Virginia Sancho-Ochoa

Ms. Virginia Sancho-Ochoa


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 December 2025 in Information
Verified
Journal Article
Open access
PDF file
MRMiquel Romero-Obon
Miquel Romero-Obon
Khadija Rouaz El HajouiKhadija Rouaz El Hajoui
Khadija Rouaz El Hajoui
VSVirginia Sancho-Ochoa
Virginia Sancho-Ochoa
RVRonny Vargas
Ronny Vargas
Pilar Pérez-LozanoPilar Pérez-Lozano
Pilar Pérez-Lozano
Encarna Garcia-MontoyaEncarna Garcia-Montoya
Encarna Garcia-Montoya
The pharmaceutical industry’s pursuit of enhanced product quality, regulatory compliance, and operational efficiency has catalyzed the integration of Artificial Intelligence (AI) into Ongoing Process Verification (OPV) frameworks. This comprehensive review examines the synergistic application of Human-in-the-Loop (HITL) AI systems within OPV, contextualized by the evolving regulatory landscape, particularly the newly introduced Annex 22 of the European Union Good Manufacturing Practices (EU-GMP). The review delineates the sector’s strategic shift from traditional validation models toward dynamic, data-driven approaches that leverage AI for real-time monitoring, predictive analytics, and proactive process control. Central to this transformation is the HITL paradigm, which ensures that human expertise remains embedded in critical decision-making loops, thereby safeguarding patient safety, product quality, data integrity, and ethical responsibility. Annex 22 explicitly mandates deterministic behavior, traceability, and explainability for AI models used in GMP-critical applications, excluding adaptive and probabilistic systems from such contexts. The document also reinforces the necessity of multidisciplinary governance, rigorous validation protocols, and risk-based oversight throughout the AI lifecycle. This paper synthesizes current industry practices, regulatory expectations, and technological capabilities, offering a structured framework for compliant AI deployment in OPV. By aligning AI implementation with Annex 22 principles and existing GMP frameworks (e.g., Annex 11 and ICH Q9), the pharmaceutical sector can harness AI’s transformative potential while maintaining robust regulatory compliance. The review concludes with actionable recommendations for integrating HITL AI into OPV strategies, fostering a resilient, transparent, ethical, and future-ready manufacturing ecosystem.

11 July 2025 in Pharmaceuticals
Verified
Journal Article
Open access
PDF file
MRMiquel Romero
Miquel Romero
VSVirginia Sancho-Ochoa
Virginia Sancho-Ochoa
Khadija Rouaz El HajouiKhadija Rouaz El Hajoui
Khadija Rouaz El Hajoui
Pilar Pérez-LozanoPilar Pérez-Lozano
Pilar Pérez-Lozano
MSMarc Suñé-Pou
Marc Suñé-Pou
Encarna Garcia-MontoyaEncarna Garcia-Montoya
Encarna Garcia-Montoya
This comprehensive review of the synergistic use of Quality by Design (QbD) and the Pi–Buckingham theorem explores an innovative approach to enhancing product development and process optimization within the pharmaceutical industry. QbD is a systematic, proactive methodology that integrates quality considerations throughout the product lifecycle to ensure that pharmaceutical products meet regulatory standards for safety and efficacy from the outset of development. The Pi–Buckingham theorem serves as a foundational principle in dimensional analysis, facilitating the simplification of complex models by transforming physical variables into dimensionless parameters. This synergy enables researchers to better understand and control the factors affecting critical quality attributes (CQAs), thereby improving manufacturing outcomes and minimizing variability.