"AI helps those who use it, while those who don't may be left behind."
Orr Inbar is a healthcare entrepreneur, and applied AI-researcher, with a passion for fixing broken processes within healthcare by leveraging next-gen technologies.
Orr’s experience in life-science, and clinical development in particular, is what led him to found QuantHealth, as he identified disparities in clinical research that could be overcome with novel quantitative methods to increase the success rate of clinical trials.
Prior to QuantHealth, Orr co-founded ConcertAI, a Boston-based unicorn specializing in real-world data and precision oncology. Before that, he led a machine learning team at Decision Resources Group, and was a data scientist specializing in life-science strategy at Signals Analytics.
Orr holds a masters in Information Technology from Harvard University, and a B.Sc in Biochemistry from the University of UMASS Amherst.
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Table of Contents
We are thrilled to have you join us today, welcome to ValiantCEO Magazine’s exclusive interview! Let’s start off with a little introduction. Tell our readers a bit about yourself and your company.
Orr Inbar: Fast and accurate clinical trials have become increasingly important but clinical trials can often be the bottleneck for drug development.
Clinical trial failures, which amass a $50B annual loss, are mostly the result of poor protocol design processes that are driven by intuition, current knowledge and historical data.
Knowing this, with my technical background in data science, biomedical research, software engineering, and artificial intelligence, all with a focus on healthcare, I created QuantHealth.
90% of drugs fail the clinical stage, representing a direct $50B annual waste to pharma companies. To address this challenge at its core, QuantHealth’s Clinical-Simulator predicts how each patient in a clinical trial will respond to treatment, allowing trial design teams to predict how many different clinical trials will play out, and optimize trial design.
Based on its novel AI engine and a vast dataset of 350m patients and over 700K therapeutics, QuantHealth’s simulator can predict clinical trial results with 86% accuracy, allowing users to answer mission critical questions such as cohort optimization, indication selection, in-licensing asset evaluation, and more.
Prior to QuantHealth, I co-founded ConcertAI, a leader in precision oncology, where I led data science and engineering.
Prior to that, I held a variety of leadership roles in small and large life-science technology companies in Israel and the US, where he led R&D, product development, and customer delivery teams.
I have an MA in Information Technology from Harvard University, and a B.Sc in Biochemistry from the UMass-Amherst.
Can you share with us your journey towards integrating AI into your business operations?
Orr Inbar: My background in data science, biomedical research, and AI led me to know that integrating AI into businesses will remain crucial to improving accuracy and efficiency across all industries, and especially healthcare.
Before QuantHealth, I co-founded ConcertAI, a leader in precision oncology, where I led data science and engineering. After ConcertAI, in founding QuantHealth, AI was the foundation of the business.
I saw how it was clear that the decreasing success rates of clinical trials was becoming an untenable situation for the industry and with hardly any solutions having been developed, I knew this was something to be solved.
What specific areas of your business have been most impacted by AI, and how?
Orr Inbar: Within the healthcare industry, there have been significant strides to incorporating AI to help improve patient outcomes and industry worker experience.
In creating the AI solutions, it is necessary to evaluate where the gaps are. In the clinical trial space specifically, there are major gaps in research.
Through AI, we are taking the steps to close those gaps with data-backed information to expedite, derisk, and optimize drug development.
The integration of AI within this sector of healthcare opens up new opportunities to develop specialty drugs as well as advance and transform the way clinical trials operate.
What are the biggest obstacles you’ve faced in implementing AI, and how did you overcome them?
Orr Inbar: Some of the biggest obstacles include laying the foundation to gather good research and high quality solutions, to surpass the reputation of faulty AI solutions in the industry.
AI can amplify human prejudices rather than avoid them. Machine learning learns from data, and many records contain or reflect implicit, societally ingrained bias.
Through our access to a dataset of 350 million patients, large biomedical knowledge-graphs, and clinical trial data, QuantHealth has been able to develop modern technology to predict outcomes of 86% accuracy.
The importance lies in having the right research and data to inform accurate outcomes.
What advice would you give to other CEOs looking to integrate AI into their business?
Orr Inbar: It is critical to look at AI as a tool that can solve well defined problems and inefficiencies within existing business workflows, and not as a general technology that can solve everything.
Although generative AI has brought us closer than ever to general artificial intelligence, we are still far from AI replacing people en masse.
AI will not replace employees on its own, rather, employees leveraging AI will replace those who don’t.
How do you see AI evolving in your industry over the next 5 years?
Orr Inbar: AI has already made a profound impact on drug discovery.
Over the next couple years we will see dramatic adoption of AI in later stages of drug development, particularly preclinical and clinical development.
Once AI will be proven in clinical trials, together with greater penetration of AI into healthcare at large, we will start to see regulators begin to look more closely into AI to support drug approvals as well as improve their own internal processes.
What does “success” in 2024 mean to you? It could be on a personal or business level, please share your vision.
Orr Inbar: QuantHealth measures success across multiple variables. On the simulation side, reduced time to simulation is a key factor in driving more efficient results from trials, which QuantHealth has reduced from six months to one month.
Accuracy compared to real world results is just as important, and QuantHealth boasts an 86% accuracy rate on average.
Growth is also a measure of success for QuantHealth. This year, they’ve doubled their employee count from 14 to 28 to support the scaling of their technology.
Included in this growth is their recent hire of a Chief Commercial Officer and General Manager of U.S. operations, which marked the Israeli company’s entry in the U.S. market.
Additionally, they’ve onboarded three new customers onto their platform, including biotech and pharmaceutical companies. Furthermore, the company has crossed $1M in ARR, and doubled their YOY revenue in 2023. We strive to be the premier clinical operating system for pharma companies.
Brooke Young, VIP Contributor to ValiantCEO and the host of this interview would like to thank Orr Inbar for taking the time to do this interview and share his knowledge and experience with our readers.
If you would like to get in touch with Orr Inbar or his company, you can do it through his – Linkedin Page
Disclaimer: The ValiantCEO Community welcomes voices from many spheres on our open platform. We publish pieces as written by outside contributors with a wide range of opinions, which don’t necessarily reflect our own. Community stories are not commissioned by our editorial team and must meet our guidelines prior to being published.
