The advancements in the last years in the field of biological systems technology, especially since the dawning of the so-called «omics era», have revealed that living beings are not simply groups of genes or proteins that exert their function independently.
«Everything that alters somehow the normal physiological state of a cell or a tissue, ranging from gene mutations to the physiological effects of a drug, has a global impact that goes beyond the mutated gene or target protein.»
Accordingly, when studying complex biological systems it is not sufficient to identify and characterize the individual parts of the system. It is also necessary to obtain a thorough understanding of the global interactions between molecules and biological pathways. This is even truer for comprehending multifactorial diseases such as cancer, multiple sclerosis or Alzheimer’s disease, to name a few.
Systems biology meets this need by integrating all the available knowledge from genomics, interactomics and other ‘omics’ disciplines into complex mathematical models that emulate the behaviour of biological systems. In this manner, it has become an indispensable tool for investigations attempting to fully understand the global consequences of biological phenomena.
Biomedical research, drug development and other related areas have already benefited from incorporating systems biology in their normal procedures.
The potential of systems biology
The potential of systems biology in accelerating research and increasing our understanding of biological phenomena is vast, and it keeps growing as new technologies are developed and knowledge is generated. Among other advantages, this multidisciplinary approach can provide assistance to:
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- Investigate and understand the highly complex processes involved in the development of diseases and other physiological alterations.
- Identify therapeutic targets and drugsthat affect multiple pathways in complex diseases, thus achieving an appropriate polypharmacological effect.
- Overcome pathway redundancy causing resistance to treatmentin cancer and other diseases where classical approaches turn ineffective.
- Determine the relevance of a specific molecule or pathwayfor the overall behaviour of the system or in the pathogenesis of a disease.
- Assess the suitability of new chemical or biological entitiesas drugs by evaluating their mechanism of action in a global context.
- Integrate data from different experiments, revealing complex properties that may not be apparent from single experiments, and interpret new experimental data in the contextof the accumulated available knowledge about the functioning of biological systems.
- Explore novel scenes and develop hypotheses to guide the design of new and promising experiments.
- De-risk scientific decisions and reduce research costsby identifying the most promising targets and drugs from a systematic, holistic point of view.
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To date, systems biology solutions have been only available to a few. However, research institutions and companies working in the health sciences field can now benefit from them thanks to easy affordable new tools. Were you asking yourself, ¿how do they do it?, here you have the awaiting answer.
Therapeutic Performance Mapping System (TPMS)
Solutions and services developed by the spanish company Anaxomics 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).
Founded in 2007 and headquartered in Barcelona (Spain), and thanks to a seasoned team of skilled experts, Anaxomics offers cutting-edge systems biology approaches in combination with a strong expertise in the fields of drug development, clinical research and biotechnology.
Living beings under the systems biology perspective
Their TPMS platform integrates all available biological, pharmacological and medical knowledge into mathematical models that simulate in silico the behaviour of human physiology. In this manner, with this platform can be tested and evaluated 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. Let pass to take a look on how it is developed the construction and evaluation of the created mathematical models.
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, etc) 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. These are the steps in the methodology:
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 their 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). Their 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:
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- What is the mechanism of action of my drug? → Mechanism of action
- Will my drug be effective? Will it be safe? → Clinical safety and efficacy profile
- What other uses can I find for my drug? → Drug repositioning
- Which compounds of my pipeline should I prioritize? → Early Product Development Strategy
- How can I avoid or control drug safety issues? How can I enhance drug efficacy? → Strategies and solutions for clinical trials
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The field of the systems biology is open! Discover now the new capacities that bring us bioinformatics, as AI tools to diagnostic diseases, new devices based on DNA to store and manage vast amount of information, platforms that allow virtual medical atention, algorithms to predict pharmacological targets, and platforms to learn by your own bioinformatics.
Dont stop and discover all these possibilities!!