Scaling Nucleic Acid Therapeutic Manufacturing: The Promise of Raman

In the fast-evolving world of nucleic acid therapeutics, scientists and manufacturers are constantly in search of analytical techniques that deliver accuracy, speed, and cost-efficiency. From DNA and RNA to their modified derivatives, these therapies are transforming medicine—powering mRNA vaccines, gene therapies, and CAR-T treatments. Yet, scaling these breakthroughs from research to production is often impacted by expensive, time-consuming quality control steps.

Traditional tools like HPLC, MS, and NMR are well-established for characterizing nucleic acid therapeutics—but each comes with trade-offs in speed, sample prep, or cost. Raman spectroscopy is emerging as a compelling alternative. Already proven in protein therapeutic manufacturing for its non-destructive nature and minimal sample preparation, Raman spectroscopy offers molecular specificity and speed that could dramatically streamline analytics for nucleic acid-based drugs.

But what is Raman spectroscopy? It’s a vibrational spectroscopic technique that detects changes in light scattered off molecules. When a laser interacts with a sample, most light is elastically scattered (Rayleigh scattering), but a tiny fraction undergoes inelastic scattering—shifting in energy based on molecular vibrations. This shift forms a unique spectral fingerprint, enabling the identification of chemical bonds and molecular structures. In nucleic acids, the base components—adenine, thymine, guanine, and cytosine—generate strong Raman signals, allowing researchers to extract rich structural and compositional information. Raman is a Process Analytical Technology, or PAT, which enhances capabilities in scaling bioprocesses, optimizing upstream processes to ensure efficient and consistent processing. Read our compendium on PAT-enabled scaling and optimization of upstream bioprocesses.

A Proof of Concept: Measuring PolyA Tail Length with Raman

To explore Raman’s capabilities in nucleic acid analysis, we performed a proof-of-concept study targeting one critical quality attribute: the number of adenine bases in the polyA tail of oligonucleotides. Using a process Raman analyzer, the team analyzed synthetic DNA strands with varying lengths of polyA tails.

The study employed chemometric models—including principal component analysis (PCA) and principal component regression (PCR)—to classify the sequences and quantify adenine content based on their Raman spectra. Spectral preprocessing steps, like baseline correction and normalization, were used to fine-tune the data for modeling. The model was then validated using independent test samples, achieving strong performance metrics: an R² of 0.93 and a prediction error of just ±1 adenine.

Why This Matters for the Future of Nucleic Acid Therapeutics

This proof-of-concept study shows that Raman spectroscopy can be a powerful tool for identifying oligonucleotide sequences and quantifying adenine content—two critical capabilities in the development and manufacturing of nucleic acid therapeutics. The ability to distinguish oligonucleotides based on their sequence allows researchers and manufacturers to ensure the identity and integrity of therapeutic candidates early in the development process. This is particularly important given that even minor sequence deviations can significantly impact a therapy’s function, stability, or immunogenicity.

Quantifying the number of adenines in the polyA tail is also a vital quality attribute, especially in messenger RNA (mRNA) therapeutics. The polyA tail plays a key role in enhancing mRNA stability, nuclear export, and translational efficiency. A tail that is too short can result in reduced protein expression, while one that is too long can impact regulatory mechanisms. Therefore, accurately measuring polyA tail length is essential for ensuring consistent therapeutic performance.

Currently, techniques like ion-pair reversed-phase HPLC are used for polyA quantification, but they often require labor-intensive protocols and are not well suited for real-time or in-process applications. Raman spectroscopy, by contrast, enables rapid, label-free, and non-destructive analysis that can be integrated directly into manufacturing workflows. This shift toward real-time analytics opens the door to improved process control, reduced batch failures, and accelerated product release timelines.

This study also speaks to a larger trend in biopharma: the growing demand for Raman-based chemometric models that are robust, transferable, and applicable across diverse upstream workflows. Raman spectroscopy has already been successfully applied to monitor critical parameters across multiple cell lines and media types. Read our application note to see how transferable models can enhance upstream bioprocess monitoring for a variety of biologics.

As the industry pushes toward more scalable and efficient production of DNA and RNA-based drugs, Raman spectroscopy offers a promising path forward—one that aligns with the growing demand for speed, specificity, and cost-effective quality assurance in biopharma manufacturing.

Want to dive deeper into the data and methodology? Read the full article on Raman-based analytics for nucleic acid therapeutics.

A New Frontier: Real-Time Monitoring of IVT with Raman

The study also draws attention to Patent WO2024074726A1, which introduces a method for spectral monitoring of in vitro transcription (IVT) reactions using Raman spectroscopy. This patent demonstrates how biopharmaceutical companies are leveraging Raman spectroscopy to track IVT reactions in real time by comparing the spectral signatures of reactants and products during RNA synthesis. The ability to monitor changes in IVT enables automation through feedback control, improving both the quantity and quality of mRNA while reducing batch-to-batch variability.

Notably, similar experimental feasibility has been previously demonstrated by the authors, reinforcing the practical value of Raman-based monitoring in RNA manufacturing.

This innovation has the potential to streamline manufacturing workflows, reduce costs, and enhance reproducibility in RNA-based therapeutics.

As the field of nucleic acid therapeutics continues to expand, Raman spectroscopy is poised to be a game-changer—delivering faster, more efficient, and more accessible treatments, while offering mutual benefits in cost and time for manufacturers.