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Background <p>First-cycle regulatory approval is influenced by the maturity, auditability, and lifecycle integration of a sponsor’s pharmaceutical quality system (PQS). However, no staged framework currently translates pharmaceutical quality-management-system (QMS) maturity into a quantitative regulatory-readiness construct.</p> Objective <p>To develop Regulatory Readiness Level-Pharma (RRL-P), a nine-level quality-maturity framework for pharmaceutical development and lifecycle management, and to examine its internal behaviour using simulation-based logistic models of first-pass approval readiness.</p> Methods <p>RRL-P levels were mapped to ICH Q8-Q10, ICH Q12, WHO GMP, EU GMP, FDA 21 CFR Parts 210/211, and relevant data-integrity expectations. A synthetic cohort of 500 simulated projects was generated across RRL-P levels, product classes, and sponsor-experience strata. Three interpretable logistic model structures were evaluated to assess the internal consistency and directional behaviour of the proposed scoring architecture. The modelling component was designed as a proof-of-concept simulation exercise, not as external empirical validation.</p> Results <p>In the synthetic dataset, the continuous weighted-score model showed the strongest internal discrimination and calibration (AUC = 0.85; Brier = 0.15). A 0.10 increase in simulated QMS maturity score was associated with approximately two-fold higher simulated approval odds. Step-wise effects were non-uniform, with the largest simulated gains around the transition from process qualification to submission/approval readiness.</p> Conclusion <p>RRL-P provides a staged, auditable framework for structuring pharmaceutical QMS maturity and regulatory readiness. The modelling results should be interpreted as simulation-based and hypothesis-generating, not as external empirical validation of first-pass approval prediction. Real-world validation will require linked sponsor-level QMS maturity data and regulatory outcome data.</p> Summary <p>Purpose: Develop a staged, nine-level Regulatory Readiness Level-Pharma (RRL-P) ladder that translates pharmaceutical QMS maturity into auditable milestones. Methods: Delphi-informed weighting across nine QMS domains; simulation of 500 dossiers; three interpretable logistic model specifications benchmarked for internal behaviour. Results: The continuous-score model achieved AUC 0.85 in the synthetic dataset; each 0.10 simulated score gain was associated with approximately two-fold higher simulated approval odds; the largest simulated readiness gains occurred around P5-P7. Conclusion: RRL-P offers a structured, simulation-tested framework for assessing pharmaceutical regulatory readiness, while external validation remains necessary before real-world prediction claims can be made. Teaser. A staged QMS maturity ladder provides a simulation-based framework for assessing pharmaceutical regulatory readiness.</p>

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Regulatory Readiness Level-Pharma (RRL-P): A Nine-Level Quality-Maturity Framework and Simulation-Based Model for First-Pass Approval Readiness

  • 期刊论文

  • 发表日期：

    2026年7月4日

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  • Mehdi Zadehnour

摘要

Background

First-cycle regulatory approval is influenced by the maturity, auditability, and lifecycle integration of a sponsor’s pharmaceutical quality system (PQS). However, no staged framework currently translates pharmaceutical quality-management-system (QMS) maturity into a quantitative regulatory-readiness construct.

Objective

To develop Regulatory Readiness Level-Pharma (RRL-P), a nine-level quality-maturity framework for pharmaceutical development and lifecycle management, and to examine its internal behaviour using simulation-based logistic models of first-pass approval readiness.

Methods

RRL-P levels were mapped to ICH Q8-Q10, ICH Q12, WHO GMP, EU GMP, FDA 21 CFR Parts 210/211, and relevant data-integrity expectations. A synthetic cohort of 500 simulated projects was generated across RRL-P levels, product classes, and sponsor-experience strata. Three interpretable logistic model structures were evaluated to assess the internal consistency and directional behaviour of the proposed scoring architecture. The modelling component was designed as a proof-of-concept simulation exercise, not as external empirical validation.

Results

In the synthetic dataset, the continuous weighted-score model showed the strongest internal discrimination and calibration (AUC = 0.85; Brier = 0.15). A 0.10 increase in simulated QMS maturity score was associated with approximately two-fold higher simulated approval odds. Step-wise effects were non-uniform, with the largest simulated gains around the transition from process qualification to submission/approval readiness.

Conclusion

RRL-P provides a staged, auditable framework for structuring pharmaceutical QMS maturity and regulatory readiness. The modelling results should be interpreted as simulation-based and hypothesis-generating, not as external empirical validation of first-pass approval prediction. Real-world validation will require linked sponsor-level QMS maturity data and regulatory outcome data.

Summary

Purpose: Develop a staged, nine-level Regulatory Readiness Level-Pharma (RRL-P) ladder that translates pharmaceutical QMS maturity into auditable milestones. Methods: Delphi-informed weighting across nine QMS domains; simulation of 500 dossiers; three interpretable logistic model specifications benchmarked for internal behaviour. Results: The continuous-score model achieved AUC 0.85 in the synthetic dataset; each 0.10 simulated score gain was associated with approximately two-fold higher simulated approval odds; the largest simulated readiness gains occurred around P5-P7. Conclusion: RRL-P offers a structured, simulation-tested framework for assessing pharmaceutical regulatory readiness, while external validation remains necessary before real-world prediction claims can be made. Teaser. A staged QMS maturity ladder provides a simulation-based framework for assessing pharmaceutical regulatory readiness.