Representation of Fibrosis Stage Within Mechanistic Model of Non-Alcoholic Fatty Liver Disease (NAFLD)/Non-Alchoholic Steatohepatitis (NASH) Aligns with Histologic Assessments

Conference: ACoP
Software: NAFLDsym®

Objective

NAFLD encompasses a histological spectrum of liver pathophysiology ranging from steatosis to NASH and may result in cirrhosis and ultimately liver failure. A reduction in fibrosis stage, which has been cited as the strongest predictor for disease-specific mortality¹, is a standard primary outcome when investigating efficacy of potential treatments for NASH patients. Therefore, capturing changes in fibrosis stage is critical to enable accurate predictions of efficacy for treatments within NAFLDsym®, a quantitative systems pharmacology (QSP) model that describes NAFLD pathophysiology ²,³.

Methods

To maximally leverage available collagen and fibrosis data, a multivariate regression model⁴ was used to infer percent fibrosis (or collagen index) from reported serum levels of fibrosis markers for different fibrosis stage patients in multiple studies ⁵,⁶,⁷. Additionally, a relationship between liver hydroxyproline content and percent fibrosis was used to convert liver hydroxyproline content to total hepatic collagen per wet weight ⁸,⁹,¹⁰. Using the aforementioned data, known spatiotemporal dynamics of collagen deposition, and insight into histologic fibrosis scoring methods¹¹, a computational logic scheme was devised to sequentially compare zonal¹² dynamic collagen amounts and categorize a simulated individual into their appropriate fibrosis stage F0-F4 based on each individual’s healthy (i.e., non-NAFLD/NASH) comparator status. The calculations are included within NAFLDsym.

Results

SIMPOPS™ CAPTURE DIVERSE PATHOPHYSIOLOGY OF NAFLD/NASH PATIENTS

  • Simulated NAFLD patients include combinations of parameter ranges based on reported responses from literature³
  • SimPops incorporate variability in steatosis and lipotoxicity pathways
  • SimPops incorporate variability in inflammation and fibrosis sub-models

SPATIOTEMPORTAL DYNAMICS OF COLLAGEN PLAY A CRUCIAL ROLE IN DETERMINING FIBROSIS STAGE

  • Methods (described above) utilized to infer connection
    between histologic fibrosis stage and level of collagen, zonally and in total liver
  • Model captures detectable amounts of collagen observed in
    healthy, non-NASH patients¹⁵
  • Default fibrosis stage status (F1, F2, F3, etc.) for each simulated individual determined relative to the healthy (non-NAFLD/NASH) comparator for that particular individual
    • Fibrosis stages are defined by the extent to which the collagen level in particular zones (CL, ML, PP) is elevated compared to the normal collagen level for that patient
  • Changes in collagen are the consequence of the simulated number of activated hepatic stellate cells (aHSCs); this number varies across zones with CL predominance¹²
    • This is consistent with clinical data showing the degree of HSC activation highest in CL in NASH patients¹⁶
    • Driven by different susceptibilities for HSC activation across zones
  • Rates of collagen synthesis are greater in higher fibrosis stages, consistent with clinical data¹⁷
  • Collagen level is reversible, leading to potential reduction in fibrosis stage with treatment

SIMULATED CHANGES IN FIBROSIS STAGE DUE TO NGM282 TREATMENT CONSISTENT WITH REPORTED CLINICAL DATA

NGM282, an engineered analogue of FGF19 which interacts with FGFR1 and FGFR4, was simulated in NAFLDsym. Simulations in a SimCohorts (N=168) that mimicked NGM282 clinical patients predicted a change in mean fibrosis stage of -0.2 and -0.3 with 1 and 3 mg QD NGM282 for 12 weeks, respectively, consistent with clinical data13 that reported a mean fibrosis stage change of -0.1 and -0.5.

SIMULATIONS PREDICT LACK OF FIBROSIS STAGE IMPROVEMENTS FOR CENICRIVIROC, CONSISTENT WITH CLINICAL DATA

Cenicriviroc (CVC), a CCR2/5 antagonist, was simulated in
NAFLDsym. Simulations in a NAFLD/NASH SimCohorts
(n=73) consisting of individuals with stage 3 fibrosis scores
predicted a -0.03 change in mean fibrosis stage with 150
mg QD CVC for 2 years. This was consistent with lack of
clinical efficacy that was reported¹⁴ as the cause for termination of the phase 3 clinical trial. Exploratory
simulations suggest the possibility of a more potent CCR2/5 antagonist being more efficacious at reducing fibrosis stage and improving NAFLD/NASH outcomes.

Conclusion

  • NAFLDsym captures the spatiotemporal dynamics of collagen associated with NAFLD/NASH disease progression
  • Fibrosis stage in NAFLDsym is defined relative to zonal collagen levels
  • NAFLDsym allows for the reversal of collagen levels, enabling potential reductions in fibrosis stage due to interventions
  • Accurate predictions of fibrosis stage in NAFLDsym can be used to properly represent the target population for clinical trials and subsequently used to determine efficacy of
    NAFLD/NASH treatments based on reductions in fibrosis stage

References

1. Ekstedt. Hepatol 2015; 61(5): 1547.
2. Siler. Hepatol 2018; 68(S1): 448A.
3. Akpinar-Singh. ACoP10 2019, ISSN: 2688-3953, Vol 1, T-090.
4. Takamatsu. J Gastroenterol 1997; 32(3): 355.
5. Sakugawa. World J Gastroenerol 2005; 11(2): 255.
6. Santos. Braz J Med Biol Res 2005; 38(5): 747.
7. Aida. Int J Clin Exp Med 2014; 7(11): 4191.
8. Nakabayashi. Acta Heatol Jap 1993; 34(3): 212.
9. Aycock. Connect Tissue Res 1989; 23(1): 19.
10. Rojkind. Gastroenerology 1979; 76(4): 710.
11. Brunt. Am J Gastroenerol 1999; 94(9): 2467.
12. Generaux. JPKPD 2018; 45: S102.
13. Yang. AAPS 2021: W7145V.
14. Battista. Hepatol 2021, 74(S1): 1149A.
15. Masugi. Hetpatol Commun 2017; 2(1): 58.
16.Washington. Hum Pathol 2000; 31(7): 822.
17. DeCaris. Hepatology 2017; 65(1): 78.

By Zackary R. Kenz, Christina Battista, Kyunghee Yang, Diane M. Longo, Grant Generaux, Lisl K.M. Shoda, Scott Q. Siler

Thirteenth American Conference on Pharmacometrics (ACoP13) Annual Meeting, October 30 – November 2, 2022, Aurora, Colorado