Problem to be Solved by h.o.p.e. 

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What are the best pro-growth ideas for each cell type in the brain? This information must be known to increase our odds for success. 

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There are more individual proteins (over 30,000) in a single cell than most people have days in their lives, making it impossible for a single person to “know” all of the complexities of a single cell. There are tens of millions of published papers on pro-growth strategies, tens of millions of unique chemical compounds from which to choose a therapeutic regimen, and a trillion-cell CNS supercomputer made up of a thousand different cell types to regrow. This complexity is beyond the understanding of a single person, and not knowing all of the relevant pro-growth strategies makes designing a successful comprehensive treatment strategy impossible. 

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The old adage in medicine is immediately relevant: There are two types of treatments patients never receive - those the doctor does not know or those the doctor forgot. There is a third type of treatment a patient does not receive - a treatment that does not yet exist. 

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A database of all pro-growth strategies needs to exist to identify which treatment options are the best and to identify where treatments do not yet exist. This will allow us to design our regrowth strategies with a realistic understanding of the current strengths and weaknesses of existing technologies. 

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Technology to be Orchestrated 

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The field of neuroscience has produced an enormous amount of information over the last century. This has allowed an understanding of the complexities and nuances of neural repair never before conceivable. Just as importantly, rapid advances across equally vital fields have accelerated, including machine learning, brain atlases, informatics, engineering, cell biology, computer modeling, pharmacology, human physiology, etc. The amount of information generated in the last 50 years is remarkable 
and ready to be integrated into a comprehensive strategy. 

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Machine Learning

Machine learning allows curation and ingestion of the staggering amount of information now available. The computer is able to “learn” based on parameters it is instructed to do, such as determining which words appear most frequently and in what relationship to each other. For example, including search terms such as “brain,” “growth factors,” “journal,” and “clinical trial” would allow the computer to produce a knowledge graph of which particular growth factors were studied in a clinical trial related to the brain. This narrowing of the field would allow the h.o.p.e. Orchestra experts on growth factors to review this knowledge graph and add their expertise to decide what information is of the highest quality with respect to each cell type. This additional curation of the knowledge base would allow the computer to further narrow the literature based on even more specific search parameters, repeated over and over again. 

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Informatics

The field of informatics has evolved to allow  the processing of complex information in ever more simple schematics. This is incredibly important in order to narrow the complexity of the billions of data points into digestible parts for understanding and manipulation. Search parameters have continually improved, allowing for the user-friendly experience of these databases to thrive.

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Goal of h.o.p.e. 

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We will use artificial intelligence to develop the first knowledge base of pro-growth strategies. The integration of all brain atlases, drug library databases, all cellular pro-growth strategies, drug delivery options, toxicology, and the scientific literature base will ensure our scientific orchestra is always absolutely current. A comprehensive cell biology team, encompassing every cell type in the brain, will curate this knowledge base alongside machine learning experts. Bioinformatic experts will organize this database relative to the patient’s specific injury and translational disciplines (cell type, drugs, clinical delivery, etc.). This knowledge base section will assist the comprehensive cell biology section to increase the sophistication of the regrowth simulation of the individual’s injury, the design of the regrowth regimen, and the testing of this regimen in the lab clinical trial. We must ensure every good idea is known and considered, as any gap in knowledge decreases our chance for success. 

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This knowledge base will be built as answers are sought to each question relevant to the patient. Therefore, this knowledge base will be divided into the specific focuses of cell types to make progress realistic.

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This database will by curated by

1. The individual’s neurological region of injury;

2. Cell type: neurons, astrocytes, microglia, oligodendrocytes, cerebrospinal system, ependymal, vasculature, lymphatic, and pericytes;

3. Technology arena: brain atlases, PubMed, image analysis techniques, human connectome project, stereology, drug libraries, Roche biochemical cell pathways, Ventner Institute mathematical modeling, cell migration kinetics, drug combo ranker, Food and Drug Administration database, biotechnology companies’ annual reports, pharmaceutical companies’ annual reports, world patent database, drug toxicology database, drug–drug interaction database, drug delivery literature, drug clearance database, bioreactors, tissue engineering, human brain physiology, electrophysiology, hydrodynamics, mechanotransduction, clinical delivery, material science, cell culture reagents, cell culture imaging, and 3D printing. 

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The machine learning team and comprehensive cell biology team will curate the knowledge base to select data and technology with the largest consensus regarding quality in the relevant areas necessary for pro-growth strategies for the patient’s unique anatomical injury. The informatics team will display the resultant knowledge graph in a searchable database easily queried by the key areas. We will maintain absolute rigor, so each promising therapy is considered and the context of each drug is known. We will make continual scheduled updates to ensure all literature and ideas are current. Given literature is delayed from idea creation to publication, continual check-in with the field is a must, and will be provided by each scientist. We will integrate vertical knowledge (e.g., information on a cell protein) for the first time with horizontal knowledge (e.g., information on functional nervous tissue) in a translational approach around an individual injury. This will be the first knowledge base in a useable format for each orchestra member to integrate essential vertical and horizontal decision points around an individual injury. 

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Impact of h.o.p.e. 

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The h.o.p.e. Orchestra will produce a pro-growth knowledge base that will be a resource for all future pro-growth steps, both for the h.o.p.e. Orchestra and the entire biomedical research community. Artificial intelligence will allow more literature and data to be absorbed than previously possible by any academic or industry lab, as no academic lab or company has ever invested the resources to ensure they have the knowledge of every promising treatment option, as their incentives are different than ours. 

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The field will be dramatically accelerated forward, as will our chance for success, because it will be the first knowledge base to be

1. Curated by each cell type by a comprehensive cell biology team; 

2. Focused on solving the problems of one patient’s unique anatomical injury at a time;

3. Focused on pro-growth solutions;

4. Pulled from all relevant databases;

5. More expansive than any individual scientist physician could individually obtain.