Modelling of Systemic versus Pulmonary Chloroquine Exposure in Man for COVID-19 Dose Selection

  1. Ghaith Aljayyoussi
  2. Rajith KR Rajoli
  3. Henry Pertinez
  4. Shaun H Pennington
  5. W. David Hong
  6. Paul M. O’Neill
  7. Andrew Owen
  8. Steve A Ward
  9. Giancarlo A Biagini

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Abstract

Chloroquine has attracted intense attention as a potential clinical candidate for prevention and treatment of COVID-19 based on reports of in-vitro efficacy against SARS-CoV-2. While the pharmacokinetic-pharmacodynamic (PK-PD) relationship of chloroquine is well established for malaria, there is sparse information regarding its dose-effect relationship in the context of COVID-19.

Here, we explore the PK-PD relationship of chloroquine for COVID-19 by modelling both achievable systemic and pulmonary drug concentrations. Our data indicate that the standard anti-malarial treatment dose of 25mg/kg over three days does not deliver sufficient systemic drug exposures for the inhibition of viral replication. In contrast, PK predictions of chloroquine in the lungs using in-vivo data or human physiologically-based PK models, suggest that doses as low as 3mg/kg/day for 3 days could deliver exposures that are significantly higher than reported antiviral-EC 90 s for up to a week. Moreover, if pulmonary exposure is a driver for prevention, simulations show that chronic daily dosing of chloroquine may be unnecessary for prophylaxis purposes. Instead, once weekly doses of 5mg/kg would be sufficient to achieve a continuous cover of therapeutically active pulmonary exposures.

These findings reveal a highly compartmentalised distribution of chloroquine in man that may significantly affect its therapeutic potential against COVID-19. The systemic circulation is shown as one site where chloroquine exposure is insufficient to inhibit SARS-CoV-2 replication. However, if therapeutic activity is driven by pulmonary exposure, it should be possible to reduce the chloroquine dose to safe levels. Carefully designed randomized controlled trials are urgently required to address these outstanding issues.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.24.20078741: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    ii. in-vitro based PBPK Modelling and human lung prediction: CQ plasma and lung concentrations were also simulated using a whole-body physiologically based PK (PBPK) model implemented in Matlab (Mathworks, v.
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)
    All simulations were performed using IQRtools package for systems pharmacology and pharmacometrics version 1.1.1 through R version 3.5.3.
    IQRtools
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    In addition to the caveats described, it is important to also note that the assumption that the predicted pulmonary drug concentrations reflect drug concentrations at the local site of viral invasion and replication which may not be correct. Our modelling framework will be useful in defining optimised dosage regimens once ongoing clinical trials begin to readout. If these trials demonstrate efficacy it would suggest that lung rather than blood drug concentrations drive efficacy. Under these circumstances it may be possible to reduce CQ dosage and durations for this priority disease indication which in turn will deliver benefits in terms of drug supply and safety for a COVID-19 treatment/prophylactic with the potential for rapid global deployment.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.04.24.20078741 on medRxiv