Platform combines proprietary longitudinal data with agentic AI to provide unparalleled insights into the longevity biotech landscape.
Longevity.Technology today unveiled DLT (decoding longevity trends), a new AI-native intelligence platform designed to bring structure, clarity and analytical power to a rapidly accelerating longevity ecosystem. The move is the start of an evolution for the sector’s leading media brand, as it becomes a data-centric intelligence platform for the global longevity industry.
The company is first releasing DLT Biotech – a comprehensive database covering more than 600 longevity-focused biotech companies. Many are self-declared longevity biotechs, while others are small- to medium-sized companies working on aging pathways and the treatment and prevention age-related diseases.
“We’re turning the longevity ecosystem into a living, queryable dataset,” said Phil Newman, CEO of Longevity.Technology. “We’ve started with longevity biotech and aging disease therapeutics as these are the most complex to build and train our AI systems on. Now we’ve completed this work, we’ll move quickly to cover the rest of the longevity industry.”
DLT Biotech captures detailed information on each company’s science, high-fidelity analysis of all pre-clinical and clinical assets in development, technology platforms, intellectual property, teams, competitors and partnerships, layering this with intelligent tools for watchlists, landscapes, deal spotting and portfolio monitoring.
Live dashboards provide high-level visual insights, while an integrated chatbot allows users to ask complex, nonlinear questions of the dataset, surfacing results that would be difficult or impossible to compile manually. The platform also offers detailed profiles of company leadership and scientific advisory boards, with direct links to individual LinkedIn profiles, adding a valuable layer for business development, collaboration and recruitment.
While DLT Biotech is the platform’s first module, additional verticals will follow, including expansion into longevity clinics and, ultimately, coverage of the full spectrum of companies in the space, from supplements, ingredients, diagnostics and digital platforms to future markets, including cryonics, BCI, advanced bionics, organ and tissue growth.
For now, biotech-focused organizations are invited to book a 15-minute demo and explore the system, currently in a paid beta phase, for themselves.
Longevity.Technology: With the launch of DLT, Longevity.Technology is doubling-down on the future of the longevity sector – a market predicted to hit $46 billion by 2031. At a time when capital, innovation and deal activity in longevity are accelerating, DLT aims to put a powerful new layer of market intelligence into the hands of partners, investors, pharma and biotech companies. To find out more about the platform’s origins, we sat down with Longevity.Technology founder Phil Newman.
Newman explains that DLT has been built in response to a long-standing problem in the field: investors, pharmaceutical companies and biotech operators have historically had to piece together market intelligence from multiple sources, with critical data on companies, clinical programs, financing, scientific approaches and partnerships scattered, outdated or locked behind paywalls.
“It was back in 2021 that we first decided that we wanted to deeply categorize the industry so that we could analyze it properly,” says Newman. “So we created 25 individual domains of longevity, covering everything from cellular reprogramming through to reproductive longevity and even pet longevity.”
Making data ‘come alive’
Longevity.Technology then started to look at ways to make its database “come alive” – integrating company data with investment data to produce annual reports that show how much capital is flowing into the industry and at what stages.
“At that time, there wasn’t sufficient traction in the industry, and there were very few dedicated longevity funds that would be interested in accessing and paying for that data,” says Newman.
That changed in 2024 when Longevity.Technology was asked by a Top 10 pharmaceutical company if it was prepared to enrich its data to provide much more granularity about the work happening in the longevity field.
“While we understood the companies and their capitalization, we didn’t really understand the granularity of the science and the trajectories to licensing deals and exits,” recalls Newman. “We needed to understand: what drugs are they working on? What is the clinical stage? What is the therapeutic focus? What are the mechanisms, hallmarks and pathways they targeting?”
More importantly, explains Newman, Longevity.Technology needed to understand not just whether a company might succeed in its chosen disease area, but how its work relates to aging throughout the body.
“Are these drugs potentially successful in one therapeutic area only, or do they have crossover benefits?” he says. “Will they become multi-disease preventive therapies in the future?”
Data collection never stops
It took Longevity.Technology’s research team six weeks to conduct a deep manual analysis of the first 40 biotech companies.
“That tells you how much human time is needed to produce this level of insight,” says Newman. “In parallel, we started building an AI agentic system to help automate the gathering and structuring of this data.”
The human-created research became training data for the AI system, and the team tested the AI’s output against those 40 companies to refine its accuracy.
“This gave us two complementary approaches: AI plus human validation,” says Newman. “But human validation still proved onerous, so the development team created a second, completely independent AI system to judge all data from different sources. The final pass is always our human research team, and we’ll also be validating directly with the companies themselves in a continually rolling process.”
This work led to today’s first release of DLT Biotech to paid-beta users, a comprehensive database of more than 600 biotech companies, with around another 120 still to be added over the next month, ahead of full commercial availability.
“Data collection never stops. Companies are constantly raising capital, progressing through clinical stages, succeeding or failing, and new companies are being created all the time,” added Newman.
DLT Biotech is designed for three primary audiences
- Pharmaceutical business development teams can use it to identify and track promising assets across clinical stages, particularly as companies approach costly Phase 3 trials where partnerships and licensing deals become critical.
- Biotech investors can gain a clearer view of emerging trends, whether in areas like partial cellular reprogramming or mitochondrial dysfunction, while still filtering by conventional disease verticals such as cardiovascular or neurological conditions.
- Longevity biotechs themselves can use DLT to benchmark competitors, assess potential in/out-licensing opportunities and monitor shifts in the broader market.
“We’re collecting data points that, to my knowledge, other platforms don’t track, such as the hallmarks of aging and specific therapeutic modalities,” says Newman. “Other platforms are more focused on approved drugs and post-market tracking. Our sweet spot is preclinical and clinical-stage longevity biotech, specifically around aging drivers and mechanisms. We’ve built the entire platform around the thesis that the market increasingly wants to identify future longevity drugs, both in terms of their disease targets and their impact on aging biology.”
By way of an example, Newman says he asked several of the market-leading large language models to name all the cellular reprogramming companies. “They typically returned eight to ten, but we already have around 31 in our dataset,” says Newman. “That level of granularity is a key differentiator that demonstrates the fidelity of our data.”
In terms of the evolution of Longevity.Technology, Newman describes it as a “natural progression” for the company he created.
“We’re moving from a media business into a truly data-centric platform that supports the growth of longevity companies,” he says. “The industry is now ready. The biotech winter is over, more capital is flowing into the space, and we’re turning the entire longevity landscape into a living, queryable dataset.”
