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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 (<25%). 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.

HDV Translational Science

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.

Multi-Therapy LIFT hepatitis (HDV) Study: A Phase 2 Study of Lonafarnib, Ritonavir and Peginterferon Lambda Based on the successful indications from two previous monotherapy studies using LNF-RTV and Interferon Lambda, this multi-therapy this multi-therapy study was developed for a first-in-humans clinical trial for patients with chronic HDV. This combination of monotherapies into one treatment regimen confirmed the treatment was safe and tolerable for up to 6 months. Not only was it well-tolerated, but there was a sustained ant-HDV response recorded. The research ends with a question as to whether an increased duration of therapy might lead to increased response rates. Our research is ongoing to characterize and analyze the kinetics through mathematical modeling to better understand the viral-host dynamics. This Multi-Therapy LIFT hepatitis (HDV) study illustrates the direct benefits and impact of research where the outcome is new data or insights which is useful for developing new studies that could lead to new basic science information or a treatment/solution.

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]. Given the maximum LNF tolerated dose was 200 mg bid, the clinical trial would need to be adapted to patient-real-world experience. The addition of RTV allows for slower metabolization of the LNF, resulting in lower dosage and higher efficacy. In the LOWR HDV-3 study combining LNF 100 mg bid with RTV was investigated and exceeded the predicted 99% efficacy concentration [AALSD oral abstract #38]. It was associated with dramatic HDV viral load declines and better tolerability than higher doses of LNF monotherapy. The model was also able to reproduce the observed viral, HBsAg and ALT kinetics in each patient and provide insights into viral-host-drug dynamics. The benefit to patients was real-time modeling of viral kinetics which can be used to individualize duration of therapy. In general, this type of modeling can empower patients to participate in shared decision-making regarding 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.

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]

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 (<25%). 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,...

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 (<25%). 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. 

  • Translational Science Used in Promising Results for Transplant Recipients
    A compelling example of our interdisciplinary and translational research is the research by Prof. Uprichard and colleagues which revealed that HCV cell-to-cell spread is a critical antiviral drug target and that the FDA-approved drug ezetimibe (EZE; trade name Zetia®) blocks HCV entry and cell-to-cell spread (Nature Medicine). This same foundational knowledge has been applied in a new way with significant results while exploring lung and kidney transplants infected with HCV. Dahari Lab along with Prof. Jordan Feld and colleagues (Canadian cohort) showed that patients can receive a short combo of EZE + direct-acting antiviral (DAA) therapy to block the development of HCV infection once infected transplant is received. This has significant implications for the availability of organs, patient risk and care, as well as DAA cost (Lancet Gastro and Hepatol). This comes at a time when HCV infection and mortality rates in younger populations are on the rise due to the ongoing opioid crisis (CDC).
  • Better Understanding of the Role of the Liver in HCV Clearance through Modeling
    While the liver, specifically hepatocytes, are widely accepted as the main source for HCV production, the role of the liver/hepatocytes in the clearance of circulating HCV remains largely unknown. Through kinetic and theoretical modeling (in silico) results from both liver transplantation (LT) cases (in vivo) and in cell culture experiments (in vitro) we show that the liver (and hepatocytes) plays a major role in clearing HCV from blood circulation (eLife). To the best of our knowledge, this study is the first one to investigate very detailed HCV kinetics during the absence of the liver and immediately after graft reperfusion. Our study, along with in vitro experiments suggests a role for hepatocytes in the clearance of the virus, a phenomenon which may be limited to hepatotropic viruses. The finding that the liver plays a key role in clearing HCV from the circulation has implications for clinical best practices regarding transplantation and antiviral treatment. For LT, the fact that viral levels remain at a steady state during the absence of the liver phase or anhepatic phase (i.e., the time period after patient liver is removed until the new liver is engrafted), reinforces the need of achieving viral clearance* prior to the anhepatic phase to prevent infection of the liver graft by circulating HCV in blood and avoid antiviral treatment after LT. * Viral clearance is defined as less than 1 copy of the virus genome in the blood stream. A patient is deemed “cured” (also referred to as a sustained virological response, SVR) if six months after the end of antiviral treatment or after LT the virus is not detected in the blood.
  • Modeling cell-to-cell spread of hepatitis C viral (HCV) infection in vitro
    HCV has two modes of transmission. It enters and spread via the cell-free mode of transmission circulating throughout the host. Once infection is established in the host via cell-free transmission, it can also spread via cell-to-cell. In this case, an infected cell can transmit the virus to adjacent cells. While much is understood about HCV entry and infection via cell-free mode of transmission, the role of HCV cell-to-cell spread in the liver is not as well known. In our research, in collaboration with Dr. Frederik Graw, we set out to quantify cell-to-cell transmission and assess the impact of cellular factors, viral factors, and antivirals (J Virology, Viruses, BioRxiv). Our ongoing research using agent-based modeling (ABM) has greatly enhanced our understanding of this phenomenon. The ABM developed for the study more closely mirrors the complex biological system and cellular functions. The model allowed us to better approximate how the virus spreads in the liver. Due to its complexity, study of HCV in the liver is less common, relying typically, on samples found in the blood. This interactive model (Anylogic) shows what happens when direct viral infection is removed as a variable and only cell-to-cell transmission is allowed. As a result, we are able to study not only the specific mechanism by which the drugs block cell-to-cell spread, but more importantly, measure and quantify their efficacy. Our study included the use of EZE, a cell-to-cell inhibitor, which was also used successfully in blocking HCV infection in transplant patients (The Lancet Gastroenterology & Hepatology). An increased understanding of cell-to cell transmission is important because it is seen a major contributor to viral persistence including developing resistance to therapies. In the case of inhibitor drug therapies or the patient’s own antibodies which block the virus from spreading, the virus can continue to spread via cell-to-cell. Conversely, armed with this knowledge, it is possible to develop more effective anti-virals and treatments.
  • Limitations, Advancements and Free Open Source Numerical Methods for Parameter Estimation of HCV Kinetic Models"
    Dahari Lab’s commitment to advances in HCV treatment thru viral kinetic models requires constant vigilance in the area of advanced computational and mathematical methods. Modeling is not without its limitations and we are committed to pushing the boundaries in this field. Equally important is the promoting and access of these models for others to build on in their own research. We believe in an open source mindset where applicable, ensuring the greatest number of researchers world-wide have access to advance their own work. In 2016, a partnership with Prof. Danny Barash and colleagues set in motion a series of papers that exemplify this commitment. In 2017 a robust and efficient numerical method was presented for the solution of HCV multiscale models of partial differential equations (PDE). Based on this method, a simulator for PDE with a graphical user interface (GUI) was developed (Frontiers in Applied Mathematics and Statistics). The following year the properties of the numerical solution were investigated and fine-tuned in light of advances in numerical methods (Mathematical Biosciences). The GUI was also given enhancements improving its utility (AIP Conference Proceedings). A 2019 paper followed up with a unique procedure developed to perform parameter estimation directly from the model equations (Bulletin of Mathematical Biology). This was further developed and improved in 2020 (Mathematics Special Issue Mathematical Modelling in Biomedicine). The compound effect of this research has resulted in viral kinetic models that can be calibrated efficiently for more complicated cases. The model simulators also allow for associated quantities to be known or predicted like viral trajectory over time and patient treatment time-to-cure (Journal of Infectious Diseases; Antiviral Research). Click here to access our free (HCV) viral kinetic model simulators (standard or multiscale).
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