How we developed 7HC

The 7HC project is in the field of application concerning the development of new drugs, their repositioning or the development of nutritional supplements which has always been driven by an intense interdisciplinary effort.

This process begins with the identification of biological targets, and continues with the design and optimization of the candidate molecules until the pre-clinical “in vitro” and “in vivo” phase that determines whether the candidate compounds meet a set of criteria for the start of clinical development.

The need for resource optimization is evident when one considers that on average 12-14 years and over 1 billion euros are required to bring a drug to market from the moment of its discovery.

Currently the development process of a molecule is characterized by a very high number of failures, largely due to inadequate pharmacokinetics, lack of efficacy, toxicity, side effects in humans and various commercial factors.
7HC fits into this context with an integrated software platform for the in silico prediction of pharmacological efficacy.

The 7HC algorithm, already developed and tested by the designers of the project, is able to make an estimation of parameters of extreme importance to guide the initial design and optimization of a drug by strongly reducing the in vitro tests with extremely high costs (thousands of euros per molecule).

7HC will provide a highly usable and dynamic computational platform, designed and developed to be used in a business environment by chemists, biologists or pharmacologists in an absolutely intuitive way.

The possibility to support, guide and optimize laboratory experiments is therefore the real challenge of 7HC, whose intrinsic characteristics allow the definition of a “highly efficient and highly effective” process.

7HC project is also focused on mathematical models able to predict the patient’s health trajectory when perturbed by specific pathologies, and to test in parallel possible therapies able to downgrade the disease progression.
This tool can be used to predict the personalized effect of a specific therapy, based on the patient’s condition.

The idea is to predict the most likely evolution of the pathology and to understand how the patient’s clinical variables change during the above-mentioned prediction.

The 7HC systems are created ad-hoc to be virtualized and implemented into HPC systems and be available as a service on demand.


7HC is the first software platform in the pharmaceutical field able to provide a solid IT service able to estimate parameters of extreme importance in the design phase of new molecules, reducing the cost associated with experiments.


The web interface will guarantee the confidentiality of the data, so that the secrecy of data concerning the chemical structure of the tested molecules is guaranteed


7hc is based on the concept of Cloud Computing. The integrated platform will manage the IT resources needed for data storage, processing and transmission, according to the user’s requests.

7HC project is focused on an integrated software platform that will be able to:


Read the customer’s data through the web interface. The user is asked to select within a database a certain protein that represents the pharmacological target and a certain number of molecules to be tested.


The algorithm based on molecular modeling methodologies will process the data provided by the user and perform an estimate of affinity and kinetics of each molecule-candidate within the pharmacological target of interest (e.g. target protein).


The candidate molecules are now classified according to the kinetics and affinity estimated in the previous step, providing a list of the best candidates in terms of pharmacological efficacy…

7HC project consists of 2 modules:


web-based frontend able to read and display the input data provided by the customer and to provide in output the results of the estimates made by the backend module. The user will be asked to indicate a certain protein that represents the pharmacological target (a large number of 3-D structures of proteins and nucleic acids is available for example in the “Protein Data Bank”), and a certain number of candidate molecules to be tested. The user will receive the list containing the estimated affinity and kinetics of each candidate molecule with respect to the set pharmacological target. The frontend module will be composed by an optimized interface realized with HTML 5 and Javascript.


the backend will take care of data collection and processing the input. The backend will run inside an instance of Amazon EC2 (Elastic Compute Cloud) and the static files will be saved on Amazon S3 (Simple Storage Service) storage. The backend will be able to interface and recall the software necessary to calculate the pharmaco-receptor interaction kinetics (e.g. GROMACS) with a series of calls to allow interfacing to the underlying database and storage system.


The main objective of the 7HC project, since its conception, has been to reduce the time and costs concerning the initial stages of the development process of a drug and/or natural solutions such as supplements and nutritional supplements, in order to optimize and make more efficient the production flow of current market players. The project represents an important step of innovation by proposing algorithms on the frontier of scientific research with the idea of putting them at the service of the pharmaceutical industry and more generally, of companies operating in research, design and development of drugs.


Pharmaceutical companies will be guided by the integrated platform and thus be able to significantly reduce the number of experiments to be carried out in the first phase of drug development.


The estimation of important parameters of the drug-design pipeline will be quickly provided.


Provides the possibility to apply complex methodologies, without specialized training.


In order to guarantee the customer the possibility to apply the algorithms developed by the platform without having expensive hardware resources such as a super-computer able to provide the combined CPU-GPU calculation.

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