By Rohit Nambisan, CEO & Co-founder at Lokavant
In a world where precision science is transforming how we develop new therapies, one part of the clinical trial process remains frustratingly primitive: how we forecast and plan studies.
Despite billions spent on innovation, many trial teams are still relying on manual processes, gut assumptions, and outdated tools when trying to answer critical questions like: Where should we run this study? How long will it take? What’s the risk of failure?
The truth is, we’re building the future of medicine on a foundation of inadequate information and guesswork - that has to change.
Clinical trials are getting more complex—more countries, more complex designs, more pressure to deliver faster. But when it comes to planning and feasibility, most organizations are using static models and labor-intensive methods that cannot keep up.
It’s no wonder timelines slip, amendments multiply, and costs balloon.
Here’s what I’ve observed again and again:
We don’t just have an efficiency problem. We have a visibility problem.
When you cannot forecast accurately, risk hides in the gaps. Delays become normal, amendments pile up, and patients wait. This has become the status quo for clinical trials.
And it’s not because teams lack data. It’s because the systems and thinking we’ve relied on were never built to handle today’s complexity—or tomorrow’s uncertainty.
At Lokavant, we’ve analyzed over 500,000 historical clinical trials, and one thing is clear. No two studies are exactly alike, but there are patterns—if you know how to find them.
We’ve learned that combining different AI approaches—generative AI to process protocol criteria, machine learning to model scenarios, and causal AI to recommend optimization paths—can give teams a clearer, more adaptive forecast than ever before.
Not a static prediction, but a living model. One that updates with every new decision, every amendment, every market shift.
That’s the kind of intelligence that study teams need to provide to ensure accurate study outcomes.
The clinical research industry is at a crossroads. External pressures—from regulatory changes to geopolitical shifts—are creating more volatility. Meanwhile, the cost of trial delays has never been higher.
It’s time for a new standard: one that brings the same level of precision to operations as we demand from science.
In the coming days, we’ll be sharing something new. It’s not just another feature but a reimagined approach to clinical trial forecasting—built to reduce uncertainty, accelerate decisions, and empower the people closest to the work.
We believe clinical research teams deserve clarity, not chaos.
More to come soon. If you’re ready to be part of the change, look for an exciting announcement coming soon.
(Originally published on LinkedIn)