R2H
Clarisyn · Multi-agent biomedical analysis platform · Now live

RODENT2HUMAN

The evidence exists. Knowing what to do with it is another matter. R2H builds the intelligence layer in between.

Drug discovery is drowning in data and starving for clinical reasoning.

R2H builds the bridge from the first scientific question to the last abandoned compound.

How It Works
DISCOVERY
PRECLINICAL
PHASE I
PHASE II
PHASE III
Raw signals
Fragmented data
Noise
Unconnected evidence
Scattered findings
Failed drug information
R2H intelligence layer
STRUCTURED OUTPUT
[sys_init] executing multi-omics tensor alignment (v4.2.1)
> extracting pharmacokinetic embeddings ... [ok]
> noise_filter: discarding false-positive tox signals
0x8F9A2B: CROSS_SPECIES_TRANSLATION_MATRIX = [[0.82, 0.11], [0.04, 0.91]]
> mapping rodent hepatotoxicity markers to human homology
[processing] 11010100 10100010 11110011 00011010
> synthesis complete. resolving clinical outcome...
[sys] generating human-readable report...
> appending evidence trails to nodes 42-109...
> compiling toxicity prediction matrix...
Present at every question. Every stage. Every decision.
The problem. The fix.
$2.23B

Per drug.

Most of it spent on decisions that didn't have to go wrong.

10+ yrs

To market.

Every wrong question costs months. Every abandoned compound costs years.

93%

Never reach approval.

Half of those failures aren't biology they're clinical reasoning.

Most of this is preventable.

That's what R2H is built for.

Hear from the people
using Clarisyn

"I found Clarisyn particularly valuable for comprehensive literature exploration and scientific idea development. Its life-science-specific focus allows it to provide deeper and more relevant insights than general-purpose AI tools, making it a useful companion throughout my PhD, especially for early-stage research and hypothesis generation."

Yigit Sibal

PhD Student in Computational Systems Biotechnology

École Polytechnique Fédérale de Lausanne (EPFL)

"Clarisyn turns days of literature review into minutes, delivering a structured, reliable report that is immediately usable. Where deeper expert interpretation is needed, a built-in consultation pathway transforms it from a starting point into a genuine collaborative tool."

Prof. Alan Boobis, OBE

Emeritus Professor of Toxicology

Imperial College London | Former Chair, UK Committee on Toxicity

"Clarisyn helps researchers save time by turning complex scientific questions into detailed, well-referenced reports. Its answers are more comprehensive and better supported by academic sources than the general-purpose AI tools I’ve used."

Kieran

PhD Researcher in Molecular and Cellular Pharmacology

University of East Anglia

"Clarisyn generates evidence-based toxicity mitigation strategies grounded in literature and mechanistic reasoning, each one contextualised with established ADMET principles. What stands out is the depth: a real grasp of structure-activity relationships and toxicological mechanisms, not generic advice. For any medicinal chemistry team balancing speed and scientific rigour, that's a substantial competitive advantage."

Ganesh Shahane

Principal Scientist, ML, BioPhysics & Drug Design

OMass Therapeutics

"What I appreciate most about Clarisyn is how easy the reports are to navigate and explore. It doesn't just pull literature together; it lays out clear comparisons of different experimental approaches, so I can weigh my options quickly rather than piecing them together myself."

Gizem Ozturk

PhD Student in Chemistry

University of Illinois at Urbana Champaign (UIUC)

"Clarisyn produced a technically rigorous, programme-ready analysis of a genuinely complex drug development question. What sets it apart is its honesty: it's clear about the limits of its own evidence rather than overstating what it knows. For teams who need reliable scientific intelligence quickly, and need to trust it, that makes a real difference."

Nikoleta Sachini

Senior Scientist, Preclinical Pharmacology & Oncology Drug Development

"I found Clarisyn particularly valuable for comprehensive literature exploration and scientific idea development. Its life-science-specific focus allows it to provide deeper and more relevant insights than general-purpose AI tools, making it a useful companion throughout my PhD, especially for early-stage research and hypothesis generation."

Yigit Sibal

PhD Student in Computational Systems Biotechnology

École Polytechnique Fédérale de Lausanne (EPFL)

"Clarisyn turns days of literature review into minutes, delivering a structured, reliable report that is immediately usable. Where deeper expert interpretation is needed, a built-in consultation pathway transforms it from a starting point into a genuine collaborative tool."

Prof. Alan Boobis, OBE

Emeritus Professor of Toxicology

Imperial College London | Former Chair, UK Committee on Toxicity

"Clarisyn helps researchers save time by turning complex scientific questions into detailed, well-referenced reports. Its answers are more comprehensive and better supported by academic sources than the general-purpose AI tools I’ve used."

Kieran

PhD Researcher in Molecular and Cellular Pharmacology

University of East Anglia

"Clarisyn generates evidence-based toxicity mitigation strategies grounded in literature and mechanistic reasoning, each one contextualised with established ADMET principles. What stands out is the depth: a real grasp of structure-activity relationships and toxicological mechanisms, not generic advice. For any medicinal chemistry team balancing speed and scientific rigour, that's a substantial competitive advantage."

Ganesh Shahane

Principal Scientist, ML, BioPhysics & Drug Design

OMass Therapeutics

"What I appreciate most about Clarisyn is how easy the reports are to navigate and explore. It doesn't just pull literature together; it lays out clear comparisons of different experimental approaches, so I can weigh my options quickly rather than piecing them together myself."

Gizem Ozturk

PhD Student in Chemistry

University of Illinois at Urbana Champaign (UIUC)

"Clarisyn produced a technically rigorous, programme-ready analysis of a genuinely complex drug development question. What sets it apart is its honesty: it's clear about the limits of its own evidence rather than overstating what it knows. For teams who need reliable scientific intelligence quickly, and need to trust it, that makes a real difference."

Nikoleta Sachini

Senior Scientist, Preclinical Pharmacology & Oncology Drug Development