[ 01 / Foundation ]
The full universe of programs and companies, organized in seconds.
Robo turns landscapes into connected records that can be searched, explored, modified, and evaluated. It's nothing like a database or a report that every other company has access to. It is your own custom universe, your own data foundation.
Explore the drug universe.
Search across indications, modalities, mechanisms, development stages, companies, and other relevant attributes.
Build focused landscapes.
Define the universe of programs or companies relevant to a therapeutic area, strategic question, or screening mandate.
Bring your own information.
Add programs, lists, and information from your organization alongside external intelligence.
Keep the universe connected.
Work with consistent program and company identities, so research from different projects can build on the same underlying records.
[ 02 / Evaluate ]
Your criteria. Applied consistently.
Every pharma company has its own view of what makes drug programs interesting or valuable.
Robo turns that perspective into consistent, repeatable, complex evaluations across programs, companies, therapeutic areas, and more.
Bring the scientific, clinical, regulatory, or commercial questions that matter to you, and our specialized AI agents will research the evidence.
Agent reasoning appears here, with each finding linked to the evidence it came from.
- Trial[ Source reference ]
- Paper[ Source reference ]
- Deck[ Source reference ]
Evaluations built for pharma.
Start with reusable research and evaluation templates for common BD&L and Search & Evaluation questions.
Make the logic yours.
Adapt criteria to your scientific priorities, therapeutic strategy, and decision process without writing code.
Research at scale.
Run evaluations across many programs in parallel, bringing together relevant evidence rather than relying on a single data source.
See the reasoning.
Inspect findings and supporting references to understand how an evaluation was reached.
Compare consistently.
Apply the same evaluation framework across a landscape, with results structured for side-by-side comparison.
[ 03 / Decide ]
From research to the decisions it supports.
A landscape is rarely the end goal.
Your team needs to identify promising opportunities, compare alternatives, prepare for discussions, and decide where to spend its attention.
Robo helps turn a broad set of evaluated programs into the specific views and outputs each decision requires.
Opportunity shortlists
Identify and rank the programs that best match your criteria.
Competitive landscapes
Compare programs across clinical evidence, mechanisms, development stages, and differentiating characteristics.
Company screens
Evaluate potential partners or acquisition targets against your strategic priorities.
Conference preparation
Prioritize abstracts, programs, and companies for further investigation.
Research and readouts
Go deeper into the evidence and turn your evaluations into material your team can use.
[ 04 / Automate ]
Keep your landscapes current on autopilot.
The drug landscape doesn't stand still.
New programs enter development. Clinical results emerge. Companies change direction. Competitive positioning evolves.
Robo helps maintain the research and evaluations behind your landscapes as new information becomes available.
The goal is simple: when your team returns to a landscape, the work is still up to date and useful.
Identify additions to the landscape that may deserve evaluation.
Incorporate relevant clinical, scientific, regulatory, and commercial developments.
Refresh research and assessments as the underlying evidence changes.
Keep track of previous findings and how evaluations have evolved.
[ 05 / Understand ]
The important update isn't always the new data.
It's what that data changes about your assessment.
Robo connects new developments to the evaluations your team cares about, helping distinguish routine updates from information that may change a program's priority.
Northstar Bio announced interim Phase 2 clinical results for NB-117.
NB-117 now meets your predefined efficacy threshold and has moved onto your shortlist.
Medium fitchanged toHigh fitIts evaluation has changed from Medium to High fit, driven by stronger clinical evidence and an improved competitive position.
The updated findings, previous evaluation, and supporting sources are available for review.
Stay informed about what changed, and understand what to do with it.
[ Under the hood ]
Drug intelligence is fragmented. Robo connects the dots.
Reliable evaluations depend on a reliable understanding of the underlying programs, companies, and evidence.
Our data foundation brings information from different sources into a structured and connected view of the drug landscape.
Identity resolution
Different names, codes, and records can describe the same drug program or company. Robo works to reconcile those identities so research is connected to the right entity.
A connected knowledge graph
Programs, companies, and associated evidence are organized into a connected data model that supports discovery, research, and evaluation.
Evidence normalization
Information from different sources is structured into comparable fields and concepts, helping agents evaluate programs consistently.
Public, licensed, and internal data
Bring together information from scientific literature, clinical registries, regulatory sources, patents, commercial data providers, and your organization's own material.
Source-level traceability
Research findings retain connections to their supporting evidence, making it possible to investigate and verify assessments.
Continuously improving coverage
The foundation evolves as new records are identified, existing information is updated, and additional sources become available.
[ Built to work together ]
One place for the programs, evidence, and evaluations that matter to your team.
Robo isn't just a way to generate research.
It's a workspace where that research stays connected to the drug programs and companies you're evaluating.
Living worksheets
Research and compare programs in a familiar, structured interface, with AI-powered fields and evaluations.
Persistent program knowledge
Keep research and evaluations tied to the programs and companies they describe, rather than scattered across disconnected outputs.
Your organization's perspective
Bring your criteria, internal information, and previous work into the evaluation process.
Reusable intelligence
Build new research and evaluations on existing records and findings. Revisit earlier assessments as your questions evolve.
A history of understanding
See how evidence and evaluations have changed, and return to the reasoning behind previous conclusions.
