Tiiman teaches detection of Aβ aggregate sizes between 260 kDa (50-70 monomers), to 2.105 monomers by FCS, a range that comprises nano-aggregates of 50-100 000 monomers (Tiiman, page 7206, see 2nd-3rd paragraph). Tiiman further teaches using Thioflavin T to assay Aβ peptides (Tiiman, page 7203, ‘Abstract’, lines 12-13).
Kitamura teaches that amyloid fibrils are cytotoxic (Kitamura, page 2, ‘1.3. Amyloid Beta/β-Amyloid Peptide’, lines 5-6).
It would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention that, when detecting Aβ aggregates in bodily fluid by FCS as taught by Kitamura and the cited art above, one would necessarily also detect Aβ nano-aggregates of 20-100 000 monomers (peptides), because of the teaching of Tiiman et al. that aggregates the size of protofibrils (between 50-100 000 monomers) are detectable with this specific reagent, consistent with that which is claimed.
Further, the ordinarily skilled artisan would be motivated to detect aggregates of different sizes, because of the teaching of Kitamura that amyloid fibrils are cytotoxic.
Considering that the combination of the cited art is teaching the same method of detection using a fluorescent probe detection reagent for detecting the same type of target, one would reasonably expect, when performing the method as taught by the combination of the prior art, that one would necessarily detect aggregates within the claimed size (nano-aggregates having sizes 50 to 100 000 peptides, present in a subject’ sample, which falls within the claimed size range of 20-100000).
The artisan of ordinary skill would have a reasonable expectation of success, because Kitamura teaches that FCS without amplifying individual Aβ aggregates can detect Aβ aggregates of varying sized and the teaching of success of Griffin detecting amyloids in bodily fluids using Thioflavin T labeling.
Claim 82 is rejected under 35 U.S.C. 103 as being unpatentable Kitamura et al. in view of Tiiman et al., Henriksen et al., Griffin et al., and Wyss et al., as applied to claim 73 above, and further in view of Colby et al. Prion detection by an amyloid seeding assay. Proceedings of the National Academy of Sciences. 2007 Dec 26;104(52):20914-9. (PTO-892, 12/28/2023) and Concha-Marambio et al., Detection of prions in blood from patients with variant Creutzfeldt-Jakob disease. Science Translational Medicine. 2016 Dec 21;8(370), 7 pages (see PTO-892, 12/28/2023).
Regarding claim 82, Kitamura and the cited art above teaches a method substantially as claimed, for the detection of amyloid associated disease that is Alzheimer’s Disease.
Kitamura does not teach the detection of a prion disease that is Creutzfeldt-Jakob disease.
Colby teaches detecting prion proteins in brain samples from humans with sporadic Creutzfeldt-Jakob disease by an amyloid seeding assay (Colby, page 20914, abstract, lines 3-8). Colby further teaches using Thioflavin T (ThT) to monitor amyloid formation in solution (Colby, page 20914, 3rd paragraph, lines 1-2). Still further, Colby teaches that many prion strains are capable of seeding the polymerization of recPrP into amyloid (Colby, page 20914, 3rd paragraph, lines 11-12). Still further, Colby teaches that this method provides a sensitive rapid, and accurate means of detecting and characterizing prions (Colby, page 20918, 2nd column, lines 5-6).
Concha-Marambio teaches that there is no approved assay for sensitive, objective, and noninvasive diagnosis of vCJD, which is a major problem for public health, because the disease is transmitted iatrogenically from human to human and because asymptomatic carriers may far outnumber clinically affected individuals.
It would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Kitamura and the cited art above in order to detect a prion disease that specifically is Creutzfeldt-Jakob disease, because of the teaching of Concha-Marambio that the lack of an approved sensitive, objective, and noninvasive vCJD assay is a major problem for public health. As a result, it would have been obvious to use the method as taught by Kitamura and the cited art above to detect amyloid aggregates in bodily fluid without amplification, because labeling the aggregates without amplification increases the signal-to-noise ratio and the method allows detection of soluble aggregates at earlier timepoints than other measurements, thereby providing a sensitive, noninvasive assay.
The ordinary artisan would have a reasonable expectation of success, because Kitamura and the cited art above teaches detecting prions using ThT to label amyloid aggregates and Colby teaches labeling amyloid aggregates from people afflicted by prion disease, in particular Creutzfeldt-Jakob disease, using ThT. As such Colby teaches that amyloid aggregates in vCJD can be rendered detectable by labeling them with ThT, and therefore one would expect success because Kitamura and the cited art is teaching success labeling amyloid aggregates with ThT and Griffin teaches success detecting amyloids in bodily fluids using Thioflavin T labeling.
Claims 84 are rejected under 35 U.S.C. 103 as being unpatentable over Kitamura et al. in view of Tiiman et al., Henriksen et al., Griffin et al., and Wyss et al., as applied to claim 58 above, and further in view of Schrader et al., WO2011050864A1.
Regarding claim 84, Kitamura and the cited art above teach a method substantially as claimed.
Kitamura fails to teach a method wherein the FIFA comprises calculating the number of peaks which is larger than at least 5 standard deviations of a control sample.
Wyss teaches an automatic routine which identified a translocation event when the fluorescence signal rose above a user-defined threshold which corresponded to a multiple of standard deviation of the fluorescence baseline (control; Wyss, page 7230, 2nd column, line 16 – page 7231, line 3).
Schrader teaches a method relating to the field of protein misfolding and diseases which are associated with it such as Alzheimer’s disease (Schrader, ‘Abstract’, lines 1-3). Schrader further teaches that data evaluation involved determination of the number and height of peaks measure above a threshold given by 5 times the standard deviation of the fluorescence fluctuation (Schrader, page 81, lines 28-30). Schrader further teaches a method of treating Alzheimer’s disease with aminopyrazoles, which bind selectively to the backbone of misfolded peptides residing in the β-sheet confirmation. Schrader further teaches characterizing direct interaction of aminopyrazole derivatives with Aβ(1-42) by fluorescence correlation spectroscopy (Schrader, page 8, line 31-page 9, line 9). Schrader further teaches control samples with pure Aβ (Schrader, page 39, lines 16-18 and Figure 4A). Put another way, Schrader teaches measurements above 5 times the standard deviation in samples, which comprise control samples. As such, Schrader teaches calculating the number of peaks which is larger than at least 5 standard deviations of a control sample.
It would have been prima facie obvious to one of ordinary skill in the art before the claimed invention was effectively filed to have applied the known technique of Schrader of measuring the peaks above a threshold given by 5 times the standard deviation as an obvious matter of applying a known technique to a known method, since the prior art in view of Kitamura, Tiiman, Henriksen, Griffin, and Wyss recognizes the base method of using multiple standard deviations to establish a threshold in Fluorescence Correlation Spectroscopy (Wyss teaching a user-defined threshold) and Schrader teaches determining the number and height of peaks above a threshold of 5 times the standard deviation when analyzing data from samples comprising Aβ(1-42) aggregates. One of ordinary skill in the art would have recognized that applying the known technique of Schrader to the base method as taught by the prior art would have predictably yielded the result of being able to analyze the interaction molecules comprising Aβ(1-42) with each other.
Response to Arguments
Applicant’s arguments, see page 17, 3rd paragraph, filed 4/20/2026, with respect to Applicant’s arguments that the references do not disclose and would not have suggested determining frequency of single event occurrence by calculating the average number of single event occurrences per unit of time which is proportional to the concentration of individual amyloid aggregates and that that Kitamura, Tiiman, and Wyss relies on conventional fluorescence correlation spectroscopy approaches, in which concentration is derived from temporal autocorrelation of fluorescence intensity fluctuations which requires that the fluorescence signal be sufficiently continuous to yield meaningful concentration information. Applicant further argues that Wyss uses autocorrelation to determine concentration and applies single fluctuation analysis only to characterize properties of individual events related to size and does therefore not disclose determining concentration based on the frequency of discrete events have been fully considered and are persuasive.
The rejection of claims 58, 60-75,78-84, and 86-91 has been withdrawn.
See new rejection under 35 U.S.C. 103
The following arguments are not persuasive.
Applicant argues, starting on page 16 that claim 58 is directed to a method including using fluorescence correlation spectroscopy and fluorescence intensity fluctuation analysis to determine concentration and/or size of individual amyloid aggregates and has been amended to further required determining concentration via frequency of single event occurrence, size via temporal autocorrelation, a limitation reflecting the number of individual amyloid aggregates and exclusion of non-target amyloid species.
Applicant argues that the references do not disclose and would not have suggested the method of amended claim 58 and is further improper because it relies on hindsight reconstruction of fundamentally different experimental approaches.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
This argument is not persuasive.
Wyss does use individual spikes (single event occurrences) to calculate average concentration and teaches measuring both duration and amplitude of each individual fluorescent event within the recorded time trace using single fluctuation analysis (fluorescence intensity fluctuation analysis) and teaches that one benefit of the method is to provide membrane expression levels. Therefore applying the method not only to size but also expression levels.
Applicant further argues, starting on page 19, that the cited references do not disclose the analytical framework, which separates determination of concentration and size, determining concentration by single event frequency and size by a temporal autocorrelation curve. Applicant argues that Kitamura and Tiiman use a conventional fluorescence correlation spectroscopy approach in which both concentration and size are derived from temporal autocorrelation and Wyss discloses combining autocorrelation analysis with fluctuation-based burst analysis for characterizing particle properties and therefore neither suggests using fluctuation analysis for determining concentration while using autocorrelation solely for size determination.
This argument is not persuasive.
As explained previously in detail above, Wyss teaches using single fluctuation analysis to determine expression levels (of exosomal markers) therefore using the method to measure concentration and Tiiman teaches using a temporal autocorrelation curve to measure size. The observation that Tiiman also measures concentration does not teach away from using a temporal autocorrelation curve to measure size.
Applicant further argues that the cited references do not disclose that the individual amyloid aggregates present in the observation volume element is below about 1000.
This argument is not persuasive.
This limitation does not comprise an active method step and as such is not a feature of the method but rather the sample examined. A limitation describing the sample fails to clearly result in a manipulative difference that would patentably distinguish the claim from the prior art.
Applicant further argues, starting at the bottom of page 21, that non off the cited references disclose detection of target amyloid aggregates in bodily fluids without the use of non-target amyloid species. Applicant argues that Tiiman is directed to taction of artificially prepared amyloid beta peptides in buffer solutions and does not disclose detection of endogenous target amyloid aggregates in bodily fluids. Applicant argues that artificially prepared systems, such as the system described in Tiiman, represent non-target amyloid entities and do not reflect the conditions of the claimed method.
This argument is not persuasive.
Tiiman teaches a detecting a target which is an amyloid aggregate. There is no limitation in the claim nor recitation in the specification of such artificially prepared amyloids as ‘off-target’ amyloids or that they differ from endogenous amyloids in a way that is relative to their detection by fluorescence correlation spectroscopy. Further, the claims are not limited to endogenous amyloids.
Applicant further argues that the cited references do not provide a reasonable expectation of success and do not support the Office’s assertion that the claimed method would have been a predictable variation. Applicant argues that Henriksen review blood-based biomarkers for Alzheimer’s disease but does not teach that the detection of amyloid biomarkers in blood is straightforward but rather emphasizes the difficulty and unreliability of measuring such biomarkers in blood. Applicant further argues that Griffin discloses bulk fluorescence measurements in serum but does not disclose resolving individual amyloid aggregates or determine concentration via discrete event detection and therefore does not support the proposition that single-molecule, event-based detection of amyloid aggregates in bodily fluids would have been predictable. Applicant argues that in a sample with high, correlated background and sub-nanomolar concentrations of the investigated analyte, conventional temporal autocorrelation analysis such as described in the cited references cannot be applied as it would give information only about the correlated background rather than the sparse analyte that is to be characterized. Further, according to applicant, in a sample with high, correlated background and sub-nanomolar concentrations of the investigated analyte, the SFA described by Wyss similarly cannot give information about the concentration of the analyte and that Wyss does not disclose and would not have suggested how SFA can be used to determine the concentration of extracellular vesicles, nor does it demonstrate SFA in samples characterized by high, correlated background and sub-nanomolar analyte concentration.
This argument is not persuasive.
The combination of the art does teach the limitations of the claim. Griffin discloses detection of Thioflavin T in blood, Tiiman teaches analysis of fluorescence correlation spectroscopy by a temporal autocorrelation curve and Wyss teaches determination of a concentration using single events measured by fluorescence correlation spectroscopy. Therefore, the prior art teaches the limitations of the claims.
For all the reasons above, the arguments are not persuasive.
Communication
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/STEFANIE J. KIRWIN/Examiner, Art Unit 1677
/Soren Harward/Primary Examiner, TC 1600
