Grigorios Agkyralidis ^*

• Boehringer Ingelheim (Germany), Hannover, Germany

Currently there has been a lot of discussion for the future of medicines. From research and development to regulatory approval and access to patients until withdrawal of a medicinal product from the market there have been many challenges and a lot of barriers to overcome. In parallel, the business environment changes rapidly. So, the big question is how pharma ecosystem will evolve in the future? Methods: Current literature with regards to latest business and scientific evolutions and trends was reviewed. Results: In the business environment vast changes have taken place via the development of the Internet as well as the Internet of Things. A new approach in production has emerged in a frame called Creative Commons; producer and consumer may be gradually identified in the context of the same process. As technology rapidly evolves, it is dominated by Artificial Intelligence and its subset Machine Learning and the use of Big Data and Real-World Data that lead to Real-World Evidence. Nanotechnology is an inter-science field that gives new opportunities for the manufacturing of devices and products that have dimensions of a billionth of a meter. Artificial Neural Networks and Deep Learning are mimicking the use of the human brain, combining computer science with new theoretical foundations of complex systems. The implementation of these evolutions has already initiated in medicinal products' lifecycle including screening of drug candidates, clinical trials, pharmacovigilance, marketing authorization, manufacturing and supply chain emerging a new ecosystem which features characteristics such as free on-line tools and free data available online. Personalized medicine is a breakthrough field where tailor-made therapeutic solutions can be provided customized to the genome of each patient. Conclusion: Various interactions take place as the pharma ecosystem and technology rapidly evolve. This can lead to better, safer, and more effective treatments, developed faster and with a more solid, data-driven and evidence concrete approach to be brought and drive the benefit for the patient.