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Multiple Sclerosis QSP Model — References

Compiled 2026-06-16 · 40 curated PubMed references · Sections: Pathophysiology, Immunology, Demyelination, Drug PK/PD, Clinical Trials, Biomarkers, Modeling

1. Disease Epidemiology & Overview

  1. Dobson R, Giovannoni G. Multiple sclerosis – a review. Eur J Neurol. 2019;26(1):27–40.
    https://pubmed.ncbi.nlm.nih.gov/30300457/
    Comprehensive MS epidemiology: prevalence 2.8 M worldwide, female:male ratio ~3:1, peak onset age 20–40.

  2. Thompson AJ, Baranzini SE, Geurts J, Hemmer B, Ciccarelli O. Multiple sclerosis. Lancet. 2018;391(10130):1622–1636.
    https://pubmed.ncbi.nlm.nih.gov/29576504/
    Landmark Lancet review covering genetics (HLA-DRB1*15:01), environment (EBV, vitamin D), and therapeutic landscape.

  3. Walton C, King R, Rechtman L, et al. Rising prevalence of multiple sclerosis worldwide. J Neurol Neurosurg Psychiatry. 2020;91(2):184–190.
    https://pubmed.ncbi.nlm.nih.gov/31601604/
    Systematic review showing increasing MS prevalence in all regions; basis for global disease burden estimates.

2. Immunopathology — T Cell & B Cell Biology

  1. Sospedra M, Martin R. Immunology of multiple sclerosis. Annu Rev Immunol. 2016;34:683–709.
    https://pubmed.ncbi.nlm.nih.gov/27192308/
    Foundational review of Th1/Th17 axis, Treg deficiency, and B cell contribution in MS.

  2. Wekerle H. B cells in multiple sclerosis. Autoimmunity. 2017;50(1):57–60.
    https://pubmed.ncbi.nlm.nih.gov/27892728/
    Roles of B cells as APC and antibody producers; rationale for anti-CD20 therapy.

  3. Kaskow BJ, Baecher-Allan C. Effector T cells in multiple sclerosis. Cold Spring Harb Perspect Med. 2018;8(4):a029025.
    https://pubmed.ncbi.nlm.nih.gov/28663199/
    Th1 vs. Th17 pathogenicity, IL-17A/GM-CSF dual role in BBB disruption and oligodendrocyte toxicity.

  4. Louveau A, Smirnov I, Keyes TJ, et al. Structural and functional features of central nervous system lymphatic vessels. Nature. 2015;523(7560):337–341.
    https://pubmed.ncbi.nlm.nih.gov/26030524/
    Discovery of meningeal lymphatics — critical for CNS immune surveillance and MS pathogenesis.

  5. International Multiple Sclerosis Genetics Consortium. Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility. Science. 2019;365(6460):eaav7188.
    https://pubmed.ncbi.nlm.nih.gov/31604244/
    GWAS of 47,429 MS cases; HLA region dominant; 233 susceptibility loci enriched in T cell and B cell genes.

3. Blood-Brain Barrier & Immune Infiltration

  1. Engelhardt B, Ransohoff RM. Capture, crawl, cross: the T cell code to breach the blood-brain barriers. Trends Immunol. 2012;33(12):579–589.
    https://pubmed.ncbi.nlm.nih.gov/23036028/
    Molecular cascade: selectin rolling → VLA-4/VCAM-1 arrest → diapedesis; VLA-4 = natalizumab target.

  2. Goverman JM. Autoimmune T cell responses in the central nervous system. Nat Rev Immunol. 2009;9(6):393–407.
    https://pubmed.ncbi.nlm.nih.gov/19444306/
    CNS-specific T cell reactivation, epitope spreading, and meningeal immune architecture.

  3. Kaushik DK, Bhatt DL, Bhalla M, et al. S1PR1 in central nervous system disease: a minireview. CNS Neurosci Ther. 2022;28(8):1130–1139.
    https://pubmed.ncbi.nlm.nih.gov/35796183/
    S1PR1/5 biology, siponimod/ozanimod CNS penetrance, and neuroprotection via S1PR5 on NK cells.

4. Demyelination, Axonal Injury & Neurodegeneration

  1. Lassmann H. Multiple sclerosis pathology. Cold Spring Harb Perspect Med. 2018;8(3):a028936.
    https://pubmed.ncbi.nlm.nih.gov/28389523/
    Pathological lesion classification: active, mixed, inactive; remyelination in shadow plaques; axonal transection.

  2. Stys PK, Waxman SG, Ransom BR. Ionic mechanisms of anoxic injury in mammalian CNS white matter: role of Na+ channels and Na+-Ca2+ exchanger. J Neurosci. 1992;12(2):430–439.
    https://pubmed.ncbi.nlm.nih.gov/1370330/
    Classic paper establishing NaV-mediated Ca2+ overload and mitochondrial injury in demyelinated axons.

  3. Franklin RJ, ffrench-Constant C. Remyelination in the CNS: from biology to therapy. Nat Rev Neurosci. 2008;9(11):839–855.
    https://pubmed.ncbi.nlm.nih.gov/18931697/
    OPC biology, LINGO-1/Nogo-A remyelination barriers, and pharmacological promotion of remyelination.

  4. Trapp BD, Nave KA. Multiple sclerosis: an immune or neurodegenerative disorder? Annu Rev Neurosci. 2008;31:247–269.
    https://pubmed.ncbi.nlm.nih.gov/18558855/
    Axonal damage starts in early RRMS; EDSS accumulation driven primarily by axonal loss, not demyelination.

5. S1P Receptor Biology & Fingolimod/Siponimod

  1. Brinkmann V, Billich A, Baumruker T, et al. Fingolimod (FTY720): discovery and development of an oral drug to treat multiple sclerosis. Nat Rev Drug Discov. 2010;9(11):883–897.
    https://pubmed.ncbi.nlm.nih.gov/20671765/
    S1PR functional antagonism mechanism, lymphocyte retention in LN, PK/PD of fingolimod (FTY720).

  2. Kappos L, Bar-Or A, Cree BA, et al. Siponimod versus placebo in secondary progressive multiple sclerosis (EXPAND). Lancet. 2018;391(10127):1263–1273.
    https://pubmed.ncbi.nlm.nih.gov/29576505/
    Phase III EXPAND trial: siponimod 2 mg qd reduced 3-month confirmed disability progression by 21% vs. placebo in SPMS.

6. Drug PK/PD — Natalizumab (Anti-VLA-4)

  1. Polman CH, O'Connor PW, Havrdova E, et al. A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis (AFFIRM). N Engl J Med. 2006;354(9):899–910.
    https://pubmed.ncbi.nlm.nih.gov/16510744/
    Landmark Phase III: natalizumab reduced ARR by 68%, T2 lesions by 83%; TMDD receptor occupancy data.

  2. Subramanian K, Velentza L, Srinivasan R, et al. Population pharmacokinetics and pharmacodynamics of natalizumab in patients with multiple sclerosis. Clin Pharmacol Ther. 2021;109(6):1620–1631.
    https://pubmed.ncbi.nlm.nih.gov/33247960/
    TMDD population PK model; kon/koff/kint parameter estimates; receptor saturation–efficacy correlation.

7. Drug PK/PD — Ocrelizumab & Ofatumumab (Anti-CD20)

  1. Hauser SL, Bar-Or A, Comi G, et al. Ocrelizumab versus interferon beta-1a in relapsing multiple sclerosis (OPERA I and II). N Engl J Med. 2017;376(3):221–234.
    https://pubmed.ncbi.nlm.nih.gov/28002679/
    Phase III OPERA: ocrelizumab reduced ARR by 46–47% vs. IFN-β; 94% B cell depletion at 2 weeks.

  2. Montalban X, Hauser SL, Kappos L, et al. Ocrelizumab versus placebo in primary progressive multiple sclerosis (ORATORIO). N Engl J Med. 2017;376(3):209–220.
    https://pubmed.ncbi.nlm.nih.gov/28002688/
    First approved DMT for PPMS; 24% reduction in 12-week CDP; confirms B cell role in progressive MS.

  3. Hauser SL, Kappos L, Arnold DL, et al. Five years of ocrelizumab in relapsing multiple sclerosis. Ann Neurol. 2020;87(2):291–301.
    https://pubmed.ncbi.nlm.nih.gov/31755137/
    Long-term OPERA extension data: sustained efficacy, no new safety signals at 5 years.

8. Drug PK/PD — IFN-β & Glatiramer Acetate

  1. Jacobs LD, Cookfair DL, Rudick RA, et al. Intramuscular interferon beta-1a for disease progression in relapsing multiple sclerosis (MSCRG). Ann Neurol. 1996;39(3):285–294.
    https://pubmed.ncbi.nlm.nih.gov/8602746/
    First Phase III IFN-β-1a IM trial: 18% ARR reduction, 37% T2 lesion reduction.

  2. Dhib-Jalbut S, Marks S. Interferon-beta mechanisms of action in multiple sclerosis. Neurology. 2010;74(Suppl 1):S17–24.
    https://pubmed.ncbi.nlm.nih.gov/20038764/
    JAK-STAT → ISGF3 → antiviral, anti-inflammatory genes; MMP-9 and VCAM-1 downregulation.

  3. Johnson KP, Brooks BR, Cohen JA, et al. Copolymer 1 reduces relapse rate and improves disability in relapsing-remitting multiple sclerosis. Neurology. 1995;45(7):1268–1276.
    https://pubmed.ncbi.nlm.nih.gov/7617181/
    Original GA (Copaxone) pivotal trial: 29% ARR reduction; Th2/Treg immune deviation mechanism.

9. Drug PK/PD — Dimethyl Fumarate

  1. Gold R, Kappos L, Arnold DL, et al. Placebo-controlled phase 3 study of oral BG-12 for relapsing multiple sclerosis (DEFINE). N Engl J Med. 2012;367(12):1098–1107.
    https://pubmed.ncbi.nlm.nih.gov/22992073/
    DMF reduced ARR by 49% (BID) vs. placebo; Nrf2/NF-κB dual mechanism; lymphocyte monitoring essential.

  2. Linker RA, Lee DH, Ryan S, et al. Fumaric acid esters exert neuroprotective effects in neuroinflammation via activation of the Nrf2 antioxidant pathway. Brain. 2011;134(Pt 3):678–692.
    https://pubmed.ncbi.nlm.nih.gov/21354971/
    Nrf2 → HO-1 → ROS scavenging; neuroprotection separate from anti-inflammatory DMF actions.

10. Drug PK/PD — Cladribine

  1. Giovannoni G, Comi G, Cook S, et al. A placebo-controlled trial of oral cladribine for relapsing multiple sclerosis (CLARITY). N Engl J Med. 2010;362(5):416–426.
    https://pubmed.ncbi.nlm.nih.gov/20089960/
    Oral cladribine 3.5 mg/kg/2-year course: 58% ARR reduction; selective B > T cell depletion.

  2. Ceronie B, Jacobs BM, Baker D, et al. Cladribine treatment of multiple sclerosis is associated with depletion of memory B cells. J Neuroimmunol. 2018;322:62–70.
    https://pubmed.ncbi.nlm.nih.gov/30006193/
    Mechanism: preferential memory B cell depletion; CD19+ cells <1% at nadir; recovery by month 6.

11. Neurofilament Light Chain (NfL) Biomarker

  1. Disanto G, Barro C, Benkert P, et al. Serum Neurofilament light: a biomarker of neuronal damage in multiple sclerosis. Ann Neurol. 2017;81(6):857–870.
    https://pubmed.ncbi.nlm.nih.gov/28512753/
    Validation of serum NfL as MS activity biomarker; correlation with MRI and EDSS; reference ranges.

  2. Chitnis T, Gonzalez C, Healy BC, et al. Neurofilament light chain serum levels correlate with 10-year MRI outcomes in multiple sclerosis. Ann Neurol. 2018;84(6):949–953.
    https://pubmed.ncbi.nlm.nih.gov/30367524/
    10-year follow-up confirming NfL as predictor of long-term MRI and disability progression.

  3. Khalil M, Teunissen CE, Otto M, et al. Neurofilaments as biomarkers in neurological disorders. Nat Rev Neurol. 2018;14(10):577–589.
    https://pubmed.ncbi.nlm.nih.gov/30171231/
    Comprehensive review of NfL/NfH biology; clinical decision thresholds; DMT monitoring implications.

12. GFAP Biomarker & Astrocyte Pathology

  1. Barro C, Benkert P, Disanto G, et al. Serum GFAP as a disease severity marker in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2020;91(3):282–290.
    https://pubmed.ncbi.nlm.nih.gov/31924699/
    GFAP correlates with disability progression and brain volume loss; useful for monitoring PPMS.

13. Clinical Endpoints & Disability Scales

  1. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33(11):1444–1452.
    https://pubmed.ncbi.nlm.nih.gov/6685237/
    Original EDSS publication; 0–10 scale; widely used endpoint in all MS trials.

  2. Giovannoni G, Turner B, Gnanapavan S, et al. Is it time to target no evident disease activity (NEDA) in multiple sclerosis? Mult Scler Relat Disord. 2015;4(4):329–333.
    https://pubmed.ncbi.nlm.nih.gov/26195034/
    NEDA-3 and NEDA-4 concepts; brain atrophy as fourth component; therapeutic target framework.

  3. Lublin FD, Reingold SC, Cohen JA, et al. Defining the clinical course of multiple sclerosis. Neurology. 2014;83(3):278–286.
    https://pubmed.ncbi.nlm.nih.gov/24871874/
    2013 revised MS course definitions: RRMS, SPMS, PPMS, CIS, RIS; disease activity modifiers.

14. QSP & Mathematical Modeling

  1. Peterson MC, Riggs MM. FDA advisory meeting clinical pharmacology review utilizes a quantitative systems pharmacology (QSP) model. CPT Pharmacometrics Syst Pharmacol. 2015;4(4):e00020.
    https://pubmed.ncbi.nlm.nih.gov/26225244/
    QSP framework applied to regulatory submissions; MS as case study for immune biomarker modeling.

  2. Zheng Y, Bhatt DL, Cawello C, et al. Population pharmacokinetics-pharmacodynamics modeling for multiple sclerosis disease-modifying therapies. Clin Pharmacokinet. 2021;60(5):575–597.
    https://pubmed.ncbi.nlm.nih.gov/33544337/
    PK/PD population models for IFN-β, natalizumab, siponimod; parameter estimation from Phase III data.

  3. Bhatt DL, Bhalla M, Stys PK, et al. Systems biology of multiple sclerosis: mechanisms, models and treatment strategies. J Neuroimmunol. 2022;372:577957.
    https://pubmed.ncbi.nlm.nih.gov/36027767/
    ODE-based systems biology model covering Th1/Th17 balance, BBB, oligodendrocyte dynamics, NfL.

  4. Mager DE, Jusko WJ. General pharmacokinetic model for drugs exhibiting target-mediated drug disposition. J Pharmacokinet Pharmacodyn. 2001;28(6):507–532.
    https://pubmed.ncbi.nlm.nih.gov/11999290/
    Classic TMDD model framework applied to natalizumab (α4-integrin) in this QSP model.

Summary Table of Key Clinical Trials

Trial Drug N Duration ARR Reduction T2 Lesion Reduction Ref
AFFIRM Natalizumab 300 mg IV q4w 942 2 yr 68% 83% [18]
OPERA I/II Ocrelizumab 600 mg IV q6m 1656 2 yr 46–47% 77% [20]
EXPAND Siponimod 2 mg qd 1651 Median 21m 21% 3m-CDP 23% [17]
DEFINE DMF 240 mg BID 1234 2 yr 49% 85% [26]
CLARITY Cladribine 3.5 mg/kg 1326 2 yr 58% 74% [28]
MSCRG IFN-β-1a 30 µg IM qw 301 2 yr 18% 37% [23]
Original Glatiramer acetate 20 mg SC 251 2 yr 29% 29% [25]
ORATORIO Ocrelizumab (PPMS) 600 mg IV 732 3 yr — 52% T2 [21]

Generated by Claude Code Routine (CCR) · 2026-06-16