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95% of the eligible patients for a clinical trial are never considered. It’s time for a transformation.

Buzz in the Pharma industry continues regarding the application of machine learning to drug discovery. Industry leaders like Novartis and breakout startups like Recursion Pharmaceuticals are working hard to accelerate drug research with computational techniques.

However, the science of drug discovery is only half of the picture. Over 50% of the spend/time/pain associated with bringing a drug to market actually resides within clinical trial operations. This is the critical stage where promising treatments are delivered to patients to generate enough clinical evidence for commercial approval.

Phase 1 through Phase 3 clinical trials are the stages in which Pharmaceutical companies select research hospitals (sites), enroll patients, and collect data to build a base of clinical evidence for submission to regulatory bodies. This process is a critical step to validate pre-clinical scientific discoveries/theories, and is a phase that can take far too long.

Site Selection and the Clinical Trial Power Law

The lifeblood of any clinical trial is the patient base that participates in the trial and generates the clinical feedback that validates the drug. By and large, patients are recruited through the hospitals (sites) that are selected to run the trial. As a result, there is tremendous weight placed on site selection when a trial is getting launched.

Many clinical trials are still run largely manually, with large teams of people at Pharma companies and outsourced firms called CROs working together to launch and continuously operate a trial. As a result, there is a great deal of subjective human judgement involved to determine which sites are selected to be included in a trial.

This introduces inefficiency, but also something even more destructive: bias.

Ultimately, clinical trial hospital sites are chosen for a wide variety of reasons that are completely irrelevant to their ability to help run and complete a trial.

Sites are chosen because they are world-famous research hospital (like the old adage: “You can’t get fired for buying IBM”), because they have the best doctors or newest equipment, or because they have a prior relationship to the CRO/Pharma partner running the trial — all factors that may have little connection with their ability to actually run/complete trials. And so site selection today looks a lot like baseball scouting in the 1950s: “I like the way he swings the bat.”

70% of clinical trials are run by a select group of the top 5% sites. This effectively leaves the vast majority of sites, and by association the vast majority of patients, out of clinical trials. Industry experts estimate that only 5% of the eligible patients for a clinical trial are ever aware that the trial existed [1].

The Current Methods are Failing Us (and Patients)

At this point, there is consensus in the industry that clinical trials are broken. The statistics speak volumes toward an underlying problem in how these trials are run. I was personally stunned by these numbers:

• 80% of clinical trials are delayed due to patient recruiting
• 30% of sites chosen for clinical trials fail to recruit a single patient
• Of the patients that do enroll, 18% drop out at some point during a trial
• 85% of clinical trials fail to recruit enough patients [2, 3]

In addition to the current challenges, a number of macro shifts in the industry are putting additional pressure on clinical trials:

• Clinical trials are growing at a tremendous pace. The global clinical trial marketplace is expected to grow at a 6% annual CAGR to be a $60B+ market by 2026 [4]
• Blockbuster trials are larger and longer than before. Any drug with a commercial comparable requires additional data and scrutiny to justify approval. Industry calls this the “Better than Beatles” effect, and regulatory agencies require more patient data than before [5].
• Clinical trials are becoming more fragmented. As drugs continue to be developed for more niche patient populations, Pharma companies are being forced to expand trials to more sites in order to expand access to patients [6].

Enter Inato: Moneyball + Marketplace For Clinical Trials

Inato started out by partnering with some of the world’s largest Pharma companies to build a comprehensive dataset on all of the clinical trial sites in the world. By aggregating public and proprietary data, Inato is able to have a full picture on critical attributes of a hospital site such as: the number of trials that each site has run in the past, the disease and therapeutic areas of the trials run at each site, historical performance of the site in those trials, and the sponsoring physician involved.

Based on the industry data collected, Inato has shown that there is no real correlation between how many clinical trials a site has run in the past and how successful a site is at completing a new trial. There are many low-activity sites that have historically performed as well or even better than the most experienced sites.

Trial performance by quartile is not correlated to how active a clinical trial site is

Given this crucial realization, Inato has since expanded the scope of the company to activate these overlooked, “untapped sites” by helping them get enrolled in trials, and delivering support to perform against new trials. The company’s product breaks down into two key pieces:

1. A “Moneyball” engine (Given the baseball comment earlier, you know that this was coming). Inato uses data science and ML to better match potential sites for a specific trial’s protocol, and to remove bias from that decision. This allows Pharma companies to access a larger group of sites for a trial, and as a result, access to a larger patient population. These are patients that are ignored today simply because they don’t happen to be treated at a “top” clinical trial site.
2. “Future of Work” software tools for sites. For sites that choose to participate in Inato’s managed marketplace, Inato offers dedicated software to lighten the administrative overhead involved in running trials. This contributes to bridging the experience gap that less active sites have and increases the success rate of new trials that are matched to these sites.

Inato believes that the future of clinical trials is sitting right in front of us. In the space between the current industry practice of repeatedly enrolling prominent research sites and the far-out vision of running fully decentralized trials, lies the real opportunity: bring clinical trials to sites that already have research experience. There is a long history of Silicon Valley startups using software to streamline inefficient marketplaces and this might be one of the most important yet.

We are excited to lead Inato’s Series A and support Kourosh, Will, Liz, and the rest of the team to build a truly transformation company in clinical trials.