A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: application to a dose-finding trial for a novel Russell’s viper antivenom in Myanmar
Watson JA., Lamb T., Holmes J., Warrell D., Thwin KT., Aung ZL., Nwe MT., Smithuis F., Ashley EA.
<jats:title>Abstract</jats:title><jats:p>For most antivenoms there is little information from clinical studies to infer the relationship between dose and efficacy or dose and toxicity. Antivenom dose-finding studies usually recruit too few patients (e.g. less than 20) relative to clinically significant event rates (e.g. 5%). Model based adaptive dose-finding studies make efficient use of accrued patient data by using information across dosing levels, and converge rapidly to the contextually defined ‘optimal dose’. Adequate sample sizes for adaptive dose-finding trials can be determined by simulation studies.</jats:p><jats:p>We propose a model based, Bayesian phase 2 type, adaptive clinical trial design for the characterisation of optimal initial antivenom doses in contexts where both efficacy and toxicity are measured as binary endpoints. This design is illustrated in the context of dose-finding for <jats:italic>Daboia siamensis</jats:italic> (Eastern Russell’s viper) envenoming in Myanmar. The design formalises the optimal initial dose of antivenom as the dose closest to that giving a pre-specified desired efficacy, but resulting in less than a pre-specified maximum toxicity. For Russell’s viper efficacy is defined as the restoration of blood coagulability within six hours, and toxicity is defined as anaphylaxis. Comprehensive simulation studies compared the expected behaviour of the model based design to a simpler rule based design (a modified ‘3+3’ design). The model based design can identify the optimal dose after fewer patients than the rule based design. Open source code for the simulations can be used to calculate sample sizes under <jats:italic>a priori</jats:italic> beliefs of efficacy and toxicity.</jats:p><jats:p>Antivenom dose-finding trials would benefit from using standard model based adaptive designs. Dose-finding trials where rare events (e.g. 5% occurrence) are of clinical importance necessitate larger sample sizes than current practice. We will apply the model based design to determine a safe and efficacious dose for a novel lyophilised antivenom to treat <jats:italic>Daboia siamensis</jats:italic> envenoming in Myanmar.</jats:p><jats:sec><jats:title>Author summary</jats:title><jats:p>Snakebite envenoming is one of the most neglected tropical diseases relative to its mortality and morbidity. Antivenoms are the only known effective treatment for snake-bite envenoming but are frequently responsible for high rates of adverse reactions. Clinical development of antivenoms rarely follows the iterative phases of clinical development applied to other drugs. Dosing is typically based on pre-clinical testing.</jats:p><jats:p>Here we propose a Bayesian model based adaptive design for clinical trials aiming to determine the optimal dose of antivenom needed. Optimality is defined using safety and efficacy thresholds contextual to the study. This design can be applied to all antivenoms which have binary efficacy and toxicity endpoints. Our design formally specifies a desired efficacy and a maximum tolerated toxicity. We use simulation studies to characterise the sample size necessary to determine the optimal dose in different scenarios. The simulation studies highlight the advantages of a model based design over simpler rule based alternatives. We intend to use this design to determine an effective and safe dose of the new lyophilised viper antivenom currently in use to treat Russell’s viper envenoming in Myanmar.</jats:p></jats:sec>