Process development analytics for pDNA and mRNA therapeutics

Erika Morato-Perlera, Sr Manager, Analytical Development & Quality Control
Cytiva process development services analytics team

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The emergence of plasmid DNA (pDNA) and mRNA-based therapeutics has transformed the biopharmaceutical industry, presenting both immense potential and new challenges. As companies race to develop mRNA-based therapies, balancing process development (PD) analytics with phase 1 filing readiness is a crucial yet often overlooked aspect. Analytics for PD refers to the application of analytical methods and data-driven strategies to support the design, optimization, and scale-up of pDNA and mRNA therapeutics to help ensure that critical quality attributes (CQAs) of the product are understood. This article addresses the need for a strategic, risk-based approach that ensures a robust analytics program without burdening early-phase programs with unnecessary complexity. The balance between these two efforts must be harmonized to accelerate timelines and secure confidence in product quality.

We present perspectives from analytical scientists supporting early-phase therapeutic drug development in various modalities. We aim to provide practical guidance to PD scientists, analytical leads, QC organizations, and regulatory teams on how to prioritize and scale analytical strategies in the early development of pDNA and mRNA programs, all while balancing scientific rigor, regulatory expectations, and operational realities during the critical transition from PD to clinical manufacturing.

Introduction: pDNA and mRNA process development

Nucleic acid modalities like pDNA and mRNA are evolving rapidly, but the analytical and manufacturing requirements are still maturing (1,2, 9,11,12). Unlike mAbs or other well-characterized biologics, there is less regulatory precedent for analytical method expectations in early development of pDNA and mRNA therapeutics (3–5,13–15). This uncertainty puts pressure on PD analytics teams to deliver meaningful data that supports process optimization and prepares the program for clinical success.

Equally important, pDNA is no longer viewed solely as a raw material for in vitro transcription; it is progressing as a direct therapeutic modality (e.g., DNA vaccines) and remains crucial to the production of viral vectors, where it provides the genetic material required for packaging the therapeutic payload (17,18).

PD scientists often ask common questions, such as: How much of the genetic material is enough? Do all analytical methods need to be qualified for phase 1? Must all labs operate under GMP? These are not trivial questions, and the answers depend on risk-based analysis, process understanding, and effective collaboration (6–8,16).

The role of analytics in pDNA and mRNA process development

In process development, analytics plays a large role in turning experimentation into actionable knowledge that de-risks programs and accelerates therapies to patients. Assays for monitoring cell growth and productivity, evaluating plasmid or mRNA yield, confirming purity and impurity profiles, measuring product integrity and potency, and showing regulatory readiness are common techniques to perform necessary steps in both upstream and downstream process development. In fact, there are characterization requirements that are unique to pDNA and mRNA workflows. pDNA and mRNA differ fundamentally from traditional biologics. The structural complexity and large size of mRNA (~1–5 kb) and pDNA (> 3 kb) complicate their separation and detection. Methods developed for protein chromatography and liquid chromatography-mass spectrometry (LC-MS) are often not directly applicable. The high net negative surface charge of these molecules results in strong interactions with silica-based stationary phases, leading to broad or tailing peaks. Consequently, ≤100 mM salt or ion-pair modifiers are needed to maintain resolution (19).

Additionally, their large hydrodynamic radius and lower folding density contribute to poor resolution and tailing. Molecular heterogeneity, particularly in untranslated regions (UTRs), poly(A) tails, and capping efficiency affect potency and translational fidelity, posing challenges for platform analytics (19).

Regulatory uncertainty also presents difficulties. Although guidelines exist for impurity and identity testing, thresholds for certain impurities, such as double-stranded RNA (dsRNA), are not well defined. It is advisable to have contingency methods and risk-based justifications ready for discussions with regulatory authorities.

Key analytical targets during process development include mRNA integrity, purity/impurities, potency indicators, and molecular size and homogeneity. mRNA integrity is typically assessed by capillary gel electrophoresis (CGE) or fragment analysis (1,3), and high integrity mRNA correlates with translational competence.

In terms of purity and impurities, for mRNA this includes dsRNA measured by ELISA, residual enzymes like T7 polymerase, and the absence of pDNA-derived templates. For pDNA, typical purity assays encompass host-cell protein (HCP), genomic DNA, and endotoxin. pDNA and mRNA modalities are analyzed for residual RNA or DNA respectively, though the target matrices differ.

Potency indicators for mRNA involve capping efficiency and poly(A) tail length, while for pDNA, supercoiled percentage and topology serve as indirect potency surrogates in early development (2).

Finally, techniques such as size-exclusion chromatography (SEC), anion exchange chromatography (AEX), and dynamic light scattering (DLS) are employed to analyze molecular size and homogeneity, requiring method development tailored to RNA or DNA behavior (2).

Lipid nanoparticle (LNP) formulation and its associated analytics are essential downstream steps after mRNA—or pDNA—drug substance production; however, an in-depth review is beyond the scope of this article. For detailed LNP process development and release-testing guidance, readers are encouraged to consult Cytiva BioPharma Services, whose published workflows and case studies cover encapsulation, particle characterization, and stability strategies.

Bridging PD analytics and phase 1 filing readiness

Do methods need to be qualified and GMP? A balanced view

Not all analytical methods need to be fully qualified or executed in GMP laboratories for phase 1 studies. However, methods supporting release and stability must be robust, reproducible, and at least partially qualified (6–8, 10). PD-developed methods can be transferred from non-GMP laboratories, provided that method transfer protocols and data traceability are established (6–8). GMP execution is anticipated for stability, release, and comparability studies intended for clinical filing (6).

In practice, PD analytics teams have the capability to develop and preliminarily qualify methods before transferring them to GMP-certified laboratories for formal execution, thus enabling early learning without delay in project timelines. Although the International Council for Harmonisation (ICH) and US Food and Drug Administration (FDA) guidance allow phase-appropriate method qualification, it remains critical that pivotal assays meet minimal performance thresholds (7). Refer to Table 1.

Table 1. Minimal performance expectations for assay qualification in phase 1

Method type	Minimum expectation for phase 1
Identity	Partially qualified, documented specificity
Impurity (dsRNA, residual DNA)	Fit-for-purpose, trending capable
Purity	Quantitative method with defined Lower Limit of Quantification (LLoQ)
Potency surrogate	Justified, with trending and bridge strategy
Stability	Stability indicating and traceable to drug substance (DS)/ drug product (DP) batch

 

Gaining insight with early stability studies

While full ICH stability programs may come later, early PD stability studies offer critical insight (1,4). Once the PD process is semi-locked, simple trending can highlight risks and inform future formulation and filing decisions.

Below is a list of recommended analytical assays that can be studied during the PD stage:

• pH stability: effect of buffer pH on integrity and degradation
• Freeze/thaw cycles: number of tolerable cycles for DS or LNPs
• Thermal stress: degradation rate under heat exposure
• Time-out-of-refrigeration: practical handling limits
• Hold time: for DS and formulation intermediates

These studies help define shipping and storage conditions, input for batch record limits, and triggers for in-process hold monitoring (1,3,4).

In addition, this is a list of analytical methods recommended for stability insights:

• CGE or Bioanalyzer: degradation and integrity <lireverse-phase></lireverse-phase>
• UV absorbance or fluorescence: titer and general purity
• Dynamic light scattering (DLS) or nanoparticle tracking analysis (NTA) for LNPs: particle stability and aggregation

Actual release and long-term stability studies supporting clinical batches must be done by GMP labs, but early PD studies help define conditions and prepare for method validation.

Impurity clearance studies

Clearance studies are critical even in early PD. Demonstrating where and how impurities are removed builds confidence in the process and informs method selection (4,5). Early mapping of process impurity clearance builds confidence and supports regulatory dialogue. A few assays recommended for investigating and determining the impurity profile and CQA requirements include:

• qPCR: quantify residual DNA across purification steps
• ELISA: detect and trend residual enzymes (e.g., T7 polymerase), dsRNA, or host proteins
• A260/A280 and chromatography: profile total RNA purity and contaminants

Mapping impurity clearance not only supports regulatory expectations, but also provides evidence for robustness, informs in-process controls, and highlights process risks.

Communication between PD and analytics: a core requirement

It’s essential to understand how each step in the process is designed to meet the product CQAs and align on the required analytical assays that will ensure robust and reproducible results. This approach requires close collaboration between PD and analytical teams to enable more agile iterations (3,4):

• Analytics informs process performance: For example, if dsRNA clearance is insufficient, chromatographic steps can be adjusted.
• Process informs analytical method performance: For example, if a new impurity profile arises post-purification, analytical methods must be revised.

A cross-functional communication culture between PD scientists and PD analytics is critical. Shared understanding of CQAs and failure modes ensures alignment across both disciplines. Regular touchpoints, data visualization tools, and clear documentation practices are crucial.

Equally important, QC, clinical manufacturing, regulatory affairs, and supply chain teams should be looped into the same early touchpoints so that equipment choices, sampling plans, and protocols content are co-created—rather than retrofitted—across the full product life cycle.

Clinical success: strategy to transition to phase 1

Transitioning from process development to phase 1 clinical manufacturing requires a deliberate and proactive strategy. Analytics play a central role in demonstrating product understanding, process control, and regulatory compliance. To support a successful and timely filling, developers must anticipate technical and regulatory expectations early, especially for complex modalities like pDNA and mRNA. The following sections outline key elements of this strategy, focusing on analytics transition planning, stability program development, and risk mitigation.

Analytics transition planning

Establishing a robust analytics transition plan early in development helps avoid delays and costly rework. The key is to ensure that critical assays are not only scientifically sound but also appropriately qualified for GMP use. Moreover, proactive selection of platforms and instrumentation supports long-term method life cycle management and avoids technical transfer challenges that often arise at the phase 1 interface. Key tips include:

• Begin GMP readiness planning early in development (6).
• Focus on qualifying critical assays (e.g., CGE, qPCR) that support stability and release.
• Use risk-based justifications for interim methods (7,8).
• Where methods are developed in non-GMP labs, document performance (e.g., precision, linearity) to streamline formal qualification and ensure proper transfer to GMP for phase 1 execution.
• Select major instrumentation early (chromatography platform, DLS/NTA vendor, light-scattering detector) to minimize cross-site tech transfer issues; mismatched HPLC dwell volumes or detector angles are a top cause of schedule slippage (20).

Stability program planning

Stability data is a cornerstone of regulatory submission, informing product shelf life, storage conditions, and manufacturing hold times. For newer modalities like pDNA and mRNA, these data are often limited at early stages, so it is essential to generate stability insights during development and design assays that translate smoothly to GMP execution. Key tips include:

• Conduct PD stress and trending studies early.
• Design transfer-friendly, high-throughput formats (e.g., 96-well qPCR, microfluidics) (2).
• Generate data for formulation hold time, storage temperature, and shipping strategy.
• Engage GMP labs early for long-term ICH stability programs to support investigational new drugs (INDs) (4,6).

Proactive risk mitigation

Anticipating analytical process risks can prevent late-stage surprises that can risk timelines or regulatory confidence. Integrating structured risk assessment and contingency planning into development workflows helps teams respond more agilely to analytical gaps or evolving expectations. Key tips include:

• Use failure mode and effects analysis (FMEA) or similar risk tools to link process steps to CQAs (7,8).
• Develop backup assays or alternate techniques where regulatory ambiguity exists.
• Revisit risks from time to time to reassess for new risks and/or changes.

Driving toward success in early-phase mRNA and pDNA process development

Success in early-phase mRNA and pDNA development hinges on thoughtful, scalable analytics and early alignment with manufacturing needs. While not all methods must be fully GMP or validated during PD, they must be reliable enough to inform decisions and withstand regulatory scrutiny (6). Early stability insights, impurity clearance mapping, and analytical scalability help reduce risk and build a foundation for long-term success (1,4). The future of mRNA and pDNA therapeutics depends not just on novel science, but also on thoughtful analytical design, clear process understanding, and proactive collaboration.

References

1. Baiersdörfer M, Boros G, Muramatsu H, et al. A Facile Method for the Removal of dsRNA Contaminant from In Vitro-Transcribed mRNA. Mol Ther Nucleic Acids. 2019;15:26-35. doi:10.1016/j.omtn.2019.02.018
2. Schoenmaker L, Witzigmann D, Kulkarni JA, et al. mRNA-lipid nanoparticle COVID-19 vaccines: Structure and stability. Int J Pharm. 2021;601:120586. doi:10.1016/j.ijpharm.2021.120586
3. ICH Harmonized Guideline: Analytical Procedure Development Q14. Step 2 Draft. International Council for Harmonisation (ICH). March 2022. Accessed September 15, 2025. https://database.ich.org/sites/default/files/ICH_Q14_Document_Step2_Guideline_2022_0324.pdf
4. Guidance for Industry: Chemistry, Manufacturing, and Control (CMC) Information for Human Gene Therapy Investigational New Drug Applications (INDs). US Food and Drug Administration (FDA). January 2020. Accessed September 15, 2025. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/chemistry-manufacturing-and-control-cmc-information-human-gene-therapy-investigational-new-drug
5. Verbeke R, Lentacker I, De Smedt SC, Dewitte H. The dawn of mRNA vaccines: The COVID-19 case. J Control Release. 2021;333:511-520. doi:10.1016/j.jconrel.2021.03.043
6. New Chapter <1220> Analytical Life Cycle. US Pharmacopeia. May 2022. Accessed September 16, 2025. https://www.uspnf.com/notice-gc-1220-prepost-20210924
7. ICH Harmonized Guideline: Validation of Analytical Procedures Q2(R2). ICH. November 1, 2023. Accessed September 15, 2025. https://database.ich.org/sites/default/files/ICH_Q2%28R2%29_Guideline_2023_1130.pdf
8. ICH Harmonized Guideline: Pharmaceutical Development Q8(R2). ICH. August 2009. Accessed September 15, 2025. https://database.ich.org/sites/default/files/Q8_R2_Guideline.pdf
9. Pardi N, Hogan MJ, Porter FW, Weissman D. mRNA vaccines — a new era in vaccinology. Nat Rev Drug Discov. 2018;17(4):261-279. doi:10.1038/nrd.2017.243
10. Sahin U, Muik A, Derhovanessian E, et al. COVID-19 vaccine BNT162b1 elicits human antibody and T_H1 T cell responses. Nature. 2020;586:594-599. doi:10.1038/s41586-020-2814-7
11. Whitley J, Zwolinski C, Denis C, et al. Development of mRNA manufacturing for vaccines and therapeutics: mRNA platform requirements and development of a scalable production process to support early phase clinical trials. Transl Res. 2022;242:38-55. doi:10.1016/j.trsl.2021.11.009
12. C. Challener, “Analysis of mRNA Therapeutics and Vaccines,” BioPharm International 35 (2) (2022). https://www.biopharminternational.com/view/analysis-of-mrna-therapeutics-and-vaccines
13. Analytical Procedures for mRNA Vaccine Quality (Draft Guidelines)- 2nd Edition. US Pharmacopeia. April 2023. Accessed September 16, 2025. https://www.uspnf.com/notices/analytical-procedures-mrna-vaccines-20230428
14. Yamout K. Driving breakthroughs in mRNA therapeutics with advanced analytical techniques. American Pharmaceutical Review. https://www.americanpharmaceuticalreview.com/Featured-Articles/610779-Driving-Breakthroughs-in-mRNA-Therapeutics-with-Advanced-Analytical-Techniques/. Published February 1, 2024. Accessed September 16, 2025.
15. Rogers M. Analytical considerations for mRNA-based therapies. American Pharmaceutical Review. https://www.americanpharmaceuticalreview.com/Featured-Articles/609921-Analytical-Considerations-for-mRNA-based-Therapies/. Published December 2, 2023. Accessed September 16, 2025.
16. Dickman MJ. New workflow for the analysis of mRNA therapeutics. European Pharmaceutical Review. https://www.europeanpharmaceuticalreview.com/article/180078/new-workflow-for-the-analysis-of-mrna-therapeutics. Published March 1, 2023. Accessed September 16, 2025.
17. Kamenšek U. Editorial on Special Issue “Plasmid DNA for Gene Therapy and DNA Vaccine Applications”. Pharmaceutics. 2025;17(5):630. doi:10.3390/pharmaceutics17050630.
18. Estipona D. A Review of Viral Vectors in Gene Therapy. Biocompare. https://www.biocompare.com/Editorial-Articles/619487-A-Review-of-Viral-Vectors-in-Gene-Therapy/. Published June 5, 2025. Accessed September 23, 2025.
19. Fekete S, Doneanu C, Addepalli B, et al. Challenges and emerging trends in liquid chromatography-based analyses of mRNA pharmaceuticals. J Pharm Biomed Anal. 2023;224:115174. doi:10.1016/j.jpba.2022.115174.
20. Wojcik J, Sikorski T, Wang J, et al. 2024 White Paper on Recent Issues in Bioanalysis: Three Way-Cross Validation; Urine Clinical Analysis; Automated Methods; Regulatory Queries on Plasma Protein Binding; Automated Biospecimen Management; ELN Migration; Ultra-Sensitivity Mass Spectrometry. Bioanalysis. 2025;17(5):299-337. doi:10.1080/17576180.2025.2450194