Da abordagem reativa à preditiva: um framework integrado de modelagem preditiva microbiológica para suporte à estratégia de controle de contaminação em produtos estéreis
Palavras-chave:
Controle preditivo da biocarga, Produtos estéreis, Estratégia de controle de contaminação, Gerenciamento de riscos à qualidade, Indústria farmacêutica
Resumo
A revisão do Anexo 1 referente às Boas Práticas de Fabricação de medicamentos estéreis da União Europeia exige justificativa científica quantitativa para limites de biocarga e hold times, enquanto a modelagem preditiva microbiológica (MPM), madura em alimentos, permanece fragmentada no setor farmacêutico. O objetivo do trabalho foi propor um framework integrado de MPM baseada em risco para suporte à Estratégia de Controle de Contaminação (CCS) em produtos estéreis. O estudo combinou revisão integrativa da literatura, análise documental do corpus regulatório e síntese conceitual abdutiva no paradigma Design Science Research. O framework resultante organiza-se em três eixos e cinco blocos, articulando uma árvore de decisão para seleção de técnicas de MPM e uma técnica semiquantitativa ponderada para avaliação da aderência à CCS, com interfaces explícitas e retroalimentação. Os resultados operacionalizam o deslocamento da abordagem reativa para a preditiva e fundamentam as decisões para o CCS em fabricação estéril.Referências
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BARANYI, J.; ROBERTS, T. A. A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology, v. 23, n. 3-4, p. 277-294, 1994. DOI: 10.1016/0168-1605(94)90157-0.
BECHTOLD-PETERS, K.; et al. Risk-based approach to setting sterile filtration microbial bioburden limits - Focus on biotech-derived products. European Journal of Pharmaceutics and Biopharmaceutics, v. 198, p. 114151, 2024. DOI: 10.1016/j.ejpb.2023.11.016.
BOTELHO, L. L. R.; CUNHA, C. C. A.; MACEDO, M. O método da revisão integrativa nos estudos organizacionais. Gestão e Sociedade, v. 5, n. 11, p. 121-136, 2011. DOI: 10.21171/ges.v5i11.1220.
BRASIL. Agência Nacional de Vigilância Sanitária (ANVISA). Resolução da Diretoria Colegiada - RDC nº 658, de 30 de março de 2022. Dispõe sobre as diretrizes gerais de boas práticas de fabricação de medicamentos. Diário Oficial da União: Seção 1, Brasília, DF, 31 mar. 2022.
CLONTZ, L. Microbial limit and bioburden tests: validation approaches and global requirements. 2. ed. Boca Raton: CRC Press, 2009. ISBN 978-1-4200-5348-7.
DAHIYA, S.; KHAR, R. K.; CHHIKARA, A. Opportunities, challenges and benefits of using HACCP as a quality risk management tool in the pharmaceutical industry. The Quality Assurance Journal, v. 12, n. 2, p. 95-104, 2009. DOI: 10.1002/qaj.446.
DAO, H.; et al. Microbial stability of pharmaceutical and cosmetic products. AAPS PharmSciTech, v. 19, p. 60-78, 2018. DOI: 10.1208/s12249-017-0875-1.
DEN BESTEN, H. M. W.; et al. Next generation of microbiological risk assessment: potential of omics data for exposure assessment. International Journal of Food Microbiology, v. 287, p. 18-27, 2018. DOI: 10.1016/j.ijfoodmicro.2017.10.006.
DRESCH, A.; LACERDA, D. P.; ANTUNES JÚNIOR, J. A. V. Design Science Research: método de pesquisa para avanço da ciência e tecnologia. 1. ed. Porto Alegre: Bookman, 2015. ISBN 978-85-8260-298-0.
ESLAMI, M.; JUNGBAUER, A. Control strategy for biopharmaceutical production by model predictive control. Biotechnology Journal, Weinheim, v. 40, n. 2, p. e3426, 2024. DOI: 10.1002/btpr.3426.
EUROPEAN COMMISSION. EudraLex. Volume 4 - EU Guidelines for Good Manufacturing Practice for Medicinal Products for Human and Veterinary Use. Annex 1: Manufacture of Sterile Medicinal Products. Brussels: European Commission, 2022. Disponível em: https://health.ec.europa.eu/system/files/2022-08/20220825_gmp-an1_en_0.pdf. Acesso em: 19 out. 2023.
FILTER, M.; et al. Towards efficient use of data, models and tools in food microbiology. Current Opinion in Food Science, v. 46, p. 100834, 2022. DOI: 10.1016/j.cofs.2022.100834.
FOOD AND DRUG ADMINISTRATION (FDA). Guidance for Industry: Sterile Drug Products Produced by Aseptic Processing - Current Good Manufacturing Practice. Rockville: FDA, 2004. Disponível em: https://www.fda.gov/media/71026/download. Acesso em: 21 ago. 2024.
FUNDAÇÃO OSWALDO CRUZ (FIOCRUZ). Guia de gestão de riscos da Fiocruz. Rio de Janeiro: Fiocruz, 2019. Disponível em: https://fiocruz.br/documento/2019/03/guia-de-gestao-de-riscos-da-fiocruz. Acesso em: 26 jul. 2023.
GARRE, A.; ZWIETERING, M. H.; DEN BESTEN, H. M. W. Multilevel modelling as a tool to include variability and uncertainty in quantitative microbiology and risk assessment. Thermal inactivation of Listeria monocytogenes as proof of concept. Food Research International, v. 137, p. 109374, 2020. DOI: 10.1016/j.foodres.2020.109374.
GELMAN, A.; et al. Bayesian Data Analysis. 3. ed. Boca Raton: CRC Press, 2013. 675 p. ISBN 978-1-4398-4095-5.
HAMILTON, K. A.; et al. Research gaps and priorities for quantitative microbial risk assessment (QMRA). Risk Analysis, v. 44, p. 2521-2536, 2024. DOI: 10.1111/risa.14318.
HENTZ, N. G. Pharmaceutical bioburden testing. In: FLICKINGER, M. C. (ed.). Encyclopedia of industrial biotechnology. Hoboken: Wiley, 2013. p. 757-774. DOI: 10.1002/9780470054581.eib655.
HEVNER, A. R.; et al. Design science in information systems research. MIS Quarterly, v. 28, n. 1, p. 75-105, 2004. DOI: 10.2307/25148625.
HIURA, S.; et al. Bayesian generalized linear model for simulating bacterial inactivation/growth considering variability and uncertainty. Frontiers in Microbiology, v. 12, p. 674364, 2021. DOI: 10.3389/fmicb.2021.674364.
INTERNATIONAL COUNCIL FOR HARMONISATION OF TECHNICAL REQUIREMENTS FOR PHARMACEUTICALS FOR HUMAN USE (ICH). ICH Q8(R2): Pharmaceutical development. Geneva: ICH, 2009. Disponível em: https://database.ich.org/sites/default/files/Q8%28R2%29%20Guideline.pdf. Acesso em: 12 maio 2023.
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INTERNATIONAL COUNCIL FOR HARMONISATION OF TECHNICAL REQUIREMENTS FOR PHARMACEUTICALS FOR HUMAN USE (ICH). ICH Q9(R1): Quality risk management. Geneva: ICH, 2023. Disponível em: https://database.ich.org/sites/default/files/ICH_Q9%28R1%29_Guideline_Step4_2025_0115_0.pdf. Acesso em: 14 maio 2023.
INTERNATIONAL ORGANIZATION FOR STANDARDIZATION (ISO). ISO 31010:2019: Risk management - Risk assessment techniques. Geneva: ISO, 2019.
KARAMCHETI, S. T.; et al. Hierarchical Bayesian linear mixed model to estimate variability in the thermal inactivation parameters for Listeria species. Food Microbiology, v. 128, p. 104731, 2025. DOI: 10.1016/j.fm.2025.104731.
KOLLURI, S.; et al. Machine learning and artificial intelligence in pharmaceutical research and development: A review. AAPS Journal, v. 24, n. 1, p. 19, 2022. DOI: 10.1208/s12248-021-00644-3.
LINSTONE, H. A.; TUROFF, M. The Delphi Method: techniques and applications. Newark: New Jersey Institute of Technology, 2002. 618 p.
MARSIT, N. M.; SAADAWI, S.; ALENNABI, K. Challenges of growth-based microbiological methods in sterility assurance of pharmaceutical product manufacturing. Discover Pharmaceutical Sciences, v. 1, p. 13, 2025. DOI: 10.1007/s44395-025-00020-6.
MATTOSO, J. M. V.; et al. Comparison of Statistical Process Control Models for Monitoring the Biological Burden of a Buffer Solution Used as Input to Produce an Attenuated Viral Vaccine. Processes, v. 13, n. 9, p. 2917, 2025. DOI: 10.3390/pr13092917.
McMEEKIN, T. A.; ROSS, T. Predictive microbiology: providing a knowledge-based framework for change management. International Journal of Food Microbiology, v. 78, n. 1-2, p. 133-153, 2002. DOI: 10.1016/S0168-1605(02)00231-3.
MEMBRÉ, J. M.; BOUÉ, G. Quantitative microbiological risk assessment in food industry: Theory and practical application. Food Research International, v. 106, p. 1-12, 2018. DOI: 10.1016/j.foodres.2017.11.025.
MENDES, K. D. S.; SILVEIRA, R. C. C. P.; GALVÃO, C. M. Revisão integrativa: método de pesquisa para a incorporação de evidências na saúde e na enfermagem. Texto & Contexto - Enfermagem, Florianópolis, v. 17, n. 4, p. 758-764, 2008. DOI: 10.1590/S0104-07072008000400018.
MESSENS, W.; et al. Use of risk assessment and predictive microbiology in regulatory science related to the scientific opinions of the EFSA BIOHAZ Panel. International Journal of Food Microbiology, v. 403, 110302, 2023. DOI: 10.1016/j.ijfoodmicro.2023.110302.
MILLER, M. J. Microbiology for the pharmaceutical industry. 2. ed. Bethesda: PDA/DHI, 2019. 2 v. ISBN 978-1933722894.
NAUTA, M. J. Microbiological Risk Assessment Models for Partitioning and Mixing During Food Handling. International Journal of Food Microbiology, v. 100, n. 1-3, p. 311-322, 2005. DOI: 10.1016/j.ijfoodmicro.2004.10.027.
PAGE, M. J.; et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, v. 372, n. 71, p. 372, 2021. DOI: 10.1136/bmj.n71.
PASHANG, R.; GILBRIDE, K. A.; WENK, J. Microbial dynamics and quality monitoring in biopharmaceutical production. ChemBioEng Reviews, v. 11, n. 6, p. e202400022, 2024. DOI: 10.1002/cben.202400022.
PÉREZ-RODRÍGUEZ, F.; VALERO, A. Predictive Microbiology in Foods. New York: Springer, 2013. 238 p. ISBN 978-1-4614-5519-6.
PHARMACEUTICAL INSPECTION CO-OPERATION SCHEME (PIC/S). PE 009-17: Guide to Good Manufacturing Practice for Medicinal Products, Annex 1: Manufacture of Sterile Medicinal Products. Geneva: PIC/S, 2022.
POSSAS, A.; VALERO, A.; PÉREZ-RODRÍGUEZ, F. New software solutions for microbiological food safety assessment and management. Current Opinion in Food Science, v. 44, p. 100814, 2022. DOI: 10.1016/j.cofs.2022.100814.
ROSS, S. M. Introduction to probability models. 11. ed. Amsterdam: Academic Press, 2014. 800 p. ISBN 978-0-12-407948-9.
SAATY, T. L. Decision making with the analytic hierarchy process. International Journal of Services Sciences, Geneva, v. 1, n. 1, p. 83-98, 2008. DOI: 10.1504/IJSSCI.2008.017590.
SANDLE, T. Pharmaceutical Microbiology: Essentials for Quality Assurance and Quality Control. Amsterdam: Elsevier, Woodhead Publishing, 2015. 316 p. ISBN 978-0-08-100022-9.
SANDLE, T.; DI MATTIA, M.; LEAVY, C. Use of Hazard Analysis Critical Control Point (HACCP) methodology for biocontamination control: assessing microbial risks and determining environmental monitoring locations. European Journal of Parenteral and Pharmaceutical Sciences, v. 24, n. 3, p. 18-45, 2019. DOI: 10.37521/ejpps.24302.
SNYDER, H. Literature review as a research methodology: an overview and guidelines. Journal of Business Research, v. 104, p. 333-339, 2019. DOI: 10.1016/j.jbusres.2019.07.039.
TIAN, G.; et al. Quality risk assessment and mitigation of pharmaceutical continuous manufacturing using flowsheet modeling approach. Computers & Chemical Engineering, v. 129, p. 106508, 2019. DOI: 10.1016/j.compchemeng.2019.06.033.
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Publicado
2026-08-22
Como Citar
COSTA, C. C. DA; BRANDÃO, M. L. L.; LEMES, E. M. B. Da abordagem reativa à preditiva: um framework integrado de modelagem preditiva microbiológica para suporte à estratégia de controle de contaminação em produtos estéreis. Revista Científica do UBM, v. 28, n. 55, p. 315-339, 22 ago. 2026.
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