Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
How Can General Managers Best Leverage Medical Affairs Now and in the Future?
2
Zitationen
8
Autoren
2024
Jahr
Abstract
General managers (GMs) play a crucial role as enterprise leaders of the country affiliate of multi-national pharmaceutical companies, balancing needs, objectives and governance across all local functions. One such function, Medical Affairs, has undergone a significant evolution from a support function into a strategic partner and in some organizations a strategic leader supported by the increasing complexity of medications and a shift to more specialized medicines. Although the function has progressed significantly, there is opportunity to elevate Medical Affairs to another level, with GMs and business unit directors (BUDs) recommending increased business acumen, strategic approach, innovation and project management as competencies that could be further cultivated. Examining the current trends in the industry, including the increasing complexity of innovative medicines and patient journeys, a higher burden of evidence for the reimbursement of medicines, innovative data generation opportunities, the changing stakeholder engagement expectations and the focus on corporate reputation, Medical Affairs is positioned as a key to assist in navigating the organization through these complexities. The GM can help to foster the evolving role of Medical Affairs, encouraging lateral moves for broader enterprise mindset, imparting a culture of shared governance responsibilities across functions to encourage innovative thinking and nurture upcoming leaders by investing in training to take advantage of the above trends and deliver best patient and organizational outcomes now and in the future.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.549 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.443 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.941 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.792 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.