The pharmaceutical industry is being challenged to become more cost-efficient and responsive when developing and making drugs. Scientific and technological breakthroughs, increasing societal pressures, stringent regulations, and fast-changing markets are pushing the pharmaceutical supply chain to the limit. Recent findings confirm that the industry is struggling to maintain the right levels of innovation to ensure R&D productivity. Moreover, since the relatively weak performance metrics of the past are no longer acceptable, this industry must pursuit compelling strategies towards the delivery of more affordable medicines.

The Future Pharma project goal is to develop optimization models with practical use for boosting the integration of complex decisions that occur at different levels of the pharmaceutical supply chain. This research project focuses on the development of models considering combined aspects that have received little attention, such as flexibility, cost efficiency, and sustainability issues. In addition to that, aspects related to the complexity and uncertainty in this highly regulated sector and new technological innovations that will impact the supply chain will also be tackled.

The supply chain of the future must provide aggressively short lead times through process and product diversification. The underlying project concept is to develop self-learning models for flexible, cost-efficient, and sustainable decisions to deal efficiently with all these complicated constraints.

 Contributes to the Sustainable Development Goals (SDGs):