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Record W4402802170 · doi:10.18609/cgti.2024.107

iPSC-based therapy dilemmas explored: overcoming hurdles for future success

2024· article· en· W4402802170 on OpenAlexaboutno aff
Melissa Carpenter, Lise Munsie, Kim Raineri, Bruno Marques

Bibliographic record

VenueCell and Gene Therapy Insights · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsEngineering ethicsManagement scienceMedicineRisk analysis (engineering)Intensive care medicineEngineering

Abstract

fetched live from OpenAlex

As the number of iPSC-based therapies in clinical development is increasing, the industry is seeing significant advancement following decades of the industry’s iPSC development efforts. Despite these noteworthy strides, there are still many existing dilemmas to address for sustained progress and commercial viability. In this article, four esteemed industry experts delve into the critical aspects of reshaping the future landscape of iPSC-based therapies, exploring key areas such as material access and readiness, operational intricacies, technological innovations, and standardization.Melissa Carpenter has worked on the development of cell therapies using human adult and embryonic stem cells for the last 20 years, in academia and industry, in the US and Canada. She has been involved with human embryonic stem cell (hESC) research since the field was established. Her work involves discovery research and the translation of this research into therapeutics, including developing strategies for preclinical development and navigating the regulatory issues surrounding stem cell therapies. She has held leadership positions at three of the major stem cell companies: CytoTherapeutics, Inc (StemCells, Inc.), Geron, Corp., and Novocell, Inc (Viacyte, Inc). Currently, Carpenter is President of Carpenter Group Consulting and works with early stage companies, academic groups and investors to translate discovery based research into stem cell therapies. She is credited with numerous publications and patents in the stem cell field.Lise Munsie earned her PhD at McMaster University, Hamilton, ON, Canada, focusing on drug discovery in neurodegenerative diseases. Following this, she completed a post-doctoral research fellowship at the Centre for Applied Neurogenetics at the University of British Columbia, Vancouver, BC, Canada, where she focused on the genetic causes of Parkinson’s Disease. Lise joined CCRM, Toronto, ON, Canada, in 2015 and is currently the Vice President of the iPSC Technology Platform for CCRM, and its affiliate, OmniaBio Inc. Lise manages iPSC reprogramming, gene editing, cell banking, scale-up, and differentiation projects. Lise’s team critical focus is enabling these technologies to be manufactured to produce clinically relevant products.Kim Raineri is the Chief Technology Officer for Aspen Neuroscience, Inc., San Diego, CA, USA. He is responsible for the manufacturing, process and analytical development, technology development, and delivery device functions of a leading autologous iPSC derived cell therapy company targeting CNS diseases. Prior to this position he was the Chief Manufacturing and Technology Officer for AVROBIO, Inc., responsible for the CMC, process and analytical development, supply chain, and external manufacturing functions of a leading gene therapy company targeting Lysosomal Storage Disorders through ex vivo lentiviral gene therapy. Prior to this role, he held various positions of responsibility in cell and gene therapy CDMO as Vice President of Operations for Nikon CeLL innovation, Business Director for Lonza Bioscience Singapore Pte Ltd., and Director of Operations for Lonza Walkersville. Raineri has a MBA from Kennesaw State University, Kennesaw, GA, USA, and BSc from the University of Miami, Coral Gables, FL, USA.Bruno Marques is Vice President of Process and Product Development at Century Therapeutics, Philadelphia, PA, USA, with a focus on allogeneic, iPSC-derived therapies for cancer and autoimmune diseases. He is a chemical engineer by training, with a PhD from Carnegie Mellon University, Pittsburgh, PA, USA, and a BS from the Illinois Institute of Technology, Chicago, IL, USA.

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 categoriesnone
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 score0.469
Threshold uncertainty score0.689

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)0.0000.000

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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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