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A Monte Carlo framework for managing biological variability in manufacture of autologous cell therapy from mesenchymal stromal cells therapies

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journal contribution
posted on 25.03.2020 by Andrew Picken, Jon Harriman, Andreea Iftimia-Mander, Lyndsey Johnson, Amy Prosser, Robin Quirk, Rob Thomas
Manufacturing processes for autologous cell therapy need to reproducibly generate in specification (quality and quantity) clinical product. However, patient variability prevents the level of control of cell input material that could be achieved in a cell line or allogeneic-based process. We have applied literature data on bone marrow–derived mesenchymal stromal cells variability to estimate probability distributions for stem cell yields given underlying truncated normal distributions in total nucleated cell concentration, stem cell percentage and plausible aspirate volumes. Monte Carlo simulation identified potential variability in harvested stem cell number in excess of an order of magnitude. The source material variability was used to identify the proportion of donor manufacturing runs that would achieve a target yield specification of 2E7 cells in a fixed time window with given proliferative rates and different aspirate volumes. A rapid, screening, development approach was undertaken to assess culture materials and process parameters (T-flask surface, medium, feed schedule) to specify a protocol with identified proliferative rate and a consequent model-based target aspirate volume. Finally, four engineering runs of the candidate process were conducted and a range of relevant quality parameters measured including expression of markers CD105, CD73, CD44, CD45, CD34, CD11b, CD19, HLA-DR, CD146 (melanoma cell adhesion molecule), CD106 (vascular cell adhesion molecule) and SSEA-4, specific metabolic activity and vascular endothelial growth factor secretion, and osteogenic differentiation potential. Our approach of using estimated distributions from publicly available information provides a route for data-poor earl- stage developers to plan manufacture with defined risk based on rational assumptions; furthermore, the models produced by such assumptions can be used to evaluate candidate processes, and can be incrementally improved with accumulating distribution understanding or subdivision by new process variables.

Funding

Engineering Biological Science - Processes and Systems for Haematopoietic Stem Cell Based Therapy Manufacture : EP/K00705X/1

Developing efficient models to define economic and low risk high value manufacture of cell based products : EP/R031649/1

LocateBio, as part of an award from InnovateUK

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Cytotherapy

Volume

22

Issue

4

Pages

227 - 238

Publisher

Elsevier BV

Version

VoR (Version of Record)

Rights holder

© International Society for Cell and Gene Therapy

Publisher statement

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Acceptance date

11/01/2020

Publication date

2020-02-27

Copyright date

2020

ISSN

1465-3249

eISSN

1477-2566

Language

en

Depositor

Prof Rob Thomas. Deposit date: 24 March 2020

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