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 .
Applicant’s election without traverse of Group I, claims 1-11 in the reply filed on 07/13/2026 is acknowledged. Accordingly, claims 12-29 are withdrawn from consideration as non-elected group.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/19/2023 and 01/22/2025 was noted and the submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings were received on 10/19/2023. These drawings are acknowledged.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-8 and 10-11 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ariosto Silva et al. (Journal of Visualized Experiments, (101), e53070, 2015).
Silva discloses a method of measuring tumor chemosensitivity in a subject with multiple myeloma (an ex vivo platform for the prediction of clinical response in multiple myeloma (Title). In one embodiment, Silva discloses a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and heterogeneity of patient-derived multiple myeloma (MM) cells. This approach consists in seeding primary MM cells freshly extracted from bone marrow aspirates into microfluidic chambers implemented in multi-well plates, each consisting of a reconstruction of the bone marrow microenvironment, including extracellular matrix (collagen or basement membrane matrix) and stroma (patient-derived mesenchymal stem cells) or human-derived endothelial cells (HUVECs). The chambers are drugged with different agents and concentrations, and are imaged sequentially for 96 hours through bright field microscopy, in a motorized microscope equipped with a digital camera. Digital image analysis software detects live and dead cells from presence or absence of membrane motion, and generates curves of change in viability as a function of drug concentration and exposure time. These patient-tailored models can then be used to simulate therapeutic regimens and estimate clinical response (abstract). The culture media (comprising 384 or 1,536-multi well plates) in each well is supplemented with the patient's own plasma, and the plate Is incubated overnight for stroma adhesion and equilibrium of soluble factors, Fig. 1); contacting the multiple myeloma cells with one or more individual anti-cancer agents and/or combinations of two or more anti-cancer agents (next day, the plate is drugged up to 31 drugs in a 384-well plates and 127 drugs in a 1,536-well plate and placed in a microscope for bright-field live Imaging for 4 days, Fig. 1); taking an Image of said multiple myeloma cells at least two times (placed in a microscope for bright-field live imaging for 4 days one picture every 30 minutes, Fig. 1); and applying an image analysis algorithm to said images to determine viability across time and/or concentration (digital image analysis algorithm quantifies cell death and generates ex vivo dose response curves, which in turn are used to parameterize patient/drug-specific mathematical models of chemosensitivity. Silva discloses that the significance of the protocol is the ability of assess drug response of primary cancer cells in an ex vivo reconstruction of the bone marrow microenvironment in a non-destructive manner, so that sequential measurements can be made, thus providing much more detailed information of the pharmacodynamics, rather than at fixed time points. The current assay allows assessment of viability across any range of drug concentrations, since each well is a separate entity (Supplemental Figure 4). Additional disclosure includes that the main innovations of the platform are: (a) small number of cancer cells required (1,000-10,000 per drug concentration); (b) assessment of drug efficacy in physiological conditions (extracellular matrix, stroma, patient-derived growth factors); (c) No toxicity from viability markers since only bright field imaging is used, thus no need to transfect cells with fluorescence or bioluminescence; (d)
continuous imaging provides drug effect as a function of concentration and exposure time (pharmacodynamics); and (e) the integration between in vitro and computational evolutionary models, to estimate clinical outcome (page 2).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-11 are rejected under 35 U.S.C. 103 as being unpatentable over Silva et al, (US 2016/0258931) in view of Ariosto Silva et al. (Journal of Visualized Experiments, (101), e53070, 2015) (herein after ‘Silva).
Silva discloses non-destructive methods for quantifying cell viability, the method can comprise culturing a plurality of cells from a subject in a chamber; capturing a first optical signal from the cells at a first time point; capturing a second optical signal from the cells at a second time point; analyzing the first optical signal and the second optical signal to detect cell membrane motion of the cells; and analyzing the cell membrane motion to quantify the viability of the cells (0007). Methods can be used to test cytotoxicity of a drug on abnormal cells, such as an antineoplastic drug on cancer cells (examples, the cells are cancer cells, which can include solid tumor cells or hematological cancer cells (e.g., multiple myeloma) (0008). Active agent can comprise an anticancer agent, such as a chemotherapeutic agent. In some examples, the active agent can comprise a combination of active agents. For example, the anticancer agent can be a composition comprising melphalan, bortezomib, FAM-HYD-1, Marizomib (NPI-0052), Carfilzomib, Cytoxan, Dexamethasone, Thalidomide, Lenalidomide, Oprozomib, Panobinostat, Quisinostat, and Selinexor, or any combination thereof (0011). n some examples, the first optical signal, the second optical signal, or a combination thereof involves any optical microscopy illumination techniques suitable to detect cell membrane activity, such as a bright field illumination, dark field illumination, and phase contrast illumination (0012). In one embodiment, the methods comprise first preparing a three-dimensional dose-response curve by assessing the viability of cells from the subject in response to the active agent at a plurality of time points at a plurality of dosages. The method can then involve generating a multi-parameter model that summarizes the three-dimensional dose-response curve. The multi-parameter model can then be used to calculate the rate of accumulation of damage in the cells due to the active agent and the active agent-induced cell death due to the accumulated damage. The rate of accumulation of damage in the cells and the active agent-induced cell death due to the accumulated damage can then be extrapolated to predict a response of the subject to the active agent. For example, a three-dimensional dose-response curve based on 2, 3, 4, 5, 6, 7 days of viability data can be extrapolated to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more years of response by the subject (0015). The methods further comprise selecting a cancer treatment regimen for the subject based on predicted responses to 2, 3, 4, 5, 6, 7, 8, 9, 10, or more different active agents (0016). FIG 9 primary MM cells in co-culture with patient stroma are significantly more resistant to melphalan. Digital images analysis identified live cells and cells were imaged every 5 minutes for 48 h (0028). In some examples, methods comprising a dose-response platform, for in vitro screening of drugs, the in vitro component can include a 3D reconstruction of a cancer microenvironment, e.g., including primary cancer cells, extracellular matrix, and patient-derived stroma and growth factors, live microscopy and digital image analysis can be used to detect cell death events in different drug concentrations, which can then be used to generate dose-response surfaces and from the in vitro data, the model can identify the size and chemosensitivity of subpopulations within the patient's tumor burden, and simulate how the tumor would respond to the drug(s) in physiological conditions in a clinical regimen (0068).
Silva fails to disclose image analysis algorithm to images to determine viability across time and/or concentration forming a model of drug sensitivity.
‘Silva discloses a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and heterogeneity of patient-derived multiple myeloma (MM) cells (abstract). The method comprises contacting the multiple myeloma cells with one or more individual anti-cancer agents and/or combinations of two or more anti-cancer agents (e next day, the plate is drugged. up to 31 drugs in a 384-well plates and 127 drugs in a 1,536-well plate and placed in a microscope for bright-field live Imaging for 4 days, Fig. 1); taking an Image of said multiple myeloma cells at least two times (placed in a microscope for bright-field live imaging for 4 days one picture every 30 minutes, Fig. 1); and applying an image analysis algorithm to said images to determine viability across time and/or concentration (digital image analysis algorithm quantifies cell death and generates ex vivo dose response curves, which in turn are used to parameterize patient/drug-specific mathematical models of chemosensitivity. Additional disclosure includes that the main innovations of the platform are: (a) small number of cancer cells required (1,000-10,000 per drug concentration); (b) assessment of drug efficacy in physiological conditions (extracellular matrix, stroma, patient-derived growth factors); (c) No toxicity from viability markers since only bright field imaging is used, thus no need to transfect cells with fluorescence or bioluminescence; (d) continuous imaging provides drug effect as a function of concentration and exposure time (pharmacodynamics); and (e) the integration between in vitro and computational evolutionary models, to estimate clinical outcome (page 2).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate image analysis algorithm to determine viability across time and/or concentration forming a model of drug sensitivity as taught by ‘Saliva into Silva’s method of testing cytotoxicity of a drug on abnormal cells. The person of ordinary skill in the art would have motivated to make those modifications because ‘Silva teaches that discloses that the significance of the protocol (method of measuring tumor chemosensitivity) is the ability of assess drug response of primary cancer cells in an ex vivo reconstruction of the bone marrow microenvironment in a non-destructive manner, so that sequential measurements can be made, thus providing much more detailed information of the pharmacodynamics, rather than at fixed time points. The current assay allows assessment of viability across any range of drug concentrations, since each well is a separate entity (Supplemental Figure 4) and reasonably would have expected success because ‘Silva teaches that the protocol extends this original assay into a high-throughput organotypic dose-response platform, for in vitro screening of drugs, based on a digital image analysis algorithm to non-destructively quantify cell viability and from in vitro data , a mathematical model identifies the size and chemosensitivity of sub-populations within the patient’s tumor burden, and can be used to simulate how the tumor would respond to the drug(s) in physiological conditions in a clinical regimen.
Conclusion
No claims are allowed at this time.
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/J.R.S/Examiner, Art Unit 1618 /JAKE M VU/Primary Examiner, Art Unit 1618
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