Health & Life Sciences Research Tech

Where technology meets humanity.

Wednesday, Aug 19th at 12:00 PM ET

Introductory Presentation by Greenbook + Tech Demos with Live Q&A

See agenda

Agentic AI is spreading quickly across the research workflow. Even without this new level of autonomy, research automation can make the work seem less intimate for researchers, perhaps diminishing their sense of connection to participants or research tasks. What can this kind of disengagement mean in a domain where the research participants are patients, caregivers, and clinicians making life-affecting decisions?

The platforms built for health and life sciences research are streamlining workflows, and solutions can be as varied as the research contexts. For example, patient community platforms now generate regulatory-grade evidence; decentralized trial infrastructure has become a primary research channel; and AI-powered advisory systems have compressed workflows that once took months.

AI is now part of almost every vendor pitch, and vendors are more likely to be better at explaining their tech than they are at explaining your practice. Adaptive interviews, agentic research deployment, synthetic control arms, and conversational RWE analytics land differently depending on your therapeutic area, your compliance environment, and what you already have in place. It helps to have the ability to translate your needs into their capabilities and vice versa.

Join us Wednesday, August 19th to see health and life sciences research technology in action!

Explore how to adapt it to your workflow as we cover what distinguishes different types of solutions, discuss typical users and use cases, and what kinds of features you can expect now and in the near future.

Who should attend?

Pharma and biotech insights and market research teams
Patient experience and patient advocacy teams
Medical affairs and KOL engagement professionals
Clinical research and trial operations teams
Market access and health economics researchers
Research and insights buyers at any stage of evaluation

Greenbook's Guide to Health & Life Sciences Research Technology

Class

12pm ET

20 min

Health & life sciences research technology overview
Types of solutions
Key features
Next frontiers

Learn more

TriVoca Health: Rethinking Your Research Data Ecosystem: A Data-First Strategy for Faster, Smarter Decisions

Demo

12:20pm ET

20 min

Your teams generate an enormous amount of primary research every year — and most of its value quietly disappears. Studies get delivered, then scatter across vendors, drives, and inboxes where no one can find or reuse them. Without cross-organizational access, the same questions get asked twice, hard-won insight evaporates, and the fragmented data you're left with is exactly what makes it so hard to stand up the trustworthy AI that could help you decide faster.

There's a better way: a data-first strategy that rethinks your research data ecosystem. Instead of treating each study as a one-off, you capture and connect all your primary research into a single owned asset that compounds with every project — so the next study learns from the last, anyone can tap the data you've already collected, and you finally harness the value you're losing today. A consistent taxonomy is the foundation that makes it possible.

Join Isaac Rogers, CEO of TriVoca Health, to see a data-first research ecosystem in action — the tools used to build it, and what you can build on top of it, including AI that turns your collected insight into faster, smarter, decision-ready answers.

Map of the Landscape

See health and life sciences research technology as a set of distinct solution types addressing diverse use cases and leave with a framework for evaluating the differences.

The Features that Matter Most

Understand which capabilities are genuine differentiators as well as where AI is changing the workflow and where it isn't.

What to Ask Vendors

Leave with a clearer sense of your own requirements and the questions that separate genuine capability from a polished demo.