About CycloGen AI
Building a new path from biological insight to therapeutic discovery.
CycloGen AI is a drug discovery technology company developing computational systems to help scientists identify, design, and evaluate new therapeutic candidates.
Our focus includes some of the hardest problems in medicine — rare diseases, emerging diseases, cancer, and conditions where effective treatment options remain limited or do not yet exist.
Why We Built CycloGen
A more integrated approach to discovery
Drug discovery increasingly depends on computational methods, yet many workflows remain divided across specialized tools, infrastructure, and scientific disciplines.
CycloGen AI was built to bring these capabilities into a more integrated discovery environment — connecting molecular structure, target analysis, small-molecule discovery, and therapeutic protein design.
Our platform combines AI, molecular modeling, structural biology, and computational chemistry to help research teams move from a biological question toward experimentally testable candidates.
"Better therapeutics begin with better decisions about what to test."
We believe computation should complement experimental science, not replace it. By narrowing the search space and prioritizing promising candidates, computational discovery can help researchers focus experimental resources where they have the greatest potential value.
What We Are Building
From biological question to candidate
CycloGen AI is developing an integrated computational environment for early-stage therapeutic discovery.
01
Understand the Target
Analyze molecular structure, potential binding regions, and biological characteristics relevant to therapeutic discovery.
02
Explore Molecular Space
Evaluate and generate potential small molecules, proteins, peptides, and other therapeutic modalities around a defined biological objective.
03
Design & Prioritize
Use computational modeling and AI-assisted design to narrow large candidate spaces and identify candidates worth advancing.
04
Prepare for Validation
Produce structured computational evidence that can support candidate selection and subsequent experimental testing.
Mission
Expand what is possible in therapeutic discovery.
Our mission is to accelerate the discovery of new medicines, with particular attention to rare diseases, emerging diseases, difficult therapeutic targets, and conditions for which effective treatments remain unavailable. We are building technologies that can shorten the path from biological insight to experimentally testable therapeutic candidates.
Vision
A future where difficult diseases are not overlooked.
We envision a future where advanced computational discovery makes it possible to investigate more biological targets, explore more therapeutic ideas, and pursue diseases that have historically been difficult or uneconomical to address. Our goal is to make sophisticated drug discovery technology more capable, integrated, and accessible to the scientists working on these problems.
Our Approach
Computation guides the experiment.
The experiment determines what is real.
CycloGen AI is built around a simple scientific principle: computational models are most valuable when they help researchers make better experimental decisions. Our technology is designed to generate hypotheses, evaluate possibilities, prioritize candidates, and provide evidence for what should be tested next.
Leadership & Advisors
Founder & CEO
Linu Lawrence
AI Infrastructure • Computational Drug Discovery • Scientific Computing
Linu Lawrence founded CycloGen AI with the goal of building a more integrated computational foundation for therapeutic discovery.
With more than 15 years of experience across high-performance computing, GPU infrastructure, distributed systems, AI/ML platforms, and scientific computing, he has built and supported technology environments for large-scale research and computational workloads.
At CycloGen AI, he leads the development of the company's technology platform and its application to molecular discovery, protein engineering, and computational therapeutic design.
Strategic Advisor
Ross Timson
Cloud Infrastructure • SRE • DevOps • Scalable AI Systems
Ross Timson advises CycloGen AI on technology strategy, infrastructure, scalability, and production engineering.
Based in the United Kingdom, Ross brings extensive experience in cloud-native infrastructure, SaaS scalability, site reliability, and production technology systems.
His experience supports CycloGen AI's development of secure and scalable infrastructure for computational discovery.
Some diseases are difficult.
Discovering new ways to treat them should not stop there.
CycloGen AI is building the computational foundation to explore more targets, evaluate more therapeutic possibilities, and help promising ideas move toward experimental validation.