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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/25/2025 has been entered.
Claim Status and Formal Matters
This action is in response to papers filed 7/25/2025.
Claims 19-24, 32 are pending.
Claim 19 has been amended.
Applicant’s election of claims 19-25 in the reply filed on 1/12/2022 is acknowledged. Because applicant did not distinctly and specifically point out the supposed errors in the restriction requirement, the election has been treated as an election without traverse (MPEP § 818.01(a)).
Priority
The instant application was filed 01/07/2020 is a national stage entry of PCT/CA2018/050833 having an international filing date: 07/09/2018 and claims priority from provisional application 62529767, filed 07/07/2017.
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 119(e), 120, 121, 365(c), or 386(c) as follows: The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994)
The disclosure of the prior-filed application, Application No. 62529767 fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. The provisional application does not recite, “longitudinal Logit or (l_logit). Thus the amendment is not supported by the provisional application.
Response to Arguments
The response provides no arguments to the priority issue.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 19-24, 32 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 19 has been amended to recite, “detecting the change in the level of each of the time-varying biological indicators over time from day 1 to up to 28 days as compared with a corresponding benchmark level[s] for each of the time-varying biological indicators from surviving septic patients..” The recitation of “corresponding benchmark levels ” encompasses from the same time, same concentration, etc. The response asserts support can be found in paragraph s 0020, 0120 and 0139. Paragraph 0020 states:
FIGURE 7 shows personalized mortality risk profile that highlights the relative contribution of each TVBI to the risk of dying. The profile provides information about how different TVBIs affect the patient's risk of dying on a given day relative to a benchmark representing the best 10th percentile of survivors in terms of the predicted hazard of dying as of the last day. The top panel shows the separate effects of day 1 and change variables of each TVBI. The middle panel shows the net additive effects of the day 1 and change variables for each TVBI. Since hazard ratios (HRs) are easier to interpret than differences in the log of hazard, the latter measures were converted into the former measures, For ease of visualization, the HRs are expressed as "1R-I" as shown in the bottom panel.
This does not provide antecedent basis for the limitations or provide benchmarks as figure 7 provides data with respect to septic patients and non-septic patients.
Paragraph 0120 states
[00120] In addition to generating a predicted probability for each patient (as a survivor or non-survivor), this assessment tool can generate personalized mortality risk profiles that provide information about how different TVBIs affect a patient's risk of dying on any given day. To identify the main TVBIs that contribute to mortality risk and to determine how improvements in TVBIs can reduce the mortality risk of a patient in question, the construction and use of a mortality risk profile is described. As a basis for constructing a mortality risk profile, the best 10th percentile of survivor patients in terms of the predicted probability of dying as of the last day served as the benchmark for comparison.
While this recites “benchmark” the teachings are limited to 10th percentile of survivor patients and thus is different than time-varying indicators from surviving septic patients. Further the recitation of corresponding would
Paragraph 0139 states:
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This does not appear to support the full breath of the amendment. Thus the amendment appears to introduce new matter.
Response to Arguments
This is a new ground of rejection necessitated by amendment.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 19-24, 32 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 19 has been amended to recite, “ method of generating a personalized mortality risk profile for a septic patient to identify a patient at increased risk of dying based on levels of time-varying biological indicators as compared to benchmark levels of the time-varying biological indicators.” The recitation of increased risk suggest there is decreased risk. The specification and claims provide no definition or standard to differentiate increased risk from decreased risk. Further the recitation of “based on” is unclear if the identifying increased risk is limited to only levels of time-varying biological indicators as compared to benchmark levels of the time-varying biological indicators or requires additional data or analysis.
Claim 19 has been amended to recite, “a corresponding benchmark level for each of the time-varying biological indicators from surviving septic patients.” The metes and bounds are unclear as the claims and specification do no define corresponding benchmark value. Thus it is unclear if corresponding benchmark is from the say day or time point; the same concentration or value as the patient; or some other level of corresponding.
Further claim 19 recites, generating the mortality risk profile for the patient comprising a hazard ratio of the change of each of the indicator levels from their corresponding benchmark level as determined using a longitudinal logit (L-Logit) model or complementary log-log analysis of the change in indicator levels to yield an overall hazard ratio, wherein an increase in the overall hazard ratio as compared to that based on benchmark levels of the time-varying biological indicators indicates an increased risk of dying as compared to the risk of dying based on benchmark levels of the time-varying biological indicators, wherein the method exhibits a predictive power having an area under the curve (AUC) value of 0.9.” The metes and bounds are unclear how this is done as the claims merely require data for the time varying indicators from the patient, and 2 septic shot survivors, however the longitudinal logit (L-Logit) model or complementary log-log analysis are statistical methods requiring 100s if not thousands of data points from different subjects to generate mortality risk profile. Further the recitation of “an increase in the overall hazard ratio as compared to that based on benchmark levels of the time-varying biological indicators indicates an increased risk of dying as compared to the risk of dying based on benchmark levels of the time-varying biological indicators” appears to be confusing, unclear and incomplete as it appears to be circular.
Claim 19 recites, “detecting in biological samples obtained from the patient levels of time-varying biological indicators comprising circulating free DNA (cfDNA), protein C, lactate, platelet count, and creatinine, and determining a Glasgow Coma Score (GCS) time-varying biological indicator of the patient, at a plurality of time points from a day 1 up to 28 days.” It is unclear if the recitation requires the biological samples are obtained once and assayed over time, samples are obtained at certain time points over time, or something else.
Further claim 19 recites, “determining a Glasgow Coma Score (GCS) time-varying biological indicator of the patient.” The metes and bounds are unclear how “Glasgow Coma Score (GCS) time-varying biological indicator” relates to Glasgow Coma score. Further it is unclear which GCS is required as Schouela (GCS Remastered: Recent Updates to the Glasgow Coma Scale (GCS-P), July 2018) teaches GCS has changed over the years, thus it is unclear what version is required.
Response to Arguments
The response traverses the rejection in view of the amendment. These arguments have been thoroughly reviewed but are not persuasive as the amendment has raised new and/or additional issues. Further the amendment has not addresses the issue with the generating step.
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 19-24, 32 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a natural correlation and mental step without significantly more in as the claims provide no additional steps which integrate or otherwise apply the judicial exception. The claim(s) recite(s) the abstract idea or mental step of comparing. Further the claims recite, “ii) detecting the change in the level of each of the time-varying biological indicators over time from day 1 to up to 28 days as compared with a corresponding control or benchmark level[s] for each of the time-varying biological indicators from surviving septic patients; iii) generating the mortality risk profile for the patient comprising a hazard ratio of the change of each of the indicator levels from their corresponding benchmark level as determined using a longitudinal logit (L-Logit) model or complementary log-log analysis of the change in indicator levels to yield an overall hazard ratio, wherein an increase in the overall hazard ratio as compared to that based on benchmark levels of the time-varying biological indicators indicates an increased risk of dying as compared to the risk of dying based on benchmark levels of the time-varying biological indicators, wherein the method exhibits a predictive power having an area under the curve (AUC) value of 0.9. “ which is a natural law or correlation and abstract idea or mental step. This judicial exception is not integrated into a practical application because no administering step is required if there is no increase in risk of dying. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because no specific reagents are required.
Claim analysis
The instant claim 19 is directed A method of generating a personalized mortality risk profile for a septic patient to identify a patient at increased risk of dying based on levels of time-varying biological indicators as compared to benchmark levels of the time-varying biological indicators, and treating the patient, the method comprising: i) detecting in biological samples obtained from the patient levels of time-varying biological indicators comprising circulating free DNA (cfDNA), protein C, lactate, platelet count, and creatinine, and determining a Glasgow Coma Score (GCS) time-varying biological indicator of the patient, at a plurality of time points from a day 1 up to 28 days; ii) detecting the change in the level of each of the time-varying biological indicators over time from day 1 to up to 28 days as compared with a corresponding benchmark level[s] for each of the time-varying biological indicators from surviving septic patients; iii) generating the mortality risk profile for the patient comprising a hazard ratio of the change of each of the indicator levels from their corresponding benchmark level as determined using a longitudinal logit (L-Logit) model or complementary log-log analysis of the change in indicator levels to yield an overall hazard ratio, wherein an increase in the overall hazard ratio as compared to that based on benchmark levels of the time-varying biological indicators indicates an increased risk of dying as compared to the risk of dying based on benchmark levels of the time-varying biological indicators, wherein the method exhibits a predictive power having an area under the curve (AUC) value of 0.9; and iv) treating the patient at increased risk of dying as determined in step iii), wherein the treatment comprises one or a combination of reducing cfDNAs, lactate and/or creatinine levels, and/or increasing protein C, platelet levels, and/or GCS based on the mortality risk profile to reduce the patient's risk of dying as compared to the risk of dying depicted by the mortality risk profile..
The generating step is a natural correlation or phenomena and/or abstract idea or mental step. The comparing in the detecting step is a mental step or abstract idea. The treating step is can be interpreted as conditional based on step iii) of the claim.
Dependent claims set forth further limitations to the changes of the levels being analyzed and statistical methods being used.
According to the 2019 Patent Eligibility Guidance an initial two step analysis is required for determining statutory eligibility.
Step 1. Is the claim directed to a process, machine, manufacture, or composition of matter? In the instant case the Step 1 requirement is satisfied as the claims are directed towards a process.
Step 2A Prong one. Does the claim recite a law of nature, a natural phenomenon or an abstract idea? Yes, abstract idea and law of nature or natural phenomena.
Claim 19 recites, ii) detecting the change in the level of each of the time-varying biological indicators over time from day 1 to up to 28 days as compared with a corresponding control or benchmark level[s] for each of the time-varying biological indicators from surviving septic patients; iii) generating the mortality risk profile for the patient comprising a hazard ratio of the change of each of the indicator levels from their corresponding benchmark level as determined using a longitudinal logit (L-Logit) model or complementary log-log analysis of the change in indicator levels to yield an overall hazard ratio, wherein an increase in the overall hazard ratio as compared to that based on benchmark levels of the time-varying biological indicators indicates an increased risk of dying as compared to the risk of dying based on benchmark levels of the time-varying biological indicators, wherein the method exhibits a predictive power having an area under the curve (AUC) value of 0.9.” This is an abstract idea or mental step and a natural correlation..
Step 2A prong two. Does the claim recite additional elements that integrate the judicial exception into a practical application? The answer is no as the claim requires no specific additional steps which integrate the judicial exception as step iv) is limited treating to only patients with increased risk, those without increased risk are not treated..
Step 2B. Does the claim recite additional elements that are significantly more than the judicial exceptions? No, as the claims provide no limitations which specific reagents to detect the recited patient levels.
With regards to claim the active step of detecting the recited patient. The specification teaches:
[[0060] The inclusion criteria for sepsis were a modification of those defined by Bernard et al. (N Engl JMed 2001; 344: 699-709). Patients were eligible for inclusion into the septic group of this study if they had a confirmed or suspected infection on the basis of clinical data at the time of screening, at least one dysfunctional organ system, 3 or more signs of systemic inflammatory response syndrome (SIRS), and were expected to remain in the ICU for > 72 hours. The presence of organ dysfunction are: (1) SBP <90 mm Hg or MAP <70 mm Hg or SBP < 40 mm Hg for at least 1 hour despite fluid resuscitation, adequate intravascular volume status, or use of vasopressor in an attempt to maintain systolic BP >90 or MAP > 70 mm Hg; (2) P/F Ratio < 250 in the presence of other dysfunctional organs or systems, or < 200 if the lung is the only dysfunctional organ; (3) acute rise in creatinine > 171 mM or urine output <0.5 ml/kg body weight for 1 hour despite adequate fluid resuscitation; (4) unexplained metabolic acidosis (pH 7.30 or base deficit > 5 with lactate > 1.5 times the upper limit of normal; and (5) platelet count < 50,000 or a 50% drop over the 3 days prior to ICU admission. The inclusion criteria for septic shock are the same as those for sepsis except that the patient must be on vasopressors within the previous 24 hours. Patients were excluded if they were < 18 years old, were pregnant or breastfeeding, or were receiving palliative care only..
0068] Lactate and creatinine were measured via enzymatic digestion using commercially available assays, namely, the Lactic Acid assay (lactic acid conversion
to pyruvate and hydrogen peroxide by lactate oxidase) run on the ARCHITECT cSystem by Abbott, and the Creatinine assay (Kinetic Alkaline Picrate: creatinine reaction with picrate to form a creatinine-picrate complex at an alkaline pH) run on Abbott's ARCHITECT c Systems and AEROSET System.
[0069] A hematology analyzer (cell counter) was used to measure platelet count.
[0070] In this study, cfDNA was isolated from 200 gL of plasma using the QIAamp DNA Blood Mini Kit (Qiagen, Valencia, CA). The concentration of the DNA was measured by UV absorbance at 260 nm using a spectrophotometer (BioPhotometer Plus spectrophotometer, Eppendorf, Mississauga, ON). The purity of the DNA was confirmed by determining the OD260/OD2o ratio.
[0071] Plasma levels of protein C antigen were quantified by an enzyme immunoassay (Affinity Biologicals Inc., Ancaster, ON).
[0072] The GCS was measured at the bedside.
[0049] Other treatments for a septic patient may be administered to boost the immune system. These may include treatment with mesenchymal stem cells, herbal remedies such as Echinacea and ginseng, probiotics, and diet enhanced with immune boosting nutrients, vitamins and minerals (e.g. fruits and vegetables, fish (omega-3), shellfish (selenium), zinc-containing foods (beef), garlic (allicin), etc.
Thus the claim does not provide additional steps which are significantly more.
Further the art of Saukkonen (Determinants of outcome in critically ill patients (Helsinki) 2010), Clementietal., (Blood Purification,2016,41,34-40), Liaw etal. (Hemostasis, Thrombosis and Vascular biology,15December2004(15-12-2004),104(13),3958-3964), Dwivedi et al.( CriticalCare,2012,16,R151), Lokhandwala et al,(Journal of Critical Care,2017,37,179-184), Gruclu et al., (African Health Sciences,June2013,13(2),333-338), Vanmassenhove et al (BMCNephrology,July2015,16(112), Arifin et al( Paediatrica Indonesiana,March2012,52(2),111-11), Jenkins (Survival Analysis (2005) demonstrate the detecting levels in a biological sample are routine and conventional.
Response to Arguments
The response traverses the rejection in view of the amendment to provide a treating step. This argument has been thoroughly reviewed but is not considered persuasive as the claim only requires treatment of patients with increased risk. Thus there is no treatment for subjects not having increased risk and thus integration of the judicial exceptions for those patients.
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 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.
Claim 19-24, 32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saukkonen (Determinants of outcome in critically ill patients (Helsinki) 2010), Clementietal., (Blood Purification,2016,41,34-40), Liaw etal. (Hemostasis, Thrombosis and Vascular biology,15December2004(15-12-2004),104(13),3958-3964), Dwivedi et al.( CriticalCare,2012,16,R151), Lokhandwala et al,(Journal of Critical Care,2017,37,179-184), Gruclu et al., (African Health Sciences,June2013,13(2),333-338), Vanmassenhove et al (BMCNephrology,July2015,16(112), Arifin et al( Paediatrica Indonesiana,March2012,52(2),111-11), Jenkins (Survival Analysis (2005) Sonneville (. Annals of Intensive Care 2013, 3:15), Mai (SHOCK, Vol. 44, No. 2, pp. 166Y172, 2015) and Dellinger (CCRN Journal 2013) pages 580-.637)
Saukkonen teaches, “Predicting the outcome of critically ill patients is a challenging task. Traditionally, scoring systems measuring the severity of illness, e.g. the Acute Physiology and Chronic Health Evaluation II, or organ dysfunction, e.g. the Sequential Organ Failure Assessment (SOFA) are used to predict mortality or morbidity of intensive care patients. These scores are also increasingly used to assist the clinical decision-making process by, for instance, qualifying patients for new treatments such as activated protein C in severe sepsis. For large cohorts of patients, their ability to explain the mortality risk is impressive, and they form the basis for clinical research. However, at the level of the individual patient, they lack apparent clinical utility. The prediction models that are used at present utilize only data collected at or just after intensive care unit (ICU) admission, although the events before admission are evidently prognostically important and early treatment improves survival in, for example, septic shock”(page 10>
Saukkonen teaches Scoring systems (2.1.3) and disease severity scoring systems (page 17). Saukkonen teaches in table 1 APACHE II and SAPSII variables include Glasgow coma scale, creatinine. Saukkonen teaches the SOFA score includes platelet count, Glasgow Coma scale, platelet count (table 2).
Saukkonen teaches, “ Routine laboratory measurements were taken daily as part of patient follow-up and for organ failure and disease severity scores, although no specific laboratory sample protocol existed (II–IV). The measurements included serum bilirubin, C-reactive protein, creatinine, urea concentrations, and platelet count.” (page 61, other measurements).
Saukkonen teaches, “The median cell-free plasma DNA concentration at baseline was 8070 GE/ml (IQR 3883–18 934 GE/ml) and 7457 GE/ml 72 h thereafter (IQR 3668–16 311 GE/ml) in patients with severe sepsis or septic shock. The cell-free plasma DNA concentration was higher in ICU nonsurvivors than in survivors at admission (median 15 904 vs. 7522 GE/ml, p<.001) as well as 72 h later (median 15 176 vs. 6758 GE/ml, p=.004). Hospital nonsurvivors had higher plasma DNA levels than survivors at both time-points (baseline median 12 386 vs. 7678 GE/ml, p=.009 and 72-hour median 11 428 vs. 6414 GE/ml, p=.008). The increasing or decreasing plasma DNA concentration was not associated with ICU or hospital mortality (p=.42–.93).” (6.3, page 69).
Saukkonen teaches examination of protein C SNPs with outcome.
Saukkonen teaches multiple statistical models (page 63-64).
Clementi et al discloses that higher levels of cfDNA in patients with sepsis were found in non-surviving patients compared to surviving patients; hence cfDNA levels can be used to determine the risk of mortality in a septic patient.
Liaw discloses that protein C levels are lower in septic patients compared to healthy population. (table 2)
Dwivedi l discloses that using the combination of cfDNA and protein C to determine a septic patient’s prognosis has a better utility than did MODS or APACHE II scores (abstract, discussion, table 4).
Lokhandwala discloses that higher levels of lactate in patients with sepsis were found in non-surviving patients compared to surviving patients ;hence lactate levels can be used to determine the risk of mortality in a septic patient.(abstract, conclusion).
Gruclu discloses that patients with severe sepsis have a lower platelet count compared to patients with sepsis(table 3). Gruclu teaches creatinine is a markers of severe sepsis (table1).
Vanmassenhove discloses that increased creatinine levels in septic patient over the first 24 hours are indicative of a higher risk of mortality. Vanmassenhove teaches analysis of creatinine at admission and historical baseline (table 1).
Arifin discloses that septic patients with a low GCS were at higher risk of mortality (abstract, discussion).
Therefore it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the claims to combine the teachings of art to examine the expression of known sepsis biomarkers (comprising or consisting of circulating free DNA (cfDNA), protein C, lactate, platelet count, and creatinine, and determining a Glasgow Coma Score (GCS)) to monitor, treat or determine risk of mortality from sepsis over time. The artisan would be motivated to combine known markers to determine risk of sepsis and/or risk of mortality from sepsis. The artisan would have a reasonable expectation of success as the artisan is merely combining known markers associated with sepsis.
Saukkonen, Clementi., Liaw, Dwived, Lokhandwala, Gruclu., Vanmassenhove and Arifin while demonstrating the examination of cfDNA, protein C, lactate, platelet count, creatinine, and Glasgow Coma Score (GCS) over time was known to be used to identify sepsis and the use of statistical analysis. Saukkonen, Clementi., Liaw, Dwived, Lokhandwala, Gruclu., Vanmassenhove and Arifin do not specifically teach analysis of the indicators based on complementary log-log model.
However, Jenkins survival analysis (title). Jenkins teaches basic concepts in chapter 2 or hazard rate and survivor function. Jenkins teaches, “The last chapter suggested that there is no single shape for the hazard rate that is appropriate in all contexts. In this chapter we review the functional forms for the hazard rate that have been most commonly used in the literature. What this means in terms of survival, density and integrated hazard functions is examined in the following chapter. We begin with an overview and taxonomy, and then consider continuous time and discrete time specifications separately.” (page 25, middle). Jenkins teaches, “The log(log(.)) transformation is known as the complementary log-log transformation; hence the discrete-time PH model is often referred to as a cloglog model. Observe that, if each interval is of unit length, then we can straightforwardly index time intervals in terms of the interval number rather than the dates marking the end of each interval. The cloglog model is a form of generalized linear model with particular link function:
The cloglog model is a form of generalized linear model with particular link function: see (3.83). When estimated using interval-censored survival data, one derives estimates of the regression coefficients, and of the parameters : The coefficients are the same ones as those characterizing the continuous time hazard rate (t) = 0 (t) exp(βX). However the parameters characterizing the baseline hazard function 0 (t) cannot be identified without further assumptions: the summarize differences in values of the integrated hazard function, and are consistent with a number of different shapes of the hazard function within each interval. To put things another way, the
j summarize the pattern of duration dependence in the interval hazard, but one cannot identify the precise pattern of duration dependence in the continuous time hazard without further assumptions.”(page 43).
Therefore it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the invention to use the cloglog statistical method including hazard ratio or hazard function of mortality by Jenkins for the longitudinal data from septic survivor patients of Saukkonen, Clementi., Liaw, Dwived, Lokhandwala, Gruclu., Vanmassenhove and Arifin. The artisan would be motivated to determine is a profile of indicators value or score could be obtained to help determine care. The artisan would have a reasonable expectation of success as the artisan is merely analyzing known sepsis data using known statistical models.
Saukkonen, Clementi., Liaw, Dwived, Lokhandwala, Gruclu., Vanmassenhove Jenkins and Arifin do not specifically treating the patients based on the increased risk of dying.
However, Sonnevill teaches, “Because there is no specific treatment for SAE yet, treatment should focus on control of infection source and supportive measures, such as management of organ failure(s), prevention of metabolic disturbances, and avoidance of neurotoxic drugs. Preventive strategies to reduce occurrence and duration of brain dysfunction should be applied for every patient admitted to the ICU (Table 4). Symptomatic treatment of delirium and agitation does not differ from that propose in critically ill patients and has been described elsewhere [92]. Adjunctive therapies of septic shock may protect the BBB or reduce endothelial activation, but their effect has not been established. For instance, activated protein C in septic shock patients with impaired consciousness significantly reduced plasma levels of S100-β protein [93]. Steroids have been shown to reduce posttraumatic stress syndrome [94] and prevention of prolong hyperglycemia also may be neuroprotective.” (page 7, 2nd column).
Mai teaches, “We sought to further investigate the relationship between
cfDNA and sepsis pathophysiology by modifying levels of cfDNA with DNase.” (page 171, 1st column, 1st full paragraph). Ma teaches, “In summary, our studies are the first to demonstrate that delayed administration of DNase may be protective in experimental
sepsis. The timing of DNase administration may be a crucial element in future investigations of the therapeutic potential of DNase in sepsis.” (page 172).
Dellinger teaches an update to “surviving sepsis campaign for guidelines for management of Severe sepsis and septic shock (objective). Dellinger teaches diagnostic criteria for sepsis (table 1), severe sepsis (table 2). Dellinger teaches methods of management of sepsis *page 587-
Therefore it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the claims to treat sepsis and thus GCS and/or increased cfDNA in septic patients. The artisan would be motivated to provide the best treatment to the subject to prolong life. The artisan would have a reasonable expectation of success as the artisan is merely using known methods to treat known conditions.
Claims 20-22 merely set forth the intended outcome of the claims and do materially change the active steps of the claims. Thus they are obvious over the art of record. Further the art also enders the limitations obvious as detailed below.
With regards to claim 20, Saukkonen and Clementi teach cfDNA is increased.
With regards to claim 21, Lokhandwala teaches lactate changes over time (figure 1).
With regards to claim 22, Lokhandwala teaches lactate changes over time (figure 1)Afirin teaches decrease in GCS scores of 15 to less than 8. Thus it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date, that scores must change over time as it takes time to give the test and see differences. Thus it would have been prima facie obvious to one of ordinary skill in the art prior to the effective filing date of the claims both the GCS and lactate would change over time. The artisan would be motivated as the art suggests both GCS and lactate change. The artisan would have a reasonable expectation of success as the artisan is merely using known data observed over time.
The specification teaches, “the name Longitudinal Logit Model to this version, which is analogous to the CLOGLOG model” (0080) Thus claims 23-24 are obvious over the art of record.
Response to Arguments
The response traverses the rejection asserting, “This is important because the claimed combination has been determined to yield a better than expected predictive power with an AUC of 0.9, which has not previously been achieved using similar but different biological indicator combinations. Prior methods have the following predictive powers: APACHE II (AUC=0.77) but also MODS (AUC=0.80) and SOFA (AUC=0.86) “ This argument has been thoroughly reviewed but is not considered persuasive as the instant claims recite, “detecting in biological samples obtained from the patient levels of time-varying biological indicators comprising circulating free DNA (cfDNA), protein C, lactate, platelet count, and creatinine, and determining a Glasgow Coma Score (GCS) time-varying biological indicator of the patient, at a plurality of time points from a day 1 up to 28 days.” Thus the claims encompass obtaining a single sample and assaying overtime. Further the claims encompass any biological sample, while the teachings of the specification are limited to blood levels of circulating free DNA (cfDNA), protein C, lactate, platelet count, and creatinine. Further it appears the claims are limited to “Glasgow Coma Score (GCS) time-varying biological indicator” however, Schouela (GCS Remastered: Recent Updates to the Glasgow Coma Scale (GCS-P), July 2018) teaches GCS has changed . Thus the GCS prior to filing appears to be different than that of 2018.
The response continues providing arguments with respect to a novel combination of biological markers. This argument has been thoroughly reviewed but is not considered persuasive as the art demonstrates the variables were previously known markers of sepsis as detailed above. Thus the rejection is maintained.
Summary
No claims allowed.
Conclusion
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/Steven Pohnert/Primary Examiner, Art Unit 1683