How Real-World Evidence Can Support Clinical Pharmaceutical Manufacturing | PurpleLab®

This blog is part two in a series exploring the use of real-world evidence to produce meaningful insights in clinical pharma. 

Pharmaceutical manufacturers do more than just produce medications that line pharmacy and hospital shelves: they also need to closely observe and respond to market conditions, changing clinical guidelines, and safety regulations, to ensure that they’re constantly keeping up with patient needs and requirements. 

In order to be agile and fully responsive to these diverse factors, manufacturers can utilize real-world evidence (RWE) – which unlocks valuable insights into patient healthcare including the utilization and outcomes related to a treatment. This blog explores the uses of RWE throughout the clinical pharmaceutical manufacturing continuum, and discusses how it can support decision-making.

The role of manufacturing in the drug development process

Clinical pharmaceutical manufacturers, the companies that develop and manufacture prescription drugs, are responsible for producing medications throughout their entire lifecycle, with crucial differences at each stage. During initial research and development stages, they produce small quantities for testing with a high degree of flexibility. Once a drug candidate reaches clinical trials, they manufacture investigational medicinal products, adhering to strict regulatory guidelines and scaling production for larger populations. Post-regulatory approval, they upscale production for commercial manufacturing, optimizing processes for efficiency and quality while ensuring compliance. Throughout a drug’s lifecycle, manufacturers continue to produce variations based on the drug’s safety profile, market demands, or evolving clinical guidelines.

How do clinical pharmaceutical manufacturers use real world evidence? 

Real-world evidence (RWE) can offer valuable insights throughout the entire pharmaceutical manufacturing process. RWE complements traditional clinical trial data and provides manufacturers with additional insights into the safety, effectiveness, and value of their medications in real-world settings. Here’s how RWE empowers these manufacturers:

• Drug development and clinical trials: RWE can help manufacturers gain a deeper understanding of disease prevalence, diagnosis patterns, and treatment pathways in real-world clinical settings. This informs decisions about which diseases to target and how to design future medications. By analyzing how patients with a particular condition respond to existing treatments in real-world data, manufacturers can design more efficient and targeted clinical trials. This can involve optimizing trial size, eligibility criteria, and even identifying potential biomarkers to predict treatment response. This optimization includes assessing the viability of protocols based on factors such as the geographical distribution of trial sites, the expertise of investigators, and the accessibility of patients.

• Supporting regulatory decisions: While not a replacement for randomized controlled trials, RWE is increasingly being recognized by regulatory agencies like the FDA as a synthetic control It can support applications for new drug indications or even initial approvals in certain cases

• Post-approval activities: RWE allows manufacturers to continuously monitor the safety and effectiveness of their drugs once they’re on the market. This can identify rare side effects or long-term effects that might not be apparent in controlled clinical trials. Additionally, RWE can reveal how physicians are prescribing medications outside their approved labels (off-label use). This information can guide future research efforts and potential new drug label applications. Manufacturers can leverage RWE to assess the cost-effectiveness of their medications in real-world practice. This data is crucial for discussions with payers (health insurance companies) regarding pricing and reimbursement strategies.

The limitations of RWE

While RWE offers significant advantages in clinical pharmaceutical manufacturing, there are also important limitations to consider, particularly around data quality and the observational nature of RWE. Unlike data collected in meticulously controlled clinical trials, real-world data may lack the same level of robustness and standardization. Variability in data collection methodologies, patient populations, healthcare practices, and documentation standards can potentially lead to biases and inconsistencies. 

Furthermore, RWE primarily relies on observational data. While providing valuable insights into real-world treatment patterns and outcomes, it is extremely difficult to control for confounding variables, and therefore, to establish cause-and-effect relationships. For this reason, manufacturers should always complement RWE with data from random control trials to ensure  a more comprehensive understanding of the real-world impact of their interventions.

Incorporating real-world evidence into pharmaceutical manufacturing processes can enhance and streamline decision-making throughout the entire drug lifecycle, from research and development to post-approval activities.