IKTOS

Taking a drug from initial research to a preclinical candidate typically requires years of work and costs measured in hundreds of millions of euros. Much of that time is consumed in iterative cycles of molecular design, chemical synthesis, and biological evaluation — a process that remains largely manual, slow, and dependent on the intuition of medicinal chemists. Iktos has set out to accelerate these cycles radically, combining generative artificial intelligence, computational retrosynthesis, and robotic automation into a single integrated workflow. The platform Iktos has developed is designed to do what medicinal chemists cannot do alone: explore vast chemical spaces in short timeframes, propose viable synthetic routes for identified molecules, and automate the experimental steps that can be delegated to robotics. The stated goal is to compress the path from design to preclinical candidate to under 24 months — a result that would be remarkable by any standard in the pharmaceutical sector. Iktos's generative AI does not simply optimise existing molecules. It can propose entirely new chemical structures based on therapeutic target specifications, incorporating synthesisability constraints that reflect the actual capabilities of real laboratories. This distinguishes the approach from purely computational tools that generate molecules that cannot feasibly be made in practice. Iktos's customers are pharmaceutical companies, biotech firms, and research and development laboratories that want to accelerate their drug discovery programmes without having to build the necessary AI and robotics capabilities in-house. The model is B2B and oriented towards tailored collaborations. In a sector where development costs have exploded and research productivity struggles to keep pace, Iktos proposes a paradigm shift: not just faster tools, but a discovery architecture completely redesigned around intelligent automation.