Three obstacles of Europe

Europe recognizes the potential that Artificial intelligence (AI) in the development and life of medicines. An example of this is that last December the European Medicines Agency (EMA, English acronym) has published a work plan guiding its use in regulating these products. However, the use of a tool brings with it numerous problems what the body has to deal with.

The EMA found that there were three problems with this tool. They are summarized in understanding of algorithmsrisks technical glitches and the “broader” impact of the tool.

“AI and machine learning can effectively support collection, transformation, analysis and interpretation of data throughout the entire life cycle of the drug. However, this range of applications comes with numerous challenges,” explains the EMA Medical letter.

These problems primarily focus on understanding of algorithmsfeatures of its design and capabilities prejudices. We continue to focus on risk technical glitches and finally, the “broader” impact this will have on the adoption of AI in drug development and patient health.

To shed light on this issue, the EMA and medicines agency chiefs (MIAacronym in English) “provides” regulators and other stakeholders with reflection, guidance and support on the use of AI.

For example, Europe recently launched a Work Plan on the Use of AI in Medicines Regulation, running until 2028. To do this, they relied on four aspects: Leadership, Politics and product support; Tools and technologies AI; Collaboration and learning and finally Experimentation.

Each of the measurements has established goals and deadlines. The first one will provide ongoing support AI development and evolution in the life cycle of medicines; The second aims to identify and provide a network-wide framework for using tools to improve efficiency, understanding and data analysis.

Relatively Collaboration and traininginitiatives have been formulated to continuously develop the network’s potential. Finally, in Experimentation Test cycles will be carried out with a maximum duration of six months.

AI will speed up drug development

But in this regard, not only documentation about this tool has been published. In July, the EMA presented a draft policy paper on artificial intelligence to support the development, regulation and safe and effective use of human and veterinary medicines. Once the brief, for which public consultation closed at the end of December, is completed, AI recommendations will be provided “based on stakeholder views,” the regulator explains.

“The document emphasizes that person-centered approach must lead all development and implementation of artificial intelligence and machine learning. The use of AI in medicine and life cycle must always comply with current legal requirements, guarantee due respect for fundamental rights and take into account responsible ethics,” reminds the EMA.

Therefore, where artificial intelligence or machine learning is used for drug development, evolution and monitoring, the EMA “advises” developers to look for early regulatory supportthat is, through the qualification of innovative products, development methods or scientific advice.