Worldwide patient safety
Worldwide Patient Safety (WWPS) serves to enable the development and optimal use of BMS medicines through innovative pharmacovigilance and risk management to help patients prevail over serious diseases.
Pharmacovigilance (PV) is defined by the World Health Organization (WHO) as the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem.
As part of our mission to discover, develop and deliver innovative medicines that help patients prevail over serious diseases, Bristol Myers Squibb is uniquely committed to patient safety and risk management.
BMS is a world leader in pioneering risk minimization techniques to deliver safe use of medicinal products. WWPS is involved in the lifecycle management of products, including every step of the clinical development process—from inception to marketing—ensuring the safety profile of our therapies is well-defined and our patients are well-informed. Safety personnel are embedded within clinical development and project teams to help ensure the continuity of safety assessments from pre- to post-marketing.
Chrysalis
Chrysalis is our blueprint for progressive innovation in pharmacovigilance and risk management.
Our vision is to transform pharmacovigilance and risk management to drive the new era of patient safety. This will be achieved by harnessing novel methodologies and technologies including artificial intelligence, machine learning and digitization to enhance safety science and evidence-based decision making to enable development and optimal use of BMS medicines.
Publications
BMS WWPS is committed to scientific evidence generation and dissemination to promote safe use of our medicines in addition to contributing to the advancement of the science of patient safety and risk management
References:
- Danysz, K., Cicirello, S., Mingle, E. et al. Artificial Intelligence and the Future of the Drug Safety Professional. Drug Saf 42, 491–497 (2019). https://doi.org/10.1007/s40264-018-0746-z
- Mockute, R., Desai, S., Perera, S. et al. Artificial Intelligence Within Pharmacovigilance: A Means to Identify Cognitive Services and the Framework for Their Validation. Pharm Med 33, 109–120 (2019). https://doi.org/10.1007/s40290-019-00269-0
- Abatemarco, D., Perera, S., Bao, S.H. et al. Training Augmented Intelligent Capabilities for Pharmacovigilance: Applying Deep-learning Approaches to Individual Case Safety Report Processing. Pharm Med 32, 391–401 (2018). https://doi.org/10.1007/s40290-018-0251-9
- Persson, R., Lee, S., Yood, M.U. et al. Multi-database study of multiple sclerosis: identification, validation and description of MS patients in two countries. J Neurol 266, 1095–1106 (2019). https://doi.org/10.1007/s00415-019-09238-8