Ben Vaughn

Chief Strategist, Biostatistics & Protocol Design

Ben Vaughn

Chief Strategist, Biostatistics & Protocol Design

A proven leader in the industry for more than 20 years, Mr. Ben Vaughn serves as Rho’s Chief Strategist for Biostatistics and Protocol Design. In this role, he utilizes his extensive expertise to guide sponsors through marketing applications, regulatory interactions, and the design and analysis of analgesia trials.

Mr. Vaughn has supported over 75 pain trials, over 30 marketing applications, and 6 FDA advisory committee meetings (both back room and bullpen) over the course of his career and has had speaking roles in dozens of FDA Type A, B, and C meetings.

His experience spans many therapeutic areas with emphasis on abuse liability trials, substance use disorders, as well as other psychiatric disorders and rare disease (orphan) products.

Mr. Vaughn earned both his bachelor’s and master’s degrees in Biostatistics from UNC-Chapel Hill.

Why Neurology and Analgesia?

“Neurology, and specifically pain-related clinical trials, is a fascinating area of research for me due to the obstacles that are presented. The outcomes are highly subjective and prone to influence by a number of factors completely unrelated to the investigational product being tested. Missing data cannot be ignored and novel analysis approaches are needed to evaluate their influence on trial outcomes. Addressing these concerns to the agency’s satisfaction is challenging but rewarding work.”

This is what drives Ben:

“Opioids have a place in the treatment of pain, but our understanding of their roles and risks has shifted over the course of my career. I am passionate about both ensuring their appropriate availability to patients that require them and finding products that can replace opioids. In the meantime, I am an ardent supporter of research to better understand treatment of substance use disorders and the role of prescription opioids in leading to such disorders, as well as the promotion of wide availability of medication assisted therapy and naloxone.”

Content by Ben Vaughn

Blog Post

Where did the odds ratios go?

Reviewing recent FDA approvals, you may be struck by the total absence of odds ratios. Browsing the labels from the 2023 novel approvals, you can find proportions, differences in proportions, Chi-Squared analyses, CMH and variants, but logistic regression and odds ratios have practically disappeared from labeling. What gives?


Unlocking sleep’s role in PTSD

Ben Vaughn, Rho’s Chief Strategist, Biostatistics & Protocol Design, supports Tonix Pharmaceutical’s analyses of how sleep disturbances impact posttraumatic stress disorder (PTSD). Their research sheds light on a novel treatment, TNX-102 SL, which targets sleep quality and emotional memory processing.


Leveraging Interim Analyses to Optimize Late Phase Clinical Trial Decision Making

Interim analyses (IA) are an essential part of clinical trials that—as a form of adaptive design—can help sponsors make informed decisions about whether to keep a trial going or discontinue it entirely. Join Rho’s Brett Gordon, Ben Vaughn, and Scott Mollan for this Q&A roundtable that will cover some of the most frequently asked questions they get from pharma companies about interim analysis.


Challenges with Fast Enrolling Post-Operative Acute Pain Studies

There are a lot of resources on how to deal with slow enrolling studies, but what about challenges with studies that enroll very quickly?  Enrollment can be very fast for post-operative acute pain studies which brings with it unique challenges in study execution. 

Blog Post

Maintaining Trial Integrity During COVID-19: Some Statistical Rules of Thumb

The COVID-19 pandemic is having a substantial impact on many ongoing clinical studies in all phases of product development. Numerous difficult decisions are being made and steps are actively being taken to ensure the safe execution, or future resumption, of ongoing studies. While patient safety is paramount and should drive all study conduct related decisions, many of these decisions can impact the interpretability of estimates of efficacy at study conclusion.