Clinical trials are one of the slowest and most expensive processes in modern medicine.

It can take 10–15 years and up to $3 billion to bring a new drug to market — and many trials fail simply because they can’t enroll enough patients.

In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Dr. Chadi Nabhan, Chief Medical Officer at RyghtAI, to explore how AI-powered digital twins of clinical trial sites can dramatically improve the speed and success of clinical trials.

RyghtAI has built a platform that creates digital twins of thousands of clinical trial sites worldwide, allowing pharmaceutical companies to instantly identify the best locations and investigators for any given trial.

Instead of relying on manual site selection or reputation-based decisions, AI analyzes historical trial performance, patient demographics, biomarker capabilities, and infrastructure to determine which sites are most likely to enroll patients successfully.

The result: faster trials, better patient representation, and potentially life-saving therapies reaching the market sooner.

In this episode we discuss:

• Why 80% of clinical trials fall behind schedule
• Why half of clinical trial sites enroll 0–1 patients
• How AI parses 200-page trial protocols in seconds
• The role of digital twins in predicting trial success
• How AI improves patient diversity in clinical trials
• Why biomarker data is becoming essential in modern medicine
• How AI agents infer site capabilities from historical trial data
• Why informed patients using AI tools may actually improve healthcare outcomes

If AI can dramatically improve the speed and efficiency of clinical trials, it could reshape how quickly new treatments reach patients worldwide.

⏱️ TIMESTAMPS

(0:00) Welcome to Built This Week
(0:37) Introducing Dr. Chadi Nabhan from Ryght AI
(1:12) What RyghtAI is building
(2:14) The problem with clinical trial site selection
(3:07) Digital twins for clinical trial sites
(4:01) Manual vs AI-driven trial strategy simulation
(5:15) Why clinical trials fail
(6:03) The massive cost and time of drug development
(6:51) How AI identifies the best trial sites
(8:00) Ranking clinical trial sites using AI scoring
(9:03) Diversity challenges in clinical trials
(10:02) Using census data to improve patient representation
(10:35) Biomarkers and genomic trial requirements
(11:48) Predicting future trial success from past data
(12:14) How AI accelerates trial matching
(13:04) AI agents reading clinical trial protocols
(14:20) Parsing 200-page protocols in seconds
(15:00) AI identifying investigators and site contacts
(15:57) Helping overlooked clinical sites get discovered
(17:47) AI’s expanding role in healthcare innovation
(18:00) Eight Sleep raises $50M at a $1.5B valuation
(21:09) Apple releases a $599 MacBook
(23:00) Dr. Nabhan’s upcoming book: AI and Cancer Care
(23:33) Will AI replace Google for patient research?
(25:30) The future of personalized AI healthcare
(26:10) Final thoughts and wrap-up

🔗 LINKS

Ryght AI
https://ryght.ai

Dr. Chadi Nabhan
https://chadinabhan.com

Built This Week
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🎙️ HOSTS

Jordan Metzner
https://linkedin.com/in/jordanmetzner
https://x.com/mrjmetz

Sam Nadler
https://linkedin.com/in/sam-nadler-1881b75
https://x.com/Gravino05