» Our Technology » Therapeutic Performance Mapping System (TPMS)

Anaxomics' solutions and services are all supported by a proprietary technology that exploits the latest advances in systems biology to accelerate drug development and biomedical research: the Therapeutic Performance Mapping System (TPMS).


Living beings under system biology perspective

biomarker

Signal flux from target (yellow) to clinical effectors (green/red) and biomarkers (blue). Proteins in grey are not affected, proteins in white are part of the mechanism of action and arrows describe the signal flux.

Anaxomics' TPMS integrates all available biological, pharmacological and medical knowledge into mathematical models that simulate in silico the behaviour of human physiology. In this manner, we can test and evaluate the physiological effects of any pharmacological compound at the molecular level, generating mechanistic hypotheses that are in accordance with nature.

Systems biology envisages living beings as complex networks of genes or proteins that are linked by their known biochemical relationships. Any change in the biological system, such a drug treatment or a gene mutation, induces a "perturbation" that is transmitted across the network. By feeding the models with state-of-the-art scientific data, TPMS models how the signal flows and the clinical consequences of the perturbation. The most probable path connecting the altered protein, even if it is not a drug target, with the final physiological effects is termed Mechanism of Action (MoA).

However, when trying to relate perturbations in the system to indications and adverse events, one key issue arises: clinical and molecular concepts belong to entirely different worlds. As a means to tackle this problem, Anaxomics has created a dictionary that translates clinical and medical terms into molecular biology data, thus effectively linking both worlds. The Biological Effectors Database (BED) contains more than 3500 proteins in 200 pathological conditions.


Mathematical model construction and evaluation

In the context of systems biology, a mathematical model is a description of a biological system (a whole organism, a tissue, a cell) using mathematical concepts. Since models can predict some properties that might not be inferable from direct observation, they help us to better understand their real counterparts.

Using TPMS technology (described in Mas et al., 2010 [US2011/0098993]), mathematical models are created and evaluated to find answers to clients' requests. Please, click the buttons (steps) in the diagram below to learn more about our methodology.

Step 1 Step 2 Step 3 Step 4 Step 1 Step 2 Step 3 Step 4 Step 1 Step 2 Step 3 Step 4


STEP 1
Constructing a protein-protein interaction network

Anaxomics creates a virtual biological network of the complete human protein map, which includes all known genes or proteins (nodes) and functional relationships (links) between them.

For the construction of this map, Anaxomics uses public and private external databases (KEGG, BIND, BioGRID, IntAct, MatrixDB, MINT, REACTOME, MIPS …) and proprietary link information, extracted from scientific literature, manually curated by our expert team.


STEP 2
Loading the network with biological information

After the construction of the map, Anaxomics feeds this network with all the information compiled in the Biological Effectors Database (BED), which contains all the updated biological and biomedical knowledge associated with the network’s elements (proteins/genes). Our database includes drug targets, proteins involved in pathologies or adverse events, results from clinical trials, information of microarrays, their use as biomarkers, metabolic information...


STEP 3
Mathematical model generation

The previously created biological network is transformed into a mathematical model capable of both reproducing existing knowledge and predicting future data. This is achieved by training the biological network with the Truth Table, a collection of known stimulus-response relationships that act as mathematical restrictions. In this manner, the model “learns” that it has to comply with sets of restrictions based on physiological observations in order to simulate the behaviour of real biological systems.


STEP 4
Extraction of biological and clinical conclusions

The analysis of the mathematical model reveals functional properties and mechanistic insights that are otherwise inaccessible. When the models are asked with the client’s demands, they suggest new hypotheses that can be readily tested in vitro or in vivo for validation: