Preclinical research often suffers from fragmented data systems and siloed teams, masking early toxicity or failure signals. As a result, critical insights do not get shared in time, causing repeated missteps and wasted resources. Without unified knowledge management, it becomes nearly impossible to consistently prioritize the most viable candidates, leading to high attrition rates.

Operations AI dismantles silos by coordinating biology, chemistry, and toxicology teams in real-time. By sharing critical insights across projects, each preclinical effort benefits from collective knowledge. The heightened data transparency and execution consistency improve experiment reproducibility, reducing overall attrition rates. Through multimodal portfolio prioritization, Unipr AI helps research leaders consistently focus on the most promising pipeline assets, increasing the probability for more assets to achieve IND readiness.

Insight | Multibillion Dollar Portfolio Decisions: When Guesstimates Aren’t Enough

Development timelines stretch on due to fragmented trial coordination, slow go/no-go decisions, and manual data handling across multiple parties. Critical functional handoffs from research to development or from clinical to regulatory submission often introduce further delays and last-minute surprises. Consequently, inadequate foresight and cross-functional alignment during development can easily push the overall timelines to a decade or more.

Operations AI unifies data across R&D, clinical, and regulatory functions, providing a single source of truth for every stakeholder. By automating routine tasks and analyzing dwell times, candidate attrition rates, and resource demands across stages, Unipr AI pinpoints bottlenecks early and suggests optimal timelines, budgets, and resources for different modalities in different phases. Real-time visual dashboards offer a comprehensive view of portfolio performance on a single page, enabling instant deep dives into specific stages or milestones. This holistic, data-driven orchestration streamlines decision-making, improves cross-functional alignment and ultimately compresses development timelines from years down to more manageable spans.

Insight | Why Connecting Data Isn't Enough? The Coordination Imperative for Accelerating Medicines

Misaligned handoffs between R&D, manufacturing, quality assurance, and supply chain frequently delay product availability even after regulatory approval, with complexities in process scale-up, equipment readiness, and external collaborations exacerbating operational bottlenecks. Once the product is produced, fragmented distribution channels, payer negotiations, and prescriber education add further delays. Moreover, global launches face hurdles from country-specific regulations and distribution infrastructures that disjointed systems or third-party vendors can compound. As a result, newly approved therapies often take weeks—or even months—before they reach the patients who need them.

Unipr AI’s scenario-planning capabilities model a range of potential launch conditions—e.g., accelerated approvals or restricted product labels—and instantly adapt the launch playbook rather than forcing teams to scramble at the last minute. By orchestrating hundreds of parallel tasks across marketing, training, distribution, and payer engagement, it eliminates gaps where one group is waiting on another, enabling the entire organization to move fluidly and proactively. With Generative AI, leaders can simulate multiple reimbursement and distribution strategies in real-time, equipping launch teams with actionable insights for each strategic path. The Operations AI-powered launch coordination ensures that every stakeholder persistently stays aligned on the same real-time plan, making same-day availability of new therapies upon approval far more attainable worldwide.

Insight | How Gilead's Livdelzi Began Earning Revenue Within 24 Hours of Approval

Large pharmaceutical organizations often channel 40–50% of their revenue into R&D and SG&A functions, yet much of that spending is undermined by inefficiency and duplication. Mergers, legacy IT systems, and disjointed processes create complex, siloed environments where critical workflows (e.g., pharmacovigilance, quality assurance, and supply chain management) demand significant manual effort. With operations spanning over 100 markets and multiple product lines—on top of extensive compliance and oversight requirements—redundant workflows further drive up costs. Although heavy R&D investment is vital, insufficient automation and fragmented knowledge sharing frequently lead to inefficient operations and higher headcount than truly necessary, all while many projects continue to fail or perform suboptimally. As a result, these compounded inefficiencies can keep operating margins low, even with healthy gross margins.
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Unipr AI reduces operational friction by seamlessly aligning and coordinating workflows across R&D, Commercial, and Supply Chain in real-time, enabling smoother decision-making, faster problem-solving, and superior execution efficiency. With Predictive AI, leaders gain granular insight into which activities deliver the most value, allowing them to reallocate resources in real-time with precision and focus on the highest-return opportunities. End-to-end operational excellence uncovers underperforming functions—whether in manufacturing, trial management, or portfolio strategy—so companies can streamline operations before costs balloon. By empowering management to make targeted, data-driven improvements rather than blanket cuts, Unipr AI helps lower overhead, maintain a strong pipeline, and ultimately push operating margins beyond the 40% mark.

Insight | The Era of Operational Excellence