COMPUTATIONAL BIOLOGY - NATURAL LANGUAGE PROCESSING - MACHINE LEARNING
Data-Driven Drug Discovery Platform
At BioXplor we are building an integrated drug discovery platform to enable scientists to make novel discoveries faster and to commercialize promising drug candidates via very early stage drug discovery partnerships. We are building an AI to uniquely prioritize candidates based on safety and efficacy by combining the latest structured literature, with public and private knowledge bases. The knowledge discovery engine is powered by natural language processing with integrated machine learning models for interpretation of genomics (or multiomics) datasets with obvious and non-obvious biomedical entity relationships generated by our proprietary ABCD model and 30+ custom biomedical ontologies.
We have successfully applied the platform for Indication Expansion, Drug Repositioning, Pathway Analysis, Target ID, and Clinical Trial Responder ID / Personalized Medicine, with top 5 pharma and biotech clients including Novartis, Merck and Bayer. BioXplor collaborates with academic teams for early stage drug discovery programs in oncology, including validation of predicted novel drug targets and novel drug designs in bioactivity assays and pre-clinical studies. BioXplor’s technology is available for licensing and we operate a CRO model.
BioXplor Discovery Software Suite
BioXplor's knowledge-base consists billion's of structured sentences from over 35M biomedical publications. These data are machine read using natural language processing and over 30 proprietary biomedical ontologies to uncover over 150M entity relationships between drugs, disease, genes, variants, pathways, biological processes, tissues, cell types, co-morbidities, adverse events, safety and toxicity terms. The entity relationship types include causation, interaction, gene expression, mechanism of action, and much more. BioXplor has structured content for 1000's of methods and applications, as well as instrumentation, research antibodies, recombinant proteins, ELISA assays, biochemicals, animal and cell models, and much more.
Biomedical Knowledgebase
BioXplor was founded in January 2017 and is backed by UC Berkeley Skydeck, Merck & European Commission (EIC - Horizon 2020) accelerators, amongst other investment partners. The 10 person strong team has combined expertise in computer science and biomedical science applied to drug discovery, which are the core components of what we do, in equal measure. We are passionate about developing data-driven approaches to accelerate biomedical discoveries and to help reduce failures Life Science R&D.
Advisory Board: Dr. David Kwon, MD PhD (Harvard) MBA (UC Berkeley), former medical director at Novartis & Gilead, Prof. Jody Haigh, Haematology & Oncology, Department of Pharmacology and Therapeutics, University of Manitoba / CancerCare Manitoba, and Bill Allison, CTO at UC Berkeley.
Management Team: Mark Rogers, MSc (Molecular Biotech) is CEO and has a over 15 years experience in emerging biotechnology, previously Associate Director, Emerging Biotechnology Initiative at Merck KgaA. Pavel Kartasevs, MEng (Computer Engineering), MSc (Bioinformatics) is CTO, and has a specialised CompBio background combining high performance computing, bioinformatics and software engineering. Anna O'Leary, BA (Economics & Finance) is COO, and brings management, finance and business operations expertise to the team from Aramark and RBS Global Markets. John Conway, MSc (Data Science), is Head of Machine Learning at BioXplor, and brings over 20 years experience in hands-on analytics, data science and management in the Financial Industry to the team.
About Us
