Building a Better Data Foundation: 8 R&D Life Sciences Predictions for 2024

Sponsors will simplify end-to-end data flow to reduce clinical research site burden

As clinical research sites continue to consolidate and reduce staff into 2024, sponsors will have to compete for the highest-performing sites and principal investigators. They’ll do this by building stronger relationships and streamlining their tech stacks to reduce site burden.

Since the pandemic, there’s been an explosion of technology intended to give patients more technology options for clinical trials. While this is helpful for patients, it has translated into more technology for sites to deal with. It also placed more emphasis on where trials are being conducted rather than how trial data and information are collected and shared.

From these challenges, we expect to see sponsors investing more in site engagement strategies and site-facing technology, and more investment in simplifying the end-to-end data flow. Not only will this approach streamline study execution and management, but it will also lessen the transactional nature of site-sponsor relationships.

Holistic data management will help sponsors deliver complex studies more efficiently

As the complexity of clinical research increases sharply in the coming years, we will realize new operating models for patients, sites, and sponsors. To deliver new data and user journeys that connect all clinical research contributors, we will call time on disconnected tools and embrace the platform era.

In previous decades, the industry addressed challenges by throwing resources at every problem. When that didn’t work, we created burdensome point solutions that lowered productivity. Sponsors undertaking today’s complex trials, including in gene and cell therapy, will need data-driven connectivity so patients can participate effectively and trial data can be reviewed and actioned in real time. This is only feasible when all relevant data can be managed on the same platform.

Data will be distributed across research participants in a controlled and appropriate manner. Instead of silos, each data point will automatically initiate the next step in clinical trial execution. Humans will remain in the loop even while there is less need for manual intervention and facilitation. This system interoperability will drive science forward by providing the flexibility to work with diverse, distributed, and exponentially growing data sources.

Targeted automation will elevate safety to a strategic partner

In 2024, safety will shift to operate as a strategic partner. A major part of this shift will be thanks to automation and analytics, especially as adverse event data volume continues to grow with the increasing popularity of real-world data for signal detection. Targeted automation will be critical in scaling operations without significantly increasing overhead or sacrificing quality – particularly for smaller and emerging biotechs with leaner teams.

Historically, safety teams have garnered a reputation as a critical but often overlooked business function. As automation becomes the norm for safety processes like case intake and processing, we expect to see pharmacovigilance teams stepping out of the shadows and moving away from their compliance focus. Instead, safety will increasingly partner with clinical, quality, and commercial teams to collaborate on strategic activities like protocol design, risk management, and product labeling.

Biopharmas that rethink big data will pull ahead on personalized medicine

The life sciences industry has been waiting a long time for big data to transform the commercial viability of personalized medicine. With automation now coming of age, R&D teams can finally seize the opportunity — as long as their big data is also clean, standardized, interoperable, and secure.

In 2024, companies will focus on making big data (which could range from raw trial and site-specific data to IT data points, such as cycle times) more usable by resolving common pain points around cleaning, ownership, and standards. As a result, the volume and frequency of access to study data will increase exponentially. This will require a transparent data model with stringent user access controls to address data privacy and cyber-security concerns.

Leading companies will use automation to make hundreds of marginal and incremental efficiency gains across the development lifecycle, whether deep querying protocols, detecting patterns during medical imaging analysis, or verifying the origin of chemical components. A growing industry impetus will lead to more direct data APIs between sponsors, health institutes, and regulatory authorities so that “big (clean) data” becomes a reality, creating the right conditions for commercially viable, personalized medicines to reach patients in need.

Regulatory teams will adopt an agile project delivery mindset

Challenged by the pace of global regulatory change, sweeping initiatives such as the move to data submissions, and the general directive to do more with less, more regulatory operations and affairs departments will adopt an agile “DevOps” mindset. Signs of significant culture change and a new emphasis on continuous improvement are already visible.

While they work to speed approvals in more product areas and more regions, regulatory teams will also take a deeper look at how internal operations can be improved. More of them will use the same data they send to regulatory agencies to spot trends, solve problems, and improve business performance. Continuous publishing will receive particular attention, as fully end-to-end platforms enable savings and efficiency. Another focus will be using technology to improve manufacturing change control, traditionally handled using time-consuming manual processes that often delay the availability of treatments.

Ready access to unified QA and QC data will improve efficiency and lead to better, faster decisions

The volume of QA and QC data generated for today’s quality operations is creating a review burden and stressing quality operations. To make this data readily accessible across functions, quality leaders will deepen their understanding of how different users need and prefer to use it. Rather than consider each data point from a single user group’s perspective, access will reflect multiple points of use and bring it to each decision point to improve decision speed.

More accessible quality data will enable greater use of novel approaches such as real-time batch release, which involves diverse areas such as jurisdiction, deviations, manufacturing, quality control, and batch genealogy. Overall, making end-to-end quality data readily available to all decision makers will support “right first time” results, and help speed the adoption of automation within quality.

As digital therapeutics evolve, top device manufacturers will stake their claim in the space

When Pear Therapeutics became the first company to receive payer funding for a mobile app to treat substance use disorder in 2021, it seemed like the industry was gearing up for digital therapeutics to go mainstream.

A lot has changed in two years. The digital health market suffered some losses that have cast a shadow on the budding industry, with some companies filing for bankruptcy and others leaving the payer market to go direct-to-consumer (DTC).

Despite these setbacks, digital therapeutics will continue to gain traction in 2024 – especially for larger companies that have the resources to learn lessons from these early trailblazers in the space. In the coming years, we expect to see top companies testing out varied commercial strategies for digital therapeutics, including going DTC or developing companion apps to previously established therapies. Heavy hitters like Pfizer, AstraZeneca, Boehringer Ingelheim, and Roche have already joined the Digital Therapeutics Alliance, and more will likely join the FDA’s newly formed Digital Health Advisory Committee.

Medical will prove pivotal as scrutiny of value for money intensifies in Europe

Given the continued strain on European public healthcare systems, health technology assessment (HTA) bodies have been laser-focused on the cost-effectiveness of new medicines. With more pressure on biopharma to demonstrate value for money alongside clinical efficacy, medical will be instrumental in securing access and feedback from high-potential markets.

Companies will require a clear initial picture of a drug’s patient population, dosage, and usage requirements to decide on the most effective commercial strategies. Medical will set the stage through productive and early engagement with the healthcare community and continue its education and outreach efforts until launch. These interactions will provide ongoing stakeholder feedback on a drug’s potential value – not just in clinical terms but also value for money.

The past few years have already shown significant improvements in connectivity between patients, sites, and sponsors. The newest leap forward will see technology and data converge so that clinical and medical are more connected. This will help leading companies to surmount market access barriers and improve their chances of being prescribed following regulatory approval.