In silico research, De Novo design and development of new drugs, encompassing all stages
Through the use of artificial intelligence tools, our scientific team dedicates itself to leveraging all of its knowledge and potential for the benefit of our clients, accelerating the research, creation and development of new molecules and biomolecules for selected therapeutic targets.
The scope of our proprietary software DESIN AI allows its application to be applicable to:
- Any therapeutic target.
- Any biological target, antibody, protein, virus, bacteria, fungus, RNA, DNA and synthetic molecule.
-- Identification of unexplored and/or previously unidentified therapeutic targets using our biomolecular and biochemical activity prediction tool, leveraging scientific creativity.
The main differential of our proprietary software DESIN AI is its capacity and speed of data processing, compression and decompression using blockchain encryption, patented and developed internally, ensuring, additionally the inviolability of data.
Drug Repurposing
The process of Drug Repurposing involves evaluating existing medications for new therapeutic targets.
Identifying new therapeutic targets for existing medications allows expanding the market for the selected drugs, providing greater financial gains and extending their lifespan.
The identification of new therapeutic targets for existing medications is not eligible for intellectual property protection (patenting); however, within the services offered by DesignInSilico, we aim to go beyond simple identification of new therapeutic targets. We research and develop molecular models that allow variations in the structure of selected compounds, enabling the possibility of registering new patents. This ensures exclusivity for the client regarding the specific medication.
Stage 1: Research and Creation - In Silico Drug Design of New Medications
Using our proprietary software DESIN AI, we collect data on the selected target diseases, interrelating globally available information within their biomedical context, including diseases and their etiologies, therapeutic targets, existing molecules and biomolecules, and biological, chemical, and physical interactions among them. We structure, understand and organize biomedical data to create and develop new compounds with potential for the selected therapeutic targets.
With the structured data, using our biomolecular and biochemical activity prediction tool and harnessing the scientific creativity of our team, we develop simulations and conduct in silico validation of new molecules and biomolecules - including toxicity and safety prediction - for the selected therapeutic targets as well as other unexplored and/or previously unidentified targets. .
Stage 2: In Silico Development of Bioprocesses and/or Chemical Synthesis for validation in the Wet Lab (in vitro, ex vivo, and in vivo studies in animal models)
After the validation of new molecules and biomolecules, our proprietary software for simulating chemical syntheses and developing bioprocesses - including protein/biomolecule expression and purification - enables the evaluation and validation of the most suitable synthesis routes and bioprocesses for producing the new compounds.
The development of in silico chemical synthesis routes is conducted using a database of transition routes and our simulation tool for predicting experimental yields of organic and inorganic reactions.
The development of in silico bioprocesses is carried out using our screening tool, which allows for the selection of chromatography steps through the use of algorithms, rapidly developing multidimensional and selective integrated processes for the expression and purification of proteins with therapeutic activity and identification of impurities. The integrated development described above enables potential gains in operational efficiency, cost reduction, and material savings, as well as a shorter development time for the bioprocess.
Stage 3: Preclinical and Clinical Studies In Silico
Our proprietary software for comparing and predicting results of preclinical and clinical studies allows comparison of study designs conducted and published for the selected therapeutic targets, optimizing the final study design for their best potential performance across all necessary metrics. This generates personalized reports with proof-of-concept data and impacts on probabilities generated from inputs including OMICs data, drug structure, assay protocol, preclinical and clinical data, publications, and patents.