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 .
Claim Status
Claims 1-18 are currently pending and under exam herein.
Priority
The instant Application claims the benefit of priority to US Provisional Application 63/126,199, filed 16 December 2020. Priority for each of claims 1-18 is acknowledged.
Information Disclosure Statement
The Information Disclosure Statement filed 15 December 2023 is in compliance with the provisions of 37 CFR 1.97 and has therefore been considered. A signed copy of the IDS is included with this Office Action.
Drawings
The Drawings filed 16 December 2021 are accepted. It is noted that the Petition to Accept Color Drawings under 37 CFR 1.84(a)(2) has been granted and a separate communication indicating such was mailed on 18 February 2022.
Specification
Note: All references to the Specification herein pertain to the PG publication: US20220183621.
Claim Objections
Claim 5 is objected to because of the following informalities: Claim 5 includes a period after claim step letters “a” and “b”, which is not the proper format. Periods may not be used elsewhere in the claims except for abbreviations. See Fressola v. Manbeck, 36 USPQ2d 1211 (D.D.C. 1995). Appropriate correction is required.
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 5-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The instant rejection reflects the framework as outlined in the MPEP at 2106.04:
Framework with which to Evaluate Subject Matter Eligibility:
(1) Are the claims directed to a process, machine, manufacture or composition of matter;
(2A) Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
(2B) If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Claim Interpretation
Under the broadest reasonable interpretation (BRI), the claims are presumed to have their plain meaning consistent with the Specification as it would be interpreted by one of ordinary skill in the art (MPEP 2111).
Claim 5:
Step (a) includes providing to a computing device the multi-modal biomarker comprising at least one of a structural MRI-based parameter from a brain of the patient and a functional MRI-based parameter from the brain of the patient, wherein said step includes providing data via a computer, wherein said computer is generically recited and under the BRI includes any generic computer that performs computing functions. As such, the step is one of receiving data (input).
Step (b) recites transforming, using the computing device, the multi-modal biomarker into the estimated pain level using a machine learning model, wherein said step recites the operation of “transforming” using a machine learning model. The Specification further elucidates that the transformation, for example, may be performed using graph theory mathematics [0081].
Thus, based on the plain meaning of claim 5 under the BRI, said claim is directed to getting input data and performing graph theory mathematics using machine learning.
Claim 6 further includes the specific machine learning model as a SVM.
Claim 7 includes that the particular data include cortical and sub-cortical thickness and a parameter from fMRI.
Claim 8 defines the matrix parameters.
Claim 9 include the biomarker data inputs.
Claim 10 includes the type of score for the “estimated” level of pain.
Claim 11 provides a training step by using a training set of data.
Claims 12-18 are the analogous system claims to 5-11 recited above and are interpreted in the same manner, including that the recited “system” herein is generically recited and is, under the BRI, interpreted as any generic computing system.
Framework Analysis as Pertains to the Instant Claims:
Step 1 Analysis: Are claims directed to process, machine, manufacture/composition of matter
With respect to step (1): yes, the claims are directed to a method and system of estimating a pain level based on a multi-modal biomarker.
Step 2A, Prong 1 Analysis: Do claims recite abstract idea
With respect to step (2A)(1), the claims recite abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
mathematical concepts, (mathematical formulas or equations, mathematical relationships and mathematical calculations);
certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
With respect to the instant claims, under the (2A)(1) evaluation, the claims are found herein to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information).
The claim steps to abstract ideas are as follows:
Claims 5 and 12 are directed to transform the multi-model biomarker into the estimated pain level, which under the BRI of the claim when read in light of the Specification includes “transforming” that encompasses operations of “estimating” that can be performed by the human mind, save for the recitation of “using a machine learning model”. The “model” is not particularly defined nor is the “use” of said model and therefore, any model may be utilized as a tool by which to aid in said transformation to provide a “level” (indicator; score; index etc…)
The dependent claims include steps directed to the particular data for input into a model. Hence, the claims explicitly recite numerous elements that, individually and in combination, constitute abstract ideas.
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined herein to each cover performance either in the mind (calculations by hand or pen and paper). There are no specifics as to the methodology involved in transforming for estimations and thus, under the BRI, one could simply, for example, perform said operation with pen and paper, or, alternatively with the aid of a generic computer as a tool to perform said calculations. These recitations are similar to the concepts of collecting information, analyzing it and providing certain results from the collection and analysis (Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations (Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in (Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind with pen and paper, and can include mathematical concepts.
Further, see MPEP § 2106.04(a)(2), subsection III. The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation (see, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674: noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016): holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper"). Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind" (see Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016): holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
Step 2A, Prong 2 Analysis: Integration to a Practical Application
Because the claims do recite judicial exceptions, direction under (2A)(2) provides that the claims must be examined further to determine whether they integrate the abstract ideas into a practical application (MPEP 2106.04(d). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim is said to fail to integrate the abstract idea into a practical application (MPEP 2106.04(d).III).
With respect to the instant recitations, the claims recite the following additional elements:
Claims 5 and 12 recite the step of “computer” implementation and “systems” and further include the step of providing the multi-model biomarker to the computer.
Dependent claims further limit additional elements in the claims by further defining data (claims 7 and 14; 9 and 16; 11 and 18).
Further with respect to the additional elements in the instant claims, those steps directed to data gathering perform functions of collecting the data needed to carry out the abstract idea. Data gathering does not impose any meaningful limitation on the abstract idea, or on how the abstract idea is performed. Data gathering steps are not sufficient to integrate an abstract idea into a practical application. (MPEP 2106.05(g).
Further steps herein directed to additional non-abstract elements of “processor; computer; storage medium etc…” do not describe any specific computational steps by which the “computer parts” perform or carry out the abstract idea, nor do they provide any details of how specific structures of the computer, such as the computer-readable recording media, are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the abstract idea. Hence, these are mere instructions to apply the abstract idea using a computer, and therefore the claim does not integrate that abstract idea into a practical application. The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc… are recited so generically (i.e., no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer, and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer. (see MPEP 2106.05(f)).
Step 2B Analysis: Do Claims Provide an Inventive Concept
The claims are lastly evaluated using the (2B) analysis, wherein it is determined that because the claims recite abstract ideas, and do not integrate that abstract ideas into a practical application, the claims also lack a specific inventive concept. Applicant is reminded that the judicial exception alone cannot provide the inventive concept or the practical application and that the identification of whether the additional elements amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they provide significantly more than the judicial exception. (MPEP 2106.05.A i-vi).
With respect to the instant claims, the additional elements of data gathering described above do not rise to the level of significantly more than the judicial exception. As directed in the Berkheimer memorandum of 19 April 2018 and set forth in the MPEP, determinations of whether or not additional elements (or a combination of additional elements) may provide significantly more and/or an inventive concept rests in whether or not the additional elements (or combination of elements) represents well-understood, routine, conventional activity. Said assessment is made by a factual determination stemming from a conclusion that an element (or combination of elements) is widely prevalent or in common use in the relevant industry, which is determined by either a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the “data” input into the generically recited computing elements, said data does not change the operation of the computer herein and as such, is merely “input”, which is a generic computing operation. The additional elements are set forth at such a high level of generality that they can be met by a general purpose computer. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than an abstract idea (see MPEP 2106.05(b)I-III). In contract to, for example, DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258-59, 113 USPQ2d 1097, 1106-07 (Fed. Cir. 2014), wherein said claims were found to include improvements to the actual functioning of the computer that included modifications to a conventional Internet hyperlink protocol, the instant claims do not include the same. As such, said steps of providing data (data gathering) are not considered significantly more herein.
The dependent claims have been analyzed with respect to step 2B and none of these claims provide a specific inventive concept, as they all fail to rise to the level of significantly more than the identified judicial exception.
For these reasons, the claims, when the limitations are considered individually and as a whole, are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Note: With respect to patent eligibility under 35 USC 101, instant claims 1-4 are eligible, as they do not recite any judicial exception and are directed to a multi-model biomarker only.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
1. Claim 1 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et al. (Pain (2019) Vol. 160:550-560).
Claim 1 is directed to:
A multi-modal biomarker predictive of a pain level in a patient, the biomarker comprising at least one of a structural MRI-based parameter from a brain of the patient and a functional MRI-based parameter from the brain of the patient.
The prior art to Lee et al. discloses multivariate machine-learning model that learns from
central and autonomic features, and then classifies clinical pain states and predicts pain intensity, wherein multi-modal biomarkers include resting-state functional connectivity of the back representation in primary somatosensory cortex and whole-brain regional cerebral blood flow (rCBF) functional images [page 551, col. 1; col. 2; page 552, col. 1]. As such, Lee et al. anticipate claim 1.
2. Claims 5-6 and 12-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et al. (Pain (2019) Vol. 160:550-560).
Claim 5 is directed to:
A computer-implemented method of estimating a pain level in a patient based on a multi- modal biomarker, the method comprising:
a. providing to a computing device the multi-modal biomarker comprising at least one of a structural MRI-based parameter from a brain of the patient and a functional MRI-based parameter from the brain of the patient; and
b. transforming, using the computing device, the multi-modal biomarker into the estimated pain level using a machine learning model.
Claim 12 is directed to the system claim that operates the method as in claims 5 and thus is anticipated for the same reasons as in claim 5. Further with respect to computer implementation, Lee et al. disclose machine learning and inherently include computer systems and operation.
Lee et al. discloses multivariate machine-learning model that learns from central and autonomic features, and then classifies clinical pain states and predicts pain intensity, wherein multi-modal biomarkers include resting-state functional connectivity of the back representation in primary somatosensory cortex and whole-brain regional cerebral blood flow (rCBF) functional images [page 551, col. 1; col. 2; page 552, col. 1]. Lee et al. further disclose classification of clinical pain using machine learning that includes support vector machines [page 553, col. 1; Figure 4]. As such, Lee et al. anticipate claims 5-6 and 12-13.
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.
1. Claims 2-4 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Pain (2019) Vol. 160:550-560), as applied to claim 1 above and in view of Boissoneault et al. (Curr Rheumatol Rep (2017) 19(5): 9 pages).
With respect to claim 1, the prior art to Lee et al. discloses multivariate machine-learning model that learns from central and autonomic features, and then classifies clinical pain states and predicts pain intensity, wherein multi-modal biomarkers include resting-state functional connectivity of the back representation in primary somatosensory cortex and whole-brain regional cerebral blood flow (rCBF) functional images. Functional connectivity includes global connectivity as assessed by “whole-brain connectivity”. [page 551, col. 1; col. 2; page 552, col. 1].
Lee et al. do not specifically disclose wherein the parameters for the MRI-based parameter (structural) is one of cortical thickness and a sub-cortical volume. However, with respect to claims 2-4, the prior art to Boissoneault et al. the development of brain biomarkers for chronic musculoskeletal pain disorders using machine learning (ML) [page 2, col. 1] wherein the use of structural and functional brain imaging to discriminate patient groups from healthy controls have been used for the study of chronic pain [page 2, col. 2]. Boissoneault et al. further disclose that pain biomarkers are derived from structural biomarkers [page 4, col. 2], including cortical and subcortical thickness, as well as functional biomarkers [page 5, col. 2] .
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the techniques that provide for a multi-modal combined biomarker as in Lee et al. with the teachings of different types of biomarkers, both structural and functional as in Boissoneault et al. because Boissoneault et al. specifically motivate one to develop clinical and ML-based biomarkers for chronic musculoskeletal pain conditions derived from structural and functional neuroimages... Current reports describe novel biomarkers capable of separating patient groups and healthy controls with accuracies ranging from 70 to 93%. Such studies provide valuable mechanistic information regarding both the unique and common neural correlates of these conditions, with the potential to highlight differences between both musculoskeletal pain patient groups and controls to which traditional statistical approaches may not be sensitive, or identify mechanistic subgroups within certain pain conditions [page 7, col. 2]. As both references are in the same field of endeavor and specifically operate in the realm of lower back pain, one would have had a reasonable expectation of success in so doing.
2. Claims 7-9 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Pain (2019) Vol. 160:550-560), as applied to claims 5-6 and 12-13 above and in view of Boissoneault et al. (Curr Rheumatol Rep (2017) 19(5): 9 pages).
Claim 5 is directed to:
A computer-implemented method of estimating a pain level in a patient based on a multi- modal biomarker, the method comprising:
a. providing to a computing device the multi-modal biomarker comprising at least one of a structural MRI-based parameter from a brain of the patient and a functional MRI-based parameter from the brain of the patient; and
b. transforming, using the computing device, the multi-modal biomarker into the estimated pain level using a machine learning model.
Claim 12 is directed to the system claim that operates the method as in claims 5 and thus is anticipated for the same reasons as in claim 5. Further with respect to computer implementation, Lee et al. disclose machine learning and inherently include computer systems and operation.
With respect to claims 5-6 and 12-13, Lee et al. discloses multivariate machine-learning model that learns from central and autonomic features, and then classifies clinical pain states and predicts pain intensity, wherein multi-modal biomarkers include resting-state functional connectivity of the back representation in primary somatosensory cortex and whole-brain regional cerebral blood flow (rCBF) functional images. Functional connectivity includes global connectivity as assessed by “whole-brain connectivity”. [page 551, col. 1; col. 2; page 552, col. 1]. Lee et al. further disclose classification of clinical pain using machine learning that includes support vector machines [page 553, col. 1; Figure 4].
Lee et al. do not specifically disclose wherein the parameters for the MRI-based parameter (structural) is one of cortical thickness and a sub-cortical volume. However, with respect to claims 7-9 and 14-16, the prior art to Boissoneault et al. the development of brain biomarkers for chronic musculoskeletal pain disorders using machine learning (ML) [page 2, col. 1] wherein the use of structural and functional brain imaging to discriminate patient groups from healthy controls have been used for the study of chronic pain [page 2, col. 2]. Boissoneault et al. further disclose that pain biomarkers are derived from structural biomarkers [page 4, col. 2], including cortical and subcortical thickness, as well as functional biomarkers [page 5, col. 2].
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the techniques that provide for a multi-modal combined biomarker as in Lee et al. with the teachings of different types of biomarkers, both structural and functional as in Boissoneault et al. because Boissoneault et al. specifically motivate one to develop clinical and ML-based biomarkers for chronic musculoskeletal pain conditions derived from structural and functional neuroimages... Current reports describe novel biomarkers capable of separating patient groups and healthy controls with accuracies ranging from 70 to 93%. Such studies provide valuable mechanistic information regarding both the unique and common neural correlates of these conditions, with the potential to highlight differences between both musculoskeletal pain patient groups and controls to which traditional statistical approaches may not be sensitive, or identify mechanistic subgroups within certain pain conditions [page 7, col. 2]. As both references are in the same field of endeavor and specifically operate in the realm of lower back pain, one would have had a reasonable expectation of success in so doing.
3. Claims 10-11 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (Pain (2019) Vol. 160:550-560) in view of Boissoneault et al. (Curr Rheumatol Rep (2017) 19(5): 9 pages), as applied to claims 5-9 and 12-16 above, in further view of Antonucci et al. (Pain Ther (2020) Vol. 9:601-614; published 3 September 2020).
With respect to claims 5-9 and 12-16, said claim elements are taught above with respect to Lee et al. in view of Boissoneault et al.
Neither Lee et al. nor Boissoneault et al. specifically include that estimated pain levels comprise estimated scores as in claims 10 and 17, 11 and 18. However, the prior art to Antonucci et al. discloses that there are multiple factors that play a role in chronic pain and further teach methods of assessing chronic pain utilizing several scales of measurement, including quality of life, physical and mental health, personal functioning, etc. [page 601, col. 2]. Said features were utilized in a SVM for training and classification of chronic pain, including those from the SF-36 assessment [page 605, col. 1].
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the parameters that included pain scores as derived from self-reporting and/or questionnaires, as is disclosed in Antonucci et al. with the techniques of Lee et al. and Boissoneault et al., as discussed above. Further, the prior art to Boissoneault et al. motivate the combination in that said reference includes that it is conceivable that subgroups within a diagnostic category could be identified solely based upon physiological measurements using unsupervised ML methods and later validated upon self-report [page 4, col. 1].
Conclusion
No claims are allowed.
E-mail Communications Authorization
Per updated USPTO Internet usage policies, Applicant and/or applicant’s representative is encouraged to authorize the USPTO examiner to discuss any subject matter concerning the above application via Internet e-mail communications. See MPEP 502.03. To approve such communications, Applicant must provide written authorization for e-mail communication by submitting following form via EFS-Web or Central Fax (571-273-8300): PTO/SB/439. Applicant is encouraged to do so as early in prosecution as possible, so as to facilitate communication during examination.
Written authorizations submitted to the Examiner via e-mail are NOT proper. Written authorizations must be submitted via EFS-Web or Central Fax (571-273-8300). A paper copy of e-mail correspondence will be placed in the patent application when appropriate. E-mails from the USPTO are for the sole use of the intended recipient, and may contain information subject to the confidentiality requirement set forth in 35 USC § 122. See also MPEP 502.03.
Inquiries
Papers related to this application may be submitted to Technical Center 1600 by facsimile transmission. Papers should be faxed to Technical Center 1600 via the PTO Fax Center. The faxing of such papers must conform to the notices published in the Official Gazette, 1096 OG 30 (November 15, 1988), 1156 OG 61 (November 16, 1993), and 1157 OG 94 (December 28, 1993) (See 37 CFR § 1.6(d)). The Central Fax Center Number is (571) 273-8300.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Lori A. Clow, whose telephone number is (571) 272-0715. The examiner can normally be reached on Monday-Thursday from 12:00PM to 10:00PM ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Karlheinz Skowronek can be reached on (571) 272-9047.
Any inquiry of a general nature or relating to the status of this application or proceeding should be directed to (571) 272-0547.
Patent applicants with problems or questions regarding electronic images that can be viewed in the Patent Application Information Retrieval system (PAIR) can now contact the USPTO’s Patent Electronic Business Center (Patent EBC) for assistance. Representatives are available to answer your questions daily from 6 am to midnight (EST). The toll free number is (866) 217-9197. When calling please have your application serial or patent number, the type of document you are having an image problem with, the number of pages and the specific nature of the problem. The Patent Electronic Business Center will notify applicants of the resolution of the problem within 5-7 business days. Applicants can also check PAIR to confirm that the problem has been corrected. The USPTO’s Patent Electronic Business Center is a complete service center supporting all patent business on the Internet. The USPTO’s PAIR system provides Internet-based access to patent application status and history information. It also enables applicants to view the scanned images of their own application file folder(s) as well as general patent information available to the public.
/Lori A. Clow/ Primary Examiner, Art Unit 1687