Lokavant has introduced a sophisticated new forecasting platform aimed at transforming clinical trial planning, using AI to drastically reduce timelines and improve enrollment predictability in a volatile R&D landscape.

The clinical trial intelligence company, has launched Spectrum v15, an AI-powered platform that the company claims significantly reduces uncertainty in clinical trial feasibility and enrollment forecasting. Powered by machine learning, generative AI, and causal AI, Spectrum reduces five weeks of manual analysis to five minutes and offers forecasts with more than 80% confidence, according to Lokavant.

At the core of Spectrum is Lokavant’s Clinical Intelligence Platform, built using data from more than 500,000 historical studies. This infrastructure allows for real-time scenario modeling that accounts for shifting variables—such as protocol amendments, site activation delays, screen failures, or patient dropouts—that typically derail clinical timelines.

“With the industry grappling with increasing complexity and volatility, we must move beyond static feasibility assumptions toward dynamic, data-driven adaptability,” said Jonathan Crowther, head of predictive analytics at Pfizer.

“Solutions like Spectrum exemplify the next generation of intelligent trial design. This isn’t just operational efficiency—it’s strategic foresight.”

Crowther said the ability to conduct live feasibility assessments and simulate outcomes under different scenarios helps R&D teams de-risk timelines, optimize budgets, and prioritize investments across their portfolios.

According to Lokavant, Spectrum allows sponsors and CROs to dynamically model trial feasibility across different combinations of countries and sites, both before study initiation and throughout its duration. The tool supports granular forecasting at the site, country, region, and study level, incorporating inputs across enrollment, discontinuation, and screen failure rates—even accounting for non-enrolling sites.

It also supports adaptive trial designs, enabling forecasting around multiple enrollment-driven interim analyses and protocol-defined pauses. Spectrum’s continuous integration of live study data enables users to compare ongoing performance with forecasted expectations and adjust course in real time.

The company said the solution is already being adopted by global biotech sponsors to guide early feasibility planning and monitor ongoing enrollment performance. The company emphasized Spectrum’s ability to quantify the level of uncertainty with each variable change—functioning similarly to predictive weather models.

“As an industry experiencing unprecedented volatility, there is a great need to quantify uncertainty while identifying reliable paths to study enrollment success,” said Rohit Nambisan, CEO and founder of Lokavant.

“Spectrum analyzes country approval timelines, site activations, indication, and enrollment rates, leveraging the most advanced models to quantify levels of uncertainty with each forecast and each new variable. Like weather forecasting, predicting enrollment empowers teams to make better decisions.”

Lokavant positions Spectrum as a strategic solution in an environment where delays and inefficiencies not only inflate costs but can derail product launches and affect patient access to life-saving therapies. By offering dynamic, data-driven planning capabilities, the company believes Spectrum could set a new benchmark in intelligent clinical development.