Applications of Influenza Viral Kinetic Modeling in Drug Development
Purpose of Review
Seasonal influenza epidemics continue to cause significant morbidity and mortality, especially in high-risk subpopulations. The rise of drug-resistant influenza strains and high rates of vaccine mismatches drives the search for new safe and effective antiviral drugs. The purpose of this review was to summarize how mathematical models―viral kinetic models, in particular―have advanced our understanding of influenza biology and antiviral pharmacology and to explore how these models may be further developed in the future.
Viral kinetic models that use a population approach have been helpful in elucidating the major sources of intra- and inter-individual variability. Thus, these models can help explain why some influenza patients become much sicker than others. Linking viral kinetic models to pharmacokinetic/pharmacodynamic models has enabled quantification of drug effects based on their mechanism of action and in silico evaluation of the efficacy of drug combinations. Viral kinetic models have also been applied to optimizing the design of clinical trials. Future directions for viral kinetic models include coupling to epidemiological models to assess the effectiveness of various public health treatment strategies. These models can also inform health economic decision-making.
Since the 1970s, the field of viral kinetic modeling of influenza has made great advances in informing our knowledge of this infectious disease. This tool is being coupled to other types of modeling approaches and will continue to be a critical weapon in our infectious disease armamentarium.
KeywordsPharmacokinetics/pharmacodynamics Influenza virus Viral kinetic modeling Oseltamivir treatment Mathematical modeling Monoclonal antibody
The authors would like to thank Christopher Howard Lincoln for his graphic design assistance.
Compliance with Ethical Standards
Conflict of Interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
- 3.Beauchemin CA, Handel A. A review of mathematical models of influenza a infections within a host or cell culture: lessons learned and challenges ahead. BMC Public Health. 2011;11 Suppl 1:S7-2458-11-S1-S7.Google Scholar
- 13.Eubank S, Guclu H, Kumar VS, Marathe MV, Srinivasan A, Toroczkai Z, et al. Modelling disease outbreaks in realistic urban social networks. Nature. 2004;429(6988):180–4.Google Scholar
- 14.Fidler M, Patel K, Kirkpatrick C, Rayner C, Kamal M, Smith P, et al. A symptom driven multiscale model of influenza. Chicago: Options Ix; 2016.Google Scholar
- 15.Guo D, Li KC, Peters TR, Snively BM, Poehling KA, Zhou X. Multi-scale modeling for the transmission of influenza and the evaluation of interventions toward it. Sci Rep. 2015;5:8980. https://doi.org/10.1038/srep08980.
- 16.Hadjichrysanthou, C., Cauet, E., Lawrence, E., Vegvari, C., de Wolf, F., & Anderson, R. M.. Understanding the within-host dynamics of influenza A virus: From theory to clinical implications. J R Soc Interface. 2016;13(119), https://doi.org/10.1098/rsif.2016.0289.
- 28.Laskowski M, Greer AL, Moghadas SM. Antiviral strategies for emerging influenza viruses. 2014.Google Scholar
- 29.Lukens S, DePass J, Rosenfeld R, Ghedin E, Mochan E, Brown ST, Grefenstette J, Burke DS, Swigon D, Clermont GA. Large-scale immuno-epidemiological simulation of influenza A epidemics. BMC Public Health. 2014;14:1019.Google Scholar
- 33.Patel, K., Kirkpatrick, C., Stroh, M., Smith, P., & Deng, R. Population Pharmacokinetic/Pharmacodynamic (PK/PD) modeling of MHAA4549A, an anti-influenza A monoclonal antibody, in healthy subjects challenged with influenza A virus. Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA. 2015a.Google Scholar
- 34.Patel, K., Rao, G., Kirkpatrick, C., Kamal, M., Forrest, A., & Patel, K. Population modelling of influenza viral kinetics, immune response, symptom dynamics and the effect of oseltamivir. 17th Annual Population Approach Group in Australia and New Zealand Meeting, Melbourne, Australia. 2015b.Google Scholar
- 35.Patel, K., Smith, P., Nieforth, K., & Kirkpatrick, C.. Challenges and pitfalls of building models for Flu/RSV and respiratory viruses. World Conference on Pharmacometrics, Brisbane, Australia. 2016.Google Scholar
- 36.Patel K, Smith P, Dall G, Lovern M, Sloan S, Trevejo J, et al. Population pharmacokinetic and viral dynamic modeling of VIS410, a monoclonal antibody against influenza a virus in a human challenge model. New Orleans: ASM Microbe; 2017a.Google Scholar
- 37.Patel, K., Smith, P., Nieforth, K., Rayner, C., & Kirkpatrick C. Performance of estimation methods in modelling the kinetics of respiratory virus infection. Population Approach Group of Australia & New Zealand. 2017b;2017.Google Scholar
- 42.WHO guidelines for pharmacological management of pandemic influenza A(H1N1) 2009 and other influenza viruses. (2010). Retrieved April 5, 2017, from http://www.who.int/csr/resources/publications/swineflu/h1n1_guidelines_pharmaceutical_mngt.pdf.
- 43.Wollacott AM, Boni MF, Szretter KJ, Sloan SE, Yousofshahi M, Viswanathan K, et al. Safety and upper respiratory pharmacokinetics of the hemagglutinin stalk-binding antibody VIS410 support treatment and prophylaxis based on population modeling of seasonal influenza a outbreaks. Ebiomedicine. 2016;5:147–55.CrossRefPubMedPubMedCentralGoogle Scholar