The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Quality by design in pharmaceutical manufacturing: A systematic review of current status, challenges and future perspectives
Abstract
Quality by Design (QbD) was originated in the broad domain of Quality Management and was recently adapted and formalized in specific terms for assisting pharmaceutical companies efforts towards market and operational excellence. However, despite some impressive success stories, the pharmaceutical industry have not yet fully embraced QbD, particularly in routine commercial manufacturing [1,2]. In this review, we aim to analyse the current state of implementation of QbD methodologies and tools in the pharmaceutical industry, extracting patterns and trends and identifying gaps and opportunities that may be considered to improve QbD adoption. For this purpose, a critical analysis of 60 research papers was performed, whose contents were classified, compared and summarized at different abstraction levels. Our analysis reveals the following tools as the frequently adopted for conducting each activity: Risk Assessment (RA) - Ishikawa Diagram, Failure Mode and Effects Analysis (FMEA) and Risk Estimation Matrix (REM); Screening Design of Experiments (DoE) - 2-level Full and Fractional Factorial Designs; Optimisation DoE - Central Composite Design (CCD). Emerging trends include the growing interest in quantifying and managing the impact of raw materials' attributes variability on process and product, as well as the development of Retrospective QbD approaches (rQbD) in complement to standard QbD.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Draper, N. R., & Smith, H. (1998) · Wiley Series in Probability and Statistics · doi:10.1002/9781118625590 · Cited by 5,024
The design of optimum multifactorial experiments
PLACKETT, R. L., & BURMAN, J. P. (1946) · Biometrika · doi:10.1093/biomet/33.4.305 · Cited by 3,906
Design and Analysis of Experiments
Dean, A., Voss, D., & Draguljić, D. (2017) · Springer Texts in Statistics · doi:10.1007/978-3-319-52250-0 · Cited by 2,891
Understanding pharmaceutical quality by design
Yu, L. X., Amidon, G., Khan, M. A., Hoag, S. W., Polli, J., Raju, G. K., & Woodcock, J. (2014) · The AAPS Journal · doi:10.1208/s12248-014-9598-3 · Cited by 1,475
Pharmaceutical Quality by Design: Product and Process Development, Understanding, and Control
Yu, L. X. (2008) · Pharmaceutical Research · doi:10.1007/s11095-007-9511-1 · Cited by 1,191
Center for Drug Evaluation and Research
National Cancer Institute (2020) · Definitions · doi:10.32388/doq9wu · Cited by 674
Juran on Quality by Design: The New Steps for Planning Quality into Goods and Services
Juran, J. M. (1992) · Cited by 608
A Class of Three-Level Designs for Definitive Screening in the Presence of Second-Order Effects
Jones, B., & Nachtsheim, C. J. (2011) · Journal of Quality Technology · doi:10.1080/00224065.2011.11917841 · Cited by 483
The Future of Pharmaceutical Manufacturing Sciences
Rantanen, J., & Khinast, J. (2015) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.24594 · Cited by 442
Quality by Design: Concepts for ANDAs
Lionberger, R. A., Lee, S. L., Lee, L., Raw, A., & Yu, L. X. (2008) · The AAPS Journal · doi:10.1208/s12248-008-9026-7 · Cited by 391
Cited by
Optimization of formulations using robotic experiments driven by machine learning DoE
Cao, L., Russo, D., Felton, K., Salley, D., Sharma, A., Keenan, G., Mauer, W., Gao, H., Cronin, L., & Lapkin, A. A. (2021) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2020.100295 · Cited by 75
Bioprocessing 4.0 in Biomanufacturing: Paving the Way for Sustainable Bioeconomy
Pandey, K., Pandey, M., Kumar, V., Aggarwal, U., & Singhal, B. (2024) · Systems Microbiology and Biomanufacturing · doi:10.1007/s43393-023-00206-y · Cited by 58
Narukulla, S., Bogadi, S., Tallapaneni, V., Sanapalli, B. K. R., Sanju, S., Khan, A. A., Malik, A., Barai, H. R., Mondal, T. K., Karri, V. V. S. R., et al. (2024) · Microchemical Journal · doi:10.1016/j.microc.2024.111875 · Cited by 52
Metadata
- Authors
- Grangeia, H. B., Silva, C., Simões, S. P., & Reis, M. S.
- Venue
- European Journal of Pharmaceutics and Biopharmaceutics
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 147
- Pages
- 19-37
- ISSN
- 0939-6411 (ISSN-L)
- OpenAlex
- W2995891886
- Cited by
- 257
- References
- 44
- FWCI
- 4.51
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quality by design in pharmaceutical manufacturing: A systematic review of current status, challenges and future perspectives. https://app.cochat.ai/papers/10.1016/j.ejpb.2019.12.007
- The paper
- Grangeia, H. B., Silva, C., Simões, S. P., & Reis, M. S. (2020). Quality by design in pharmaceutical manufacturing: A systematic review of current status, challenges and future perspectives. European Journal of Pharmaceutics and Biopharmaceutics. https://doi.org/10.1016/j.ejpb.2019.12.007
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.