Computational biology, biomedical intelligence, environmental science and applied AI for complex living systems.
The program is presented as a scientific notebook: architecture, assumptions, applications, validation logic and visual evidence for researchers, innovators, students, professors, commercial partners and philanthropic organizations.
MetabolAite
AI
curing
diabetes
PROBABILISTIC GENOMICS
MASSIVE AI-GENERATED MUTATIONS THROUGH PREDICTIVE MODELS
GENERATION OF VIRTUAL MOLECULES AND MicroRNA FOR FIGHTING VIRUSES, CANCERS,
ENHANCING HUMAN GENOMES,
DISCOVERING AND VALIDATING DRUGS
M.VIVIANI, M.BISOGNI, N.L.BRAGAZZI
,
14,
GENERATION OF VIRTUAL MOLECULES AND MicroRNA FOR FIGHTING VIRUSES, AMR, CANCERS,
by Transhumangene
Eggenhöffner
Roberto
, Professor, Physicist at Department of Integrated Surgical and Diagnostic Sciences (DISC) University of Genoa, Head of the Research Group in Medical Biophysics & Lab
, CEO
, Research Associate Professor at University at Buffalo, genomics, and ethics
, researcher associated with the International Space Consortium and NASA specialized in AI human Interaction developing international patents
Scientific collaboration model
Research programs are organized around computational hypotheses, validation discipline, experimental caution and ethical review.
Diabetes represents a serious and challenging public health concern, the magnitude of which has more than
doubled
within the last decades, due to
demographic changes (population growth and aging)
doption of western, unhealthy lifestyles and habits, including low-quality food and lack of physical activity, has resulted in a pandemic of obese individuals.
WHY NOW?
This increase results in an unprecedented surge
of diabetes cases that
is absorbing a lot of
economic and financial
resources
imposing
a dramatically relevant societal burden.
If not counteracted, this surge could critically stress health systems. Moreover, not all diabetes phenotypes are the same and should receive a personalized treatment.
THE PROMISED LAND
Elucidating the mechanisms underlying diabetes and finding optimal treatment options can lead to better, personalized control of the disease, leading to cost-effective therapies and considerably saving resources. Moreover, individualized, tailored management instead of a one-size-fits-it-all approach can increase patient compliance and improve outcomes.
WHICH ARE THE OBSTACLES
Of course, considerable achievements have been pursued in diabetology, but if we consider specific settings, genetic mechanisms have not been fully elucidated yet. This is especially true in contexts when relationships among siblings happen more often than in other realities.
Some obstacles to a diabetes-free world population include
Most people think that the currently available drugs can be taken a lifetime. It makes little, if no sense at all, to try to “eradicate” diabetes by genetic techniques, such as immunization or another kind of AI-generated drugs. In other words, they prefer to live together with the disease and cope with it, rather than to defeat it forever
People also think that these new techniques may be costly and they could not afford them
People believe these drugs are enough to manage diabetes, being genetic and individual aspects negligible
WHAT WE HAVE DONE SO FAR
We have already successfully crystallized an insulin sequence, with an excellent resolution, one of the highest obtained results. This enables us to shed more light on the mechanisms of insulin action at a cellular and molecular level, studying its genetic variants and the primary pathogenic mechanisms leading to diabetes.
Business Plan
The Numbers
Financial
Request
& Costs for
Seed
Shareholding offered (Seed)
Total
10-20% Shares
2mln USD
Turnover (Worse Case scenario)
USD 3,5mln by the end of the 2nd
year
Company Hardware
SuperStations
(2xA100
nVidia
each station) + Servers Farm (memories) + Laboratory
allocation
General
View
Software Development
500,000 USD
Externalities
200,000 USD
Supercomputer + Server Farms 4PetaBytes
700,000 USD
Lab
Facilities & Utilities
400,000 USD
2,000,000 USD
Main Investments
HQ Structure
100,000 USD
SupComp
. + Acc.
1,000,000 USD
Revenue Projections
Run of Drug Studies for General Groups
Each 4,500,000 USD
Run of Drug Studies for Personalized Cures
Each 1,500,000 – 6,000,000 USD
Other Related Computing Services
Yearly 500,000 USD
Each Superstation is able to process between 4 to 5 target groups with similar DNA
Breakeven Point & Business Model
The B.E.P. will be reached between 12 – 15 months
Our Markets: Big & Small Pharma, Universities & National Health institutions and Hospitals & Clinics
Business Model
most
of the products are in the
form
of a
hybrid
Pay
per service (
DownPayment
Results
prototype
selling)
We
want
to
write
the words «the end» to
disease
by AI
generated
drugs
gene therapies and
vaccines
