Equivalence assessment of creams with quali-quantitative differences in light of the EMA and FDA regulatory framework.

EMA and FDA are upgrading guidelines on assessing the quality and the equivalence of topically applied drug products for developing copies of originator products and supporting post-marketing variations. For topical products having remarkably similar composition, both EMA and FDA accept the equivalence on the bases of the comparison of rheological properties and in vitro drug release constant (k) and skin permeation flux (J) values, instead of clinical studies. This work aims to evaluate the feasibility to expand this approach to variations of the composition of complex semi-solid preparations. Ibuprofen (IB) creams at two different strengths (i.e., 1 % and 10 %) were used as a model formulation. Two formulative changes were performed: (a) the addition of the humectant to simulate a minor post-marketing variation; (b) the substitution of the emulsifying system to simulate a major one. These variations impacted only in 1 % IB formulations where both the equivalences of rheological data and J-values failed. At the highest concentration, the presence of IB crystals broke down the differences in rheological patterns and lead the IB thermodynamic activity at the maximum figuring out an overlapping of the J-values. Such data suggest the combination of these studies, which are thought mainly for the development of copies, could be also applied to the management of post-marketing variations that involve product composition.

Garbage in, toxic data out: a proposal for ethical artificial intelligence sustainability impact statements.

Data and autonomous systems are taking over our lives, from healthcare to smart homes very few aspects of our day to day are not permeated by them. The technological advances enabled by these technologies are limitless. However, with advantages so too come challenges. As these technologies encompass more and more aspects of our lives, we are forgetting the ethical, legal, safety and moral concerns that arise as an outcome of integrating our lives with technology. In this work, we study the lifecycle of artificial intelligence from data gathering to deployment, providing a structured analytical assessment of the potential ethical, safety and legal concerns. The paper then presents the foundations for the first ethical artificial intelligence sustainability statement to guide future development of AI in a safe and sustainable manner.