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 19-43 are cancelled.
Claims 1-18 are currently pending and under exam herein.
Claims 1-18 are rejected.
Claims 11 and 18 are objected to.
Priority
The instant application claims benefit to provisional application No. 63/194,987 filed on 29 May 2021. It is noted that 29 May 2022 was a Saturday and 30 May 2022 was a holiday. Domestic benefit is acknowledged. At this point in examination, the effective filing date of claims 1-18 is 29 May 2021.
Information Disclosure Statement
No information disclosure statement has been filed.
Drawings
The drawings filed on 31 May 2022 are received and accepted.
Specification
The disclosure is objected to because of the following informalities:
Paragraph [0021]: “logistical regression” should read “logistic regression” (see claim objections)
Paragraph [0107]: “computing device 200” should read “computing device 400”
Paragraph [0113]: “models database 606” should read “models database 606D” or “models database 606d”
Appropriate correction is required.
Claim Objections
Claim 11 is objected to because “using a logistical regression” should read “using a logistic regression.” Thus, the recitation of “logistical regression” in claim 11 is understood to mean “logistic regression,” and claim 11 should be corrected to recite such.
Claim 18 is objected to because it recites “treating the specific patient for one of IBD, RA, JIA, AS, PsO, PsA, MS,” without defining the meaning of each acronym in the claims. This objection may be overcome by completely spelling out each acronym on its initial appearance in the claims, followed by the acronym in parentheses.
Claim Interpretation
Claim 1 recites a method containing the limitation “useful for adjusting at least one of a dose and a dose interval of a dosing regimen of the drug for administering to the specific patient.” The language of “useful for” raises a question as to its limiting effect on the claim. Under MPEP 2111.04, claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed. A whereby clause in a method claim is not given weight when it simply expresses the intended result of a process step positively recited. See Hoffer v. Microsoft Corp., 405 F.3d 1326, 1329, 74 USPQ2d 1481, 1483 (Fed. Cir. 2005). The limitation of claim 1 simply expresses the intended use of the nomogram resulting from the method of claim 1. Therefore, the limitation “useful for adjusting at least one of a dose and a dose interval of a dosing regimen of the drug for administering to the specific patient” of claim 1 does not have a limiting effect on the claim.
Claim Rejections - 35 USC § 112
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 1-18 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 regards as the invention.
As stated in the MPEP, the meaning of every term used in a claim should be apparent from the prior art or from the specification and drawings at the time the application is filed. Claim language may not be "ambiguous, vague, incoherent, opaque, or otherwise unclear in describing and defining the claimed invention." In re Packard, 751 F.3d 1307, 1311, 110 USPQ2d 1785, 1787 (Fed. Cir. 2014). Although clear on its face, a claim may be indefinite when a conflict or inconsistency in the specification renders the scope of the claim uncertain. Accordingly, when there is more than one meaning for a term, it is incumbent upon applicant to make clear which meaning is being relied upon to describe the claimed invention.
The term “dosing regimen” in claim 1 is indefinite because the specification sets forth inconsistent definitions. In paragraph [0054], “’dosing regimen’ includes at least one dose amount of a drug or class of drugs and a recommended schedule for administering the at least one dose amount of the drug to a patient.” In paragraph [0058], “’dosing regimen’ may include a dose amount of a drug and a recommended schedule for administering the dose amount to a patient.” Therefore, claim 1 is rejected under 112(b) because the scope of the claim is rendered uncertain by the indefiniteness of the term “dosing regimen.” Claims 2-18 are similarly rejected under 112(b) due to their dependency on claim 1. This rejection may be overcome by making clear which meaning of “dosing regimen” is being relied upon to describe the claimed invention (i.e. remove one definition, or modify one definition to match the other).
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 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.
It is noted that “effective half-life” as used in claims 1-18 is defined in the specification at paragraph [0043] to mean “the rate of accumulation or elimination of a biochemical or pharmacological substance in an organism.” In the art, half-life is known as the time taken for the concentration of a substance to decrease by half its original value, while effective half-life is the time required to reduce the radioactivity level of an internal organ or of the whole body to exactly one half its original value due to both elimination and decay, as evidenced by Half Lives [NucMedTutorials (22 September 2020), para.1, at 1; para.1, at 6]. Because the pathway of elimination was not specified in the definition (i.e. radioactive decay or biological clearance), the term “effective half-life” recited in the claims will be seen as equivalent to the term known in the art as “half-life.”
Claims 1-3, 5-9, and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Strik (Scandinavian Journal of Gastroenterology, Vol. 56, (8 December 2020)), in view of Zhou (Journal of Pharmaceutical Sciences, Vol. 85, (August 1996)), Smith (J. Med. Chem., Vol. 61, (7 November 2017)), Munnink (Clin. Pharmacol. Ther., Vol. 99, (11 August 2015)), Pippenger (Cleveland Clinic Journal of Medicine, Vol. 51, (June 1984)), and Holford (Transl Clin Pharmacol., Vol. 26, (19 December 2018)), as evidenced by Useful PK Equations (University of Florida College of Pharmacy (31 January 2013)) and Certara (What are Compartmental Models? (5 January 2011)). The italicized text corresponds to the instant claim limitations.
Regarding claim 1, Strik discloses a method of using a computer system employing a two-compartment population pharmacokinetic (PK) model to treat a patient with a personalized dosing regimen of infliximab (IFX) [col.1 para.2, at 147] (a method of treating a specific patient with a personalized therapeutic dosing regimen of a drug comprising a monoclonal antibody or monoclonal antibody construct). Before personalization, optimization of the IFX dose occurs, in which the dose amount and/or interval is adjusted to achieve a trough level within a certain therapeutic range [col.1 para.2, at 146]. Strik teaches that personalization begins with identification of a patient’s target trough level [col.1 para.3, at 146] (receiving data indicative of a target drug trough concentration). The PK model receives data regarding the patient’s weight, measured IFX trough levels, and previous IFX doses, and forms a framework for providing a drug concentration curve [col.1 para.2, at 147; col.2 para.2, at 151] (receiving data indicative of a prior dose amount of the drug; data indicative of a patient's weight of the specific patient; and data indicative of a measured drug trough concentration in the specific patient). The system offers multiple potential times where a next corresponding dose amount can be administered to a patient, aiming to achieve the target trough concentration [col.2 para.6, at 151; col.1 para.2, at 146] (simulating a plurality of time-to-target values for the specific patient, each time-to- target value corresponding to an available dose in a plurality of available doses). Strik then determines the optimal dose amount and interval based on the measured IFX levels, and administers the new dose to the patient [col.1 para.2, at 147; col.1 para.2, at 149] (administering a new dose of the plurality of available doses of the drug to the specific patient).
Strik does not explicitly recite the data being received at an input module of a processor. However, Strik discloses that the method is computer-implemented [col.2 para.4, at 151]. Inherent in this disclosure are the components essential to the functionality of a computer, which includes a processor to receive information. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to receive the data at the input module of a processor.
Strik fails to teach the limitations of simulating an effective drug half-life range and a corresponding range of expected drug trough concentrations at the current dose interval based on the patient's weight, a range of drug clearance values, the current dose interval, and the prior dose amount of the drug; plotting the corresponding range of expected drug trough concentrations against the effective drug half-life range as a drug concentration curve on a nomogram; and determining an effective drug half-life of the specific patient based on the identified measured drug concentration on the drug concentration curve.
However, Zhou discloses a computer-implemented method of determining a dose release duration to maintain drug concentrations within a target range using a nomogram to assess the half-life values for a patient [Abstract, at 791]. Zhou teaches simulating a half-life range at dosing intervals of 12 and 24 hours based on the dosing interval and the target concentration to determine an optimal release duration for the specific patient [col.1 para.2, at 792] (simulating an effective drug half-life range based on the current dose interval). Zhou also simulates the corresponding concentration ratios, calculated from the target peak and trough concentrations, for each half-life value in the range [col.2 para.2, at 792]. Zhou plots the simulated half-life range against the corresponding concentration ratios as a concentration curve on a nomogram [Figure 3, at 794; col.2 para.3, at 793] (plotting the corresponding range of concentrations against the effective drug half-life range as a drug concentration curve on a nomogram). Zhou notes that clearance does not influence the optimal release duration, but clearance does affect the optimal dose amount [col.2 para.4, at 792]. A person having ordinary skill in the art would be motivated to modify Zhou’s method of simulating a half-life range to account for clearance to determine optimal dose amount.
As further taught by Smith, the dose required to achieve a maximum or minimum target exposure is related to half-life, t1/2, through the elimination rate constant, kel (t1/2 = ln(2)/kel) [Equation 1, col.2 para.2, at 4273]. The elimination rate constant is dependent on clearance, CL, and volume of distribution, Vd (kel = CL/Vd) [col.2 para.3, at 4278]. Smith discloses that the equation for half-life can be appreciated in terms of its determinants (t1/2 = ln(2)Vd/CL), which demonstrates that half-life is directly influenced by clearance [Equation 2, col.1 para.2, at 4276]. Thus, a person having ordinary skill in the art would understand that a half-life range accounting for clearance must be based on a range of clearance values when half-life depends on clearance and volume of distribution. Smith also teaches about the relationship between half-life and the current dosing interval [cols.1 and 2, at 4274]. Accumulation will increase as the half-life becomes a larger fraction of the dosing interval, and half-life values that are short relative to the dosing interval result in large swings in exposure, potentially incurring safety risks and suboptimal efficacy [cols.1 and 2, at 4274; col.1 para.1, at 4275]. A person having ordinary skill in the art would recognize that simulating a half-life range at the current dose interval based on a range of clearance values results in a more advantageous dosing regimen because half-life impacts accumulation and exposure levels relative to the current dosing interval.
The method of Zhou simulates the corresponding concentration for each half-life as a peak-to-trough ratio, but does not explicitly simulate expected trough concentrations. However, Munnink teaches that there is significant interpatient variability in the clearance of monoclonal antibodies (mAbs), which highly affects drug concentrations at the end of the dosing interval (trough concentration) [col.2 para.2, at 420]. Munnink discloses that mAb trough concentrations are predictive of long-term clinical outcomes [col.1 para.2, at 426]. A person having ordinary skill in the art would recognize that the expected drug concentration corresponding to each half-life should be predicted at trough because variability in clearance significantly impacts concentration at that exposure level, and the concentration at trough is informative of the long-term clinical efficacy of mAbs.
Munnink further discloses that a patient’s body weight influences drug concentrations by virtue of its relation to the volume of distribution [col.1 para.2 and col.2 para.1, at 421]. Pippenger discloses that knowledge of the patient’s weight and prior dose amount is necessary to mathematically determine the patient’s total daily drug dose in mg/kg, which in turn allows the prediction of the patient’s expected drug concentration [col.1 para.4, at 252]. A person having ordinary skill in the art would know that simulating a half-life range and a corresponding range of expected trough concentrations at the current dose interval must be based on the patient's weight, a range of drug clearance values, the current dose interval, and the prior dose amount.
Strik discloses a method of using a population PK model to treat a patient with a personalized dosing regimen of IFX. Zhou discloses a method of determining a release duration by simulating and plotting on a nomogram a half-life range and a corresponding drug concentration based on the dosing interval and the target concentration. Smith teaches that clearance influences half-life, and half-life impacts accumulation and exposure levels depending on the current dosing interval. Munnink teaches that clearance of mAbs is patient specific and highly affects trough concentrations, which are indicative of long-term clinical results. Pippenger discloses that the patient’s weight and prior dose amount are necessary to predict expected trough concentrations.
Through the teachings of Zhou, Smith, Munnink, and Pippenger, a person having ordinary skill in the art would recognize that modifying the method of Strik by simulating a half-life range and corresponding trough concentrations would result in an improved method of treating a specific patient by further personalizing and more accurately predicting an optimal dosing regimen because clearance is patient specific and significantly affects trough concentration, and half-life depends on clearance and significantly impacts the optimal dose amount and interval. Additionally, through the teachings of Zhou, Smith, Munnink, and Pippenger, a person having ordinary skill in the art would know that simulating a half-life range and corresponding concentration range should be based on the patient's weight, a range of drug clearance values, the current dose interval, and the prior dose amount.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the method of Strik with Zhou’s method of simulating and plotting a half-life range and corresponding concentration range based on the dosing interval, modified by Smith to be at the current dose interval based on a range of clearance values, further modified by Munnink and Pippenger to simulate trough concentrations based on the patient’s weight and the prior dose amount. A person of ordinary skill in the art would reasonably expect this modified method of Strik to result in an improved method of treating a patient with a personalized dosing regimen when considering a specific patient’s half-life because half-life depends on clearance, which is patient specific, and half-life and clearance influence the optimal dose amount and interval for a specific patient (simulating an effective drug half-life range and a corresponding range of expected drug trough concentrations at the current dose interval based on the patient's weight, a range of drug clearance values, the current dose interval, and the prior dose amount of the drug). Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Strik, modified by Zhou, Smith, Munnink, and Pippenger, fails to teach the limitations of identifying the measured drug trough concentration in the specific patient on the drug concentration curve on the nomogram; and determining an effective drug half-life of the specific patient based on the identified measured drug concentration on the drug concentration curve.
However, Holford discloses a method of reaching the best dosing regimen for a specific patient using a measured drug concentration to predict PK parameters [col.1 paras.1 and 3, at 153]. Holford teaches of the distinction between therapeutic drug monitoring (TDM), where dose adjustments occur when a measured concentration is outside a therapeutic range, and target concentration intervention (TCI), which identifies interpatient variability in parameters to predict the dosing regimen required to achieve the target exposure level [col.1 para.3 and col.2 para.1, at 152]. During TCI, Holford identifies a measured drug concentration in a patient on a drug concentration curve [col.1 para.3 and col.2 para.1, at 152; Figures 4 and 5] (identifying the measured drug concentration in the specific patient on the drug concentration curve). Based on the measured concentration and time identified on the concentration curve, Holford estimates the half-life of the patient [col.2 paras.2 and 3, at 153] (determining an effective drug half-life of the specific patient based on the identified measured drug concentration on the drug concentration curve). Holford notes that unless trough concentration is paired with a peak concentration, it is the least informative exposure level because clearance determines the average concentration and measuring a concentration in the middle of the dosing interval will be closer to the average [col.1 para.4, at 153]. Holford recommends using TCI when interpatient variability is high, such that group-based dosing (e.g. using weight or age) does not provide a safe and effective treatment for the whole group, because TCI can further reduce variability and improve the probability of patients being within an acceptable range around the target concentration [col.2 para.3, at 152].
Munnink teaches that there is significant interpatient variability in mAb clearance, which highly affects drug trough concentrations [col.2 para.2, at 420]. Munnink discloses that group-based dosing using body weight is typically employed for mAbs, but can be inaccurate at the extremes of body composition (i.e. lean or obese patients) [col.1 para.2 and col.2 para.1, at 421]. A person of ordinary skill would know that combining the TCI method of Holford with the method of Strik, modified by Zhou, Smith, Munnink, and Pippenger, would result in an improved method of treating a patient with a personalized dosing regimen of IFX because TCI can further reduce variability and improve the probability of patients being within an acceptable range around the target concentration. Additionally, while Holford notes that trough concentration alone is the least informative exposure level, Munnink teaches that the interpatient variability in mAb clearance highly affects trough concentrations. Therefore, one of ordinary skill in the art would know that the method of Strik, as modified by Zhou, Smith, Munnink, Pippenger, and Holford (hereinafter ZSMPH), should involve exposure levels at trough concentration. Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Regarding claim 2, Strik discloses a method of using a computer system employing a two-compartment population PK model to treat a patient with a personalized dosing regimen of IFX [col.1 para.2, at 147]. Strik does not explicitly disclose that a processor is configured with the pharmacokinetic model. However, as discussed above, a processor is inherent in a computer, and a computer system employing a PK model inherently has a processor configured with a PK model (wherein the processor is configured with a pharmacokinetic model). Strik discloses inputting data regarding the patient’s weight and previous IFX doses into the PK model [col.1 para.2, at 147; col.2 para.2, at 151] (inputting into the pharmacokinetic model the prior dose amount, and the patient weight). Through the PK model, the system predicts expected trough concentrations for each potential dosing time and amount before providing multiple potential times where a corresponding dose amount can be administered to achieve the expected trough concentration [col.1 para.2, at 146; col.1 para.2, at 147; col.2 para.6, at 151] (using the pharmacokinetic model, to provide a plurality of expected drug trough concentrations; outputting from the pharmacokinetic model the plurality of drug trough concentrations as the range of expected drug trough concentrations).
Strik, modified by ZSMPH, uses a population PK model to simulate an effective half-life range based on patient weight and a range of clearance values, and estimate the corresponding trough concentration for each clearance value (the range of drug clearance values, using the pharmacokinetic model, to provide a plurality of expected drug trough concentrations; computing, using the pharmacokinetic model, a plurality of effective drug half- lives for the patient weight, each effective drug half-life corresponding to a drug clearance value of the plurality of drug clearance values). The PK model receives data regarding the prior dose amount, the current dose interval, and the patient’s weight, and outputs the half-life range and the corresponding range of trough concentrations as a concentration-curve on a nomogram (inputting into the pharmacokinetic model the prior dose amount, the current dose interval, and the patient weight; outputting from the pharmacokinetic model the plurality of effective drug half- lives as the effective drug half-life range and the plurality of drug trough concentrations as the range of expected drug trough concentrations, wherein each drug trough concentration corresponds to an effective drug half-life of the plurality of effective drug half-lives).
Strik, modified by ZSMPH, does not explicitly incrementally step through a plurality of drug clearance values in the range of drug clearance values. However, the model produces a range of half-lives and trough concentrations based on a range of clearance values, meaning it inherently incrementally steps through clearance values when one trough concentration is calculated using one clearance value, as evidenced by Useful PK Equations [col.2 Trough (multiple dose), at 1 (showing trough depends on one elimination rate constant value); col.1 Elimination rate constant, at 1 (showing elimination rate constant depends on one clearance value)].
Regarding claim 3, Strik discloses a method of using a computer system employing a two-compartment PK model to treat a patient with a personalized dosing regimen [col.1 para.2, at 147]. Strik does not specify if the PK model is open or has a linear clearance and/or a linear first order absorption. However, the model is inherently an open two-compartment model because PK models are not closed systems, as evidenced by Certara [para.1 after 2-Compartment Model bullets]. Additionally, Munnink teaches that at therapeutic doses, mAb targets are generally saturated and mAb clearance is described by linear clearance [col.2 para.2, at 422]. Therefore, it would have been obvious to a person having ordinary skill in the art to modify the two-compartment PK model of Strik to include a linear clearance (the method of claim 2, wherein the pharmacokinetic model is an open two- compartment model with at least one of a linear clearance and a linear first order absorption). Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Regarding claim 5, Strik discloses that after an induction treatment, patients undergo maintenance dosing [col.1 para.1, at 145; col.2 para.2, at 146] (the method of claim 1, wherein the specific patient is a patient undergoing maintenance dosing and wherein the maintenance dosing begins with a first maintenance dose after an induction dosing period is completed).
Regarding claim 6, Strik discloses a method of using a computer system employing a two-compartment PK model to treat a patient with a personalized dosing regimen of infliximab (IFX) [col.1 para.2, at 147] (the method of claim 1, wherein the drug comprises infliximab).
Regarding claim 7, Strik discloses that the standard dosing for maintenance treatment of IFX is 5 mg/kg, and 28% of patients were receiving an intensified dosing regimen with either a higher dose or a shortened infusion interval at the start of receiving treatment via Strik’s method [col.2 para.7, at 151]. Thus, patient’s receiving treatment via Strik’s method receiving a prior dose amount of 5 mg/kg of IFX is inherent in the disclosure of Strik (the method of claim 6, wherein the prior dose amount comprises 5 mg/kg of infliximab).
Regarding claim 8, Strik discloses aiming to achieve and maintain an IFX trough concentration of 3 µg/mL [col.2 para.4, at 146] (the method of claim 7, wherein the target concentration is between 1 µg/mL and 20 µg/mL).
Regarding claim 9, Strik does not explicitly disclose treating a patient with a personalized dosing regimen of a drug other than IFX. However, Strik teaches that higher serum concentrations for fistula healing are needed for both IFX and adalimumab treatment [col.1 para.2, at 151]. Strik suggests using the disclosed method for patients with perianal fistulising disease at higher target concentrations [col.1 para.2, at 151]. Therefore, it would have been obvious to a person having ordinary skill in the art to treat a patient with perianal fistulising disease with a personalizing dosing regimen of adalimumab using the method of Strik, as modified by ZSPMH (the method of claim 1, wherein the drug comprises any one of adalimumab, vedolizumab, golimumab, ustekinumab, abatacept, rituximab, ixekizumab, certolizumab pegol, entanercept, dupilumab, tocilizumab, alemtuzumab, secukinumab, guselkumab, reslizumab, mepolizumab, omalizumab, benralizumab, sarilumab, risankizumab, tildrakizumab, ocrelizumab, and natalizumab). Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Regarding claim 16, while Strik does not explicitly teach setting a new dose interval for each of the of available doses to the plurality of time-to-target values for the specific patient, Strik discloses that the computer system optimizes dose and interval by advising an adjusted dosing interval and/or dose amount when indicated [col.1 para.2, at 149 - col.2 para.1, at 150]. Strike also discloses the system offering multiple potential times where a next corresponding dose amount can be administered to a patient to achieve the target trough concentration (time-to-target) [col. 2 para. 6, at 151; col. 1 para. 2, at 146]. Thus, the system can inherently set a dose interval for each dose amount to the multiple time-to-target values because it advises optimal dose amount and corresponding interval for a specific patient, and offers multiple time-to-target values that correspond to a dose amount.
Alternatively, a person having ordinary skill in the art would be motivated to modify the system of Strik to set a dose interval for each dose amount to the multiple time-to-target values. Strik teaches that multiple time-to-target values are provided for the convenience of the patient or physician to account for periods when dosing is not possible, such as during vacation times [col.2 para.6, at 151]. Knowing the dose interval for each dose amount when determining the optimal time-to-target value for the patient would provide further convenience to the patient and physician by allowing them to know future dosage times for each time-to-target value for the patient. Therefore, a person having ordinary skill in the art would be motivated to modify the method of Strik by setting a dose interval for each dose amount to the multiple time-to-target values for the patient (the method of claim 1, further comprising setting a new dose interval for each of the plurality of available doses of the drug for the specific patient to the plurality of time-to-target values for the specific patient). Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Regarding claim 17, Strik discloses using a Bayesian approach for PK modeling regardless of the new dose interval [col.1 para.3, at 146] (the method of claim 16, further comprising providing a recommendation to use Bayesian individualized dosing for the specific patient, in an event the new dose interval is less than a standard-of-care dose interval).
Regarding claim 18, Strik teaches treating patients for inflammatory bowel disease (IBD) with intravenous administration of IFX doses as recommended by the system [col.1 para.1, at 145; col.1 para.2, at 149 – col.2 para.1, at 150] (the method of claim 16, further comprising treating the specific patient for one of IBD, RA, JIA, AS, PsO, PsA, MS, atopic dermatitis, eczema, and asthma, with an intravenous or subcutaneous administration of the new dosage of the monoclonal antibody or the monoclonal antibody construct at the new dose interval).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Strik, Zhou, Smith, Munnink, Pippenger, and Holford as applied to claims 1-3, 5-9, and 16-18 above, and further in view of Haraya (Drug Metabolism and Pharmacokinetics, Vol. 34 (February 2019)) and Ammons (Neoplasia, Vol. 5 (April 2003)).
Regarding claim 4, Strik, modified by ZSMPH, does not explicitly simulate a range of half-lives between 2 days and 25 days. Strik discloses a method of treating a patient with a personalized dosing regimen of a mAb [col.1 para.2, at 147]. Munnink teaches of the significant interpatient variability in mAb clearance and half-life [col.2 para.1, at 419; col.2 para.2, at 420]. Additionally, Haraya teaches that most mAbs have a half-life of 5-25 days [col.1 para.1, at 25], while some mAbs have a half-life of only 2 days, as taught by Ammons [col.1 para.1, at 151].
A person having ordinary skill in the art would know that the method of treating a patient with a personalized dosing regimen of a mAb, as taught by Strik and modified by ZSMPH, should simulate a half-life range between 2 days and 25 days to account for all known mAb half-lives (the method of claim 1, wherein the effective drug half-life range comprises effective half-lives between 2 days and 25 days). When accounting for all known mAb half-lives during execution of the method of Strik, modified by ZSMPH, the system simulates both a half-life range between 2 and 25 days and a corresponding range of expected trough concentrations. The simulated ranges are plotted on a nomogram, and the nomogram is used to determine a patient’s half-life based on the patient’s measured trough concentration. Simulating all known mAb half-lives accounts for the significant interpatient variability in mAb clearance and half-life, which allows for an improved method of treating a patient with a personalized dosing regimen of a mAb. To illustrate, a method of simulating a half-life range between 5 and 25 days would not be able to provide a personalized dosing regimen to a patient with a mAb half-life of 2 days because their measured trough concentration would not be present on the nomogram to allow determination of the patient’s mAb half-life and, ultimately, optimal dosing regimen. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of treating a patient with a personalized dosing regimen of an mAb, as taught by Strik and modified by ZSMPH, by simulating a half-life range between 2 days and 25 days. One of ordinary skill in the art would reasonably expect that applying the known range of mAb half-lives to the method of Strik, modified by ZSMPH, would result in an improved method of treating a patient with a personalized dosing regimen of an mAb because it accounts for the significant interpatient variability in mAb half-life. Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Strik, Zhou, Smith, Munnink, Pippenger, and Holford as applied to claims 1-3, 5-9, and 16-18 above, and further in view of Powell (Clin. Pharmacol. Ther., Vol. 109 (January 2021)).
Regarding claim 10, Strik, modified by ZSMPH, fails to teach determining a label dosage for the drug by plotting a region of effective drug half-lives of patients who participated in clinical trials for the drug. Strik discloses a method of treating a patient with a personalized dosing regimen of a mAb [col.1 para.2, at 147]. Zhou discloses plotting the half-lives of simulated patients representing a wide range of potential pharmacokinetic cases [col.2 para.3, at 793] (plotting a region of effective drug half-lives of patients). Smith teaches that half-life is directly influenced by clearance [equation 2, col. 1 para. 2, at 4276]. Munnink teaches that the significant interpatient variability in mAb clearance highly affects a patient’s trough concentration, necessitating dosing adjustment to achieve maximal clinical efficacy and minimize adverse effects [col.2 para.2, at 420; col.1 para.3, at 423]. Additionally, Powell explains that a patient’s drug clearance can be predictive of whether a dosing regimen will be safe and effective for that patient [col.2 para.3, at 66]. Powell discloses that current drug labels typically either dose to a set biomarker or one dosing regimen is approved for all adult patients without accounting for the patient’s age, size, organ function, genetics, or drug interactions [col.1 para.1 & col.2 para.1, at 65]. Powell teaches that recently, companies have been expected to perform PK study clinical trials to determine whether interpatient variability in clearance necessitates dosing adjustment [col.2 para.3, at 66]. Depending on the efficacy and safety of a dosing regimen in the clinical trials, drug labels may reflect dosing adjustments for factors affecting a patient’s clearance based on observed PK alterations [col.2 para.3, at 66; col.1 para.2, at 67].
One of ordinary skill in the art would know that mAb labels should reflect dosing adjustments accounting for clearance because the significant interpatient variability in mAb clearance impacts the dosing regimen required to achieve a safe and effective mAb concentration. One of ordinary skill in the art would know that the label adjustments can be determined based on clinical data that provides a safe and effective dosing regimen for each patient, derived from the patient’s mAb clearance. One of ordinary skill in the art would appreciate that clearance can be accounted for by incorporating half-life when determining dosing regimen because half-life is indicative of clearance when half-life depends on clearance. Therefore, a person having ordinary skill in the art would know that combining the method of treating a patient with a personalized dosing regimen of a mAb where patient half-lives are plotted, as taught by Strik and modified by ZSMPH, could be used to provide dosing regimens for clinical trial patients with various half-lives to determine a label dosage for the mAb (the method of claim 1, further comprising determining a label dosage for the drug by plotting a region of effective drug half-lives of patients who participated in clinical trials for the drug). One of ordinary skill in the art would reasonably expect that using the method of Strik, modified by ZSMPH, to determine a label dosage for the mAb will result in a label dosage that is safer and more effective than previous one-size-fits-all dosage by providing dose adjustments for factors affecting a patient’s clearance based on observed PK alterations. Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Claims 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Strik, Zhou, Smith, Munnink, Pippenger, and Holford as applied to claims 1-3, 5-9, and 16-18 above, and further in view of Casteele (Clin. Gastroenterol. Hepatol., Vol.19 (4 May 2020)) and USDHHS (U.S. Department of Health and Human Services (January 2006)).
Regarding claim 11, Strik fails to teach generating a probability plot of a probabilities of a patient response over the effective drug half-life range, wherein the probabilities are determined using a logistical regression of a dataset for a patient population and the dataset comprises a patient response for each patient in the population. However, Casteele discloses using a population PK model to estimate a baseline IFX clearance for individual patients in a population, and multivariable logistic regression models to calculate the probability of endoscopic healing based on clearance and patient- and disease-related factors [col.2 para.3, at 1210; col.1 para.1, at 1211; col.2 para.2, at 1213] (wherein the probabilities are determined using a logistical regression of a dataset for a patient population). Casteele notes that the definition used for endoscopic healing is now more commonly referred to as mucosal healing [col.1 para.1, at 1215]. The population dataset of Casteele includes the estimated clearance for each patient, as well as C-reactive protein concentration and corticosteroid use for each patient [Table 1, at 1211] (the dataset comprises a patient response for each patient in the population). Casteele teaches that achieving mucosal healing with IFX is associated with beneficial long-term outcomes in patients, but there is significant interpatient variability in response to therapy [col.1 para.1, at 1210]. Casteele’s use of logistic regression models is associated with fewer hospitalizations and superior endoscopic and clinical outcomes by identifying patients with high and low mucosal healing probabilities before therapy initiation, which guides selection of effective treatment in a timely manner [col.1 para.2, at 1214; col.1 para.2, at 1215].
A person having ordinary skill in the art would be motivated to combine the method of treating a patient with a personalized dosing regimen of a mAb, as taught by Strik and modified by ZSMPH, with the logistic regression models, taught by Casteele, to identify patients with high and low mucosal healing probabilities and guide selection of effective treatment in a timely manner. One of ordinary skill in the art would appreciate that the half-life determined from the method of Strik, modified by ZSMPH, can be used in place of Casteele’s estimated clearance when determining the probability of mucosal healing because the interpatient variability in mAb clearance causes similar interpatient variability in mAb half-life when half-life depends on clearance. One of ordinary skill in the art would reasonably expect the combination to result in an improved method of treating a patient with a personalized dosing regimen of a mAb because the logistic regression models are associated with fewer hospitalizations and superior endoscopic and clinical outcomes. Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Casteete fails to teach generating a probability plot of a probabilities of a patient response over the effective drug half-life range. Casteele reports values as the median and interquartile range in table format [Table 1, at 1211; Supplementary Table 3, at 1217.e2]. USDHHS teaches that means or medians may not adequately convey the interpatient variability of responses to treatment, necessitating the display of individual responses by graphical representation [para. 1, at 10]. USDHHS notes that graphs are commonly used to convey dose-response information and to illustrate differences in magnitude of response [Common Uses of Graphs, at 12].
A person having ordinary skill in the art would know that the probability of mucosal healing as it relates to mAb half-life is best represented in graphical form due to the significant interpatient variability in mAb pharmacokinetics. One of ordinary skill in the art would reasonably expect a graphical representation of probabilities to result in an improved selection of effective treatment in a timely manner because the graph would adequately convey the interpatient variability of mAb half-life. Therefore, it would be obvious to a person having ordinary skill in the art to plot the probabilities of mucosal healing, as taught by Casteele, over the half-life range, as taught by Strik and modified by ZSMPH (the method of claim 1, further comprising generating a probability plot of a probabilities of a patient response over the effective drug half-life range, wherein the probabilities are determined using a logistical regression of a dataset for a patient population and the dataset comprises a patient response for each patient in the population). Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Regarding claim 12, Casteele discloses the patient population dataset including an IFX clearance for each patient, estimated using a population PK model, but does not disclose an effective half-life for each patient [Table 1, at 1211; col.2 para.3, at 1210]. The method of Strik, modified by ZSMPH, determines the effective half-life for each patient using a PK model. Smith teaches that half-life can be determined from clearance and volume of distribution, and half-life must be considered because it affects accumulation and exposure metrics, potentially incurring safety risks and suboptimal efficacy. [Equation 2, col.1 para.2, at 4276; cols.1 and 2, at 4274; col.1 para.1, at 4275]. Munnink teaches that there is significant interpatient variability in the clearance of mAbs, which highly affects trough concentrations [col.2 para.2, at 420]. A person of ordinary skill in the art could have substituted half-life for clearance, and the results of the substitution would have been predictable because both half-life and clearance are known elements relevant to the optimal dosing regimen (the method of claim 11, wherein the dataset further comprises an effective drug half-life for each patient in the population). The simple substitution of one known element for another is likely to be obvious when predictable results are achieved. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, B).
Regarding claim 13, Casteele discloses predicting the probability of achieving a positive Mayo score, and uses a population dataset that includes C-reactive protein concentration and corticosteroid use for each patient [col.1 para.1 and Table 1, at 1211] (the method of claim 12, wherein the patient response is one of. Crohn's disease activity index (CDAI), mucosal healing, fecal calprotectin (FCP) concentration, C-reactive protein (CRP) concentration, development of anti-drug antibodies (ADA), steroid usage, Mayo score, partial Mayo score, Harvey-Bradshaw index, and concentration of Factor VIII protein).
Claims 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Strik, Zhou, Smith, Munnink, Pippenger, and Holford as applied to claims 1-3, 5-9, and 16-18 above, and further in view of Sazonovs (Aleksejs Sazonovs et al., (9 September 2018)).
Regarding claim 14, Strik fails to teach generating a plot of probabilities of anti-drug antibody (ADA) presence over time, wherein a probability-time curve is generated for each of a set of effective drug half-life sub-ranges. Strik, modified by ZSMPH, discloses a method of treating a patient with a personalized dosing regimen of a mAb based on the patient’s half-life, which is indicative of the patient’s clearance. Munnink teaches that ADA formation is associated with increased mAb clearance and subsequently reduced mAb concentrations, which can result in loss of response to treatment [col.1 para.3, at 422]. Additionally, Sazonovs discloses identifying genetic variants associated with ADA development to allow the targeted use of immunomodulator therapy to minimize risk and maximize response [para.2, at 4; para.4, at 12]. Sazonovs analyzes the probability of ADA development over time, accounting for differences in covariates such as sex, drug type, and immunomodulator use for each patient [para.2, at 4] (probabilities of anti-drug antibody presence over time). Sazonovs plots the probability of ADA development over time as a probability-time curve for the covariates of interest [Figure 5, at 10] (wherein a probability-time curve is generated for each of a set of sub-ranges). Sazonovs notes that patients treated with IFX have a higher risk of ADA development than patients treated with adalimumab, and ADA formation is the most frequently cited cause of treatment failure, hypersensitivity reactions, and treatment discontinuation [paras.1 and 2, at 2].
Strik, modified by ZSMPH, contains a base method of treating a patient with a personalized dosing regimen of a mAb based on the patient’s half-life. Munnink demonstrates that ADA development is a known problem in the art. Sazonovs contains a technique of identifying genetic variants associated with ADA development to minimize risk and maximize response to treatment with IFX or adalimumab. A person having ordinary skill in the art would recognize that associating ADA development with patient-specific characteristics, as taught by Sazonovs, can be applied to the method of treating a patient with a personalized dosing regimen of a mAb based on the patient’s half-life, as taught by Strik and modified by ZSMPH. The resulting method would predictably identify half-lives associated with higher ADA development. One of ordinary skill in the art would appreciate that the resulting method would be an improved system of treating a patient with a personalized dosing regimen of a mAb because the system provides an indication of patients at a higher risk of ADA development based on half-life, which allows for dose adjustment to avoid treatment failure, hypersensitivity reactions, and treatment discontinuation. Applying a known technique to a known method ready for improvement to yield predictable results is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, D).
Moreover, a person having ordinary skill in the art would be motivated to combine associating ADA development with patient-specific characteristics, as taught by Sazonovs, with the method of treating a patient with a personalized dosing regimen of a mAb, as taught by Strik and modified by ZSMPH, to allow targeted use of immunomodulator therapy to minimize risk and maximize response. One of ordinary skill in the art would reasonably expect the combination to result in an improved method of treating a specific patient with a safe and effective mAb dosing regimen because ADA formation is the most frequently cited cause of treatment failure, hypersensitivity reactions, and treatment discontinuation. Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, G).
Regarding claim 15, Sazonovs evaluates the time to ADA development for patients based on the patient’s genetic variation [para.4, at 1; para.1, at 11]. As discussed above, a person having ordinary skill in the art would recognize that the ADA development association technique can be applied to the method of treating a patient based on the patient’s half-life to predictably result in a system that identifies half-lives associated with higher ADA development. One of ordinary skill in the art would understand that when associating ADA development with patient-specific characteristics, that characteristic must be used in the estimation of ADA development. When the technique of Sazonovs is applied to the method of Strik, modified by ZSMPH, the evaluation of the time to ADA development for patients must be based on the patient’s half-life (the method of claim 14, further comprising evaluating a time-to-first-anti- drug-antibody value for the specific patient based on the determined effective drug half- life). Applying a known technique to a known method ready for improvement to yield predictable results is likely to be obvious. See KSR International Co. v. Teleflex Inc., 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) (see MPEP § 2143, D).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
William J. Spruill et al., Concepts in Clinical Pharmacokinetics, 6th ed., American Society of Health-System Pharmacists, ISBN: 978-1-58528-387-3 (2014). Explains known PK modeling techniques and provides PK equations applicable to general models and drug specific models.
Iris Dotan et al., Patient factors that increase infliximab clearance and shorten half-life in inflammatory bowel disease: a population pharmacokinetic study, Inflamm Bowel Dis., Vol. 20 (1 December 2014). Discusses association between IFX clearance and half-life, and articulates various patient-specific factors that impact both.
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/E.A.D./ Examiner, Art Unit 1685
/OLIVIA M. WISE/ Supervisory Patent Examiner, Art Unit 1685