Iktos

We are a leader in artificial intelligence and robotic solutions applied to research in medicinal chemistry and new drug design. Iktos' proprietary and innovative generative AI solution enables 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 through the SaaS software platforms Makya™ for generative drug design and Spaya™ for retrosynthesis, and through strategic collaborations with pharma companies where Iktos mobilizes its unique platform and leading-edge capabilities to expedite small molecule drug discovery for the benefit of its partners. Iktos has also developed Iktos Robotics, a unique AI-driven synthesis automation platform that dramatically accelerates the Design-Make-Test-Analyze cycle in drug discovery and is developing its own pipeline of drug candidates targeting oncology and auto-immune and inflammatory diseases. In March 2023, Iktos completed a 15.5M€ Series A financing round co-led by M Ventures and Debiopharm Innovation with contribution by Omnes Capital. In July 2024, Iktos announced the acquisition of Synsight, thereby complementing its Chemistry AI platform with a groundbreaking biology platform for the discovery of new drugs targeting Protein-Protein Interactions (PPI) and RNA-Protein Interactions (RPI).

http://iktos.ai/

51-200 employees

Growth Trajectory

Iktos' growth is fueled by partnerships with pharmaceutical and biotech companies, expansion in the APAC region, and the development of an in-house drug discovery pipeline. Ongoing integration of purification, multidimensional biological data, and in-cellulo screening into Iktos Robotics and advancements in their automated AI and robotics platform are key drivers for future development. The company's focus on generative AI for de novo drug design and AI-driven retrosynthesis further enhances their potential for expansion.

Technical Challenges

Ensuring synthetic feasibility of AI-designed molecules

Rapid synthesis and testing of molecules

Integrating purification, multidimensional biological data and in-cellulo screening

Complexity of drug targets

Structural and biological complexity of drug targets

Tech Stack

Generative AI (Makya)Retrosynthesis AI (Spaya)RoboticsChemspeed platformMicrotubule Bench technology (MT bench®)AWSKnimePipeline PilotJupyter NotebookIlaka (Orchestration AI)

Team Size

Cloud engineering team

Chemistry team

Biology team

AI/ML team

Robotics team

Key Risks

Complexity of drug targets may pose ongoing technical and scientific challenges.

Competition in the AI-driven drug discovery market necessitates continuous innovation.

Reliance on partnerships with pharmaceutical and biotech companies creates dependence on external factors.

Market adoption of AI-driven drug discovery platforms may face resistance or skepticism.

Keeping up with the rapidly evolving AI technology landscape requires significant investment in R&D.

Opportunities

Expanding partnerships with pharmaceutical and biotech companies to further penetrate the drug discovery market.

Leveraging AI-driven molecular design and automation to address unmet medical needs in various therapeutic areas.

Advancing the integrated drug discovery platform to enhance speed and efficiency in generating preclinical candidates.

Expanding operations in the APAC region to capture emerging market opportunities.

Developing novel AI algorithms and robotics technologies to maintain a competitive edge in the industry.

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