Although conventional drug development aims to design drugs that selectively target a single molecular entity (e.g., a disease-driving protein), drugs often are found to interact with more than one target. These off-target interactions can be problematic as they may result in adverse effects and suboptimal drug effectiveness. Drug repositioning provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposing leads based on big data resources, hence further accelerating and de-risking the drug development process by computational means.
Biovista is one such firm that delivers custom drug repositioning, drug de-risking, and clinical hold solutions for the BioPharma Industry. Biovista also develops powerful platform technologies for Life science and Biotechnology companies. The firm applies a systematic Artificial Intelligence platform to develop its pipeline of repositioned drug candidates in disease areas such as neurodegenerative diseases, epilepsy, oncology, and orphan diseases. Biovista also works with its collaborators to proactively position and to reposition their assets, whether new chemical entities or existing compounds.
Biovista's scientists use the most robust technology platform to analyze massive data resources and identify non-obvious, mechanism-of-action based associations between compounds, molecular targets, and diseases. It uses this insight to find new uses for existing drugs or drug combinations, assess their risk profile and advance them to PoC and Clinical Phase IIa/b sooner, cheaper, and with a higher probability of success than has been possible to date.
Revolutionary Products and Solutions Delivered
Biovista Vizit: It is a visual exploration tool for biomedical literature research. Vizit allows one to search and explore a biomedical domain, such as a disease, a pathway, a gene, etc. in a visual manner. When any connection is shown, validation is given in the form of a NCBI PubMed reference. Add a name of a biomedical term in the Vizit whiteboard. Then ask Vizit to find connected terms. And unlike PubMed or Google, instead of a list of publications or pages, get a live graph of related terms. It helps scientists conduct their biomedical literature research and find your Life Science products in a visually engaging interactive environment and to explore medical conditions, drugs, and their side effects.
Drug Repositioning: Systematic Drug Repositioning (SDR) goes a step further by allowing companies to practice repositioning on a permanent and repeatable basis thereby offering senior management an effective tool with which to help shape strategy, avoid competitor predatory market-share moves and manage the company pipeline. Biovista's systematic discovery COSS™ platform supports their team of biologists, medical doctors, epidemiologists, and IP experts to generate robust Mechanism-of-Action rationale to support drug-disease associations that are non-obvious and aligned with strategic pipeline priorities. Biovista works with their clients, using where appropriate in-house data to evaluate and rank high-value opportunities generated by their platform.
Personalized Medicine: Biovista's systematic discovery COSS™ platform supports their biologists, medical doctors, and IP experts in creating multi-dimensional profiles of drug combinations of two or more individual drugs. These profiles can be assessed both in terms of their expected efficiency in a disease of interest and terms of potential adverse drug interactions with each other. The firm generates a robust Mechanism-of-Action rationale to optimize the therapeutic effect of the combination by identifying synergistic drug interactions and/or to minimize the adverse drug events by selecting combinations with antagonistic adverse event profile.
Drug De-risking: Biovista helps to generate robust Mechanism-of-Action rationale to identify or characterize suspected side effects. The firm works using where appropriate your in-house data to fully characterize the risk profile of the drug. It creates a multi-dimensional representation of each possible adverse reaction and multi-dimensional profile of your drug and enriches the profile by cheminformatics analysis which helps to identify additional off-targets and associate them to known or predicted adverse reactions. And finally matches and ranks the profile of a drug against all possible adverse reactions using mechanism-of-action and other associations.
The Leader Upfront
Dr. Andreas Persidis serves as the Chief Executive Officer of Biovista. He has conducted research in the fields of machine learning and applied Artificial Intelligence and has led the launch of multiple international research projects.
Dr. Persidis has managed on behalf of the European Commission a roadmap study on systematic innovation, has served as an expert reviewer and evaluator for the European Commission and has advised the Greek and Austrian governments in the areas of IT and the life sciences. Since 2010 Dr. Persidis is the President of the Hellenic BioCluster (HBio). He has published extensively in international journals and is an invited speaker at forums on drug repositioning, innovation and export oriented high-tech companies.