Classifications

• • C—CHEMISTRY; METALLURGY
  • C07—ORGANIC CHEMISTRY
  • C07K—PEPTIDES
  • C07K16/00—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
  • C07K16/18—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans
  • C07K16/28—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
  • C07K16/2839—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants against the integrin superfamily
  • C07K16/2842—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants against the integrin superfamily against integrin beta1-subunit-containing molecules, e.g. CD29, CD49
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
  • A61P25/00—Drugs for disorders of the nervous system
  • A61P25/28—Drugs for disorders of the nervous system for treating neurodegenerative disorders of the central nervous system, e.g. nootropic agents, cognition enhancers, drugs for treating Alzheimer's disease or other forms of dementia
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
  • A61K39/00—Medicinal preparations containing antigens or antibodies
  • A61K2039/505—Medicinal preparations containing antigens or antibodies comprising antibodies

Definitions

• MS Multiple sclerosis
• RMS relapsing
• RRMS relapsing-remitting
• PPMS primary progressive multiple sclerosis
• PPMS primary progressive multiple sclerosis
• SPMS secondary progressive multiple sclerosis
• abundant clinical, imaging, and genetic data suggest that PPMS is a part of the spectrum of progressive MS phenotypes, and analyses of natural history cohorts demonstrate that worsening proceeds at a similar rate in both SPMS and PPMS.
• MRI magnetic resonance imaging
• Tysabri® is an anti-very late antigen (VLA)-4 humanized monoclonal IgG4 antibody that inhibits the migration of lymphocytes throughout the blood-brain barrier by blocking VLA-4 interactions with vascular cell adhesion molecules (VCAM)-l and reducing inflammatory lesions.
• VLA very late antigen
• VCAM vascular cell adhesion molecules
• natalizumab is only used in patients who have had at least one relapse event, as determined by their clinician, while in Europe natalizumab treatment requires the diagnosis of at least one relapse event along with the identification of at least one acute lesion (typically defined as an increase in lesion load/size in a T2 or a T1 gadolinium-enhanced lesion on MRI).
• at least one acute lesion typically defined as an increase in lesion load/size in a T2 or a T1 gadolinium-enhanced lesion on MRI.
• the present disclosure provides methods for treating and/or reducing chronic white matter lesion activity (CWMLA), also referred to as chronic lesion activity (CLA), in patients in need thereof, including Radiologically Isolated Syndrome (RIS) patients, with appropriate disease modifying therapies, e.g. anti-VLA-4 antibodies.
• CWMLA chronic white matter lesion activity
• RIS Radiologically Isolated Syndrome
• the present invention demonstrates that certain presentations of CWMLA visible with specific magnetic resonance imaging techniques correlate with disease progression, and thus patients having this confluence of radiological markers can be effectively treated with more aggressive disease-modifying antibody therapies even in the absence of the clinical manifestations (e.g, relapses) conventionally used to justify such therapies.
• the disclosure provides methods for treating Radiologically Isolated Syndrome (RIS) in a patient in need thereof comprising administering a therapeutically effective amount of a disease-modifying antibody therapy to said patient, wherein said patient has CWMLA as defined by at least one phase rim lesion (PRL) in at least one susceptibility-weighted magnetic resonance image (MRI).
• RIS Radiologically Isolated Syndrome
• the patient has CWMLA as defined by at least one phase rim lesion (PRL) in at least one susceptibility-weighted magnetic resonance image (MRI).
• PRL phase rim lesion
• MRI susceptibility-weighted magnetic resonance image
• SEL slowly expanding lesion
• the patient has CWMLA as defined by at least one SEL that is detected using single time-point non-contrast Tl- and T2-weighted MRI.
• the patient has CWMLA as defined by at least one SEL that co localizes with at least one PRL, or vice-versa.
• the at least one SEL is detected using single time-point non-contrast Tl - and T2-weighted MRI.
• the SEL is detected using a machine-learning based classifier that discriminates acute from chronic MS lesions, and/or SEL from non-SEL, using unenhanced T1/T2 information from a single MRI scan.
• a patient suspected of having RIS, or a patient previously identified as having RIS and at further risk of developing MS may be referred for an MRI scan of the brain at a single time point, and without agent contrast.
• the scan may then be input into the classifier algorithm, which may identify and distinguish between acute and chronic lesions present on the brain scan, and/or between SEL and non-SEL. Based on that identification and distinction, an appropriate disease-modifying antibody therapy can be administered that is suitable to the particular patient and disease state.
• one or more features having predictive value with respect to the classification of a lesion as either acute or chronic and/or as SELs are utilized.
• said features are selected from the group comprising or consisting of: features that quantify the first order intensity of the core region of a lesion as it appears on a T2-weighted scan image; features that quantify the amount of signals appearing as low-gray around the periphery of a lesion as it appears on a Tl -weighted scan image; features that quantify the amount of high-gray signals that are present in the periphery and/or core of a lesion as it appears on a Tl-weighted scan image; features that relate to the inhomogeneity present in the images; features that relate to the structure of the image, as relating to the presence of repeating patterns; and features that relate to the texture of the images.
• the disease-modifying antibody therapy is selected from natalizumab, BIIB107 and ocrelizumab.
• the disease-modifying antibody therapy is an anti-VLA-4 antibody, e.g. natalizumab or BIIB107.
• the anti-VLA-4 antibody is natalizumab administered in a biphasic dosing regimen, wherein the biphasic regimen comprises an induction phase comprising administration of natalizumab once a month for about 10 to about 14 months followed by a chronic phase comprising administration of natalizumab once every 5, 6, 7, or 8 weeks.
• the induction phase comprises administration of natalizumab once a month for about 10 months, about 11 months, about 12 months, about 13 months, about 14 months, or longer than about 14 months.
• at least one phase of a biphasic dosing regimen comprises subcutaneous (SC) administration.
• both the induction phase and chronic phase of a biphasic dosing regimen comprises SC injection.
• the induction phase of a biphasic dosing regimen comprises SC injection.
• the chronic phase of a biphasic dosing regimen comprises SC injection.
• the SC dosing and amount of natalizumab can be consistent with IV dosing.
• the therapeutically effective amount administered during the induction phase and the chronic phase are the same, and the therapeutically effective amount is between 250 - 450 mg (e.g. 250 mg, 300 mg, 350 mg, 400 mg, or 450 mg), more preferably about 300 mg, still more preferably 300 mg.
• the therapeutically effective amount administered SC during the chronic phase is between 300 - 500 mg (e.g., 300 mg, 350 mg, 400 mg, 450 mg, or 500 mg).
• the therapeutically effective amount is between about 250 - about 450 mg (e.g, about 250 mg, about 300 mg, about 350 mg, about 400 mg, or about 450 mg), more preferably about 300 mg, still more preferably 300 mg.
• the therapeutically effective amount administered SC during the chronic phase is between about 300 - about 500 mg (e.g, about 300 mg, about 350 mg, about 400 mg, about 450 mg, or about 500 mg), more preferably about 300 mg, still more preferably 300 mg.
• the anti-VLA-4 antibody is natalizumab administered in a chronic dose regimen, wherein the chronic dosing regimen comprises administration of natalizumab at a fixed interval of every 4 weeks.
• the chronic dosing regimen is a fixed, non-weight based amount of natalizumab.
• a therapeutically effective amount of natalizumab is between about 250 - 450 mg, or about 300 mg.
• a therapeutically effective amount of natalizumab is a fixed, non-weight based dose of 300 mg.
• the chronic dosing regimen is every 4 weeks for a period of about 4 months, about 5 months, about 6 months, about 7 months, about 8 months, about 9 months, about 10 months, about 11 months, about 12 months, or longer than about 12 months.
• the chronic dosing regimen comprises SC injection.
• the chronic dosing regimen comprises IV administration.
• treatment with anti-VLA-4 therapy is initiated when at least 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s total T2 hyperintense lesion volume and/or number is identified as PRL.
• treatment with anti-VLA-4 therapy is initiated when at least 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s total T2 hyperintense lesion volume and/or number is identified as SEL.
• treatment with anti-VLA-4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s SELs co-localize with their PRLs.
• treatment with anti-VLA-4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s PRLs co localize with their SELs.
• the invention provides methods of reducing and/or treating chronic active white matter lesions in an asymptomatic and/or early-stage MS patient (e.g. having no diagnosed relapses, or fulfilling consensus diagnostic criteria, e.g. Thompson AJ et al. Lancet Neurol. 2018; 17:162-173) comprising administering a therapeutically effective amount of a disease-modifying antibody therapy to said patient, wherein said patient has CWMLA as defined by at least one phase rim lesion (PRL) in at least one susceptibility-weighted magnetic resonance image (MRI).
• PRL phase rim lesion
• MRI susceptibility-weighted magnetic resonance image
• the patient has CWMLA as defined by at least one slowly expanding lesion (SEL).
• SEL slowly expanding lesion
• the patient has CWMLA as defined by at least one SEL that is detected using single time-point non-contrast Tl- and T2-weighted MRI.
• the patient has CWMLA as defined by at least one SEL that co localizes with at least one PRL, or vice-versa.
• the at least one SEL is detected using single time-point non-contrast Tl - and T2-weighted MRI.
• the SEL is detected using a machine-learning based classifier that discriminates acute from chronic MS lesions and/or SEL from non-SEL using unenhanced T1/T2 information from a single MRI scan.
• a machine-learning based classifier that discriminates acute from chronic MS lesions and/or SEL from non-SEL using unenhanced T1/T2 information from a single MRI scan.
• an asymptomatic and/or early stage patient suspected of having a brain ailment such as MS, or an asymptomatic and/or early stage patient at risk of developing MS may be referred for an MRI scan of the brain at a single time point, and without agent contrast.
• the scan may then be input into the classifier algorithm, which may identify and distinguish between acute and chronic lesions present on the brain scan, and/or between SEL and non-SEL. Based on that identification and distinction, an appropriate disease-modifying antibody therapy can be administered that is suitable to the particular patient and disease state.
• one or more features having predictive value with respect to the classification of a lesion as either acute or chronic and/or as SELs are utilized.
• said features are selected from the group comprising or consisting of: features that quantify the first order intensity of the core region of a lesion as it appears on a T2-weighted scan image; features that quantify the amount of signals appearing as low-gray around the periphery of a lesion as it appears on a T1 -weighted scan image; features that quantify the amount of high-gray signals that are present in the periphery and/or core of a lesion as it appears on a Tl-weighted scan image; features that relate to the inhomogeneity present in the images; features that relate to the structure of the image, as relating to the presence of repeating patterns; and features that relate to the texture of the images.
• the disease-modifying antibody therapy is selected from natalizumab, BIIB107 and ocrelizumab.
• the disease-modifying antibody therapy is an anti-VLA-4 antibody, e.g. natalizumab or BIIB107.
• the anti- VLA-4 antibody is natalizumab administered in a biphasic dosing regimen, wherein the biphasic regimen comprises an induction phase comprising administration of natalizumab once a month for about 10 to about 14 months, followed by a chronic phase comprising administration of natalizumab once every 5, 6, 7 or 8 weeks.
• the induction phase comprises administration of natalizumab once a month for about 10 months, about 11 months, about 12 months, about 13 months, about 14 months, or longer than about 14 months.
• at least one phase of a biphasic protocol comprises subcutaneous (SC) administration.
• both the induction phase and chronic phase of a biphasic dosing regimen comprises SC injection.
• the induction phase of a biphasic dosing regimen comprises SC injection.
• the chronic phase of a biphasic dosing regimen comprises SC injection.
• the SC dosing and amount of natalizumab can be consistent with IV dosing.
• the therapeutically effective amount administered during the induction phase and the chronic phase are the same, and the therapeutically effective amount is between 250 - 450 mg ( e.g . 250 mg, 300 mg, 350 mg, 400 mg, or 450 mg), more preferably about 300 mg, still more preferably 300 mg.
• the therapeutically effective amount administered SC during the chronic phase is between 300 - 500 mg (e.g., 300 mg, 350 mg, 400 mg, 450 mg, or 500 mg).
• the therapeutically effective amount is between about 250 - about 450 mg (e.g, about 250 mg, about 300 mg, about 350 mg, about 400 mg, or about 450 mg), more preferably about 300 mg, still more preferably 300 mg.
• the therapeutically effective amount administered SC during the chronic phase is between about 300 - about 500 mg (e.g. , about 300 mg, about 350 mg, about 400 mg, about 450 mg, or about 500 mg), more preferably about 300 mg, still more preferably 300 mg.
• the anti-VLA-4 antibody is natalizumab administered in a chronic dose regimen, wherein the chronic dosing regimen comprises administration of natalizumab at a fixed interval of every 4 weeks.
• the chronic dosing regimen is a fixed, non-weight based amount of natalizumab.
• a therapeutically effective amount of natalizumab is between about 250 - 450 mg, or about 300 mg.
• a therapeutically effective amount of natalizumab is a fixed, non-weight based dose of 300 mg.
• the chronic dosing regimen is every 4 weeks for a period of about 4 months, about 5 months, about 6 months, about 7 months, about 8 months, about 9 months, about 10 months, about 11 months, about 12 months, or longer than about 12 months.
• the chronic dosing regimen comprises SC injection.
• the chronic dosing regimen comprises IV administration.
• treatment with anti-VLA-4 therapy is initiated when at least 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s total T2 hyperintense lesion volume and/or number is identified as PRL.
• treatment with anti-VLA-4 therapy is initiated when at least 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s total T2 hyperintense lesion volume and/or number is identified as SEL.
• treatment with anti-VLA-4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s SELs co-localize with their PRLs.
• treatment with anti-VLA-4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s PRLs co localize with their SELs.
• methods for reducing and/or treating chronic white matter lesion activity in an asymptomatic and/or early-stage MS patient comprising a) identifying at least one phase rim lesion (PRL) in at least one susceptibility -weighted magnetic resonance image from a patient known or suspected of having chronic active white matter lesions, b) identifying at one slowly-expanding lesion (SEL) in at least one Tl-weighted/T2-weighted MRI from said patient; c) determining if the at least one PRL co localizes with the at least one SEL in said patient, and/or vice-versa, and d) in the event of co localization initiating treatment with a disease-modifying antibody therapy.
• PRL phase rim lesion
• SEL slowly-expanding lesion
• the at least one SEL is detected using single time-point non-contrast Tl- and T2- weighted MRI.
• the disease-modifying antibody therapy is selected from natalizumab, BIIB107 and ocrelizumab.
• the disease-modifying antibody therapy is an anti-VLA-4 antibody, e.g. natalizumab or BIIB107.
• the SEL is detected using a machine-learning based classifier that discriminate acute from chronic MS lesions and/or SEL from non-SEL using unenhanced T1/T2 information from a single MRI scan.
• a machine-learning based classifier that discriminate acute from chronic MS lesions and/or SEL from non-SEL using unenhanced T1/T2 information from a single MRI scan.
• an asymptomatic and/or early stage patient suspected of having a brain ailment such as MS, or an asymptomatic and/or early stage patient at risk of developing MS may be referred for an MRI scan of the brain at a single time point, and without agent contrast.
• the scan may then be input into the classifier algorithm, which may identify and distinguish between acute and chronic lesions present on the brain scan, and/or between SEL and non-SEL. Based on that identification and distinction, an appropriate disease-modifying antibody therapy can be administered that is suitable to the particular patient and disease state.
• one or more features having predictive value with respect to the classification of a lesion as either acute or chronic and/or as SELs are utilized.
• said features are selected from the group comprising or consisting of: features that quantify the first order intensity of the core region of a lesion as it appears on a T2-weighted scan image; features that quantify the amount of signals appearing as low-gray around the periphery of a lesion as it appears on a Tl -weighted scan image; features that quantify the amount of high-gray signals that are present in the periphery and/or core of a lesion as it appears on a Tl-weighted scan image; features that relate to the inhomogeneity present in the images; features that relate to the structure of the image, as relating to the presence of repeating patterns; and features that relate to the texture of the images.
• the method further comprises administering to said patient a therapeutically effective amount of natalizumab in a biphasic dosing regimen, wherein the biphasic dosing regimen comprises an induction phase comprising administration of the anti-VLA-4 antibody once every 2 weeks, about once very 2 weeks, once every 4 weeks, about once every 4 weeks, once every 30 days, about once every 30 days, once a month or about once a month for at least 6 months, for at least 8 months, for at least 10 months, or for at least 12 months, followed by a chronic phase comprising administration of the anti-VLA-4 antibody once every 5 to 10 weeks, or once every 5, 6, 7 or 8 weeks.
• the biphasic dosing regimen comprises an induction phase comprising administration of the anti-VLA-4 antibody once every 2 weeks, about once very 2 weeks, once every 4 weeks, about once every 4 weeks, once every 30 days, about once every 30 days, once a month or about once a month for at least 6 months, for at least 8 months, for at least 10 months, or for at
• the induction phase is from 6 to 18 months, from 8 to 16 months, from 10 to 14 months, or is 11 months, is 12 months or is 13 months. In some embodiments, the induction phase is 12 months, and the chronic phase comprises administration of natalizumab every 5 weeks, about every 5 weeks, every 6 weeks, about every 6 weeks, every 7 weeks or about every 7 weeks. In some embodiments, the induction phase is 12 months and the chronic phase comprises administration of natalizumab every 6 weeks.
• treatment with anti-VLA-4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s SELs co-localize with their PRLs.
• treatment with anti-VLA-4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s PRLs co-localize with their SELs.
• Figure 1 Association between CWMLA or whole brain volume loss and composite disability progression in the placebo arm. Change from baseline to week 108 in T1LV in (A) SELs, (B) non-SELs, and (C) CNT2 lesions was significantly associated with composite disability progression in SPMS patients. No difference in percentage change from baseline to week 108 in (D) whole brain volume was observed in SPMS patients with composite disability progression compared with those with no progression. Composite progression was confirmed at 24 weeks and end of study on one or more of the EDSS, Timed 25-Foot Walk, or 9-Hole Peg Test.
• the box spans the interquartile range, the median is marked by the horizontal line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations p values by Van Elteren test; stratified by baseline EDSS score ( ⁇ 5.5 or >6.0) and baseline T2 lesion volume category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79- 18818.49 mm 3 , and >18818.49 mm 3 ).
• CNT2 chronic nonenhancing T2
• CWMLA chronic white matter lesion activity
• EDSS Expanded Disability Status Scale
• SEL slowly expanding lesion
• SPMS secondary progressive multiple sclerosis
• T1LV Tl-hypointense lesion volume.
• Figure 2 Association between CWMLA and EDSS progression. Increase from baseline to week 108 in T1LV within (A) SELs and (C) CNT2 lesions but not (B) non-SELs was associated with EDSS progression in SPMS patients treated with placebo. (However, a consistent directional trend was observed in non-SELs.) EDSS progression was confirmed at 24 weeks and end of study.
• the box spans the interquartile range, the median is marked by the horizontal line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations p values by Van Elteren test; stratified by baseline EDSS score ( ⁇ 5.5 or >6.0) and by baseline T2 lesion volume category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79-18818.49 mm 3 , and >18818.49 mm 3 ).
• CNT2 chronic nonenhancing T2
• CWMLA chronic white matter lesion activity
• EDSS Expanded Disability Status Scale
• SEL slowly expanding lesion
• SPMS secondary progressive multiple sclerosis
• T1LV Tl- hypointense lesion volume.
• Figure 3 Association between CWMLA and 9HPT progression. Change from baseline to week 108 in T1LV within (A) SELs and (C) CNT2 lesions but not (B) non-SELs was associated with 9HPT progression in SPMS patients treated with placebo. (However, a consistent directional trend was observed in non-SELs.) 9HPT progression was confirmed at 24 weeks and end of study.
• the box spans the interquartile range, the median is marked by the horizontal line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations p values by Van Elteren test; stratified by baseline EDSS score ( ⁇ 5.5 or >6.0) and by baseline T2 lesion volume category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79-18818.49 mm 3 , and >18818.49 mm 3 ).
• 9HPT 9-Hole Peg Test
• CNT2 chronic nonenhancing T2
• CWMLA chronic white matter lesion activity
• EDSS Expanded Disability Status Scale
• SEL slowly expanding lesion
• SPMS secondary progressive multiple sclerosis
• T1LV Tl-hypointense lesion volume.
• Figure 4 Association between CWMLA and T25FW progression. Change in T1LV from baseline to week 108 within (B) non-SELs and (C) CNT2 lesions but not (A) SELs was associated with T25FW progression in SPMS patients treated with placebo. (However, a consistent directional trend was observed in SELs.) T25FW progression was confirmed at 24 weeks and end of study.
• the box spans the interquartile range, the median is marked by the horizontal line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations p values by Van Elteren test; stratified by baseline EDSS score ( ⁇ 5.5 or >6.0) and by baseline T2 lesion volume category based ontertiles ( ⁇ 6908.79 mm 3 , >6908.79-18818.49 mm 3 , and >18818.49 mm 3 ).
• CNT2 chronic nonenhancing T2
• CWMLA chronic white matter lesion activity
• EDSS Expanded Disability Status Scale
• SEL slowly expanding lesion
• SPMS secondary progressive multiple sclerosis
• T1LV Tl- hypointense lesion volume
• T25FW Timed 25-Foot Walk.
• FIG. 5 Association between CWMLA and composite disability progression in the absence of AWMLA.
• Composite progression was confirmed at 24 weeks and end of study on one or more of the EDSS, Timed 25-Foot Walk, or 9-Hole Peg Test.
• the box spans the interquartile range, the median is marked by the horizontal line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations p values by Van Elteren test; stratified by baseline EDSS score ( ⁇ 5.5 or >6.0) and baseline T2 lesion volume category based ontertiles ( ⁇ 6908.79 mm 3 , >6908.79- 18818.49 mm 3 , and >18818.49 mm 3 ).
• Figure 6 Prevalence of SELs and frequency distribution of SEL severity in the presence versus absence of AWMLA. SEL (A) number, (B) absolute volume, and (C) relative volume (percentage of baseline nonenhancing T2LV) was greater in SPMS patients treated with placebo who had AWMLA compared to those with no AWMLA.
• Acute lesions were defined as baseline Gd+ T1 lesions and postbaseline Gd+ T1 lesions and new/enlarging T2 lesions in weeks 24, 48, 72, 96, and 108.
• p values by Van Elteren test stratified by baseline EDSS score ( ⁇ 5.5 or >6.0) and baseline T2LV category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79-18818.49 mm 3 , and >18818.49 mm 3 ).
• AWMLA acute white matter lesion activity
• BL baseline
• EDSS Expanded Disability Status Scale
• Gd+ gadolinium enhancing
• SEL slowly expanding lesion
• SPMS secondary progressive multiple sclerosis
• T2LV T2-hyperintense lesion volume.
• Figure 7 Effect of natalizumab on SEL prevalence. Natalizumab reduced the (A) number, (B) absolute volume, and (C) relative volume (percentage of baseline nonenhancing T2LV) of SELs in SPMS patients.
• Box-and-whisker representations the box spans the interquartile range, the median is marked by the horizontal line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations p values by Van Elteren test; stratified by baseline Expanded Disability Status Scale score ( ⁇ 5.5 or >6.0) and baseline T2LV category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79-18818.49 mm 3 , and >18818.49 mm 3 ).
• SEL slowly expanding lesion
• SPMS secondary progressive multiple sclerosis
• T2LV T2-hyperintense lesion volume
• T2w T2 weighted.
• Figure 8 Change in CWMLA with natalizumab versus placebo. Natalizumab reduced CWMLA as measured by both (A, B) absolute increase and (C, D) percentage increase in T1LV in SELs and non-SELs compared with placebo in SPMS patients. Distribution-free quantile confidence limits are displayed p values by Van Elteren test; stratified by baseline EDSS score ( ⁇ 5.5 or >6.0) and baseline T2 lesion volume category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79- 18818.49 mm 3 , and >18818.49 mm 3 ).
• FIGS 9A-9E Overlap of SELs and PRLs.
• SELs identified based on change within pre-existing lesion from screening to week 72, outlined on Tlw images at (A) screening and (B) week 72.
• C Phase rim (PRL) annotations outlined on a co-registered frequency map at week 72.
• D T2-lesions associated with the PRLs, corresponding to the area within the rims in (C), overlaid on the FLAIR image at week 72.
• E Voxel-wise overlap between the SELs and T2-lesions associated with the PRLs (arrows denote voxels that overlap. Also shown are voxels only present in SEL, and voxels only in T2-lesions associated with PRLs).
• Figure 10 Correlation between number of SELs versus number of PRLs. Number of PRLs is depicted on the x-axis, and number of SELs is depicted on the y-axis.
• Figures 11A-11B Comparisons of lesions across types. PRL size with and without SEL co-localization (A), and SEL size with and without PRL co-localization (B).
• Figures 12A-12B Evolution of tissue damage within SEL/PRL lesions. Comparison of normalized magnetization transfer ratio (nMTR) trajectories, PRL with and without SEL colocalization (A) and SEL with and without PRL colocalization (B). In (A) nonPRL; PRL, SEL; PRL, non-SEL. In (B) Non-SEL; SEL, PRL; SEL, nonPRL. In (A) and (B), computed as weighted means over samples (PRL or SEL). Shaded areas represent 95% Cl of mean.
• nMTR normalized magnetization transfer ratio
• Figures 13A-13B Evolution of tissue damage within SEL/PRL lesions. Comparison of radial diffusicity trajectories. PRL with and without SEL colocalization (A) and SEL with and without PRL colocalization (B). In (A) nonPRL; PRL, SEL; PRL, non-SEL. In (B) non-SEL; SEL, PRL; SEL, nonPRL. In (A) and (B), computed as weighted means over samples (PRL or SEL). Shaded areas represent 95% Cl of mean.
• Figure 14 Selection of two patches (one SEL, one non-SEL) extracted from chronic unenhancing MS leasions of a brain T2 MRI scan.
• Figures 15A-15B Non-SEL patch extracted from baseline T2 MRI scan showing the core and periphery regions. (A) unhighlighted, (B) core (solid line) and periphery (dashed line). [0043] Figures 16A-16C: Illustrations of lesion volume matching between SEL and Non-SEL patches (top, SEL; bottom, non-SEL). Each of (A), (B), and (C) correspond to a volume-matched pair.
• Figure 17 Prevalence of each of the fifteen radiomic features selected for discriminating SEL from non-SEL patches, with abbreviations as follows: tip: T 1 -weighted MRI pre-contrast (i.e., feature was extracted from non-contrast Tl-weighted MRI image); t2w: T2- weighted MRI (i.e., feature was extracted from T2-weighted MRI image); core/periphery: specifies whether feature was computed within core or periphery region; glrlm: Gray-level Run- Length Matrix; glcm: Gray-level Cooccurence Matrix; glszm: Gray-level Size Zone Matrix.
• first-order statistics including the mean, median and 90th percentile of T1 intensities in the core of the patch were identified as relevant, consistent with prior studies reporting that SELs exhibit a higher degree of T1 hypo-intensity relative to non-SELs at baseline.
• Figures 18A-18D Confusion matrices showing the performance of the classification model for patch-level SEL versus non-SEL discrimination on the training, validation, and independent testing sets.
• A ADVANCE training set (balanced accuracy: 73.0%)
• B ADVANCE validation set (balanced accuracy: 66.8%)
• C ASCEND test set (balanced accuracy: 65.7%)
• D SYNERGY test set (blanaced accuracy: 68.5%).
• Figures 19A-19D Confusion matrices showing the performance of the classification model for patch-level SEL versus non-SEL discrimination on the training, validation, and independent testing sets for volume-matched patches.
• Natalizumab sold under the trade name TYSABRI ® (BIOGEN ® , MA), is an integrin receptor antagonist approved by the U.S. Food and Drug administration (FDA) for treatment of multiple sclerosis and Crohn’s disease.
• FDA U.S. Food and Drug administration
• the FDA approved standard dosing regimen is 300 milligrams (mg) infused intravenously over approximately one hour, every four weeks.
• mg milligrams
• PML progressive multifocal leukoencephalopathy
• Chronic active lesions also known as smoldering plaques, are a neuropathologic hallmark of chronic inflammation in multiple sclerosis (Elliott et al. Patterning chronic active demyelination in slowly expanding/evolving white matter MS legions. AJNR Am J Neuroradiol dx.doi.org/10.3174/ajnr.A6742).
• the chronic active lesions are generally surrounded by a rim of activated microglia and/or macrophages that may contain iron or zinc.
• These paramagnetic rim lesions (PRL) are considered a promising pathological biomarker of iron/zinc accumulation in chronic active lesions and are identified using susceptibility-weighted imaging.
• SELs slowly expanding/evolving lesions
• Tl- weighted/T2-weighted brain MRI provides an alternative readout of smoldering or chronic active plaques (Elliott etal. Slowly expanding/evolving lesions as a magnetic resonance imaging marker of chronic active multiple sclerosis lesions. Mult Scler J 2019; 25:1915-1925). Slowly expanding lesions have been described in the literature (Elliott et al. Chronic white matter lesion activity predicts clinical progression in primary progressive multiple sclerosis, Brain 2019; 142:2787- 2799).
• SELs on conventional brain MRI are contiguous regions of T2 lesions showing constant and concentric local expansion as assessed by the Jacobian determinant of the non-linear deformation between the reference and follow-up scans.
• SELs are devoid of T1 gadolinium (Gd)-enhancement, have a lower mean T1 signal intensity at baseline and exhibit a progressive decrease in T1 intensity over time, compared to non-SEL areas of pre-existing lesions (Elliott et al. Ocrelizumab may reduce tissue damage in chronic active lesions as measured by change in T1 hypointensity of slowly evolving lesions in patients with primary progressive multiple sclerosis. Poster presented at AAN; Poster 376, April 24, 2018; Los Angeles, CA).
• the combination of these two radiological markers is informative of disease progression in earlier-stage MS patients, including patients known or suspected of having RIS, thereby enabling the identification of those patients likely to benefit from more aggressive disease-modifying antibody therapies, including anti-VLA-4 antibody therapies, earlier in the disease process, and consequent treatment initiation.
• the identification or one or more chronic active white matter lesions, and/or one or more SELs, in a single unenhanced MRI scan is also informative of disease progression in earlier-stage MS patients, including patients known or suspected of having RIS, thereby enabling the identification of those patients likely to benefit from more aggressive disease-modifying antibody therapies, including anti-VLA-4 antibody therapies, earlier in the disease process, and consequent treatment initiation.
• a subject is typically a male or female human subject (patient) who is undergoing or who will undergo treatment for a particular condition.
• the condition may be an autoimmune condition or an inflammatory condition.
• autoimmune conditions are considered inflammatory conditions and vice versa, thus, in some embodiments the subject has an autoimmune condition and/or inflammatory condition.
• An autoimmune condition is a condition in which a subject’s immune system attacks the subject’s own cells/tissues.
• Non-limiting examples of the autoimmune conditions contemplated by the present invention include Radiologically Isolated Syndrome (RIS), and asymptomatic and/or early-stage multiple sclerosis (MS) ( e.g ., those having no diagnosed relapses).
• RIS Radiologically Isolated Syndrome
• MS early-stage multiple sclerosis
• Relapses in the context of MS occur in the absence of fever or infection and are not linked to environmental and systemic triggers; they denote acute inflammation in the CNS characterized by breach of integrity of the blood-brain barrier (BBB).
• BBB blood-brain barrier
• the criteria for relapses are defined as an increase in lesion load/size on T2 imaging or T1 gadolinium enhancement of lesions on magnetic resonance imaging (MRI) in the brain, spinal cord or both.
• MRI magnetic resonance imaging
• patients may present with “mild” symptoms such as e.g. pins and needles sensations that are fleeting and/or spasms that persist for a few seconds or minutes; alternatively or additionally, more severe exacerbations may include e.g.
• a “pharmaceutically effective amount” or “therapeutically effective amount,” used interchangeably, is an amount sufficient to cure or at least partially arrest the symptoms of a disease and/or the complications of a disease.
• a “disease-modifying antibody therapy” as contemplated herein for the treatment of CWMLA includes anti-VLA-4 antibodies, e.g. , natalizumab and BUB 107, as well as anti-CD20 antibodies such as ocrelizumab.
• An “anti-VLA-4 antibody” is an anti-very late antigen (VLA)-4 monoclonal antibody, a humanized, a human, or a chimeric anti-VLA-4 monoclonal antibody.
• Anti-VLA-4 antibodies have been described in the art. They include, but are not limited to natalizumab and BUB 107, a monoclonal antibody that targets alpha-4 integrins and is currently under clinical investigation (ClinicalTrials.gov no. NCT04593121). See also PCT/US2011/032641 and PCT/US2019/034962, the disclosures of which are expressly incorporated by reference herein.
• the invention teaches the simultaneous or sequential acquisition of a combination of at least one Tl- and T2-weighted image from a patient, for the identification of at least one SEL, and at least one susceptibility- weighted magnetic resonance image, for the identification of at least one PRL, and determining the extent of co-localization between the two, e.g. the percent of SEL that co-localize with PRLs, and vice-versa.
• treatment with anti-VLA-4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s SELs co-localize with their PRLs.
• treatment with anti-VLA- 4 therapy is initiated when at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s PRLs co-localize with their SELs. Greater detail regarding specific embodiments of the invention is provided herein below.
• treatment with anti-VLA-4 therapy is initiated when at least 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s total T2 hyperintense lesion volume and/or number is identified as PRL.
• treatment with anti-VLA-4 therapy is initiated when at least 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, or 75% of the patient’s total T2 hyperintense lesion volume and/or number is identified as SEL.
• the SEL is detected using single time-point non-contrast Tl- and T2-weighted MRI.
• the invention teaches a method for producing a series/set of brain images utilizing magnetic resonance imaging.
• the method includes utilizing an MRI machine to apply a standardized 3-Tesla, 3D-isotropic multi-echo, gradient echo MRI to identify any PRLs in said patient, and a Tl- and T2 weighted MRI to identify any SELs.
• the ‘co-localization’ between SELs and PRLs can be based on heuristic thresholds set from visual experience of the observer (radiologist) of the corresponding segmented volumes or alternatively rely on an automated processing pipeline determining the exact percent of SELs volume co localizing with PRLs, and vice-versa.
• the invention employs machine-learning based classifiers to classify MS lesions using unenhanced T1/T2 information from a single MRI scan, as described in Provisional Application Serial No. FR2103793 and co-pending International Application No. PCT/US2022/024450, the disclosures of which are expressly incorporated by reference herein for all purposes.
• classifiers may be able to effectively increase the sensitivity of single time-point acute MS lesion detection, and may be able to replicate, approach, or exceed the sensitivity of traditional detection of hyperintensities identified on a Tl -weighted scan with gadolinium enhancement and/or of new hyperintense lesions on a T2-weighted scan in comparison with a prior reference scan, which may be reflective of new local inflammation.
• suitable methods of classifying brain lesions based on single point in time imaging can include: accessing patient image data from a single point in time; providing the patient image data as an input to a brain lesion classification model; generating a classification for each of one or more lesions identified in the patient image data; and providing the classification for each of the one or more lesions for display on one or more display devices; wherein the brain lesion classification model is trained using subject image data for a plurality of subjects, the subject image data being captured at two or more points in time.
• the patient image data from the single point in time includes data from two or more image scan sequences.
• the data from two or more image scan sequences include unenhanced MRI data, wherein the two or more image scan sequences do not include administration of paramagnetic contrast agents.
• the classification for each of one or more lesions identified in the patient image data is selected to be one of acute or chronic, or SEL or non-SEL.
• certain radiomic features having predictive value with respect to the classification of a lesion as either acute or chronic and/or as SELs are utilized including e.g. the following exemplary embodiments:
• features may quantify the complexity of the image (the image is non-uniform and may include rapid changes in the gray levels), the variance of the gray levels with respect to a mean gray level, or the existence of homogenous patterns in the images.
• the radiomic features for discriminating SEL from non-SEL are selected from the group comprising or consisting of the radiomic features listed in Figure 17:
• Tl-weighted-MRI pre-contrast extracted from non-contrast T1 weighted MRI image, computed within the core region
• gray-level Run-Length-Matrix quantifies gray level runs
• run length non-uniformity measures similarity of run lengths throughout the image, with a lower value indicating more homogeneity among run lengths in the image
• Tl-weighted-MRI pre-contrast computed within the core region
• first order features scribe the distribution of voxel intensities within the image region defined by the mask through commonly used and basic metrics
• T2-weighted MRI extracted from T2 weighted MRI image
• first order features uniformity (a measure of the sum of the squares of each intensity value; a measure of homogeneity of the image array; greater uniformity implies a greater homogeneity or a smaller range of discrete intensity values)
• T 1 -weighted-MRI pre-contrast computed within the core region, first order features, mean (average gray level intensity within the patch)
• Tl-weighted-MRI pre-contrast computed within the periphery region
• first order features robust mean absolute deviation (the mean distance of all intensity values from the Mean Value calculated on the subset of image array with gray levels in between, or equal to the 10th and 90th percentile)
• T2-weighted MRI computed within the periphery region first order values, root mean squared (the square-root of the mean of all the squared intensity values; another measure of the magnitude of the image values)
• Tl-weighted-MRI pre-contrast computed within the core region
• Gray-level Size Zone Matrix computed within the core region
• zone entropy measure the uncertainty/randomness in the distribution of zone sizes and gray levels; higher values indicate more heterogeneneity in the texture patterns
• Tl-weighted-MRI pre-contrast computed within the periphery region, gray-level Run- Length-Matrix, run length nonuniformity (measures the similarity of run lengths throughout the image; a lower value indicates more homogeneity among run lengths in the image)
• T2-weighted MRI computed within the periphery region, first order values, skewness (measures asymmetry of distribution of values about the mean value; can be positive or negative)
• the machine learning classifier may employ one or more machine learning systems, methods, and/or models.
• a machine learning model may be considered as a model configured to receive input, and to apply one or more of a weight, bias, classification, or analysis on the input to generate an output.
• the output may include, for example, a classification of the input, an analysis based on the input, a design, process, prediction, or recommendation associated with the input, or any other suitable type of output.
• a machine learning model generally is trained using training data, e.g., experiential data and/or samples of input data, such as the types of training data described elsewhere herein, which are fed into the model in order to establish, tune, or modify one or more aspects of the model, e.g., the weights, biases, criteria for forming classifications or clusters, or the like.
• aspects of a machine learning model may operate on an input linearly, in parallel, via a network (e.g., a neural network), or via any suitable configuration.
• Training sets may be used as inputs to train the machine learning classifier, may facilitate a selection or combination of machine learning methods, directed toward creating an optimal combination of such methods.
• One goal of such selection is the creation of an optimal subset of features to provide separation on a reduced imaging biomarker space between lesion types (e.g., acute versus chronic lesions or SEL versus non-SEL) or amount or degree of progression.
• linear and non-linear feature-to-class correlation tests may be used to identify the features that account for the highest variance between the classifications.
• This evaluation and classification may employ an initial feature ranking, such as shown in Figure 17, and an initial feature selection that may, for example, identify a number of features with the strongest individual correlation. In an embodiment, there may be 50 such features selected as a feature subspace. From those features, embedded selection methods can leverage tree-based classifiers and sparse linear models including a least absolute shrinkage and selection operator (LASSO).
• LASSO least absolute shrinkage and selection operator
• the outcome of this ensemble classification mechanism may be a selected subset of classification methods that may involve linear classification methods (e.g., logistic regression, support vector machines) and/or non-linear classification methods (e.g., perceptron, deep convolutional neural networks or other types of neural networks) which act to optimize separability between the two classes (active and chronic).
• linear classification methods e.g., logistic regression, support vector machines
• non-linear classification methods e.g., perceptron, deep convolutional neural networks or other types of neural networks
• a pool of machine learning models may undergo hyperparameter tuning via an extensive randomized grid search, which may be followed by a k-fold cross- validation on the classification task of interest. This tuning may then lead to a performance benchmark that can select the highest performing models, for example, the n top-performing models. These models may then be combined under a stacking or a winner takes all or a probabilistic importance sampling ensemble strategy.
• Implementing a machine learning model may include deployment of one or more machine learning techniques, including various types of neural networks, and statistical techniques such as linear regression, logistical regression, random forest, or gradient boosted machine (GBM).
• training of the machine learning model may be supervised, or unsupervised, or both.
• Supervised learning may include providing training data and labels corresponding to the training data.
• Unsupervised training may include clustering, classification, or the like. Different types of clustering, or combinations of clustering, also may be used, and these may be supervised or unsupervised.
• a machine-learning based classifier may include one or more of a plurality of types of neural networks, including convolutional neural networks (CNN), deep or fully convolutional neural networks (DCNN, FCNN), deep learning neural networks (DNN), deep belief networks (DBN), and others with which ordinarily skilled artisans will be familiar.
• CNN convolutional neural networks
• DCNN deep or fully convolutional neural networks
• DNN deep learning neural networks
• DNN deep belief networks
• a machine learning system which may be part of a machine learning model may include one or more processors, one or more storage devices intended for non-volatile non- transitory storage, and one or more memory devices, which may be volatile memory for transitory storage, but which also may include non-volatile memory for non-transitory storage.
• a plurality of machine learning methods, implemented by one or more machine learning systems, may be employed as part of the ensemble classification process.
• the processors in a machine learning system may be graphics processing units (GPUs) or central processing units (CPUs), which can lend themselves to neural network structures or other learning frameworks.
• the present disclosure also provides biphasic dosing regimens for reducing pathological inflammation with natalizumab, wherein the dosing regimens comprise an induction phase employing standard interval dosing (SID) followed by a chronic phase employing extended interval dosing (EID).
• the dosing regimens comprise an induction phase employing standard interval dosing (SID) followed by a chronic phase employing extended interval dosing (EID).
• at least one treatment phase employs subcutaneous administration.
• both treatment phases employ subcutaneous administration.
• the same dose administered during the SID phase can be administered during the EID phase, and in some embodiments the same dose administered IV can be administered SC.
• the biphasic dosing regimen contemplated herein refers to the administration of natalizumab in at least two phases, e.g ., an induction phase and a chronic phase.
• the induction phase comprises administration of natalizumab on an SID schedule and the chronic phase comprises administration of natalizumab on an EID schedule.
• the induction phase comprises administration of natalizumab once every 2 weeks, about once every 2 weeks once every 3 weeks, about once every 3 weeks once every 4 weeks, about once every 4 weeks, once every 30 days, about once every 30 days, once a month or about once a month for at least 6 months, for at least 8 months, for at least 10 months, or for at least 12 months.
• the induction phase is from 6 to 18 months, from 8 to 16 months, from 10 to 14 months, is 11 months, is 12 months, or is 13 months.
• the chronic phase comprises administration of natalizumab once every 5 to 10 weeks.
• the chronic phase comprises administration of natalizumab every 5 weeks, about every 5 weeks, every 6 weeks, about every 6 weeks, every 7 weeks, about every 7 weeks, every 8 weeks, or about every 8 weeks.
• both the induction phase and the chronic phase comprise SC administration.
• the induction phase and the chronic phase are solely SC administration.
• the SC dosing and amount of natalizumab can be consistent with IV dosing.
• the therapeutically effective amount administered during the induction phase and the chronic phase are the same, and the therapeutically effective amount is between 250 - 450 mg ( e.g ., 250 mg, 300 mg, 350 mg, 400 mg, or 450 mg), more preferably about 300 mg, still more preferably 300 mg.
• the therapeutically effective amount administered SC during the chronic phase is between 300 - 500 mg (e.g., 300 mg, 350 mg, 400 mg, 450 mg, or 500 mg).
• the therapeutically effective amount is between about 250 - about 450 mg (e.g, about 250 mg, about 300 mg, about 350 mg, about 400 mg, or about 450 mg), more preferably about 300 mg, still more preferably 300 mg.
• the therapeutically effective amount administered SC during the chronic phase is between about 300 - about 500 mg (e.g, about 300 mg, about 350 mg, about 400 mg, about 450 mg, or about 500 mg), more preferably about 300 mg, still more preferably 300 mg.
• Representative biphasic dosing regimens are disclosed in U.S. Provisional Application Serial Nos. 63/113,864 (filed November 14, 2020), 63/113,865 (filed November 14, 2020), 63/142,968 (filed January 28, 2021), 63/142,970 (filed January 28, 2021), and co-pending International Application No. PCT/US2021/059266, the disclosures of which are expressly incorporated by reference herein.
• the present disclosure also provides a chronic dosing regimen for reducing pathological inflammation with natalizumab.
• natalizumab is administered in a chronic dose regimen, wherein the chronic dosing regimen comprises administration of natalizumab at a fixed interval of every 4 weeks.
• the chronic dosing regimen is a fixed, non-weight based amount of natalizumab.
• a therapeutically effective amount of natalizumab is between about 250 - 450 mg, more preferably about 300 mg, still more preferably a fixed, non-weight based dose of 300 mg.
• the chronic dosing regimen is every 4 weeks for a period of about 4 months, about 5 months, about 6 months, about 7 months, about 8 months, about 9 months, about 10 months, about 11 months, about 12 months, or longer than about 12 months.
• Representative chronic dosing regimens are disclosed in WO 2003/072040, the disclosure of which is expressly incorporated by reference herein.
• the chronic dosing regimen comprises SC injection.
• the chronic dosing regimen comprises IV administration.
• Representative SC administration formulations are disclosed in WO 2008/157356, the disclosure of which is expressly incorporated by reference herein.
• biomarkers for determining and/or monitoring efficacy of the treatment protocols provided herein include, e.g ., sVCAM and/or Nf-L.
• sVCAM provides an effective surrogate biomarker for a4-integrin receptor saturation, and for immune surveillance activity in general, see, e.g. Plavina et al. , Neurology (2017) 89(15): 1584-1593.
• Neurofilament proteins such as Nf-L, in contrast, provide an indication of axonal damage and neuronal death, and serve as effective surrogate biomarkers for ongoing disease activity in MS patients in particular. See, e.g., Kuhle et al. Mult Scler. (2013) 19:1597-603; Varhaug et al, Front Neurol. (2019) 10: 338.
• biphasic dosing regimens are provided for increasing the safety of natalizumab therapy.
• the biphasic dosing regimens are provided for increasing the safety of chronic natalizumab therapy.
• Safety may be increased by reducing the risk of an adverse event, e.g. PML.
• the biphasic regimen reduces the risk of PML, reduces the risk of inducing generation of anti-natalizumab antibodies, reduces the risk of patient sensitization to natalizumab, or a combination thereof.
• the biphasic regimen reduces the risk of loss of efficacy of natalizumab treatment due to the generation of anti -idiotypic antibodies to natalizumab in the patient.
• a PML risk subject has an anti-JCV antibody index level (e.g, a mean index level) of greater than 1.5.
• a low PML risk subject is a subject who has an anti-JCV antibody index level (e.g, a mean index level) of less than or equal to 0.9.
• Anti-JC virus index values are calculated from a two-step ELISA antibody assay of serum/plasma (STRATIFY JCVTM Antibody (with Index) with Reflex to Inhibition Assay; see, e.g, Lee, P. et al.
• a subj ect may be considered a high PML risk if the subj ect tested seropositive for anti- JCV antibodies prior to commencement of natalizumab therapy, or if the subject switches from a seronegative anti-JCV antibody status to a seropositive anti-JCV antibody status during natalizumab therapy.
• a subject is considered a high PML risk if the subject has an anti-JCV antibody index level of greater than 1.5 prior to commencement of natalizumab therapy, or if the subject switches from a lower anti-JCV antibody index level of less than or equal to 0.9 to a higher anti-JCV antibody index level of greater than 1.5 during natalizumab therapy.
• a subject may be tested for the presence or absence of anti-JCV antibodies prior to starting natalizumab therapy. If the test results indicate that the subject is a low PML risk subject (seronegative for anti-JCV antibodies, or having an anti-JCV antibody index level of less than or equal to 0.9), then the subject may be identified as a subject for natalizumab therapy on a SID schedule of 4-week intervals. During the course of the natalizumab therapy on a SID schedule, the subject may be re-tested for the presence or absence of anti-JCV antibodies (e.g., tested every month or every 2, 3, 4, 5 or 6 months, or every year).
• the subject may be identified as a subject for natalizumab therapy on an EID schedule of at least 5-week intervals.
• Example 1 Association between chronic white matter lesion activity and disability progression in SPMS patients with or without acute inflammation
• SELs Slowly expanding lesions
• MS primary progressive multiple sclerosis
• AWMLA acute white matter lesion activity
• CWMLA chronic white matter lesion activity
• CNT2 chronic nonenhancing T2
• AWMLA was defined by having either 1) gadolinium-enhancing (Gd+) T1 lesions at any time point in the trial up to week 108, including baseline, or 2) any postbaseline new or enlarging T2 lesions.
• Gd+ gadolinium-enhancing
• T1 -weighted (Tlw) T1 -weighted
• Tlw T1 -weighted
• the ASCEND study (ClinicalTrials.gov no. NCT01416181) was a two-part, multicenter, randomized, double-blind, placebo-controlled phase 3 study in patients with SPMS to assess the efficacy and safety of natalizumab. Details of the study design and outcomes have previously been described in detail. Kapoor et al. Lancet Neurol 2018; 17:405-415.
• the SEL analysis population represents the subset of the intention-to-treat population that had available Tlw and T2-weighted (T2w) images at all time points from baseline to week 108 (including weeks 24, 48, 72, and 96).
• EDSS Expanded Disability Status Scale
• T25FW Timed 25-Foot Walk
• 9HPT 9-Hole Peg Test
• SELs are contiguous regions of preexisting T2 lesions showing constant and concentric local expansion from baseline to week 108.
• T2 lesions Prior to SEL detection, T2 lesions were identified in baseline scans using a semi-automated method in which a fully automated segmentation of T2 lesions was subsequently manually reviewed and corrected by a single trained MRI reader. Francis SJ. In: McGill University DoN, ed., 2005.
• SEL candidates are identified as contiguous regions of >10 voxels in the baseline T2 lesion mask that a) are not Gd+ and b) show a minimum local volumetric expansion, as determined by the Jacobian determinant of the nonlinear deformation between the baseline and week 108 scans.
• the second stage of SEL detection scores each SEL candidate in turn on the basis of the concentricity and constancy of expansion across time. Considering local expansion between baseline and each intermediate time point (weeks 24, 48, 72, and 96) allows for the identification of SEL candidates undergoing constant and gradual expansion across time, while measuring concentricity allows for the identification of SEL candidates exhibiting inside-out radial expansion.
• Each SEL candidate is assigned a SEL score, calculated as the sum of the mean normalized measures for constancy and concentricity.
• SELs were identified in SPMS patients from the ASCEND phase 3 clinical trial (ClinicalTrials.gov no. NCT01416181). Non-SELs, defined as the portion of the nonenhancing baseline T2 lesion mask not identified as SELs, were also assessed, as were the totality of nonenhancing T2 lesions.
• AWMLA was defined by having either 1) Gd+ T1 lesions at any time point in the trial up to week 108, including baseline, or 2) any postbaseline new or enlarging T2 lesions.
• Gd+ T1 lesions were determined as a consensus of 2 fully manual identifications by 2 trained MRI readers, where any discrepancies were adjudicated by a third independent reader.
• New or enlarging T2 lesions were determined by comparing T2 lesion masks at successive timepoints and automatically identifying focal areas of new T2 lesions, which were not present at the previous timepoint and showed a minimum increase in T2-weighted intensity. These focal areas of new T2 lesions could be entirely in NAWM (new) or adjacent to pre-existing T2 lesions (enlarging). All automatically identified new or enlarging T2 lesions were manually reviewed and corrected where necessary.
• T2 lesion counts which vary from laboratory to laboratory
• CWMLA was measured by the change in Tl-hypointense lesion volume (T1LV) from baseline to week 108 in SELs, non-SELs, and total pre-existing chronic nonenhancing T2 (CNT2) lesions in SPMS patients in the placebo arm.
• Tl-hypointense lesions were defined as areas of T2-lesion not showing gadolinium enhancement and with T1 -weighted intensity less than or equal to median T1 -weighted intensity of gray matter.
• a two-sample proportion test was applied to compare baseline Gd+ T 1 lesions between the two treatment groups.
• CWMLA was compared between progressors and nonprogressors using the Van Elteren test, stratified for progression status, baseline EDSS score ( ⁇ 5.5 or >6.0), and baseline T2-hyperintense lesion volume (T2LV) category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79-18818.49 mm 3 , and >18,818.49 mm 3 ).
• Analyses of the association between AWMLA and SEL prevalence were based on the Van Elteren test, stratified for AWMLA, baseline EDSS score ( ⁇ 5.5 or >6.0), and baseline T2LV category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79- 18818.49 mm 3 , and >18818.49 mm 3 ).
• Comparisons of CWMLA between placebo and natalizumab were based on the Van Elteren test, stratified for treatment, baseline EDSS score ( ⁇ 5.5 or >6.0), and baseline T2LV category based on tertiles ( ⁇ 6908.79 mm 3 , >6908.79-18818.49 mm 3 , and >18818.49 mm 3 ).
• Statistical tests were two-sided and conducted at the 5% significance level without adjustment for multiplicity.
• the baseline demographics and brain MRI characteristics of the analysis population available for SEL detection and the intention-to-treat population from the ASCEND study dataset are presented in Table 4. Age and gender were distributed similarly across the SEL analysis and intention-to-treat populations and between treatment arms. In the SEL analysis population, a greater percentage of natalizumab- than placebo-treated individuals had >1 Gd+ T1 lesion at baseline (28% vs 19%), but the difference was not statistically significant. In the SEL analysis population, the natalizumab- and placebo-treated groups had a similar mean T2LV at baseline (18.1 vs 16.5 cm 3 ). Mean normalized brain volume at baseline was also similar in the two treatment groups.
• ASCEND SEL analysis population represents the subset of the ITT population that had available T1 - and T2 -weighted images at all time points from baseline to week 108 (including weeks 24, 48, 72, and 96).
• Gd+ gadolinium enhancing
• ITT intention to treat
• SD standard deviation
• SEL slowly expanding lesion
• T2LV T2- hyperintense lesion volume.
• Placebo SPMS patients with AWMLA had a higher SEL prevalence as measured by SEL number and volume (based on T2w borders of SELs at baseline) and a higher proportion of preexisting baseline T2LV identified as SELs than patients with no AWMLA (Fig 6A-C).
• SELs represent a subgroup of MS chronic white matter lesions with continual expansion and tissue destruction and predict clinical progression in progressive-onset MS.
• natalizumab treatment significantly reduced the number and volume of SELs and the proportion of baseline nonenhancing T2 lesions identified as SELs.
• Natalizumab reduced CWMLA as measured by T1LV increase in both SELs and non-SELs.
• the significant association between AWMLA and SEL prevalence suggests that the effect of natalizumab on CWMLA in progressive MS patients could be related to its high efficacy in suppressing acute inflammation.
• Prior studies demonstrating the effects of natalizumab and depletion of CD20-expressing cells further support this finding. Kappos et al. JAMA Neurol 2020; 77:1132-1140, Montalban et al.
• natalizumab decreased PK11195 uptake, reflective of activated microglia and macrophages, in nonenhancing lesions (Kaunzner et al. Mult Scler Relat Disord 2017; 15:27-33) and more specifically at the rim of chronic active lesions (Sucksdorff et al. Neurol Neuroimmunol Neuroinflamm 2019; 6:e574).
• natalizumab and/or ocrelizumab on CWMLA (in SELs and non-SELs) and/or disability progression in progressive forms of MS may be principally explained by their capacity to silence AWMLA.
• an extended approach using Bayesian inference for a principal stratum estimand can be used to assess the treatment effect in subgroups characterized by AWMLA covariate thresholds as a postrandomization event occurrence.
• phase rim lesions may both reflect chronic active lesions (Preziosa et al. Mult Scler 2020:1352458520969105).
• PRLs phase rim lesions
• Recent work has demonstrated a partial concordance between SELs and PRLs, as a substantial proportion of PRLs do not appear to expand over time and some SELs appear to be devoid of phase rims entirely (Elliott et al. Neurology 2021; 96: (15 Supplement) 4101).
• elucidating the complementarity of SEL, non-SEL, and PRL measures of CWMLA can expand the characterization of longitudinal tissue alteration properties within distinct MRI phenotypes of chronic active lesions.
• CWMLA in SELs and non-SELs is an imaging biomarker of chronic active lesions and/or secondary axonal degeneration that reflects ongoing inflammation and is associated with clinical disability progression.
• Example 2 MRI characteristics of phase rim lesions in chronic and recent acute MS lesions
• PRLs phase rim lesions
• nTl normalized T1 -weighted intensity
• nMTR normalized magnetization transfer ratio
• DTI-RD diffusion tensor imaging radial diffusivity
• Acute new T2 lesions that were PRL+ were larger at first detection (median size of 392 vs 52 mm 3) and had lower nMTR on average at detection and recovery stages compared to those acute new T2 lesions that were rimless.
• Example 3 MRI characteristics of chronic MS lesions by phase rim detection and/or slowly expanding properties
• PRLs phase rim lesions
• SELs slowly expanding lesions
• nMTR normalized magnetization transfer ratio
• DTI-RD diffusion tensor imaging radial diffusivity
• PRLs as detected on susceptibility-weighted phase images, have been associated with chronic active MS lesions (Absinta et al. J Clin Invest 2016; 126:2597-2609).
• SELs have been posited as a marker of chronic active MS lesions that can be assessed using only conventional MRI sequences (Elliot et al.
• SELs have been associated with ongoing tissue damage within lesions that is predictive of disability progression in progressive-onset MS (Elliott et al. Brain 2019; 142:2787-2799, and Elliott et al. AJNR Am J Neuroradiol 2020; 41(9): 1584-1591), and patients with > 4 PRLs demonstrated faster accumulation of disability Absinta et al. JAMA Neurol 2019; 76: 1474-1483).
• the degree of overlap of SELs with PRLs is unknown.
• Design/Methods Study Design: Brain MRI data were acquired in AFFINITY [NCT03222973], a phase II trial of opicinumab in relapsing MS with an intial blinded, placebo controlled portion followed by an open label extension study. Patients stable on disease modifying therapies (DMTs) (interferon, natalizumab, or dimethyl fumarate) were randomized to receive 750 mg opicinumab every 4 weeks of placebo in addition to their background DMT.
• DMTs disease modifying therapies
• Imaging The imaging protocol included Tl-weighted scans pre-/post gadolinium, T2-weighted FLAIR, PD-weighted and T2-weighted spin echo images, 2 spoiled gradient- recalled echo images with/without an MT pulse for calculating magnetization transfer ratio (MTR), and diffusion-weighted imaging using 32 directions.
• the protocol also included susceptibility weighted imaging (SWI) using standardized 3T Siemens 3D isotropic multi-echo spoiled gradient T2*.
• PRLs were detected from SWI phase images at Week 72 or Part 2/Dayl.
• SELs were detected as areas of Part 1 baseline T2 lesions that showed constant and concentric expansion from baseline to Week 72, using longitudinal Tl- and T2-weighted images.
• Results 41 of the patients who participated in the advanced MRI sub-study of AFFINITY Part 2 had SWI available at week 72. Patient characteristics are shown in Table 5.
• Some chronic active lesions can be detected as slowly expanding lesions (SELs) identifiable on MRI as contiguous regions of existing T2 lesions showing gradual concentric expansion (Elliott C, et al. Mult Scler. 2019;25(14): 1915-1925).
• Machine learning and texture analysis techniques may allow for the discrimination of MS lesion subtypes on conventional MRI imaging.
• disease activity is traditionally classified into two forms: relapsing MS or progressive MS. While conventional MRI provides reliable bio markers of acute disease activity associated with the relapsing form of the disease, there exists comparatively fewer established biomarkers for the detection of tissue states characterizing the progressive phase of MS.
• the algorithm presented in this Example leverages techniques of image processing from the fields of radiomics analysis combined with machine learning. As such, the solution is designed to identify a signature of textural biomarkers associated with SEL activity, and to use this signature to discriminate SELs from non-SELs, within the bounds of white matter hyperintensities.
• Tl-weighted and T2-weighted MRIs were retrospectively analysed (ADVANCE - 1512 patients with relapse-remitting MS; ASCEND - 886 patients with secondary progressive MS; SYNERGY - 419 patients with relapse remitting MS/secondary progressive MS).
• Ground truth SELs were detected in each baseline scan using a Jacobian integration-based method (Elliott C, etal. Mult Scler. 2019;25(14): 1915-1925) leveraging longitudinal MRI data spanning 1 to 2 years of follow-up.
• ground truth SELs were detected in each baseline scan using a Jacobian-based method analysing the evolution in T1 intensity across a series of longitudinal scans.
• Cubic patches of 15x15x15 mm were extracted from the SEL and non-SEL tissue of each baseline scan (Fig 14). Specifically, cubic patches of 15x15x15 mm were sampled randomly from SELs and non-SELs across all available baseline scans. For each patch, texture- based radiomic features were extracted separately from the core and periphery of the patch, as shown at Fig 15B in green and red, respectively. In more details, referring to Fig 15B, the “core” region contains all lesion voxels located less than 4 mm away from the central voxel of the patch. The “periphery” region contains voxels within a 3-mm margin outside the edge of the core region. For each patch, a set of 372 radiomic features was extracted from Tl- and T2-weighted MRI data.
• the feature selection algorithm evaluated the discriminative value of each feature. Using selected features, a pool of ML models were benchmarked. The 5 top-performing models were ensembled using a stacking strategy. A recursive loop further eliminated noninformative features.Briefly, patients from ADVANCE were split 80:20 into training and validation sets, respectively. The training set was used as input to a feature selection and ensemble classification pipeline. The feature selection pipeline evaluated the predictive value of each one of the 372 features, using an ensemble of correlation tests evaluating the association of each feature with the label of the patch, both in the univariate and in the multivariate setting. This approach produced a ranking of the radiomic features from most useful to least useful. In the input space defined by the 50 most useful features, a pool of standard machine learning models were benchmarked via 10-fold cross-validation using patient-level splits. The 5 top-performing models were combined under a stacking ensemble strategy.
• results The 15 radiomic features selected via our recursive elimination pipeline define a compact signature discriminative of SEL versus non-SEL activity. This signature primarily contains information from Tl-weighted MRI signals in the core of the patch. We observed that first-order statistics including the mean, median and 90 th percentile of T1 intensities in the core of the patch were identified as relevant, which is consistent with prior studies reporting that SELs exhibit a higher degree of T1 hypo-intensity relative to non-SELs at baseline. Radiomics signature of the 15 features included 10 from Tl-weighted MRI, 5 from Tl- weighted MRI, 8 from the “core” of patches, and 7 from the “periphery” of patches.
• Figs 18A-18D are confusion matrices showing the performance of the classification model for patch-level SEL versus non-SEL discrimination on the training, validation, and independent testing sets.
• Figs 19A-19D are confusion matrices showing the performance of the classification model for patch-level SEL versus non-SEL discrimination on the training, validation, and independent testing sets for volume-matched patches.
• a machine learning classifier was developed that is able to discriminate SELs from non-SELs using single-timepoint non-contrast conventional Tl - and T2- weighted MRI, with classification accuracy ranging from 66% to 69% under random patch sampling, versus 62% under strict lesion volume matching.
• the single-timepoint detection of SELs may alleviate the need for longitudinal analysis and enable baseline quantification of chronic MS lesion subtypes.
• Applications of the algorithm could include population enrichment in clinical trials and improved patient prognostication in the clinical setting. Future work can incorporate chronic active leasions detectable by paramagnetic rim identification into the classification algorithm.

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