Iktos
Nicolas Do Huu, PhD, is a seasoned technology leader with extensive experience in artificial intelligence and data-driven innovations. Currently serving as Founder and Chief Technology Officer at iktos since July 2017, and previously as Chief Data Officer at relevanC and Chief Technology Officer at Publicis ETO, Nicolas has consistently driven projects that integrate machine learning with big data. As Head of Data Innovation Lab at Publicis ETO, Nicolas led efforts in research and development to enhance innovative offerings in the rapidly evolving tech landscape. With a strong foundation in software engineering and deep learning, Nicolas also held positions as Advanced Modeling Expert at Quinten and Senior C++/Objective-C Software Engineer in various roles from 2008 to 2013, establishing a robust technical background in advanced software solutions. Nicolas holds a PhD in Artificial Intelligence from the Laboratoire d'Analyse et d'Architecture des Systèmes (LAAS) - CNRS and a DEA in Computer Systems from Université Paul Sabatier, Toulouse III.
This person is not in any offices
Iktos
Incorporated in October 2016, Iktos is a start-up company specializing in the development of artificial intelligence solutions applied to chemical research, more specifically medicinal chemistry and new drug design. Iktos is developing a proprietary and innovative solution based on deep learning generative models, which enables, using existingdata, the design of molecules that are optimized in silico to meet all the success criteria of a small molecule discovery project. The use of Iktos technology enables major productivity gains in upstream pharmaceutical R&D. Iktos offers its technology both as a professional services and as a SaaS software platform. Iktos offers Makya™, ligand and structure-based de novo drug design platform for multi-parametric optimisation (MPO) of lead compounds in line with Target Candidate Profile (TCP). Iktos is also developing Spaya™, a synthesis planning software based upon Iktos’s proprietary AI technology for retrosynthesis.