Question 1

How does Iktos Makya’s generative AI accelerate the drug discovery process compared to traditional methods?

Accepted Answer

Iktos Makya leverages generative AI technology specifically designed for medicinal chemists to automate de novo drug design. It generates diverse, novel, and medicinal chemistry-like molecules optimised for synthetic accessibility and multi-parametric criteria. This approach enables faster convergence towards viable drug candidates while ensuring each molecule can be efficiently synthesised. As a result, Makya reduces the initial molecule design phase from years to months, significantly accelerating drug discovery timelines.

Question 2

What unique features does Spaya provide for synthetic route planning, and how does it integrate with existing drug discovery workflows?

Accepted Answer

Spaya is an AI-driven retrosynthesis platform that quickly transforms target compounds into commercially available starting materials, delivering optimised synthetic routes in real-time. Its unique data-driven approach combines reinforcement learning and Monte Carlo Tree Search to identify the most feasible synthetic pathways. Spaya offers customisable synthesis constraints, such as preferred reaction steps, pricing, and delivery times, enabling tailored synthetic planning. Integration with external data providers and APIs enables seamless incorporation into existing workflows, such as KNIME or Jupyter notebooks, thereby enhancing efficiency in synthesis planning.

Question 3

How do Iktos tools support the full drug discovery cycle, including synthesis and biological testing?

Accepted Answer

Iktos provides an integrated platform where Makya’s generative AI designs molecules optimised for automated robotic synthesis managed by Iktos Robotics. Spaya ensures efficient retrosynthesis planning, and the autonomous lab automates synthesis, purification, and analysis workflows. Furthermore, the recent acquisition of Synsight enriches the platform by enabling in-house, AI-guided biological testing of synthesised compounds focused on challenging targets, such as protein-protein and RNA-protein interactions. This closed-loop, AI-driven Design-Make-Test-Analyse (DMTA) cycle accelerates drug candidate identification and optimisation, shortening discovery timelines to under 2 years.

Useful Links

Our Services

Contact Us