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Modeling the disruption of respiratory disease clinical trials by non-pharmaceutical COVID-19 interventions

Author

Listed:
  • Simon Arsène

    (Novadiscovery SA)

  • Claire Couty

    (Novadiscovery SA)

  • Igor Faddeenkov

    (Novadiscovery SA)

  • Natacha Go

    (Novadiscovery SA)

  • Solène Granjeon-Noriot

    (Novadiscovery SA)

  • Daniel Šmít

    (Novadiscovery SA)

  • Riad Kahoul

    (Novadiscovery SA)

  • Ben Illigens

    (Novadiscovery SA
    Dresden International University)

  • Jean-Pierre Boissel

    (Novadiscovery SA)

  • Aude Chevalier

    (OM Pharma)

  • Lorenz Lehr

    (OM Pharma)

  • Christian Pasquali

    (OM Pharma)

  • Alexander Kulesza

    (Novadiscovery SA)

Abstract

Respiratory disease trials are profoundly affected by non-pharmaceutical interventions (NPIs) against COVID-19 because they perturb existing regular patterns of all seasonal viral epidemics. To address trial design with such uncertainty, we developed an epidemiological model of respiratory tract infection (RTI) coupled to a mechanistic description of viral RTI episodes. We explored the impact of reduced viral transmission (mimicking NPIs) using a virtual population and in silico trials for the bacterial lysate OM-85 as prophylaxis for RTI. Ratio-based efficacy metrics are only impacted under strict lockdown whereas absolute benefit already is with intermediate NPIs (eg. mask-wearing). Consequently, despite NPI, trials may meet their relative efficacy endpoints (provided recruitment hurdles can be overcome) but are difficult to assess with respect to clinical relevance. These results advocate to report a variety of metrics for benefit assessment, to use adaptive trial design and adapted statistical analyses. They also question eligibility criteria misaligned with the actual disease burden.

Suggested Citation

  • Simon Arsène & Claire Couty & Igor Faddeenkov & Natacha Go & Solène Granjeon-Noriot & Daniel Šmít & Riad Kahoul & Ben Illigens & Jean-Pierre Boissel & Aude Chevalier & Lorenz Lehr & Christian Pasquali, 2022. "Modeling the disruption of respiratory disease clinical trials by non-pharmaceutical COVID-19 interventions," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29534-8
    DOI: 10.1038/s41467-022-29534-8
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    References listed on IDEAS

    as
    1. Nicola Jones, 2020. "How COVID-19 is changing the cold and flu season," Nature, Nature, vol. 588(7838), pages 388-390, December.
    2. David Adam, 2020. "Special report: The simulations driving the world’s response to COVID-19," Nature, Nature, vol. 580(7803), pages 316-318, April.
    3. Aban, Inmaculada B. & Cutter, Gary R. & Mavinga, Nsoki, 2009. "Inferences and power analysis concerning two negative binomial distributions with an application to MRI lesion counts data," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 820-833, January.
    4. Heidi Ledford, 2021. "The COVID pandemic’s lingering impact on clinical trials," Nature, Nature, vol. 595(7867), pages 341-342, July.
    Full references (including those not matched with items on IDEAS)

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