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Record W2610080631 · doi:10.1016/j.ymthe.2017.04.010

Perspectives on Manufacturing of High-Quality Cell Therapies

2017· article· en· W2610080631 on OpenAlexaboutno aff
Isabelle Rivière, Krishnendu Roy

Bibliographic record

VenueMolecular Therapy · 2017
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)BusinessBiotechnologyBiology

Abstract

fetched live from OpenAlex

Cell therapies are taking center stage in medicine spanning cancer immunotherapy, stem cell engineering, and regenerative medicine. Recently, the first ex vivo hematopoietic stem cell (HSC) gene therapy for the treatment of adenosine deaminase deficiency-severe combined immunodeficiency (ADA-SCID) received marketing approval.1Ylä-Herttuala S. ADA-SCID gene therapy endorsed by European medicines agency for marketing authorization.Mol. Ther. 2016; 24: 1013-1014Abstract Full Text Full Text PDF PubMed Scopus (14) Google Scholar By now, the majority of the 150 plus patients who have received HSC gene therapy to treat monogenic diseases have demonstrated clinical benefits.2Wang X. Riviere I. Genetic engineering and manufacturing of hematopoietic stem cells.Mol. Ther. Methods Clin. Dev. 2017; 5: 96-105Abstract Full Text Full Text PDF PubMed Scopus (18) Google Scholar Promising clinical outcomes in phase I/II trials based on T cells engineered to express T cell chimeric antigen receptors (CARs)3Sadelain M. CAR therapy: the CD19 paradigm.J. Clin. Invest. 2015; 125: 3392-3400Crossref PubMed Scopus (171) Google Scholar against hematological malignancies have also spurred unprecedented interest from pharmaceutical and biotechnology companies. As a result, CD19-targeted CAR T cells may soon receive marketing approval.4Walker A. Johnson R. Commercialization of cellular immunotherapies for cancer.Biochem. Soc. Trans. 2016; 44: 329-332Crossref PubMed Scopus (20) Google Scholar As living drugs, cell therapies pose unique commercialization challenges in terms of manufacturing, standardization, and distribution.4Walker A. Johnson R. Commercialization of cellular immunotherapies for cancer.Biochem. Soc. Trans. 2016; 44: 329-332Crossref PubMed Scopus (20) Google Scholar, 5Wang X. Riviere I. Clinical manufacturing of CAR T cells: foundation of a promising therapy.Mol. Ther. Oncolytics. 2016; 3: 16015Abstract Full Text Full Text PDF PubMed Scopus (351) Google Scholar, 6Roh K.H. Nerem R.M. Roy K. Biomanufacturing of therapeutic cells: state of the art, current challenges, and future perspectives.Annu. Rev. Chem. Biomol. Eng. 2016; 7: 455-478Crossref PubMed Scopus (45) Google Scholar Automated, robust, and cost-effective production platforms compliant with current good manufacturing practices (cGMP) coupled with robust analytics, which ensure reproducible cell quality, are needed to broaden the availability and realize the commercialization potential of these complex, predominantly personalized, therapeutic modalities. HSC and CAR-T cell engineering processes commonly start from an autologous or donor apheresis. The inter-institution and inter-patient variability that are inherent to apheresis collection and composition, the paucity of well-defined and quantifiable critical quality attributes (CQAs), and the requirement for cGMP-grade culture media components and ancillary genetic modifiers, such as viral vectors and CRISPR/Cas9 components, add to the complexity of these therapeutic modalities.5Wang X. Riviere I. Clinical manufacturing of CAR T cells: foundation of a promising therapy.Mol. Ther. Oncolytics. 2016; 3: 16015Abstract Full Text Full Text PDF PubMed Scopus (351) Google Scholar, 6Roh K.H. Nerem R.M. Roy K. Biomanufacturing of therapeutic cells: state of the art, current challenges, and future perspectives.Annu. Rev. Chem. Biomol. Eng. 2016; 7: 455-478Crossref PubMed Scopus (45) Google Scholar, 7Eyquem J. Mansilla-Soto J. Giavridis T. van der Stegen S.J. Hamieh M. Cunanan K.M. Odak A. Gönen M. Sadelain M. Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection.Nature. 2017; 543: 113-117Crossref PubMed Scopus (963) Google Scholar To decrease the production scale and shorten the time in culture, cell subsets known to provide optimal therapeutic effects and limited toxicities may be selected to initiate manufacturing8Sommermeyer D. Hudecek M. Kosasih P.L. Gogishvili T. Maloney D.G. Turtle C.J. Riddell S.R. Chimeric antigen receptor-modified T cells derived from defined CD8+ and CD4+ subsets confer superior antitumor reactivity in vivo.Leukemia. 2016; 30: 492-500Crossref PubMed Scopus (502) Google Scholar, 9Wang X. Rivière I. Manufacture of tumor- and virus-specific T lymphocytes for adoptive cell therapies.Cancer Gene Ther. 2015; 22: 85-94Crossref PubMed Scopus (72) Google Scholar or may be selectively expanded/differentiated during manufacturing. Unfortunately, for most cell therapies, these biological attributes are not yet well characterized and are likely to depend upon not only the cell type and source, but also the specific disease condition and patient profile. To establish robust and reproducible manufacturing processes, it is advisable to follow quality-by-design (QbD) principles.10Lipsitz Y.Y. Bedford P. Davies A.H. Timmins N.E. Zandstra P.W. Achieving efficient manufacturing and quality assurance through synthetic cell therapy design.Cell Stem Cell. 2017; 20: 13-17Abstract Full Text Full Text PDF PubMed Scopus (28) Google Scholar Quantifiable molecular and cellular characteristics that ensure product safety, efficacy, and potency should enable and drive the manufacturing processes from starting material to final product. This approach is contingent first upon understanding how the specific cells function in vivo in the context of a particular disease and second upon inclusion of CQAs that underlie the therapeutic benefits independently of patient variables. The scarcity of functional CQAs and consequently of early indicators of quality or batch failures poses a high risk for industry. For example, there is a need for better understanding of cell biophysics and how the microenvironment affects cell function. Besides a few metabolites and culture conditions, such as pH or oxygen content, most manufacturing platforms do not support integrated analytical tools to measure cell properties related to potency, safety, and contamination. Process analytical technologies (PATs), including non-destructive, integrated, and image-based sensors, that can provide feedback on cell quality in real time need to be developed.11Klinker M.W. Marklein R.A. Lo Surdo J.L. Wei C.H. Bauer S.R. Morphological features of IFN-γ-stimulated mesenchymal stromal cells predict overall immunosuppressive capacity.Proc. Natl. Acad. Sci. USA. 2017; 114: E2598-E2607Crossref PubMed Scopus (107) Google Scholar Human-like safety and potency assays (e.g., tissue-on-chip or related organoid models) as well as induced pluripotent stem cell (iPSC)-derived disease models may help broaden the spectrum of available biological assays. The concept of critical process parameters (CPPs) to control cell quality, how they affect cell quality, and how to control them is important in order to achieve robust manufacturing processes. These are dependent upon identification of the CQAs through deep characterization and biological studies enabled by informatics, machine learning, and big data analytics. To mitigate costly cGMP operations, laborious manual procedures, and their inherent reproducibility issues, as well as to reduce risk of contamination, closed automated systems that integrate bioreactors and robotics are required. Beyond automation, the inherent variability of source cells, especially autologous cells, necessitates the inclusion of flexible built-in process automation that can be adjusted based on CQA measurements and on feedback from real-time analytics.5Wang X. Riviere I. Clinical manufacturing of CAR T cells: foundation of a promising therapy.Mol. Ther. Oncolytics. 2016; 3: 16015Abstract Full Text Full Text PDF PubMed Scopus (351) Google Scholar, 6Roh K.H. Nerem R.M. Roy K. Biomanufacturing of therapeutic cells: state of the art, current challenges, and future perspectives.Annu. Rev. Chem. Biomol. Eng. 2016; 7: 455-478Crossref PubMed Scopus (45) Google Scholar, 12Kaiser A.D. Assenmacher M. Schröder B. Meyer M. Orentas R. Bethke U. Dropulic B. Towards a commercial process for the manufacture of genetically modified T cells for therapy.Cancer Gene Ther. 2015; 22: 72-78Crossref PubMed Scopus (132) Google Scholar Novel cell separation technologies, such as acoustic waves, microfluidic separation platforms,13Urbansky A. Lenshof A. Dykes J. Laurell T. Scheding S. Separation of lymphocyte populations from peripheral blood progenitor cell products using affinity bead acoustophoresis.Blood. 2014; 124 (315–315)Google Scholar and phase-change hydrogel substrates,14Jesuraj N.J. Cole J.M. Bedoya F. Wells S.B. Qin G. Kevlahan S. et al.A novel phase-change hydrogel substrate for T cell activation promotes increased expansion of CD8+ cells expressing central memory and naive phenotype markers.Blood. 2016; 128 (3368–3368)Google Scholar may be integrated into these systems. Further enrichment of specific cell subsets may be promoted by cytokines or small molecules whose biological activities need to be defined against established standards.6Roh K.H. Nerem R.M. Roy K. Biomanufacturing of therapeutic cells: state of the art, current challenges, and future perspectives.Annu. Rev. Chem. Biomol. Eng. 2016; 7: 455-478Crossref PubMed Scopus (45) Google Scholar The biological activities of raw materials (e.g., cytokines and small molecules) can significantly alter the potency and safety profile of cell products. Very few reference and measurement standards are yet available across the field. Various groups are using different material sources, assays, equipment, and techniques of data analysis. In the absence of standards, this multiplicity of approaches confounds comparability and cross validation of data. Consensus best practices and measurement assurance guidelines must be developed along with eventual standards. Standardized analytical tools to assess relevant CQAs are direly needed. Reliance on cryopreservation requires that we better understand how freezing and thawing affect cell function and safety. It also limits wide distribution owing to constraints in storage and transportation.6Roh K.H. Nerem R.M. Roy K. Biomanufacturing of therapeutic cells: state of the art, current challenges, and future perspectives.Annu. Rev. Chem. Biomol. Eng. 2016; 7: 455-478Crossref PubMed Scopus (45) Google Scholar Future research should explore improved and alternative methods for live cell transportation that integrate measurements of product quality. The lack of a biomanufacturing workforce that is well trained in cGMP procedures and analytics and that could populate clinical and industrial manufacturing settings is seriously hampering the progress and translation of cell therapies. Significant investment in developing such a workforce—both at the level of 2-year community or technical colleges or standard 4-year universities—is critically needed. Robust investment in basic science and human-like disease models are crucial to elucidate how complex cell-based products function. Understanding how donor/patient variability effects source cell properties and consequently manufacturing and how recipient pathophysiology affects treatment outcome is also critical. Ensuing CQAs derived from such analyses will guide the design of combined manufacturing and analytic platforms. National Institute of Standards and Technology (NIST), the Food and Drug Administration (FDA), the Alliance for Regenerative Medicine (https://alliancerm.org/press/alliance-regenerative-medicine-launches-standards-coordinating-body-advance-development-and) and other stakeholders are coordinating task forces to develop standards and plan on publishing white papers that will help develop guidelines (https://www.nist.gov/news-events/events/2017/04/nist-fda-cell-counting-workshop-sharing-practices-cell-counting). Recently, a Standards Coordinating Body was established with public-private partnerships to facilitate standards development in this space (http://www.regenmedscb.org/). In 2016, a US national roadmap on cell therapy manufacturing was established upon a unique collaboration between companies, academic institutions, and government agencies to accelerate the path to commercialization (http://cellmanufacturingusa.org/road-map). The rise of cell therapies has spurred the development of consortia, such as CCRM (http://ccrm.ca), NIIMBL (http://www.niimbl.us), MC3M (http://www.cellmanufacturing.gatech.edu), Catapult (https://ct.catapult.org.uk), and ARMI (https://www.defense.gov/News/News-Releases/News-Release-View/Article/1035759/dod-announces-award-of-new-advanced-tissue-biofabrication-manufacturing-innovat), and the recent involvement of biotech and pharmaceutical companies. In addition, the US National Academies have established a forum on Regenerative Medicine (http://nationalacademies.org/hmd/Activities/Research/RegenerativeMedicine.aspx) in which manufacturing is a major focus. These major efforts will not only enable the production of optimal cellular components with increased safety, efficacy, robustness, and reproducibility profiles, but will also decrease cost and increase access to these potent cell therapies. Genetic Engineering and Manufacturing of Hematopoietic Stem CellsWang et al.Molecular Therapy - Methods & Clinical DevelopmentApril 21, 2017In BriefThe marketing approval of genetically engineered hematopoietic stem cells (HSCs) as the first-line therapy for the treatment of severe combined immunodeficiency due to adenosine deaminase deficiency (ADA-SCID) is a tribute to the substantial progress that has been made regarding HSC engineering in the past decade. Reproducible manufacturing of high-quality, clinical-grade, genetically engineered HSCs is the foundation for broadening the application of this technology. Herein, the current state-of-the-art manufacturing platforms to genetically engineer HSCs as well as the challenges pertaining to production standardization and product characterization are addressed in the context of primary immunodeficiency diseases (PIDs) and other monogenic disorders. Full-Text PDF Open Access

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.356
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations33
Published2017
Admission routes1
Has abstractyes

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