HDV
Translational Science
Globally, over 40 million people are infected with the Hepatitis Delta virus (HDV). In the US, there is an alarming trend in the rise of infections. Hepatitis D remains a serious challenge for three reasons. First, there is no FDA approved therapy, and the current treatment with interferon-alpha has a very low success rate, twenty five percent. It is the most aggressive form of viral hepatitis and results in accelerated liver-related deaths and hepatocellular carcinoma (a common form of liver cancer). Lastly, there are limited cell-culture and animal models to study the virus in order to test new antivirals.HDV research is still in the beginning stages and the viral dynamics are unique. It is a “satellite” virus and is only infectious in the presence of the hepatitis B virus (HBV). Infection can occur in two ways: coinfection with both HDV and HBV at the same time or the HDV superinfection of an already HBV-infected individual. It is not known why HDV superinfection (compared to co-infection) leads to a higher risk of chronic HDV infection and hepatitis. There is no vaccine for HDV, but it can be theoretically controlled as a result of the success of global HBV vaccinations.Dahari Lab works across disciplines with computational modelers, virologists, clinicians, mouse-model experts and pharmaceutical companies on advancements in treatment. Our focus is on the discovery of HDV treatment response dynamics, the optimization of HDV therapy, and the evaluation of anti-HDV mode of actions of new drugs. Research can be divided across the study of human patients, mouse models and cell cultures. Data collected from all three types of research contribute to the foundational knowledge that is essential in understanding and treating HDV. Clinical (patient) data increases our understanding of the host/virus interplay, especially with new treatments. Mouse models offer the opportunity to study acute HDV because the moment of infection can be controlled (clinical data is mostly from chronic infections.) At the cellular level, these models allow for research within the liver cells directly.Access to data from all three sources, clinical (human), mouse model, and molecular (cellular), offer richer data to develop more sophisticated multicompartmental models. The ability to isolate the virus dynamics and describe in detail the interplay at the host (human), organ (liver) and cellular level is the key to unlocking effective treatments and eventual cure.
Research Topics
Interferon-alpha (IFN-α): Effect of Interferon-alpha Monotherapy on Hepatitis D Virus (HDV)
Currently there are no FDA approved treatments and the prevalent treatment using Interferon-alpha, however patients often relapse even after years of consistent treatment. Monotherapies are often not as effective as multi-therapy treatments, but they provide useful building blocks for foundational knowledge. IFN-α is an example of a less than optimal treatment that has formed the spine of ongoing research. In the spirit of developing a better understanding of the viral kinetics of HDV, we used mathematical modeling (Hepatology), which was successful in developing optimal treatment strategies for patients with hepatitis C virus. This study provided the first detailed kinetic analysis of HDV during pegylated IFN-α therapy and provides new information about HDV infection including the HDV-host dynamics. IFN’s mode of action and effectiveness were also evaluated and contribute to basic science in viral dynamics in general and HDV specifically.
Building on our 2014 Hepatology study, we conducted a follow-up analysis (Journal of Hepatology, 2024) using data from 52 participants in the Phase 3 D-LIVR clinical trial to further characterize HDV and HBsAg kinetics during pegylated interferon-α2a (pegIFN) monotherapy. This extended 48-week study identified six distinct HDV decline patterns—including previously unreported triphasic and staircase profiles—and revealed that a >1.5 log decline in HBsAg by Week 36 was a strong predictor of sustained HDV suppression at the end of follow-up. These findings refine our understanding of HDV–host interactions under pegIFN therapy and provide key parameters for improving mathematical models and designing more effective combination treatment strategies. This preliminary analysis was presented at The International Liver Congress, the 59th Annual Meeting of the European Association for the Study of the Liver (EASL) 2024.
Mathematical modeling suggests that entry-inhibitor bulevirtide (BLV) may interfere with hepatitis D virus clearance from circulation
While in some patient data modeled by Shekhtman et al 2022, BLV (an entry HDV blocker) experienced a decline consistent with its known mode of action, a second effect was also observed. Under treatment with BLV it was possible to observe an increase of HDV before HDV declined, suggesting BLV may also affect the liver’s ability to clear the virus. This transient HDV increase pattern was also seen in study presented by Hershkovich and Shehktman et al at the 2022 International HBV Meeting*, via analyzing and modeling a published BLV monotherapy study.
*2022 International HBV meeting "Molecular Biology of hepatitis B viruses" [Paris, Sept. 18-22]
Multi-Therapy LIFT hepatitis (HDV) Study: A Phase 2 Study of Lonafarnib, Ritonavir and Peginterferon Lambda
Based on successful indications from two previous monotherapy studies using LNF-RTV and interferon-λ, this multi-therapy study (Journal of Hepatology, 2022) was developed as a first-in-humans clinical trial for patients with chronic HDV and was presented at The International Liver Congress (EASL), 2022. This combination of monotherapies into a single treatment regimen demonstrated that the therapy was safe and tolerable for up to six months. In addition to its favorable safety profile, the study recorded a sustained anti-HDV response. The research concludes by raising an important question: whether extending the duration of therapy could lead to higher response rates. Our work continues as we characterize and analyze the kinetics through mathematical modeling to better understand the viral–host dynamics. Overall, this Multi-Therapy LIFT Hepatitis D study highlights the direct benefits and impact of translational research, where new clinical data and mechanistic insights inform the development of future studies, basic science advancements, and potential therapeutic strategies.
Modeling Hepatitis Delta Virus (HDV) Dynamics During Ritonavir (RTV) Boosted Lonafarnib (LNF) Treatment–The LOWR HDV-3 Study
In further study of treatment with Lonafarnib combined with Ritonavir, data collected from a clinical trial was used to investigate viral kinetics and provide insights into HDV-HBsAg-host dynamics during LNF+RTV treatment. The data model initially predicted that a LNF monotherapy dose of 610 mg bid would achieve 99% efficacy [Hepatology Comm, 2017]. However, because the maximum tolerated LNF dose in patients was 200 mg bid, the clinical trial design needed to be adapted to real-world tolerability. The addition of RTV slows the metabolization of LNF, allowing for lower LNF dosing while maintaining higher effective exposure.
In the LOWR HDV-3 study, the combination of LNF 100 mg bid + RTV was evaluated and was shown to exceed the predicted 99% efficacy concentration [Journal of Hepatology, 2018], a finding presented at The International Liver Congress (EASL), 2018. This regimen produced dramatic HDV viral load declines and demonstrated better tolerability than higher-dose LNF monotherapy. The model also successfully reproduced the observed viral, HBsAg, and ALT kinetics in each patient, offering mechanistic insights into viral–host–drug dynamics. Importantly, real-time modeling of viral kinetics provided a tool for individualizing therapy duration. More broadly, this approach empowers patients to participate in shared decision-making regarding the length of treatment.
Lonafarnib (LNF): Oral prenylation inhibition with lonafarnib in chronic hepatitis D (HDV) infection
This first-in-man, proof-of-concept study aimed to assess the effect of the prenylation inhibitor lonafarnib (LNF) on hepatitis D (HDV) RNA, safety, and tolerability in patients with chronic HDV. Prenylation inhibition disrupts the interaction between aspects of HDV and hepatitis B (HBV) that allow for HDV to be secreted from infected cells. Clinical research with a small sample of patients, in collaboration with Theo Heller and Christopher Koh (NIH, USA), Jeffrey Glen (Stanford) and Eiger Biopharmaceuticals, yielded results strong enough to warrant further research in this area. [Lancet, 2015] The use of LNF reduced the viral load significantly faster than mono-therapies using interferon-based treatments. For the first time, we were able to estimate LNF high efficacy in blocking HDV production and estimate the half-life of HDV in the blood through mathematical modeling of patient data. LNF was effective in all the patients in the small sample, whereas interferon-based therapies often have a percentage of patients that do not see results.
A significant research benefit of LNF is that it targets only HDV, while interferon-based therapies are more general, targeting both HDV and HBV. This is a unique opportunity to better understand the interplay of HDV and HBV as well as map the mode of action.
In modeling additional data sets of patients chronically infected with HDV from the research with Koh et al., it was possible to predict that a LNF monotherapy dose of 610 mg bid would achieve 99% efficacy [Hepatology Comm. 2017]. While this research did not include clinical trials involving ritonavir, it posed the question that led to actual research on the topic.
Mathematical modeling of early hepatitis D virus kinetics in transgenic mice
In research conducted in partnership with Ploss Lab at Princeton University, we characterized the early kinetics of HDV and provided insights into early HDV-host dynamics using mathematical modeling. The study involved data from three groups of mice (immunocompetent, immunodeficient, and transgenic*) inoculated with HDV simulating single infection and reinfection. Ongoing research is currently underway to better understand all the dynamics contributing to viral clearance rates.
*Transgenically expressing human NTCP (NRG-hNTCP) the receptor for HBV/HDV entry.