On October 28, 2019, Saama Technologies’ Chief Strategy Officer Sagar Anisingaraju participated in a panel discussion titled “Future Visions: Are We Heading to Heaven, Hell or Purgatory?” at MAGI’s Clinical Research Conference – 2019 West in Las Vegas. The following is Part 1 of 4 installments of the excerpted discussion, moderated by Jonathan Zung, Ph.D., member of Saama’s Clinical Board of Advisors and EVP, WCG.
Jonathan Zung: Sagar, can you give a brief introduction and explain what led you to this journey towards clinical research?
Jonathan, thank you. It is my pleasure to be here today and discuss the topic that is near and dear to all of us in this room. We are based out of Silicon Valley and have been in business for 22 years, developing Systems of Insights.
About five years ago, we asked ourselves the inverse of the question that you are exploring here today, and did a study. We were looking backward; what did clinical research look like in the past five, ten years, twenty years?
We analyzed all the past studies that were conducted from publicly available databases. We went thru several dimensions, therapeutic areas, geographies, size of pharma, patient densities, site locations, cost elements, reason codes for abandonment, etc. We talked with several Clinical Ops heads across pharma. We were not clinical research experts, and were mostly interested to look at the issues from a data perspective across dimensions. Not knowing the area as much as most of you here do allowed us to ask some stupid questions and get a different perspective of empirical data from past studies.
And then we did what a geeky tech company would do: we put all of the data that we could gather into learning models to come up with a simple 2×2 outcome; on-time and on-budget being the two axes. The result was simple, but an eye opener for us. Less than 5% of total studies were on-plan. A good majority were way over budget, time or had been abandoned. However the key attributes that were causing time and cost overruns across the spectrum were finite and very similar across pharma. These may be no surprise to any of you: insufficient patient enrollment, lack of efficacy, SAEs, protocol deviations, and unavailable study personnel were some of the common, repeating problems across all studies.
The striking commonality of the problem and attribution gave us an indication that technology and AI can help pharma transform this state of affairs. The tech industry has been successful in driving down costs while improving speed and capability exponentially, year over year for the last 30+ years. We felt that we could create pharma’s version of Moore’s Law to bring similar changes to the industry, and started talking to pharma execs. That’s how our journey of reimagining the clinical trials ecosystem started.
We genuinely believe that the clinical trials ecosystem is fundamentally going to transform over the next five to ten years, and that it is possible to radically change the 2×2 matrix that I explained earlier. Where the cost of drug development would not be $3B but maybe $300M dollars over the next decade.
Jonathan: In your view, what is likely to be the most disruptive in the conduct of clinical research?
Visibility and reusability of data and insights across clinical research is going to be one of the most disruptive changes we will see. Let me elaborate. As a consumer of this century, we are in a hyper-aware mode for everything that we consume. We know what products are available, which vendors are offering them at the lowest price, and what the society at large is Yelping about them to form our opinions and make the most optimal decisions at any point in time. Why should clinical trials be any different? Why should information and insights about them be confined within pharma, within a study, or within a CRO?
We are seeing a few initiatives that the industry has taken up towards visibility. Network-enabled adaptive platform trials, such as I-SPY 2, LLS, industry consortiums, CT.Gov, etc., are steps in the right direction but are only touching the basics.
I feel that this will dramatically change over the next few years. First, we will see the development and adoption of common definitions of data related to studies, making the insights generated across the various stages of a study visible and accessible to every player in the ecosystem. Second, we will see learning platforms emerging which enable these insights to be reused across pharma, CROs, patients and hundreds of other players. The tech industry did not exponentially grow with every company building their own CPUs. Why should every pharma start from scratch? Building blocks for clinical trial CPUs and other peripheral devices will emerge to enable the industry to collectively leapfrog and focus on what they are best at, that of innovating drugs for patients.
Moderator: Jonathan Zung, Ph.D.
Member of Saama’s Clinical Board of Advisors and EVP, WCG
Speaker: Sagar Anisingaraju
Chief Strategy Officer of Saama Technologies.