Life Sciences

The evolving RNA therapeutics landscape

By Edita Botonjic-Sehic, Head of Process Analytics and Data Science at ReciBioPharm.

This article explores continuous manufacturing in RNA therapeutics. By moving from batch processes to digitally-controlled continuous methods with inline process analytic technologies (PAT), automation and real-time data analytics, developers can quickly overcome process bottlenecks and deliver innovative RNA therapeutics.  

RNA therapeutics are transforming the treatment of many different disease indications. Due to considerable progress in areas such as rare diseases, anti-infectives and oncology, new RNA-based products are poised to enter the various markets and improve patient outcomes1.

Rare disease markets remain a priority for RNA therapeutic developers. Estimated to be worth $216.65 billion in 2024, the rare disease treatments market is expected to grow with a compound annual growth rate (CAGR) of 11.93%, increasing the market estimate to $380.62 billion by 20292.

Although the first RNA therapy was launched in 19983, subsequent progress was slow until Covid-19 vaccine programs propelled RNA products into the forefront of pharmaceutical development. With this recent progress, 28 RNA therapies have been approved and 1,072 are currently in development1.

Capitalising on the commercial success of RNA therapeutics, meeting market demands and improving patient outcomes requires improved manufacturing processes that increase efficiency, quality and production speed.

Continuous manufacturing benefits

In traditional batch manufacturing, each processing step is performed sequentially to produce a final product. Batch processing is widely used in RNA therapeutics, but can lead to bottlenecks, long manufacturing lead times and a challenging product scale-up.

Continuous manufacturing has emerged in response to the challenges in batch manufacturing and can enhance RNA therapeutic processing, enabling developers to:

  • Accelerate production timelines.
  • Lower manufacturing costs.
  • Improve product quality.
  • Automate processes.
  • Reduce the risk of human error.

By adopting continuous manufacturing processes, developers can enhance the efficiency, speed and quality of their RNA products in development. Supporting innovation, the International Council for Harmonisation (ICH) and the US Food and Drug Administration (FDA) recognise the benefits of continuous manufacturing and promote its use in biopharmaceutical production4-7. The FDA has also recently funded the development of a fully-integrated continuous RNA manufacturing platform with an investment of $82 million. The project aims to revolutionise RNA manufacturing, propelling RNA products to the forefront of disease treatment8.

Even with the support from regulatory bodies, the biopharmaceutical industry has been slow to adopt continuous manufacturing. Switching to a continuous method requires products to go through re-approval to maintain product safety and efficacy. Continuous manufacturing also requires optimisation to provide robust and precise manufacturing outcomes, supported by effective control systems to monitor the process in real time.

Digitally controlled methods

Continuous manufacturing can be unlocked by enabling real-time RNA production and control process monitoring. Models that simulate real-world events allow developers to proactively identify risks that would cause critical quality attributes (CQAs) to fall outside of a defined range. Identifying trends over time also means that changes can be made during process development, ensuring that CQAs remain within desired ranges.

Identifying and defining the appropriate ranges for CQAs allows developers to maintain the safety and efficacy of their products and remain compliant with regulations. Regulatory bodies require analytical data to show that quality falls within the CQA range and that drug products remain safe and effective.

Monitoring analytics with integrated PAT throughout manufacturing processes also allows developers to streamline processes and quickly meet manufacturing demands. Analysis can be completed in days rather than weeks with real-time capabilities and automated sampling steps.

Leveraging online PAT

Understanding product characteristics and the impact changes in process parameters can have during production requires appropriate analytical methods. However, analyses are usually performed offline in batch production, which can lead to significant delays in manufacturing. Samples may need to be analysed in an off-site laboratory in a different location and some assays can take days to complete. Analysing the purity profiles of RNA therapeutics can be a particularly long process, highlighting the need for improved analytical approaches in RNA manufacturing.

Analytics can be improved in continuous RNA manufacturing by incorporating inline, online and at-line PAT monitoring. Machine learning (ML) and artificial intelligence (AI) are central to this approach, with advantages including real-time data analytics, in-process monitoring of CQAs, automated sample collection and reduced transport of samples to separate laboratories. Continuous RNA manufacturing with integrated PAT monitoring also provides several other advantages:

  1. Reduced wastage

Continuous monitoring minimises the risk of whole batch quality issues, leading to reduced waste. Automated systems also significantly reduce the amount of material required for analytics, sampling only the precise volumes required. As PAT monitoring can also provide an in-depth understanding of in vitro transcription (IVT) kinetics, the concentration of components can be optimised, ensuring materials are used efficiently and cost-effectively.

  1. Minimal labour burden

Inline PAT significantly reduces sample analysis times, meaning fewer full-time employees (FTEs) are required in continuous manufacturing compared with batch processing. A reduction in FTEs results in more efficient and cost-effective manufacturing.

  1. Risk mitigation

Switching from offline quality control (QC) to inline and online processes reduces the risk of human error. All processes and QC testing are performed in a single suite, with an uninterrupted production flow that minimises human interaction.

Although PAT-driven continuous processes can help accelerate product manufacturing and quickly deliver RNA therapeutics to patients, significant investment is required to move away from well-established batch manufacturing processes. However, the success of RNA therapeutics is still relatively recent. This presents an opportunity for developers to adopt innovative continuous manufacturing processes without the burden of modifying long-standing manufacturing methods.

The evolving RNA landscape

Continuous manufacturing can enable developers to get ahead in the evolving RNA therapeutics landscape. However, developing a continuous manufacturing process requires a quality-by-design (QbD) strategy, ensuring product safety, efficacy, quality and adherence to regulatory requirements.

Incorporating cutting-edge technologies, including inline analytics, automation and real-time analysis, can provide a flexible continuous process and future-proof RNA manufacturing. A robust continuous RNA manufacturing platform should include:

  • Next-generation equipment: Next-generation tools include online, inline and at-line PAT, automation and real-time data analytics. Adding these technologies on top of baseline processes elevates continuous manufacturing and provides improved monitoring capabilities.
  • Automated infrastructure: As automated processes are key to accelerating timelines, RNA developers and manufacturers should aim to automate as many processes as possible in continuous manufacturing, including analytical testing. An infrastructure designed for automation allows for seamless analysis and data collection in a unified framework. Data collected can be used for model development and optimising the continuous manufacturing process.
  • Digital twin models: Continuous PAT monitoring generates a large amount of data, which can be used to develop digital models that accurately mimic the real-world environment. Digital models provide a deeper understanding and enhanced process control, particularly when multiple models are generated from different constructs. Multiple models for each unit operation add flexibility to manufacturing processes and help developers navigate the evolving RNA therapeutics landscape.

Future-proofing manufacture

The RNA therapeutics landscape continues to evolve, with an increasing number of promising treatment options for many disease states highlighting the importance of effective manufacturing processes. Continuous processes can enhance RNA manufacturing by streamlining multiple unit operations into a single, uninterrupted process. The production of RNA therapeutics can therefore be accelerated with continuous manufacturing, minimising risk and improving product quality compared with traditional batch manufacturing. Next-generation technologies can also further enhance production, improve quality control, reduce manufacturing times and lower costs. Ultimately, this can accelerate patient access to life-saving treatments.

Continuous manufacturing is set to play a prominent role in the evolving RNA therapeutics landscape. Developers that successfully leverage continuous manufacturing can accelerate the development and manufacturing of their RNA therapeutics. As this can lead to improved patient outcomes, continuous manufacturing is likely to play an increasingly important role in producing RNA therapeutics in the future.



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