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Location: InsideDNA ltd, 5th Floor(740-750), Salisbury House, London Wall, London, United Kingdom United Kingdom
Founded in: 2015
Stage: Pre-launch
Number of employees: 6-15
Short URL: vator.co/insidedna
Awards and mentions
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Venture Kick aims at early identification, structuring and promotion of promising business ideas with a clear vision: to double the number of spin-offs at Swiss universities, to accelerate the time-to-market and to raise the attractiveness of these young companies for professional investors. Venture Kick helps potential entrepreneurs by giving them the opportunity to win up to CHF 130,000 in pre-seed capital. Moreover, startups can also use the know-how of experienced experts and entrepreneurs and be granted access to a national network of investors. Venture Kick provides a unique and leading approach with a proven track-record of creating new high-tech startups in Switzerland.
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InsideDNA

AI, machine learning and multi-omics for drug discovery
Startup/business
London, United Kingdom United Kingdom
http://www.insidedna.ai
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Company description

Today's drugs production takes 12 years and $1.5B for a single drug. The most expensive and risky stages of drug development are clinical trial phases II and III which often fails because drug either is too toxic or doesn't cure the patients due to poor choice of drug candidates at the discovery/target validation stages.

InsideDNA is a cloud based platform that helps biopharmaceutical companies to shorten discovery/target validation stages and to reduce the risks of phases II & III. It applies artificial intelligence and bioinformatics approaches to multi-omics data and mine public databases and research papers to find the best drug/biomarker candidates, re-purpose existing compound libraries and optimize in-vitro cell-line experimentation. We aim to reduce the risk of phase II attrition from 51% to 35% and shorten discovery/target validation stage from 4 years to 1 year.

 



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Team
  • Anna Kostikova
    Anna Kostikova | Founder
    I am founder of InsideDNA. I have in depth technical experience in life sciences and big data analytics; 10+ years of experience in genomics, life sciences and artificial intelligence. PhD in Computational Biology and Genomics, UNIL/SIB, Switzerland
Business model

B2B SAAS with pricing based on:

  • volume - we charge by number of drug targets and compounds to analyze or identify;
  • milestone - we charge separately at each stage of drug discovery pipeline for a number of items passing through a milestone. The charge for each successful compound or target increases at each stage

We also sublisence successful compounds that are bought from life science service companies. This way we keep an IP.

Competitive advantage

 

  • Ready-to-use solution tested on 1.5K FDA-approved drugs
  • IP protectable databases of predictive features for AI algorithms
  • Co-founders with a strong expertise in life sciences & AI
  • Wide network of contacts in life sciences & strong advisory board of experts in the field
  • On-going pilots with life science service companies
  • HIPAA compliance via Google Inc BAA (in progress)
  • Visibility (2nd winner of TechCrunch Disrupt Battlefield London 2016)