DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This action is in response to the papers filed October 31, 2025. Applicant’s remarks and amendments have been fully and carefully considered but are not found to be sufficient to put the application in condition for allowance. Any new grounds of rejection presented in this Office Action are necessitated by Applicant's amendments. Any rejections or objections not reiterated herein have been withdrawn. This action is made FINAL.
Claims 2, 6, 8, 11-14, 16-18, 21-22, and 63-66 are currently pending and have been examined herein.
Claim Rejections - 35 USC § 101
3. 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 2, 6, 8, 11-14, 16-18, 21-22, and 63-66 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception without significantly more. The claims recite a judicial exception that is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim analysis is set forth below.
Step 1: The claims are directed to the statutory category of a process.
Step 2A, prong one: Evaluate Whether the Claim Recites a Judicial Exception
The instant claims recite abstract ideas.
Claim 2 recites the following limitations:
(a) analyzing, by a machine learning model trained to mitigate overfitting, a set of circulating biomarkers
(b) detecting by the machine learning model the presence of the occult metastasis in the subject with an accuracy of greater than 70%
(c) recommending treatment, but not surgery, for the subject when the occult metastasis is detected by the machine learning model
The broadest reasonable interpretation of these steps is that they fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion.
The “analyzing” limitation is a process that under its broadest reasonable interpretation, covers performance of the limitation in the mind but the recitation of a generic machine learning model. That is, other than reciting “by a machine learning model”, nothing in the claim precludes the analyzing step from practically being performed in the human mind. For example, but for the “by a machine learning model” language, the claim encompasses the user analyzing a set of circulating biomarkers observing data on those biomarkers in laboratory report comprising data on the level of circulating biomarkers.
The “detecting” limitation is a process that under its broadest reasonable interpretation, covers performance of the limitation in the mind but the recitation of a generic machine learning model. That is, other than reciting “by a machine learning model”, nothing in the claim precludes the detecting step from practically being performed in the human mind. For example, but for the “by a machine learning model” language, the claim encompasses the user detecting the presence of occult metastasis by making a judgment based on the values of the biomarkers in a laboratory report.
The “recommending treatment” limitation can also be accomplished by a mental processes. For example, one may recommend treatment by verbally suggesting the treatment or by writing down instructions for a treatment. Here it is not clear that the method actually requires an active process step of “administering” anything.
The instant claims recite a law of nature.
The claims recite the following limitations:
(a) analyzing, by a machine learning model trained to mitigate overfitting, a set of circulating biomarkers
wherein one or more of the biomarkers do not correlate with the presence of occult metastases,
correlation between the circulating biomarkers is less than 0.6 specific for the disease or the condition;
(b) detecting by the machine learning model the presence of the occult metastasis in the subject with an accuracy of greater than 70%
Herein the claims appear to be taking individual biomarkers that are weakly or not significantly correlated with occult metastases on their own and combining those biomarkers such that the combination of biomarkers is correlated with occult metastases. Claims 11-14 and 16-17 set forth particular biomarkers. The correlation between a combination of biomarkers and occult metastases is a consequence of natural processes and is a law of nature.
Step 2A, prong two: Evaluate Whether the Judicial Exception Is Integrated Into a Practical Application
The claims do NOT recite additional steps or elements that integrate the recited judicial exceptions into a practical application of the exception(s). For example, the claims do not practically apply the judicial exception by including one or more additional elements that the courts have stated integrate the exception into a practical application:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
An additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
An additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
An additional element effects a transformation or reduction of a particular article to a different state or thing; and
An additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological
environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
In addition to the judicial exceptions the claims recite the additional element of a machine learning model. This provides nothing more than mere instructions to implement an abstract idea using a generic computer program. The machine learning model is used to generally apply the abstract ideas without placing any limits on how the machine learning model functions. Further the recitation of using a machine learning model merely indicates a field of use or technological environment in which the judicial exception is performed. Thus the additional element of a machine learning model does not integrate the judicial exceptions into a practical application.
Step 2B: Evaluate Whether the Claim Provides an Inventive Concept
In addition to the judicial exceptions the claim recites the additional element of a machine learning model. This provides nothing more than mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept.
For the reasons set forth above the claims are not directed to patent eligible subject matter.
Response To Arguments
4. In the response the Applicants traversed the rejection under 35 USC 101.
Regarding Step 2A, Prong One, the Applicants argue that none of the steps in claim 2 can be practically performed in the human mind. Applicants argue that the steps of the claimed methods are performed by a specifically-trained machine learning model, and it would be unreasonable to interpret the claimed steps as steps that can be practically performed in the human mind.
This argument has been fully considered but is not persuasive. Claim 2 recites at least two judicial exceptions. First, claim 2 recites a natural correlation between a combination of biomarkers and occult metastasis. Secondly, claim 2 recites steps that fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgement, and opinion. As explained in the rejection, the recited steps (a)-(b) are process steps that could be performed in the human mind but for the recitation of the machine learning model. That is, other than reciting a “machine learning model”, nothing in the claim precludes the analyzing and detecting steps from practically being performed in the human mind. Additionally step (c) is a process step that can be performed in the human mind. Thus steps (a)-(c) are mental processes.
Regarding Step 2A, Prong Two, the Applicants argue that the claims integrate the judicial exceptions into a practical application. The Applicants argue that the additional elements (circulating biomarkers), in combination with the alleged judicial exception, provide the claimed improvement in detecting occult metastases in early stages of disease. Additionally the Applicants argue that the additional elements (circulating biomarkers) are not insignificant and their use is not insignificant extra solution activity.
This argument has been fully considered but is not persuasive. First, it is noted that the circulating biomarkers are not considered elements in addition to the judicial exception. The circulating biomarkers are considered to be one of the judicial exceptions because they are part of the law of nature recited in the claim. The only element recited in addition to the judicial exceptions is the machine learning model. For the reasons set forth above, the machine learning model does not integrate the judicial exceptions into a practical application.
Regarding Step 2B the Applicants argue that the claims provide an inventive concept.
They argue that the additional elements (circulating biomarkers) in combination with the judicial exception provide an improvement in accurately detecting occult metastases.
This argument has been fully considered but is not persuasive. As discussed above, the only element recited in the claim in addition to the judicial exceptions is the machine learning model. This provides nothing more than mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. The rejection is maintained.
Claim Rejections - 35 USC § 112(a)
5. The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
6. Claims 2, 6, 8, 11-14, 16-18, 21-22, and 63-66 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. This is a New Matter rejection.
Claim 2 as amended is set forth below:
A non-invasive method of detecting an occult metastasis in a subject in need thereof, the method comprising:
(a) analyzing, by a machine learning model trained to mitigate overfitting, a set of
circulating biomarkers comprising an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker, wherein
the set of circulating biomarkers is obtained from a processed sample from the subject,
one or more of the biomarkers do not correlate with the presence of the occult metastases, and
correlation between the circulating biomarkers is less than 0.6;
(b) detecting, by the machine learning model, the presence of the occult metastases in
the subject with an accuracy of greater than 70%; and
(c) recommending treatment, but not surgery, for the subject when the occult metastasis is detected by the machine learning model.
In the instant case the specification does not appear to provide support for the recitation that “one or more of the biomarkers do not correlate with the presence of the occult metastases”. It is noted for the record that Applicant has not pointed out where this claim limitation is supported in the specification. The specification has been reviewed. The specification does not recite an express teaching that one or more of the biomarkers used in the method does not correlate with the presence of occult metastases. The specification discloses numerous biomarkers, including the ones set forth in claims 11, 12, 14, and 16. However the specification does not provide correlations between each of these biomarkers and occult metastases. Therefore the specification does not recite an implicit teaching that one or more of the biomarkers used in the method does not correlate with the presence of occult metastases. In the absence of express or implicit support, the recitation that the “one or more of the biomarkers do not correlate with the presence of the occult metastases” is new matter.
7. Claims 2, 6, 8, 11-14, 16-18, 21-22, and 63-66 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. This is a Written Description rejection.
A non-invasive method of detecting an occult metastasis in a subject in need thereof, the method comprising:
(a) analyzing, by a machine learning model trained to mitigate overfitting, a set of
circulating biomarkers comprising an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker, wherein
the set of circulating biomarkers is obtained from a processed sample from the subject,
one or more of the biomarkers do not correlate with the presence of the occult metastases, and
correlation between the circulating biomarkers is less than 0.6;
(b) detecting, by the machine learning model, the presence of the occult metastases in
the subject with an accuracy of greater than 70%; and
(c) recommending treatment, but not surgery, for the subject when the occult metastasis is detected by the machine learning model.
In the instant case, the claims do not describe the set of circulating biomarkers in terms of sufficient relevant identifying characteristics. The claimed set of circulating biomarkers has the following requirements
(i) it comprises an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker;
(ii) one or more of the biomarkers do not correlate with the presence of the occult metastases;
(iii) correlation between the biomarkers in the set is less than 0.6; and
(iv) the set of biomarkers is able to detect the presence of occult metastases with an accuracy of greater than 70%.
The claims encompass a potentially large genus of different sets of biomarkers.
The specification (Example 6) imaging is a widely used but imperfect technique for detecting metastases and determining whether a PDAC patient's disease is sufficiently localized for consideration of curative-intent surgery. The model disclosed herein was tested to assess if it can identify a biomarker panel that, in conjunction with imaging, could better stage PDAC patients by distinguishing metastatic from non-metastatic disease. To train the model, 20 PDAC patients, originally staged by imaging, were selected which included 9 patients with no detectable metastasis (M0; including 7 resectable and 2 locally advanced), and 11 patients with metastasis (M1). Since some patients originally identified as M0 may have had occult metastases below the level of imaging detection, a chart review was conducted and retrospectively the M0 patients were re-stratified into two groups: 1) M0s: those with no evidence of metastatic disease intraoperatively or within 4 months of follow-up and 2) Occult metastases: those who had metastases detected intraoperatively or had metastatic recurrence within 4 months of blood draw. This stratification resulted in the training set of 8 M0 and 12 M1 (11 with imaging-confirmed metastases and one with occult metastases).
Using LASSO, a biomarker panel of 4 markers, including EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9 was selected as having the highest Accuracy (A=91%; FIG. 4B, C).
To further evaluate the panel's ability to identify occult metastatic disease, the approach to an independent blinded test set of 35 subjects with PDAC was applied as part of a clinical workflow starting with standard of care diagnostic imaging and followed by liquid biopsy. Twelve of 35 patients were identified by imaging alone as having metastases, were classified as Ml, and had no further evaluation. The remaining 23 patients were determined by baseline imaging to have no detectable metastases (MO-imaging). Upon retrospective chart review, 15 of 23 had no evidence of metastases within 4 months (median time to metastases). Eight of 23 patients were determined to have had occult metastases. The liquid biopsy workflow correctly identified 6 of 8 patients as having metastatic disease, and 13 of 15 patients as being metastasis-free. Thus, by comparing the liquid biopsy prediction to the true state of the patients, the ptest had an accuracy of detecting distant metastasis of A =83% (19/23) with sensitivity of 75% and specificity of 87% (AUC=0. 8), which compares favorably to the accuracy of imaging alone (A=65% (15/23); P<0.01. FIG. 4F) among 23 patients originally identified as M0 by imaging.
While the specification teaches a set of biomarkers EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9, it is not clear if this set has each of the required properties set forth in the claim. The set of biomarkers comprises an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker and the set of biomarkers is able to detect the presence of occult metastases with an accuracy of greater than 70%. The set of biomarkers does NOT meet the requirement that the correlation between the biomarkers in the set is less than 0.6 because the specification teaches that CA19-9 and circulating mutant KRAS allele fraction were correlated with an |R|=0.73. Further it is UNKNOWN if this set of biomarkers meet the requirement that one or more of the biomarkers does not correlate with the presence of the occult metastases because the specification does not teach the correlation between each individual biomarker and occult metastases.
The claims encompass a potentially large genus of different sets of circulating biomarkers. The specification does not provide an actual reduction to practice. The specification does not disclose the structure of a set of circulating biomarkers which meets each of the claimed requirements. The specification does not describe members of the genus by physical and/or chemical characteristics. All members of the genus have the same function, i.e., they can be used to detect occult metastasis, but no correlation between their unknown structure and this common function is disclosed. Discovering sets of circulating biomarkers that would function in the claimed method using routine methods in the prior art is not a practical way to describe the full extent of the claimed genus because finding sets of circulating biomarkers that can be used could be successful only empirically. The existence of sets of circulating biomarkers that meet each of the claimed requirements is totally unpredictable. Accordingly, one of skill in the art would conclude that applicant was not in possession of the claimed genus.
8. Claims 2, 6, 8, 11-14, 16-18, 21-22, and 63-66 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, because the specification, while being enabling for
A non-invasive method of detecting an occult metastasis of pancreatic ductal adenocarcinoma (PDAC) in a subject, the method comprising:
(a) analyzing, by a machine learning model trained to mitigate overfitting, a set of
circulating biomarkers comprising EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9;
(b) detecting, by the machine learning model, the presence of the occult metastases in
the subject with an accuracy of greater than 70%; and
(c) recommending treatment, but not surgery, for the subject when the occult metastasis is detected by the machine learning model.
does not reasonably provide enablement for the claims as broadly written. The specification does not enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention commensurate in scope with these claims.
Scope of the Claims/Nature of the Invention
The claims are drawn to a method of detecting an occult metastasis in a subject. The claims broadly encompass being able detect occult metastasis of greater than 200 different known cancer types. Only claim 8 is limited to pancreatic cancer.
The claims recite a first step of analyzing, by a machine learning model trained to mitigate overfitting, a set of circulating biomarkers comprising an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker, wherein the set of circulating biomarkers is obtained from a processed sample from the subject, one or more of the biomarkers do not correlate with the presence of the occult metastases, and correlation between the circulating biomarkers is less than 0.6. In the instant case, the claims do not describe the set of circulating biomarkers in terms of sufficient relevant identifying characteristics. The claimed set of circulating biomarkers has the following requirements
(i) it comprises an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker;
(ii) one or more of the biomarkers do not correlate with the presence of the occult metastases;
(iii) correlation between the biomarkers in the set is less than 0.6; and
(iv) the set of biomarkers is able to detect the presence of occult metastases with an accuracy of greater than 70%.
The claims encompass a potentially large genus of different sets of biomarkers.
The claims recite a second step of detecting, by the machine learning model, the presence of the occult metastases in the subject with an accuracy of greater than 70%.
The claims recite a third step of recommending treatment, but not surgery, for the subject when the occult metastasis is detected by the machine learning model.
The nature of the invention requires a reliable correlation between a set of circulating biomarkers meeting the claimed requirements and occult metastasis of ANY type of cancer.
Teachings in the Specification and Examples
The specification (Example 6) imaging is a widely used but imperfect technique for detecting metastases and determining whether a PDAC patient's disease is sufficiently localized for consideration of curative-intent surgery. The model disclosed herein was tested to assess if it can identify a biomarker panel that, in conjunction with imaging, could better stage PDAC patients by distinguishing metastatic from non-metastatic disease. To train the model, 20 PDAC patients, originally staged by imaging, were selected which included 9 patients with no detectable metastasis (M0; including 7 resectable and 2 locally advanced), and 11 patients with metastasis (M1). Since some patients originally identified as M0 may have had occult metastases below the level of imaging detection, a chart review was conducted and retrospectively the M0 patients were re-stratified into two groups: 1) M0s: those with no evidence of metastatic disease intraoperatively or within 4 months of follow-up and 2) Occult metastases: those who had metastases detected intraoperatively or had metastatic recurrence within 4 months of blood draw. This stratification resulted in the training set of 8 M0 and 12 M1 (11 with imaging-confirmed metastases and one with occult metastases).
Using LASSO, a biomarker panel of 4 markers, including EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9 was selected as having the highest Accuracy (A=91%; FIG. 4B, C).
To further evaluate the panel's ability to identify occult metastatic disease, the approach to an independent blinded test set of 35 subjects with PDAC was applied as part of a clinical workflow starting with standard of care diagnostic imaging and followed by liquid biopsy. Twelve of 35 patients were identified by imaging alone as having metastases, were classified as Ml, and had no further evaluation. The remaining 23 patients were determined by baseline imaging to have no detectable metastases (MO-imaging). Upon retrospective chart review, 15 of 23 had no evidence of metastases within 4 months (median time to metastases). Eight of 23 patients were determined to have had occult metastases. The liquid biopsy workflow correctly identified 6 of 8 patients as having metastatic disease, and 13 of 15 patients as being metastasis-free. Thus, by comparing the liquid biopsy prediction to the true state of the patients, the ptest had an accuracy of detecting distant metastasis of A =83% (19/23) with sensitivity of 75% and specificity of 87% (AUC=0. 8), which compares favorably to the accuracy of imaging alone (A=65% (15/23); P<0.01. FIG. 4F) among 23 patients originally identified as M0 by imaging.
While the specification teaches a set of biomarkers EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9, it is not clear if this set has each of the required properties set forth in the claim. The set of biomarkers comprises an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker and the set of biomarkers is able to detect the presence of occult metastases with an accuracy of greater than 70%. The set of biomarkers does NOT meet the requirement that the correlation between the biomarkers in the set is less than 0.6 because the specification teaches that CA19-9 and circulating mutant KRAS allele fraction were correlated with an |R|=0.73. Further it is UNKNOWN if this set of biomarkers meet the requirement that one or more of the biomarkers does not correlate with the presence of the occult metastases because the specification does not teach the correlation between each individual biomarker and occult metastases.
State of the Art and the Unpredictability of the Art
While methods of measuring EV-miRNA, EV-mRNA, ctDNA, and protein biomarkers are known in the art, methods of correlating EV-miRNA, EV-mRNA, ctDNA, and protein biomarkers with a phenotype such as occult metastasis are highly unpredictable. The unpredictability will be discussed below.
The claims are drawn to a method of detecting occult metastasis based on the detection of any set of circulating biomarkers which meet the following requirements
(i) it comprises an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker;
(ii) one or more of the biomarkers do not correlate with the presence of the occult metastases;
(iii) correlation between the biomarkers in the set is less than 0.6; and
(iv) the set of biomarkers is able to detect the presence of occult metastases with an accuracy of greater than 70%.
The claims encompass a potentially large genus of different sets of biomarkers. The specification does not appear to teach a set of biomarkers that meets all of these requirements. At best the specification teaches a correlation between EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9 and occult metastasis of PDAC. In the instant case it is highly unpredictable if other sets of biomarkers exist that could also be used to detect occult metastasis. The limited examples in the specification are not commensurate in scope with the breadth of the claims. The specification only provides enablement for using EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9 to detect occult metastasis of PDAC.
The claims broadly encompass a method of detecting occult metastasis of ANY type of cancer. It is noted that there are greater than 200 different types of cancer. The specification discloses biomarkers (EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9) that can be used to detect occult metastasis of PDAC. It is known in the art that different cancers have different expression patterns and different mutations. In the absence of evidence to the contrary, it is highly unpredictable if the findings between EV-miR.1299, EV-GAPDH, circulating mutant KRAS allele fraction, and CA19-9 and occult metastasis of PDAC could be extrapolated to any of the other greater than 200 different cancers known in the art.
Quantity of Experimentation:
The quantity of experimentation necessary is great, on the order of many man-years, and then with little if any reasonable expectation of successfully enabling the full scope of the claims. In support of this position, it is noted that the claimed methods encompass being able to a set of circulating biomarkers wherein the biomarkers have the following requirements
(i) it comprises an extra-cellular vesicle (EV) miRNA, an EV mRNA, a circulating tumor DNA, and a protein biomarker;
(ii) one or more of the biomarkers do not correlate with the presence of the occult metastases;
(iii) correlation between the biomarkers in the set is less than 0.6; and
(iv) the set of biomarkers is able to detect the presence of occult metastases with an accuracy of greater than 70%.
In order to practice the breadth of the claimed invention one of skill in the art would first have to recruit patients with occult metastasis of a representative number of the different cancer types encompassed by the claims and controls. Then additional experimentation would need to be performed to measure ev-miRNA, evRNA, ctDNA, and protein in samples obtained from those patients. Then all the data would need to be analyzed to determine sets of biomarkers that meeting the claimed requirements. The specification has merely provided an invitation for further experimentation. The results of such experimentation are highly unpredictable.
The amount of experimentation that would be required to practice the full scope of the claimed invention and the amount of time and cost this experimentation would take supports the position that such experimentation is undue. Attention is directed to Wyeth v. Abbott Laboratories 107 USPQ2d 1273, 1275, 1276 (Fed. Cir. June 2013):
Claims are not enabled when, at the effective filing date of the patent, one of ordinary skill in the art could not practice their full scope without undue experimentation. MagSil Corp. v. Hitachi Global Storage Techs., Inc., 687 F.3d 1377, 1380-81 [103 USPQ2d 1769] (Fed. Cir. 2012).
The remaining question is whether having to synthesize and screen each of at least tens of thousands of candidate compounds constitutes undue experimentation. We hold that it does. Undue experimentation is a matter of degree. Chiron Corp. v. Genentech, Inc., 363 F.3d 1247, 1253 [70 USPQ2d 1321] (Fed. Cir. 2004) (internal quotation omitted). Even “a considerable amount of experimentation is permissible,” as long as it is “merely routine” or the specification “provides a reasonable amount of guidance” regarding the direction of experimentation. Johns Hopkins Univ. v. CellPro, Inc., 152 F.3d 1342, 1360-61 [47 USPQ2d 1705] (Fed. Cir. 1998) (internal quotation omitted). Yet, routine experimentation is “not without bounds.” Cephalon, Inc. v. Watson Pharm., Inc., 707 F.3d 1330, 1339 [105 USPQ2d 1817] (Fed. Cir. 2013). (Emphasis added)
In Cephalon, although we ultimately reversed a finding of nonenablement, we noted that the defendant had not established that required experimentation “would be excessive, e.g., that it would involve testing for an unreasonable length of time.” 707 F.3d at 1339 (citing White Consol. Indus., Inc. v. Vega Servo-Control, Inc., 713 F.2d 788, 791 [218 USPQ 961] (Fed. Cir. 1983)). Finally, in In re Vaeck, we affirmed the PTO's nonenablement rejection of claims reciting heterologous gene expression in as many as 150 genera of cyanobacteria. 947 F.2d 488, 495-96 [20 USPQ2d 1438] (Fed. Cir. 1991). The specification disclosed only nine genera, despite cyanobacteria being a “diverse and relatively poorly understood group of microorganisms,” with unpredictable heterologous gene expression. Id. at 496. (Emphasis added)
Additionally, attention is directed to Cephalon at 1823, citing White Consol. Indus., Inc. v. Vega Servo-Control, Inc., 218 USPQ 961, that work that would require 18 months to 2 years so to enable the full scope of an invention, even if routine, would constitute undue experimentation. As stated therein:
Permissible experimentation is, nevertheless, not without bounds. This court has held that experimentation was unreasonable, for example, where it was found that eighteen months to two years’ work was required to practice the patented invention. See, e.g., White Consol. Indus., Inc. v. Vega Servo-Control, Inc., 713 F.2d 788, 791 [218 USPQ 961] Fed. Cir.1983). (Emphasis added)
Attention is also directed to MPEP 2164.06(b) and In re Vaeck, 20 USPQ2d 1438, 1445 (Fed. Cir. 1991).
Where, as here, a claimed genus represents a diverse and relatively poorly understood group of microorganisms, the required level of disclosure will be greater than, for example, the disclosure of an invention involving a “predictable” factor such as a mechanical or electrical element. See Fisher, 427 F.2d at 839, 166 USPQ at 24.
In view of such legal precedence, the aspect of having to work for so many years just to provide the starting materials for minute fraction of the scope of the claimed invention is deemed to constitute both an unreasonable length of time and undue experimentation.
Conclusions:
Herein, although the level of skill in the art is high, given the lack of disclosure in the specification and in the prior art and the unpredictability of the art, it would require undue experimentation for one of skill in the art to make and use the invention as broadly claimed.
9. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMANDA HANEY whose telephone number is (571)272-8668. The examiner can normally be reached Monday-Friday, 8:15am-4:45pm EST.
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/AMANDA HANEY/ Primary Examiner, Art Unit 1682