Challenges in Assessing COVID-19 Vaccines Safety Signals-The Case of ChAdOx1 nCoV-19 Vaccine and Corneal Graft Rejection.

The rapid and large-scale roll-out of new COVID-19 vaccines has led to unprecedented challenges in assessing vaccine safety. In 2021, the European Medicines Agency (EMA) processed about 1.7 million safety reports related to COVID-19 vaccines in the EudraVigilance (EV) database and identified more than 900 potential signals. Beyond the large amount of information to be processed, the evaluation of safety signals has faced several difficulties and limitations, both in the assessment of case reports and in the investigation of databases. The evaluation of a signal of corneal graft rejection (CGR) with Vaxzevria® was no exception to this. In this commentary, we present the challenges encountered in making regulatory decisions in the context of evolving evidence and knowledge. The pandemic crisis emphasised the importance of quick and proactive communication to address the many questions and, above all, to ensure the transparency of safety data.

Model informed dosing of hydroxycholoroquine in COVID-19 patients: Learnings from the recent experience, remaining uncertainties and gaps.

AIMS: In the absence of a commonly agreed dosing protocol based on pharmacokinetic (PK) considerations, the dose and treatment duration for hydroxychloroquine (HCQ) in COVID-19 disease currently vary across national guidelines and clinical study protocols. We have used a model-based approach to explore the relative impact of alternative dosing regimens proposed in different dosing protocols for hydroxychloroquine in COVID-19. METHODS: We compared different PK exposures using Monte Carlo simulations based on a previously published population pharmacokinetic model in patients with rheumatoid arthritis, externally validated using both independent data in lupus erythematous patients and recent data in French COVID-19 patients. Clinical efficacy and safety information from COVID-19 patients treated with HCQ were used to contextualize and assess the actual clinical value of the model predictions. RESULTS: Literature and observed clinical data confirm the variability in clinical responses in COVID-19 when treated with the same fixed doses. Confounding factors were identified that should be taken into account for dose recommendation. For 80% of patients, doses higher than 800 mg day on day 1 followed by 600 mg daily on following days might not be needed for being cured. Limited adverse drug reactions have been reported so far for this dosing regimen, most often confounded by co-medications, comorbidities or underlying COVID-19 disease effects. CONCLUSION: Our results were clear, indicating the unmet need for characterization of target PK exposures to inform HCQ dosing optimization in COVID-19. Dosing optimization for HCQ in COVID-19 is still an unmet need. Efforts in this sense are a prerequisite for best benefit/risk balance.

Population Pharmacokinetics of Hydroxychloroquine in COVID-19 Patients: Implications for Dose Optimization.

BACKGROUND AND OBJECTIVE: In the absence of characterization on pharmacokinetics and reference concentrations for hydroxychloroquine in COVID-19 patients, the dose and treatment duration for hydrochloroquine are currently empirical, mainly based on in vitro data, and may vary across national guidelines and clinical study protocols. The aim of this paper is to describe the pharmacokinetics of hydroxychloroquine in COVID-19 patients, considered to be a key step toward its dosing optimization. METHODS: We have developed a population pharmacokinetic model for hydroxychloroquine in COVID-19 patients using prospectively collected pharmacokinetic data from patients either enrolled in a clinical trial or treated with hydroxychloroquine as part of standard of care in two tertiary Belgian hospitals. RESULTS: The final population pharmacokinetic model was a one-compartment model with first-order absorption and elimination. The estimated parameter values were 9.3/h, 860.8 L, and 15.7 L/h for the absorption rate constant, the central compartment volume, and the clearance, respectively. The bioavailability factor was fixed to 0.74 based on previously published models. Model validations by bootstraps, prediction corrected visual predictive checks, and normalized prediction distribution errors gave satisfactory results. Simulations were performed to compare the exposure obtained with alternative dosing regimens. CONCLUSION: The developed models provide useful insight for the dosing optimization of hydroxychloroquine in COVID-19 patients. The present results should be used in conjunction with exposure-efficacy and exposure-safety data to inform optimal dosing of hydroxychloroquine in COVID-19.