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.

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

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.

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.

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.

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]