Generating Quality Data to Streamline Trials and Support Approvals

Drug development is very expensive. High costs are mostly due to inefficient processes, increasing complexity, and an approval slowdown. 

Some experts interpret the approval slowdown as temporary and expect the FDA to respond by accelerating its use of technologies to evaluate clinical trial data. To prepare for this increased scrutiny, sponsors must present clean, high-quality data in sharable formats. They’ll also need to rein in development costs. 

“If regulators are successful at exerting downward pressure on prices,” says Nicole Latimer, CEO of Medrio, “it’s likely that we’ll see major pharmaceuticals thinking carefully about how to create efficiencies in the development process. This will include the adoption of technology, as well as the creation of standards that allow for data exchange.”

The MedTech Dive studioID Industry Outlook report, sponsored by Medrio, explores solutions, including:

Innovative Clinical Trial Designs and Protocols

“Imagine a world in which treatments are truly personalized, in which there’s one medicine per patient,” says Latimer. “One problem that will arise—if the industry can’t create new efficiencies—is that we’ll have $1 billion in drug development costs per patient.”

Future protocols must be increasingly designed to identify patient-specific drug activities and attract diverse participants. But, these novel trial types and protocols bring greater complexity than traditional RCTs

Decentralized trials

Decentralized trials capture greater volumes of highly accurate data than on-site RCTs. They include additional endpoints and can offer more robust findings.

Synthetic control arms 

Synthetic control arms leverage real-world data in decision-making. This allows them to take advantage of healthcare data sourced from routine patient care—such as electronic health records (EHRs) or administrative claims data—instead of data collected from study patients enrolled in a control arm.

Basket and umbrella trials

Basket trials test a single intervention for efficacy against multiple indications. Umbrella trials test multiple interventions for one indication. As seen in rare disease trials, both trial types allow for more flexibility and efficiency than possible in a standard RCT.

Inline 1 Generating Quality Data to Streamline Trials and Support Approvals

Supporting Innovative Trial Designs with Technology

Tomorrow’s clinical research landscape will require stakeholders to manage this increased complexity with the right tools. As trials become more innovative and complex, their success will be more tied to the right digital technologies—ones with more sophisticated data capture, management and interoperability capabilities.

“Today’s sponsors need to be able to build a technology platform that’s standardized enough to support their entire science platform, that’s scalable, and that’s built upon templates that make it simple to configure, change and adapt to protocols as they go along,” reports Latimer

Therefore, stakeholders need to leverage technology that helps them:

  • Make advances in data management
  • Use artificial intelligence (AI) and machine learning (ML) to create efficiencies
  • Adopt big data analytics to derive insights from their data.

How Regulators are Backing and Pushing for Quality Electronic Data

Recently, regulators have been issuing new guidance on the use of digital technologies in trials. For example, in 2023, the FDA released its long-awaited first draft guidance on decentralized trials. Meanwhile, the ICH published new guidance about data amount and endpoints.

Overall, the latest regulatory guidance encourages sponsors to:

  • Innovate to increase efficiencies
  • Improve participant experience
  • Promote diversity

“I think that decentralization mandates will ultimately push decentralized trials and healthcare integration into the forefront of the clinical research landscape because these will be the only ways that sponsors can capture the data that they’ll need,” says Dr. Daniel Fox, Founder and CEO of the Clinical Research Payment Network.

Inline 2 Generating Quality Data to Streamline Trials and Support Approvals

Ethical use of AI in healthcare

The World Health Organization (WHO) and U.S Food and Drug Administration (FDA) are exploring the use of artificial intelligence (AI) in drug development. Both organizations stress responsible AI use and advocate for establishing principles, standards, and best practices in AI and machine learning within drug development.

WHO and FDA 

What to know: 

To make drug development less expensive and more effective, recent WHO guidance supports improvements in the quality of data used for public health and regulatory decision-making as well as the application of AI. 

Meanwhile, the FDA recently published a discussion paper and requested feedback on the use of AI in developing drugs and biological products.

The takeaway:
WHO and the FDA are encouraging the responsible use of AI and encouraging the creation of principles, standards and best practices to govern AI and machine learning within drug development.

Improved data collection practices

The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) has released new guidance, highlighting the importance of limiting trial data collected in trials to minimize complexity and risk.


What to know: 

New guidance from the ICH emphasizes that investigators should limit the amount of data collected in trials to information that will be:

  • Shared with regulatory bodies for assessment purposes
  • Can be assessed in accordance with the protocol’s endpoints.

The takeaway:
The goal is to minimize complexity and reduce the costs and risks associated with storing excessive data.

Prepare for the Future of Clinical Trials

As innovations like precision medicine and AI-designed clinical trials go mainstream, sponsors and CROs must adapt clinical research processes to support success. At the same time, regulators will continue to push for increased efficiency, more patient-centricity, and expanded reliance on eSource in clinical research. 

Clinical research stakeholders need to embrace emerging innovations in clinical trial design and execution and modern technology.

The information in this article is sourced from MedTech Dive studioID Industry Outlook Bench to Bedside Report, sponsored by Medrio.

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