Assessing the impact of organ-specific lesion dynamics on survival in patients with recurrent urothelial carcinoma treated with atezolizumab or chemotherapy.

BACKGROUND: Tumor dynamics typically rely on the sum of the longest diameters (SLD) of target lesions, and ignore heterogeneity in individual lesion dynamics located in different organs. PATIENTS AND METHODS: Here we evaluated the benefit of analyzing lesion dynamics in different organs to predict survival in 900 patients with metastatic urothelial carcinoma treated with atezolizumab or chemotherapy (IMvigor211 trial). RESULTS: Lesion dynamics varied largely across organs, with lymph nodes and lung lesions showing on average a better response to both treatments than those located in the liver and locoregionally. A benefit of atezolizumab was observed on lung and liver lesion dynamics that was attributed to a longer duration of treatment effect as compared to chemotherapy (P value = 0.043 and 0.001, respectively). The impact of lesion dynamics on survival, assessed by a joint model, varied greatly across organs, irrespective of treatment. Liver and locoregional lesion dynamics had a large impact on survival, with an increase of 10 mm of the lesion size increasing the instantaneous risk of death by 12% and 10%, respectively. In comparison, lymph nodes and lung lesions had a lower impact, with a 10-mm increase in the lesion size increasing the instantaneous risk of death by 7% and 5%, respectively. Using our model, we could anticipate the benefit of atezolizumab over chemotherapy as early as 6 months before the end of the study, which is 3 months earlier than a similar model only relying on SLD. CONCLUSION: We showed the interest of organ-level tumor follow-up to better understand and anticipate the treatment effect on survival.

COVA1-18 neutralizing antibody protects against SARS-CoV-2 in three preclinical models.

One year into the Coronavirus Disease 2019 (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), effective treatments are still needed 1-3 . Monoclonal antibodies, given alone or as part of a therapeutic cocktail, have shown promising results in patients, raising the hope that they could play an important role in preventing clinical deterioration in severely ill or in exposed, high risk individuals 4-6 . Here, we evaluated the prophylactic and therapeutic effect of COVA1-18 in vivo , a neutralizing antibody isolated from a convalescent patient 7 and highly potent against the B.1.1.7. isolate 8,9 . In both prophylactic and therapeutic settings, SARS-CoV-2 remained undetectable in the lungs of COVA1-18 treated hACE2 mice. Therapeutic treatment also caused a dramatic reduction in viral loads in the lungs of Syrian hamsters. When administered at 10 mg kg - 1 one day prior to a high dose SARS-CoV-2 challenge in cynomolgus macaques, COVA1-18 had a very strong antiviral activity in the upper respiratory compartments with an estimated reduction in viral infectivity of more than 95%, and prevented lymphopenia and extensive lung lesions. Modelling and experimental findings demonstrate that COVA1-18 has a strong antiviral activity in three different preclinical models and could be a valuable candidate for further clinical evaluation.

Viral kinetics analysis and virological characterization of treatment failures in patients with chronic hepatitis C treated with sofosbuvir and an NS5A inhibitor.

BACKGROUND: The combination of sofosbuvir (SOF) plus an NS5A inhibitor for 12 weeks is highly efficacious in patients with chronic hepatitis C. As the costs of generic production of sofosbuvir and NS5A inhibitor are rapidly decreasing, the combination of these DAAs will be the standard treatment in most low- to middle-income countries in the future. AIM: To identify key predictors of response that can be used to tailor treatment decisions. METHODS: A cohort of 216 consecutive patients infected with HCV genotype 1 (1a: n = 57; 1b: n = 77), 2 (n = 4), 3 (n = 33) or 4 (n = 44) were treated with sofosbuvir (SOF) + daclatasvir (n = 176) or SOF + ledipasvir (n = 40) for 12 weeks. The viral kinetics was analysed using the biphasic model and the cure boundary was used to predict time to clear HCV. RESULTS: The overall SVR rate was high (94.4%; n = 204), regardless of the time to viral suppression or low-level viraemia at the end of treatment. The model-based predicted HCV RNA levels at the end of treatment could not differentiate patients who did from those who did not achieve SVR. The presence of NS5A resistance-associated substitutions [position 28 (OR = 70.3, P<.001) and/or 31 (OR = 61.6, P = .002)] at baseline was predictive of virological failure in cirrhotic patients but was not associated with on-treatment viral kinetics. CONCLUSION: This real-world study confirms the excellent results of clinical trials with therapies based on a combination of SOF plus an NS5A inhibitor. It suggests that a personalized approach including baseline NS5A inhibitor resistance testing may inform treatment decisions in cirrhotic patients.

A Model-Based Illustrative Exploratory Approach to Optimize the Dosing of Peg-IFN/RBV in Cirrhotic Hepatitis C Patients Treated With Triple Therapy.

Hézode et al. recently reported the frequent occurrence of anemia and thrombocytopenia in the ANRS-CO20-CUPIC cohort of hepatitis C virus (HCV) cirrhotic experienced patients treated with pegylated-interferon (Peg-IFN), ribavirin (RBV), and telaprevir or boceprevir.1,2 Using frequent measurements of serum drug concentrations, hemoglobin, and platelet concentrations obtained in 15 patients of this cohort, we show how an on-treatment model-based approach could be used to individualize dose regimen and avoid the occurrence of RBV-induced anemia and Peg-IFN-induced thrombocytopenia.

HCV Kinetic Models and Their Implications in Drug Development.

Chronic infection with hepatitis C virus (HCV) affects about 170 million people worldwide and is a major cause of liver complications. Mathematical modeling of viral kinetics under treatment has provided insight into the viral life cycle, treatment effectiveness, and drugs' mechanisms of action. Here we review the implications of viral kinetic models at the different stages of development of anti-HCV agents.

A pharmacokinetic-viral kinetic model describes the effect of alisporivir as monotherapy or in combination with peg-IFN on hepatitis C virologic response.

Alisporivir is a cyclophilin inhibitor with demonstrated in vitro and in vivo activity against hepatitis C virus (HCV). We estimated the antiviral effectiveness of alisporivir alone or in combination with pegylated interferon (peg-IFN) in 88 patients infected with different HCV genotypes treated for 4 weeks. The pharmacokinetics of the two drugs were modeled and used as driving functions for the viral kinetic model. Genotype was found to significantly affect peg-IFN effectiveness (ɛ = 86.3 and 99.1% for genotypes 1/4 and genotypes 2/3, respectively, P < 10(-7)) and the loss rate of infected cells (δ = 0.22 vs. 0.39 per day in genotype 1/4 and genotype 2/3 patients, respectively, P < 10(-6)). Alisporivir effectiveness was not significantly different across genotypes and was high for doses ≥600 mg q.d. We simulated virologic responses with other alisporivir dosing regimens in HCV genotype 2/3 patients using the model. Our predictions consistently matched the observed responses, demonstrating that this model could be a useful tool for anticipating virologic response and optimizing alisporivir-based therapies.

Influence of a priori Information, Designs, and Undetectable Data on Individual Parameters Estimation and Prediction of Hepatitis C Treatment Outcome.

Hepatitis C viral kinetic analysis based on nonlinear mixed effect models can be used to individualize treatment. For that purpose, it is necessary to obtain precise estimation of individual parameters. Here, we evaluated by simulation the influence on Bayesian individual parameter estimation and outcome prediction of a priori information on population parameters, viral load sampling designs, and methods for handling data below detection limit (BDL). We found that a precise estimation of both individual parameters and treatment outcome could be obtained using as few as six measurements in the first month of therapy. This result remained valid even when incorrect a priori information on population parameters was set as long as the parameters were identifiable and BDL data were properly handled. However, setting wrong values for a priori population parameters could lead to severe estimation/prediction errors if BDL data were ignored and not properly accounted in the likelihood function.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e56; doi:10.1038/psp.2013.31; published online 17 July 2013.

The impact of fibrosis and steatosis on early viral kinetics in HCV genotype 1-infected patients treated with Peg-IFN-alfa-2a and ribavirin.

Hepatitis C viral (HCV) kinetics after initiation of interferon-based therapy provide valuable insights for understanding virus pathogenesis, evaluating treatment antiviral effectiveness and predicting treatment outcome. Adverse effects of liver fibrosis and steatosis on sustained virological response have been frequently reported, yet their impacts on the early viral kinetics remain unclear. In this study, associations between histology status and early viral kinetics were assessed in 149 HCV genotype 1-infected patients treated with pegylated interferon alfa-2a and ribavirin (DITTO trial). In multivariate analyses adjusted for critical factors such as IL28B genotype and baseline viral load, presence of significant fibrosis (Ishak stage > 2) was found to independently reduce the odds of achieving an initial reduction (calculated from day 0 to day 4) in HCV RNA of ≥2 logIU/mL (adjusted OR 0.03, P = 0.004) but was not associated with the second-phase slope of viral decline (calculated from day 8 to day 29). On the contrary, presence of liver steatosis was an independent risk factor for not having a rapid second-phase slope, that is, ≥0.3 logIU/mL/week (adjusted OR 0.22, P = 0.012) but was not associated with the first-phase decline. Viral kinetic modelling theory suggests that significant fibrosis primarily impairs the treatment antiviral effectiveness in blocking viral production by infected cells, whereas the presence of steatosis is associated with a lower net loss of infected cells. Further studies will be necessary to identify the biological mechanisms underlain by these findings.

Understanding hepatitis C viral dynamics with direct-acting antiviral agents due to the interplay between intracellular replication and cellular infection dynamics.

The current paradigm for modeling viral kinetics and resistance evolution after treatment initiation considers only the level of circulating virus and cellular infection (CI model), while the intra-cellular level is disregarded. This model was successfully used to explain HIV dynamics and Hepatitis C virus (HCV) dynamics during interferon-based therapy. However, in the new era of direct-acting antiviral agents (DAAs) against HCV, viral kinetics is characterized by a more rapid decline of the wild-type virus as well as an early emergence of resistant strains that jeopardize the treatment outcome. Although the CI model can be extended to describe these new kinetic patterns, this approach has qualitative and quantitative limitations. Instead, we suggest that a more appropriate approach would consider viral dynamics at the cell infection level, as done currently, as well as at the intracellular level. Indeed, whereas in HIV integrated DNA serves as a static replication unit and mutations occur only once per infected cell, HCV replication is deeply affected by DAAs and furthermore processes of resistance evolution can occur at the intra-cellular level with a faster time-scale. We propose a comprehensive model of HCV dynamics that considers both extracellular and intracellular levels of infection (ICCI model). Intracellular viral genomic units are used to form replication units, which in turn synthesize genomic units that are packaged and secreted as virions infecting more target cells. Resistance evolution is modeled intra-cellularly, by different genomic- and replication-unit strains with particular relative-fitness and drug sensitivity properties, allowing for a rapid resistance takeover. Using the ICCI model, we show that the rapid decline of wild-type virus results from the ability of DAAs to destabilize the intracellular replication. On the other hand, this ability also favors the rapid emergence, intracellularly, of resistant virus. By considering the interaction between intracellular and extracellular infection we show that resistant virus, able to maintain a high level of intracellular replication, may nevertheless be unable to maintain rapid enough de novo infection rate at the extracellular level. Hence this model predicts that in HCV, and contrary to our experience with HIV, the emergence of productively resistant virus may not systematically prevent from a viral decline in the long-term. Thus, the ICCI model can explain the transient viral rebounds observed with DAA treatment as well as the viral resistance found in most patients with viral relapse at the end of DAA combination therapy.

A perspective on modelling hepatitis C virus infection.

By mathematically describing early hepatitis C virus (HCV) RNA decay after initiation of interferon (IFN)-based antiviral therapy, crucial parameters of the in vivo viral kinetics have been estimated, such as the rate of production and clearance of free virus, and the rate of loss of infected cells. Furthermore, by suggesting mechanisms of action for IFN and ribavirin mathematical modelling has provided a means for evaluating and optimizing treatment strategies. Here, we review recent modelling developments for understanding complex viral kinetics patterns, such as triphasic HCV RNA declines and viral rebounds observed in patients treated with pegylated interferon and ribavirin. Moreover, we discuss new modelling approaches developed to interpret the viral kinetics observed in clinical trials with direct-acting antiviral agents, which induce a rapid decline of wild-type virus but also engender a higher risk for emergence of drug-resistant variants. Lastly, as in vitro systems have allowed a better characterization of the virus lifecycle, we discuss new modelling approaches that combine the intracellular and the extracellular viral dynamics.

Practical identifiability of HIV dynamics models.

We study the practical identifiability of parameters, i.e., the accuracy of the estimation that can be hoped, in a model of HIV dynamics based on a system of non-linear Ordinary Differential Equations (ODE). This depends on the available information such as the schedule of the measurements, the observed components, and the measurement precision. The number of patients is another way to increase it by introducing an appropriate statistical "population" framework. The impact of each improvement of the experimental condition is not known in advance but it can be evaluated via the Fisher Information Matrix (FIM). If the non-linearity of the biological model, as well as the complex statistical framework makes computation of the FIM challenging, we show that the particular structure of these models enables to compute it as precisely as wanted. In the HIV model, measuring HIV viral load and total CD4+ count were not enough to achieve identifiability of all the parameters involved. However, we show that an appropriate statistical approach together with the availability of additional markers such as infected cells or activated cells should considerably improve the identifiability and thus the usefulness of dynamical models of HIV.

Maximum likelihood estimation in dynamical models of HIV.

The study of dynamical models of HIV infection, based on a system of nonlinear ordinary differential equations (ODE), has considerably improved the knowledge of its pathogenesis. While the first models used simplified ODE systems and analyzed each patient separately, recent works dealt with inference in non-simplified models borrowing strength from the whole sample. The complexity of these models leads to great difficulties for inference and only the Bayesian approach has been attempted by now. We propose a full likelihood inference, adapting a Newton-like algorithm for these particular models. We consider a relatively complex ODE model for HIV infection and a model for the observations including the issue of detection limits. We apply this approach to the analysis of a clinical trial of antiretroviral therapy (ALBI ANRS 070) and we show that the whole algorithm works well in a simulation study.

[Treatment of acute alcoholic hepatitis with prednisolone. 45 patients]. / Traitement de l'hépatite alcoolique aiguë par la prednisolone. Quarante-cinq malades.

Whether or not prednisolone (or prednisone) should be used to treat alcoholic hepatitis remains controversial. This new controlled study performed on 45 patients with steatosis, fibrosis or cirrhosis of the liver suggests that prednisolone is not effective: after a 3-month follow-up clinical course, biochemical alterations, anatomical lesions and portal hypertension were the same in patients treated with prednisolone and in those who did not receive that drug.