The EMA’s 5 goals: Fostering innovative trial design, exploiting AI, and other recommendations

By Melissa Fassbender

- Last updated on GMT

(Image: Getty/TanawatPontchour)
(Image: Getty/TanawatPontchour)

Related tags Ema Regulation Clinical trials Wearables

The EMA recently outlined five strategic goals with a focus on fostering clinical trial innovation, optimizing capabilities in modeling and simulation, as well as exploiting AI and investing in special populations, among other objectives.

The European Medicines Agency published its draft EMA Regulatory Science to 2025​ strategy for a six-month consultation period ending June 30, 2019. It includes feedback from two workshops held in 2018 and, in addition to public feedback, will help inform the next EU Medicines Agencies Network Strategy​ (2020-2025).

“The Regulatory Science strategy to 2025 aims to build a more adaptive regulatory system that will encourage innovation in human and veterinary medicine,”​ said EMA Executive Director Guido Rasi.

The EMA’s five strategic goals for regulatory science:

  1. Catalyzing the integration of science and technology in medicines development
  2. Driving collaborative evidence generation – improving the scientific quality of evaluations
  3. Advancing patient-centered access to medicines in partnership with health care systems
  4. Addressing emerging health threats and availability/therapeutic challenges
  5. Enabling and leveraging research and innovation in regulatory science

Here, we will focus on the agency’s second goal, which aims to provide regulators and health technology assessment (HTAs)/payers with better evidence to accelerate evaluation and bring medicines to patients faster. It also focuses on the unmet needs of pediatric and rare disease patients.

According to the EMA, “Underlying much of this is the increasing incorporation of new digital tools into medicines manufacturing, development, and clinical care protocols.”

“Improved evidence generation also offers a chance to capture patient preferences better during the evaluation process and make clinical development and regulation more cost-effective, potentially reducing the burden on healthcare systems,”​ the agency added.

The EMA’s core recommendations for driving collaborative evidence generation and improving the scientific quality of evaluations are as follows:

Leverage non-clinical models and the 3Rs principles

The 3Rs strategy looks to replace, reduce, and refine animal testing. As part of this, the EMA proposes stimulating developers to use novel preclinical models and refocusing the 3Rs working group​ to support method qualification.

It also encourages the implementation of IT tools to leverage the benefits of SEND1 for the reanalysis of non-clinical studies “to support both clinical trials authorization FIM (first-in-man) and risk minimization across EU.”

Foster innovation in clinical trials

“Regulators will need to work with other bodies involved to ensure that innovative designs meet the needs of all stakeholders,”​ the agency said.

To foster this innovation, the EMA aims to drive the adoption of novel practices to facilitate clinical trial authorization, good clinical practice (GCP), and HTA acceptance. It also proposes that new and emerging endpoints be assessed for clinical value and ability to facilitate patients’ access to new medicines.

Working with stakeholders to encourage collaborative clinical trials also is recommended, as is collaborating with international partners via initiatives such as the Clinical Trial Transformation Initiative​ (CTTI) and the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use​ (ICH).

Develop the regulatory framework for emerging clinical data generation

Regulators should develop a methodology to incorporate clinical care data sources in the regulatory decision-making process, according to the EMA. GCP oversight also should be modernized to enable decentralized clinical trial models “coupled with direct digital data accrual.”

Additionally, regulators should develop assessment capabilities as it pertains to complex datasets collected from technology such as wearables.

As the EMA said, “Data from mobile and wearable technology are expected to have a major impact on health in the next five years” – ​this includes the development of novel endpoints and further ability to conduct remote clinical trials.

Thus, regulators also should “facilitate training and understanding of health care professionals and patients to access and participate effectively in such trials,”​ per the recommendations.

Expand benefit-risk assessment and communication

According to the EMA, regulators and other industry stakeholders are looking to better incorporate patient data into the benefit-risk evaluation.

“The challenges for the future include finding ways to express the elements of benefit-risk decisions in a way that assists subsequent stakeholders such as HTAs and payers to make their decisions, thus avoiding widening the gap between regulatory approval and HTA/payers’ decisions,”​ the agency explained.

To address this challenge, the EMA recommends that such assessments more broadly incorporate patient preferences into the assessment. The ability to analyze individual patient data also should be developed, while the application of structured benefit/risk methodology and quality assurance systems be promoted.

The recommendations also suggest improving communication with HTAs and payers, as well as with the public. Additionally, academic research should be incorporated into evidence-based benefit-risk communication, according to the EMA.

Invest in special populations initiatives

In Europe, social and demographic changes are renewing efforts to address the medical needs of special patient populations, including children, the elderly, and childbearing women.

The current regulatory framework for pediatric medicines has been in place for more than 10 years, and while garnered positive results, the EMA said, “there is further to go.”

“In practice, new marketing applications still often fail to include sufficient data from elderly patients, and work in understanding the consequences of medicines exposure during pregnancy needs to be intensified and broadened,”​ according to the EMA.

To address these issues, the agency proposes a focus on “speedy access”​ for patient populations in urgent need.

It also advises progressing implementation of the geriatric strategic plan​ as well as the joint EMA/European Commission (EC) pediatric medicines action plan​, in addition to developing a strategic initiative in maternal-fetal health.

Optimize capabilities in modeling, simulation, and extrapolation

Modeling and simulation are increasingly being adopted across the industry in various use cases. However, to see broad uptake, the EMA said endorsement is needed from other international regulators as well as from key decision makers, such as HTAs and payers.

The agency said, “Increased interactions and informed decision-making between scientific disciplines, stakeholders and EMA Committees will be needed.”

Subsequently, the recommendations call for the development and international harmonization of methods and standards via a multi-stakeholder platform.

The EMA also suggests the redesign of any relevant working parties to “ensure wider knowledge exchange.”

Exploit digital technology and artificial intelligence in decision making

Though making considerable strides in other industries, the use of AI remains nascent in the pharmaceutical industry.

To “exploit digital technology and artificial intelligence in decision making,”​ the EMA proposes the creation of a dedicated AI test laboratory. According to the agency, the lab would “explore the application of innovative digital technology to support data-driven decisions across key business processes.”

The recommendations also include a call to action to develop capacity and expertise across the network, to engage with digital technology, AI, cognitive computing, and any potential applications in the regulatory system.

“There is a need to develop cognitive computing tools to accelerate our ability to turn big data into meaningful scientific insight and activity,”​ per the EMA. “To ensure such tools are effective and appropriate for use they will need to be developed through close collaboration between multi-disciplinary scientists and computer scientists.”

Join the discussion! The EMA is encouraging stakeholders to use the hashtag #RegScience2025​ on Twitter​.

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