With the advent of rapid multiplex PCR, physicians have been able to test for multiple viral path... more With the advent of rapid multiplex PCR, physicians have been able to test for multiple viral pathogens when a patient presents with influenza-like illness. This has led to the discovery that many respiratory infections are caused by more than one virus. Antiviral treatment of viral coinfections can be complex because treatment of one virus will affect the time course of the other virus. Since effective antivirals are only available for some respiratory viruses, careful consideration needs to be given on the effect treating one virus will have on the dynamics of the other virus, which might not have available antiviral treatment. In this study, we use mathematical models of viral coinfections to assess the effect of antiviral treatment on coinfections. We examine the effect of the mechanism of action, relative growth rates of the viruses, and the assumptions underlying the interaction of the viruses. We find that high antiviral efficacy is needed to suppress both infections. If high ...
Defective viral genomes (DVGs) are viral genomes that contain only a partial viral RNA and so can... more Defective viral genomes (DVGs) are viral genomes that contain only a partial viral RNA and so cannot replicate within cells on their own. If a cell containing DVGs is subsequently infected with a complete viral genome, the DVG can then use the missing proteins expressed by the full genome in order to replicate itself. Since the cell is producing defective genomes, it has less resources to produce fully functional virions and thus release of complete virions is often suppressed. Here, we use data from challenge studies of respiratory syncytial virus (RSV) in healthy adults to quantify the effect of DVGs. We use a mathematical model to fit the data, finding that late onset of DVGs and prolonged DVG detection are associated with lower infection rates and higher clearance rates. This result could have implications for the use of DVGs as a therapeutic.
One of the primary cancer treatment modalities is chemotherapy. Unfortunately, traditional anti-c... more One of the primary cancer treatment modalities is chemotherapy. Unfortunately, traditional anti-cancer drugs are often not selective and cause damage to healthy cells, leading to serious side effects for patients. For this reason more targeted therapeutics and drug delivery methods are being developed. The effectiveness of new treatments is initially determined via in vitro cell viability assays, which determine the IC50 of the drug. However, these assays are known to result in estimates of IC50 that depend on the measurement time, possibly resulting in over- or under-estimation of the IC50. Here, we test the possibility of using cell growth curves and fitting of mathematical models to determine the IC50 as well as the maximum efficacy of a drug (εmax). We measured cell growth of MCF-7 and HeLa cells in the presence of different concentrations of doxorubicin and fit the data with a logistic growth model that incorporates the effect of the drug. This method leads to measurement time-independent estimates of IC50 and εmax, but we find that εmax is not identifiable. Further refinement of this methodology is needed to produce uniquely identifiable parameter estimates.
Viral titer data collected in vitro or in vivo is often analyzed by extracting viral titer charac... more Viral titer data collected in vitro or in vivo is often analyzed by extracting viral titer characteristics such as peak viral titer, time of viral peak and area under the curve (AUC). Researchers compare these characteristics in the absence and presence of various concentrations of antivirals in an attempt to quantify the effect of antivirals. Often these characteristics are estimated using only measured data points, although fitting of simple mathematical models to estimate these parameters is becoming more prevalent. In this article, our aim is to compare the estimates of different viral titer characteristics using three different approaches. The first approach is the traditional method that uses estimates based on experimentally measured data. The second approach relies on the use of a linear model to fit the viral titer data. The third approach uses an exponential model for the fitting process and the parameters of interest are extracted from there. The mathematical models are tested using in vivo and in vitro influenza infection data. Estimates of viral titer characteristics using either of the two fitting approaches were similar, but differed from estimates using the traditional method.
With the advent of rapid multiplex PCR, physicians have been able to test for multiple viral path... more With the advent of rapid multiplex PCR, physicians have been able to test for multiple viral pathogens when a patient presents with influenza-like illness. This has led to the discovery that many respiratory infections are caused by more than one virus. Antiviral treatment of viral coinfections can be complex because treatment of one virus will affect the time course of the other virus. Since effective antivirals are only available for some respiratory viruses, careful consideration needs to be given on the effect treating one virus will have on the dynamics of the other virus, which might not have available antiviral treatment. In this study, we use mathematical models of viral coinfections to assess the effect of antiviral treatment on coinfections. We examine the effect of the mechanism of action, relative growth rates of the viruses, and the assumptions underlying the interaction of the viruses. We find that high antiviral efficacy is needed to suppress both infections. If high ...
Defective viral genomes (DVGs) are viral genomes that contain only a partial viral RNA and so can... more Defective viral genomes (DVGs) are viral genomes that contain only a partial viral RNA and so cannot replicate within cells on their own. If a cell containing DVGs is subsequently infected with a complete viral genome, the DVG can then use the missing proteins expressed by the full genome in order to replicate itself. Since the cell is producing defective genomes, it has less resources to produce fully functional virions and thus release of complete virions is often suppressed. Here, we use data from challenge studies of respiratory syncytial virus (RSV) in healthy adults to quantify the effect of DVGs. We use a mathematical model to fit the data, finding that late onset of DVGs and prolonged DVG detection are associated with lower infection rates and higher clearance rates. This result could have implications for the use of DVGs as a therapeutic.
One of the primary cancer treatment modalities is chemotherapy. Unfortunately, traditional anti-c... more One of the primary cancer treatment modalities is chemotherapy. Unfortunately, traditional anti-cancer drugs are often not selective and cause damage to healthy cells, leading to serious side effects for patients. For this reason more targeted therapeutics and drug delivery methods are being developed. The effectiveness of new treatments is initially determined via in vitro cell viability assays, which determine the IC50 of the drug. However, these assays are known to result in estimates of IC50 that depend on the measurement time, possibly resulting in over- or under-estimation of the IC50. Here, we test the possibility of using cell growth curves and fitting of mathematical models to determine the IC50 as well as the maximum efficacy of a drug (εmax). We measured cell growth of MCF-7 and HeLa cells in the presence of different concentrations of doxorubicin and fit the data with a logistic growth model that incorporates the effect of the drug. This method leads to measurement time-independent estimates of IC50 and εmax, but we find that εmax is not identifiable. Further refinement of this methodology is needed to produce uniquely identifiable parameter estimates.
Viral titer data collected in vitro or in vivo is often analyzed by extracting viral titer charac... more Viral titer data collected in vitro or in vivo is often analyzed by extracting viral titer characteristics such as peak viral titer, time of viral peak and area under the curve (AUC). Researchers compare these characteristics in the absence and presence of various concentrations of antivirals in an attempt to quantify the effect of antivirals. Often these characteristics are estimated using only measured data points, although fitting of simple mathematical models to estimate these parameters is becoming more prevalent. In this article, our aim is to compare the estimates of different viral titer characteristics using three different approaches. The first approach is the traditional method that uses estimates based on experimentally measured data. The second approach relies on the use of a linear model to fit the viral titer data. The third approach uses an exponential model for the fitting process and the parameters of interest are extracted from there. The mathematical models are tested using in vivo and in vitro influenza infection data. Estimates of viral titer characteristics using either of the two fitting approaches were similar, but differed from estimates using the traditional method.
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