Our Mission: Accelerating Medicines
Clearing the path for science to become medicines for patients.
Science takes the time it takes. The rest is in our hands.
Scientific failure is inevitable. Learning about it late is optional.
Candidates fail because toxicity emerges, efficacy is insufficient, pharmacokinetics do not work, or the biology does not hold. That is what preclinical research is meant to discover, and it is why more than two thirds of the cost of bringing a medicine to approval is the cost of the candidates that did not make it. That share is not the problem.
The avoidable cost inside it is continuing to spend time and capital after evidence exists that should change the decision, or failing to carry what one program learned into the next. Rarely because anyone was careless. Usually because nothing connected the finding to the decision it should have reached.
Biology, chemistry, DMPK, and toxicology each hold part of the evidence. Unipr connects those findings to the assumptions, decisions, and portfolio priorities they affect. When evidence changes, leaders see what should be reconsidered while there is still time to act on it, and the reasoning behind earlier decisions stays available to the programs that follow. The objective is not fewer failures. It is earlier ones, and greater conviction in what survives.
Insight | How Functional Language Barriers Delay Medicines
10+ years to develop a medicine. Science explains only part of it.
A development program runs on two clocks. Scientific time is real and largely irreducible: a six-month stability study takes six months, biology does not negotiate, and evidence cannot be manufactured on demand. Organizational time is everything else. Waiting on another function. Discovering a dependency late. Reconciling plans that disagree. Continuing to work against an assumption or date that has already changed.
A molecule can have clinical, CMC, regulatory, safety, and commercial plans running simultaneously, each correctly managed in a different system. The same upstream event is written into all five under a different name: database lock, data package ready date, data cut-off, market data readiness, safety database lock. Five dependent dates, no line drawn between them. And many of the functions holding those plans are not yours at all: research organizations, manufacturers, investigator sites, and agencies.
Unipr connects those plans into a living cross-functional critical path, matching the event rather than the name. When something changes, it identifies the programs, milestones, budgets, and people affected, before teams have spent weeks planning against a date that no longer holds.
Insight | Organizational Intelligence: The Enduring Advantage When AI Is Everywhere
63 days from approval to first revenue. Some launch the same day.
By approval the regulatory decision has been made and execution becomes the dominant variable. Across Unipr's analysis of 305 United States launches, the average delay from approval to first sale was 63 days. The best-in-class benchmark is 14. Several products launched on the day of approval, which is the point: the outcome is operational, not inevitable. Typical revenue forgone per launch exceeds $10 million, and every one of those days is a day patients wait.
The contributors are consistent: additional post-marketing regulatory requirements, late changes in market or launch circumstances, distributor delays, payer negotiations. None of these is a scientific problem. Each is visible in advance to an organization that can see across regulatory, medical, manufacturing, quality, supply, distribution, commercial, and payer activities at once.
Unipr connects those workstreams into a single launch critical path, continuously exposes what is not ready, and prepares the alternate playbooks for an accelerated approval or a restricted label before the label arrives. Two Unipr customers ran their launches this way. One reached first sale in under two days, the other in under six, against a 63-day industry average.
Insight | How Gilead's Livdelzi Began Earning Revenue Within 24 Hours of Approval
Portfolio growth should increase capacity. Not coordination overhead.
As programs multiply, coordination work multiplies with them. Status has to be collected, plans reconciled, governance prepared, dependencies chased, resource conflicts resolved, and changes carried from one workstream to every other place they matter. Assignments get made on who is free and who is known rather than on skill, evidence, or workload, so scarce expertise sits on the wrong problem while the critical path waits.
Much of the work performed by highly capable program teams is not judgment. It is finding, translating, and reconciling information so that judgment can happen. That cost is why three to twelve months pass between formal portfolio reviews while the evidence behind them changes continuously.
Unipr automates that layer of work: collecting status, surfacing dependencies, escalating exceptions, maintaining launch readiness, and matching work to people by skill, experience, capacity, and priority. The goal is not fewer people. It is a portfolio that can grow faster than the coordination work required to run it, and teams spending their time on judgment rather than assembling the inputs to it.
Insight | The Question Your Portfolio Review Never Truly Answers
Who we are
Unipr has built operational technology for life sciences since 2012, has been live in production for more than twelve years, and has supported more than 500 product and indication programs across 12 of the top 50 biopharma companies. Our longest relationship has run continuously since 2014, in oncology launch. Unipr is built for all ten sectors of the industry, and its deepest proof is in biopharma.
We started because life sciences was running its programs on tools designed for other industries. Those tools arrived empty. They had no model of a clinical stage gate, a pivotal readout, a regulatory submission, or a commercial launch, and no sense of how tightly ten functions are woven together here. Teams adapted them and made them work, with people as the glue, rebuilding the same picture in a different format every month.
So we built the alternative, and it now stands on four parts that operate as one environment. Intelligence is the foundation the other three rest on: a curated evidence base of 24+ integrated databases and 340M+ records, so a timeline, a budget, or a risk reflects real industry evidence rather than a model's guesswork. Platform is where Unipr began in 2012 and remains its core: eighteen AI-native applications spanning project, program, portfolio, resource, budget, and scenario work, built as one system rather than assembled from separate tools. Ecosystem is how context travels: more than 91 connectors linking Unipr bidirectionally and in real time to the systems you already run, so it can work around an incumbent system of record instead of replacing it. Agents are fourteen production AI specialists that plan, resource, analyze, and coordinate across all of it, producing structured, auditable deliverables rather than freeform text.
Predictive AI arrived in the platform in 2014, Generative AI in 2022, and Agentic AI in 2024. Our AI does not reason only about tasks, dates, and assignees. Built on a platform that already modeled stage gates, pivotal readouts, regulatory submissions, and launches, it reasons about what a milestone means, what depends on it, and what happened the last time one like it moved.
Why now
Every day between a finished medicine and a treated patient is a day someone waits. That has always been true. What has changed is that the tool for doing something about it is no longer scarce.
The best AI is becoming something any organization can buy. Same models, same access, same price list. Each advantage in turn has stopped being one. Compute was an advantage until you could rent it by the hour. Frontier models were an advantage until good ones began arriving every few months. Proprietary data looked like the moat that would hold, but data is a record of decisions already made. It tells you where an organization has been. It does not tell you what it can do next.
When everyone holds the same tool, the difference is in the hands holding it. The gap comes from three things: how clearly an organization sees what its own people can actually do, how reliably a decision made in one place becomes true in every other place it matters, and how much of what it learned last time is still available this time. We call that Organizational Intelligence. Perceive, coordinate, learn.
Scientific time is what it is, and no software shortens a six-month stability study. Everything layered on top of it is organizational time, and that is what has only recently become addressable, because the systems carrying the work have finally begun to understand what they are looking at. The winning organizations of the coming decade will anticipate rather than react. Coordinate rather than collide. And deliver medicines while others are still diagnosing delays. Discovery earns headlines. Delivery saves lives.
What we deliver
Four things go wrong in every program. Three cost weeks at a time. The fourth costs years and is almost invisible while it does.
Every function holds a good plan for the medicine, yet nothing holds the program together. Unipr draws on the functional plans regardless of source tools and builds the true cross-functional program critical path. Work breakdown structures arrive benchmarked against real programs, with P50 and P80 confidence-rated durations and the activities driving schedule risk named rather than buried.
Something changes, and the implications take weeks to reach the people they affect. Unipr identifies every affected program, study, milestone, budget, and person at once, semantically matching events across functions recording them under different names. Scenario alternatives are prepared before they are needed, each carrying probability, impact, and the criteria for switching to it. Signal to decision to action in days, not weeks.
Scarce expertise gets assigned by proximity and availability rather than by fit to the problem. Unipr matches work on skill, experience, and capacity at task level, against portfolio priorities. Skill here means a taxonomy of 376 roles and 3,668 skills with endorsed expertise levels, and experience counted as tasks actually executed, rather than a job title standing in for capability. With the right people on the right work, deliverable quality improves, and bottlenecks clear earlier.
The reasoning behind a decision leaves with the people who made it. Unipr keeps assumptions and alternatives attached to each decision, so fewer are remade from scratch, and each one carries a defensible record of how it was reached.
Underneath those four sits the analysis. Risk registers with probability-impact scoring, costed mitigations, and how risks cascade. Portfolio optimization scenarios, stress tested across competing programs. Program economics with risk-adjusted NPV, sensitivity analysis, and Monte Carlo simulation on sector-specific assumptions. Governance checked against twenty-three tests, GxP aware. Board-ready visualization driven by natural language.
Agents attached to project tools reason only over the data inside them, which is your own history. Unipr's agents reason over yours and over a curated evidence base drawn from thousands of programs planned, managed, and benchmarked beyond your walls, so a duration or a probability reflects what happens in your industry rather than only what happened in your instance. Your programs stay in your environment, and never train a model made available to anyone else.
Every output states its confidence with a one-line reason, grades its citations by authority, and closes with what it did not analyze. Where sources disagree on a material point, the contradiction is named with the role responsible for resolving it. Each output says what it is: an analytical recommendation, not an approval, a decision, or a compliance attestation. The decision stays with the person accountable. That is deliberate, and it is why the work survives an audit. "The AI told me so" is not a compliance defense.
Values that drive how we do everything at work
As a Public Benefit Corporation, from day one we have committed to work towards the shared success of our employees, customers, and our community, in addition to our investors and shareholders.
Integrity
Being fair, honest, and upfront at all times. Doing the right thing by our employees, customers, and investors. Showing consistent and uncompromising adherence to moral and ethical principles while striving for success.
Reciprocity
Treating others like we want to be treated. Feeling about others like we want others to feel about us. Thinking about others like we want to be thought of. Speaking to and about others like we want to be spoken to and spoken of.
Professionalism
Doing our best work, being our best, and striving to be a little better each day. Taking ownership and being responsible for outcomes in our control. Leading by our actions and inspiring others around us with our work.
Communication
Listening with purpose, seeking first to understand the emotions and intentions behind the information being transmitted and received. Conveying with clarity and simplicity, in a timely and transparent manner.
Where we work from
Our core team is based at our headquarters in California. Yet, most of our team works remotely all across the world.
Bay Area, CA
333 W San Carlos St, Suite 600
San Jose, California 95110
Worldwide
Work from anywhere and at any time. Deliver outcomes. Meet expectations.
Start Building Today
Log in or create a free account to scope, build, map, compare, and enrich your projects with Planner.
Compliance
Unipr is built on trust, privacy, and enterprise-grade compliance. We never train our models on your data without your explicit request.
