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CIP-1: Molecular Profiling and Computational Modelling for Novel Cryoprotectants

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Project Overview:

Funding amount: $50,000 Researchers: Dr. João Pedro de Magalhães (https://www.linkedin.com/in/joaopedrodemagalhaes/) & Dr. Roman Bauer (https://www.linkedin.com/in/roman-bauer-05176094/)

Cryopreservation is a vanguard discipline that refers to the preservation of cells, tissues or organs at cryogenic temperatures, especially at -130˚C or below, and is crucial in cryonics. For successful cryopreservation, cryoprotectants (also known as cryoprotective agents, or CPAs), which are chemicals used to protect biological systems from freezing damage, are usually required. For at least some organs, they are believed to be needed in concentrations high enough to prevent the formation of ice crystals during cooling allowing instead preservation in a glassy state. This glassy state form of preservation, known as vitrification, is a challenge to achieve. Organs need to be able to survive not only “cooling injury” (injury caused by cooling per se) , and osmotic damage but also the direct biochemical effects of perfusion with the extremely high concentrations of CPAs that are required for the organs to be successfully vitrified. Unfortunately, there is currently little detailed information available regarding the toxicological and biochemical effects of these chemical agents.

‍This study aims to discern mechanisms of cryopreservation-related injury, and specifically pertaining to CPAs, using gene expression profiling. Very few studies have profiled gene expression in the context of cryopreservation, and more data are needed to elucidate molecular mechanisms in more systems. With the data generated we will employ machine learning and computational models to predict new, safer combinations of cryoprotectants. We will use this approach to create a patentable computational model to improve cryoprotectants used for primary cell lines.

‍Simple Summary:

Generate a unique large dataset of cryoprotectant molecular profiling in vitro and use it together with machine learning and computational models to predict new, safer combinations of cryoprotectants, new potential cryoprotectants and toxicity neutralizers for the preservation of primary cell lines.

‍Highlights:

  • High impact for cryopreservation
  • Solid evidence supporting their approach
  • All required technology established in lab
  • Patent would have direct commercial potential
  • Pre-clinical applications (e.g. cell preservation for research)
  • Comparatively low funding required
  • No university overhead, private lab without TTO/third party approval required ‍

Risks:

  • Short term commercialization might not be easy
  • Technical risk

Outcome of the evaluation and recommendation:

‍A total of X evaluators independently scored the project proposal on different categories as either: (1) Outstanding, (2) Strong, (3) Satisfactory, (4) Weak, (5) Unacceptable, (N/A) Not enough information provided, or (N/A) Not my area of expertise. This is a summary of the results:

  • Novelty and Impact: (2) Outstanding (1/X evaluators)
  • Feasibility and Data: (1) Outstanding (1/X evaluators)
  • Relevance to cryopreservation: (2) Strong (1/X evaluators)
  • Science Team: (1) Outstanding (1/X evaluators)
  • Market Advantage: (3) Satisfactory (1/X evaluators)
  • IP-NFT Potential: (2) Strong (1/X evaluators) ‍ All the evaluators consider the project worth funding by the CryoDAO community.

Mechanism of Funding:

‍This proposal recommends CryoDAO commits funding via an IP-NFT. No TTO or similar third party approval is needed.

‍Team:

‍Lead: Prof Joao Pedro de Magalhaes, Oxford Cryotechnology Ltd. Computational Biology: Dr. Roman Bauer, Oxford Cryotechnology Ltd.

View more online: https://www.cryodao.org/project/molecular-profiling-and-computational-modelling-for-novel-cryoprotectants