Research_Description-BMSystems or Bio-Modeling Systems: a leading Systems Biology / Integrative Biology company that delivers

Description

Predictive Integrative Biology / Systems Biology: The CADI™ models

The CADI™ (Computer Assisted Deductive Integration) proprietary modeling approach is the most efficient synergic process linking organic non-linear integration (Brain intelligence ) and in-silico data processing power (collecting, structuring and manipulating data) to build validated biological interaction maps. CADI ™ is based on the negative selection process invented by Dr. François Iris, founder, Chairman and CSO of the company.
The CADI™ models, belong to the non-mathematical holistic and heuristic class of models. They can describe the dynamics of a pathological process and/or the pathological mechanisms vs. control. They are surely not exact maps of the complex reality, but they are pertinent representations that gather the minimum knowledge and intelligence necessary to allow researchers to take the best possible decisions for the best possible results.

The second generation tools, CADI™ Process, development started in 2002

Because life is a non-linear integrative process, our company decided, in 2001, to switch from “leading Cartesian concepts” to CADI™, the most effective synergic process linking organic non-linear integration (Brain intelligence ) and in-silico data processing power (collecting, structuring and manipulating data)
BMSystems, invented CADI™ (Computer Assisted Deductive Integration) in 2002, the first integrative process based on “negative selection” that generated the world first, and only to date, validated and published in-silico model on a complex human disease

The unique CADI™ 4 steps validation process

The CADI™ 4 steps validation process starts when the integrative biology researchers generate the initial CADI™ model

The initial CADI™ Ver.0 model is constructed by integrative biology researchers.
Step 1: For each loop, integrative biology researchers integrate the experimental results to generate the next CADI™ Ver.n+1 model
Step 2: CADI model’s forecasts are defined by both experimental and integrative biology researchers The experimental biology researchers define and invent new innovative experimentations to test the model’s forecasts
Step 3: Experimental biology researchers implement the innovative experimental approaches to test the model’s forecasts
Step 4: Unexpected experimental results are analyzed and interpreted by both experimental and integrative biology researchers

The CADI™ 4 steps validation process stops when no key unexpected results are reported.

The CADI™ methodologies and tools.
Key aspects: Running life sciences R& D programs better, faster, cheaper and safer

Better-Faster: The CADI™ (Computer Assisted Deductive Integration) proprietary modeling approach is the first successful application of the negative selection concept invented in 2002 by Dr. François Iris, founder and CSO of the company where he made it operational. This disruptive innovation in the field of systems biology places back the biologists in the center of the game, computational science providing the necessary tools to help them work Better and Faster.
Better: The CADI™ process, has proven in 2003 (first publication in history of a biologically validated model of a complex human disease) to be the most efficient synergic process combining organic non-linear integration (Brain intelligence ) and in-silico data processing power (collecting, structuring and manipulating data) to build validated biological interaction maps that describe biological reality Better
Better and safer: The CADI™ model can describe the dynamics of a pathological process and/or a pathological status vs. control and allows to switch from “symptomatic” to “causal” medicine. Because we work on mechanisms associated with specific pathways it becomes easier to predict and identify pertinent biomarkers and to propose new therapeutic strategies. At every steps of the preclinical and clinical development program, it is easy to go back to the model and rework it if necessary, making drug development Better and safer
Faster and cheaper : The CADI™ models, belong to the non-mathematical holistic and heuristic class of models. Because we do not need to describe the complete system before delivering, the development of a CADI model leads to directly exploitable processes, when the majority of our competitors are still trying to build operational systems. CADI™ is faster and cheaper.
Faster and cheaper : The CADI™ models are surely not exact maps of the complex reality, but they are pertinent representations that gather the minimum knowledge and intelligence necessary to describe a living process in a defined context and allows researchers to take the best possible decisions for the best possible results. They can be the most efficient necessary step to define the contexts and the parameters to build local pertinent mathematical models if necessary for optimization faster and cheaper.
Better, faster and cheaper: The CADI™ process re-invented and made highly productive the synergic collaboration between experimental and integrative biology, implementing the unique CADI™ 4 steps validation process. Because a CADI™ model explains what, where, when to validate, it becomes possible to invent simple but highly pertinent & cost effective experimentation to get Yes/No answers better, faster and cheaper. Bio-Modeling Systems abandoned the Cartesian approach in 2001

The first generation: Bio-Graph™ (development period: 1998-2001)

This initial "Cartesian" integrative plate-form, called “Bio-Graph™” because largely based upon graph theories, was developed over the period 1998-2001
This technology allowed the production of the first biological models of complex human pathologies ever produced (Tamoxifen resistance, partly with the CADI™ prototype)
However, this approach was extremely limited on several fronts

It required that all the papers must be annotated before use,etc...

It required massive amounts of human intervention at all stages of the analytical process and
While allowing to efficiently analyze at the cellular level, it was woefully inadequate for tasks where different tissues or organs had to be taken into consideration