Five Predictions That Will Drive R&D Effectiveness in 2025

With drug development processes increasing in complexity, companies are working to drive research and development (R&D) efficiency, a better experience for trial participants, and improved collaboration with sites and CROs. Establishing a clean and accurate data foundation is also more critical than ever, underscored by the rise of artificial intelligence (AI) to drive speed and efficiency. Here are five predictions for 2025 that will shape life sciences and help organizations optimize R&D operations.

Process excellence will speed the flow of content and data across R&D

Today, a simple and vital task, like turning adverse events in an electronic data capture (EDC) system into safety cases, can vary drastically from company to company. One may process it as an automated workflow, and another may require hours of manual effort across disconnected systems. These inconsistencies are holding drug development back, and patients ultimately bear that burden. In 2025, biopharmas will focus on process excellence to improve content and data flow across R&D functions.

Now that sponsors see the limits of disconnected, best-of-breed solutions, the industry is ready to standardize and simplify. This will be magnified by investments in process standards. Some may focus on workflow automation to improve content and data flow across clinical, regulatory, safety, and quality. Others may rethink how their organizations are structured to create dedicated process excellence teams.

Underrepresented study populations will get more choice

Enrollment and retention of patients continue to challenge research sites and sponsors, with trial complexity and patient fatigue contributing to increasing dropout rates. In 2025, biopharmas that give patients more options for onboarding and study visits will improve their experience and expand the participant pool to previously underserved populations.

New FDA draft guidance on Diversity Action Plans urges sponsors to enroll more diverse patients and provide a statistical overview of these groups in their studies. This will affect how data is processed and analyzed for submissions, ensuring enough clean data is available to meet statistical endpoints for each demographic subgroup.

More patient options mean more data inputs and complexity. From monitoring subgroup enrollment and retention to data management and statistical analysis, unified data at the center will enable patient participation at the edges.

Biopharmas will prioritize solving site capacity issues

Clinical research sites are the backbone of drug development. But, as the number of global clinical trials grows, the clinical site workforce is decreasing with high employee turnover rates. Complex protocols with multiple amendments and too many sponsor applications per trial pull site staff away from patients, reducing their capacity to take on additional studies.

As companies rethink their site engagement strategies, they will prioritize consistent site technology and standardization across sponsors for all trials. With 55% of sites reporting that their top challenge is supporting various technologies, sponsors will drive standardization to avoid significant slowdowns in their pipelines.

The less time sites spend doing administrative work in technology applications, the more time they have to execute trials and help patients. This shift will help sites rebuild their capacity and ensure that drug development doesn’t stall.

CRO data visibility will deliver better trials

In 2025, sponsors will prioritize contract research organizations (CROs) offering complete and continuous data transparency so they can begin to derive insights right away. As companies pursue end-to-end data ownership, there will be a notable shift in dynamics when outsourcing clinical trials.

Sponsors and their CRO partners will begin to share data more fluidly across their systems. For example, to inform protocol design, onboard additional sites, identify potential rare disease participants, and move study endpoints. With access to live data as the new baseline, clinical development stakeholders will be more responsive to necessary study changes. This can improve trial success and potentially accelerate the delivery of new medicines to patients.

Emerging biotechs, sometimes fully outsourced, will benefit from improved oversight and be able to make decisions more nimbly. Data visibility will increase trust, allowing sponsors of all sizes to collaborate more effectively with their CROs.

Complete and reliable pharmacovigilance data will fuel advanced automation

Pharmacovigilance leaders continue to grapple with an ongoing question: how to handle growing data volumes with fewer resources while maintaining high quality. AI holds promise to do more with less, but unreliable, inconsistent, and disconnected data creates risk.

Safety teams will strengthen their data foundations with standardized, end-to-end safety processes to effectively support AI. Cross-functional workflows will eliminate manual data transfers and provide clear traceability back to the source. By simplifying and standardizing their technology landscape, companies will establish the groundwork required for faster automation and AI innovation.

This end-to-end data flow also opens the door for better collaboration across organizations. For example, processes like timely reporting of serious adverse events from EDC to safety can be done automatically with more complete data.

Moving the drug development forward for all stakeholders

Data and process mastery will improve how stakeholders collaborate to advance the industry. Patients can gain more options to participate in clinical trials, sites can focus on patient care with improved technology and process standardization, CROs can collaborate more effectively, and sponsors can automate their safety operations.

With advanced processes, clean and reliable data, and modern applications, biopharmas will drive greater efficiency, prioritize patient and site experiences, and deliver new therapies to patients faster.

Jim Reilly, executive vice president, Veeva R&D strategy