Collaboration in pharmacovigilance: lamotrigine and fatal severe cutaneous adverse reactions – a review of spontaneous reports

Neil Brickel,1 Haris Shaikh,1 Andrew Kirkham,2 Greg Davies,1 Michelle Chalker,1 Pascal Yoshida3 1Global Clinical Safety and Pharmacovigilance, GlaxoSmithKline, Uxbridge, Middlesex, UK; 2Classic and Established Products, GlaxoSmithKline, Brentford, Middlesex, UK; 3Clinical Safety and Post-marketing Surveillance, GlaxoSmithKline KK, Tokyo, Japan Abstract: Pharmacovigilance presents many challenges, particularly when managing unpredictable, rare conditions, eg, severe cutaneous adverse reactions (SCARs). Such rare events are often only detected from spontaneous reports, which present their own limitations, particularly during a prolonged global launch schedule. GlaxoSmithKline’s routine pharmacovigilance includes regular reviews of global adverse event (AE) reports and aggregate data from a central safety database. Lamotrigine is one of the several antiepileptic drugs associated with SCARs. After identification of increased rates of fatal SCAR cases with lamotrigine in Japan between September and December 2014, this analysis investigated the global incidence of fatal SCARs with lamotrigine and explored whether known risk factors may have contributed to these cases. Global fatal SCAR cases reported with lamotrigine administration from launch until January 2015 were reviewed for evidence of temporal association with dosing and the presence of risk factors, including comorbidities, concomitant medications, and noncompliance with the prescribing information (PI). Worldwide, the estimated cumulative exposure to lamotrigine was >8.4 million patient-years. Globally, there were 54,513 AE reports for lamotrigine, of which 3,454 (6.3%) concerned SCARs. Of these, 122 (3.5%) had a fatal outcome (attributable and nonattributable to lamotrigine), equating to 0.01 fatal SCARs per 1,000 patient-years. In Japan (estimated cumulative exposure 141,000 patient-years), 17 fatal SCARs were reported (attributable and nonattributable), equating to 0.12 per 1,000 patient-years. Seventy-one percent of fatal SCAR cases in Japan showed evidence of noncompliance with the recommended dosing regimen; in 65% of the cases, a delay in discontinuation of lamotrigine after early signs of hypersensitivity was reported. Despite a number of limitations inherent in comparing spontaneous report data, this analysis highlights the need for adherence to the lamotrigine PI and emphasizes the importance of collaboration between global and local pharmacovigilance departments, to promptly identify and reduce the risk of rare and serious events, such as SCARs. Keywords: antiepileptic drug, pharmacovigilance, Stevens–Johnson syndrome, toxic epidermal necrolysis, drug reaction with eosinophilia and systemic symptom

Q-RepEx : A Python pipeline to increase the sampling of empirical valence bond simulations

The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling. This is a particular challenge for large biochemical systems with many degrees of freedom. Replica exchange molecular dynamics (REMD) is an approach that accelerates the exploration of the conformational space of a system, and thus can be used to enhance the sampling of complex biomolecular processes. In parallel, the empirical valence bond (EVB) approach is a powerful approach for modeling chemical reactivity in biomolecular systems. Here, we present an open-source Python-based tool that interfaces with the Q simulation package, and increases the sampling efficiency of the EVB free energy perturbation/umbrella sampling approach by means of REMD. This approach, Q-RepEx, both decreases the computational cost of the associated REMD-EVB simulations, and opens the door to more efficient studies of biochemical reactivity in systems with significant conformational fluctuations along the chemical reaction coordinate

Q-RepEx: A Python Pipeline to Increase the Sampling of Empirical Valence Bond Simulations

The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling. This is a particular challenge for large biochemical systems with many degrees of freedom. Replica exchange molecular dynamics (REMD) is an approach that accelerates the exploration of the conformational space of a system, and thus can be used to enhance the sampling of complex biomolecular processes. In parallel, the empirical valence bond (EVB) approach is a powerful approach for modeling chemical reactivity in biomolecular systems. Here, we present an open-source Python-based tool that interfaces with the Q simulation package, and increases the sampling efficiency of the EVB free energy perturbation / umbrella sampling approach by means of REMD. This approach, Q-RepEx, both decreases the computational cost of the associated REMD-EVB simulations, and opens the door to more efficient studies of biochemical reactivity in systems with significant conformational fluctuations along the chemical reaction coordinate