Regulatory Considerations on the use of Machine Learning based tools in Clinical Trials.

Background: The widespread increasing use of machine learning (ML) based tools in clinical trials (CTs) impacts the activities of Regulatory Agencies (RAs) that evaluate the development of investigational medicinal products (IMPs) in clinical studies to be carried out through the use of data-driven technologies. The fast progress in this field poses the need to define new approaches and methods to support an agile and structured assessment process. Method: The assessment of key information, characteristics and challenges deriving from the application of ML tools in CTs and their link with the principles for a trustworthy artificial intelligence (AI) that directly affect the decision-making process is investigated. Results: Potential issues are identified during the assessment and areas of greater interaction combining key regulatory points and principles for a trustworthy AI are highlighted. The most impacted areas are those related to technical robustness and safety of the ML tool, in relation to data used and the level of evidence generated. Additional areas of attention emerged, like the ones related to data and algorithm transparency. Conclusion: We evaluate the applicability of a new method to further support the assessment of medicinal products developed using data-driven tools in a CT setting. This is a first step and new paradigms should be adopted to support policy makers and regulatory decisions, capitalizing on technology advancements, considering stakeholders' feedback and still ensuring a regulatory framework on safety and efficacy.

Critical Analysis and Quality Assessment of Nanomedicines and Nanocarriers in Clinical Trials: Three Years of Activity at the Clinical Trials Office.

Investigational medicinal products submitted over the course of 3 years and authorized at the Clinical Trials Office of the Italian Medicines Agency as part of a request for authorization of clinical trials were scrutinized to identify those encompassing nanomedicines. The quality assessment reports performed on the documentation submitted were analyzed, classifying and discussing the most frequently detected issues. The identification of nanomedicines retrieved and the information on their quality profiles are shared to increase the transparency and availability of information, providing feedback that can support sponsors in optimizing the quality part of the documentation and of the information submitted. Results confirm that nanomedicines tested as investigational medicinal products in clinical trials are developed and authorized in agreement with the highest standards of quality, meeting safety profiles according to the strong regulatory requirements in the European Union. Some key points are highlighted and indicate that the regulatory approach to innovation in a clinical trial setting could potentially be renewed to ride the wave of innovation, particularly in the nanotechnology field, capitalizing on lessons learned and still ensuring a strong and effective framework.

Quality Assessment of Investigational Medicinal Products in COVID-19 Clinical Trials: One Year of Activity at the Clinical Trials Office.

One year after the spread of the pandemic, we analyzed the assessment results of the quality documentation submitted to the Clinical Trials Office of the Italian Medicines Agency as part of the request for authorization of clinical trials with a COVID-19 indication. In this article, we report the classification of the documentation type, an overview of the assessment results, and the related issues focusing on the most frequently detected ones. Relevant data regarding the Investigational Medicinal Products (IMPs) tested in COVID-19 clinical trials and their quality profiles are provided in the perspective of increasing transparency and availability of information. Some criticalities that have been exacerbated by the management of clinical trials during the emergency period are highlighted. Results confirm that IMPs tested in authorized COVID-19 clinical trials are developed in agreement with the same legal requirements for quality, safety, and efficacy as for any other medicinal product in the European Union (EU). The same strong regulatory framework applies, and there is no lowering in the safety profile due to the pandemic; authorized IMPs meet the highest standards of quality. The regulatory network should capitalize on lessons learned from the emergency setting. Some take-home messages are provided that could support the regulatory framework to expand its boundaries by innovating and evolving even though remaining strong and effective.

Surfactants, Nanomedicines and Nanocarriers: A Critical Evaluation on Clinical Trials.

Advances, perspectives and innovation in drug delivery have increased in recent years; however, there is limited information available regarding the actual presence of surfactants, nanomedicines and nanocarriers in investigational medicinal products submitted as part of a request for authorization of clinical trials, particularly for those authorized in the European Economic Area. We retrieve, analyze and report data available at the Clinical Trial Office of the Italian Medicines Agency (AIFA), increasing the transparency and availability of relevant information. An analysis of quality documentation submitted along with clinical trials authorized by the AIFA in 2018 was carried out, focusing on the key terms "surfactant", "nanomedicine" and "nanocarrier". Results suggest potential indications and inputs for further reflection and actions for regulators to actively and safely drive innovation from a regulatory perspective and to transpose upcoming evolution of clinical trials within a strong regulatory framework.

Clinical Trials and Machine Learning: Regulatory Approach Review.

Machine Learning, a fast-growing technology, is an application of Artificial Intelligence that has provided important contributes to drug discovery and clinical development. In the last few years, the number of clinical applications based on Machine Learning has been constantly growing and this is now affecting the National Competent Authorities during the assessment of most recently submitted Clinical Trials that are designed, managed or that are generating data deriving from the use of Machine Learning or Artificial Intelligence technologies. We review current information available on the regulatory approach to Clinical Trials and Machine Learning. We also provide inputs for further reasoning and potential indications, including six actionable proposals for regulators to proactively drive the upcoming evolution of Clinical Trials within a strong regulatory framework, focusing on patient's safety, health protection and fostering immediate access to effective treatments.

A harmonized and efficient clinical research environment would benefit patients and enhance European competitiveness. Commentary.

The forthcoming implementation of the European Clinical Trial Regulation (Regulation (EU) No. 536/2014), which is expected to facilitate the conduct of clinical trials across the European Union, will require National Authorities to create the best conditions for the implementation of the new Regulation through national guidelines, so that sponsors may reconsider Europe as a prime location for planning clinical trials. During a meeting titled "Innovation in Clinical Research", an expert panel discussed potential local advances fostering competitiveness of European clinical research with representatives of the pharmaceutical industry, patient organisations and Italian regulatory agency in view of the forthcoming implementation of (EU) No. 536/2014 on clinical trials of medicinal products. In this article we summarise the findings of the meeting, describe features characterising clinical research patterns and offer some suggestions on the possible involvement of all stakeholders in order to foster research innovation and allow the timely access to novel medicines for patients.