Intelligencia Uses Artificial Intelligence To Provide Data Clarity For Pharma, Bridging The Gap Between Innovation And Risk Reduction
The 2011 movie Moneyball taught viewers valuable business lessons about behavioral biases and limitations of human judgment which can ultimately lead to poor decisions. In a similar way, Vangelis Vergetis co-founded Intelligencia to address the what-ifs of human decision-making by creating an AI software that helps de-risks drug development by estimating the risk of clinical trials, instead of relying solely on human analysts.
In the ninth installment of our Making Impact Podcast series, ODAIA’s co-founder, Helen Kontozopoulos chats with Vangelis to discuss the benefits of buying software like Intelligencia and how they aim to reduce the risk of clinical trials with the use of machine learning algorithms.
The Origin of Intelligencia
Vangelis got his start in consulting, specifically, working with clients at McKinsey across different healthcare and drug development areas. Though having an academic background in computer science and electrical engineering - an atypical thing for someone working with pharmaceutical clients - he fell in love with the world of healthcare. This inherently led Vangelis to create Intelligencia, blending his two worlds of machine learning and technology with healthcare clinical development. As Vangelis puts it, “I already had the bug of technology and machine learning from my academic years. So putting the two together was relatively straightforward.”
However, as he was coming up with the idea of Intelligencia, Vangelis had to pick his niche and the one area that kept coming up for him was risk and drug development. Large teams, particularly in the pharmaceutical industry, use data to help companies make better decisions but a concrete source of truth was needed to help make these decisions instead of relying on people who are bound to make errors. “After a pharma company comes to a consulting firm [numerous times] and [asks] ‘in this era of big data, do you have a [reliable] software? One that's better than benchmarks, or historical averages, to assess risk? After saying no [so many times], my co-founder Dimitrios [Skaltsas] and I figured we might as well build [the software] and say ‘yes.’”
Enabling key decision-making is important. But what else?
The main value Intelligencia aims to bring to the healthcare industry is three-fold. The first proposition is having a nuanced and clearer estimate of the real risk of a pipeline or a clinical program, “to either stop things early on or accelerate them much faster with conviction” knowing that the results of phase two will have a positive impact for stakeholders. The second is systematically reducing the risk of drug development for more effective and safe patient care down the line. If “we could take every clinical program out there that a large company has, and reduce the risk by 10%” letting the percentage compound over time, “there’s tremendous value to patients that will come from that, given more programs will succeed.” The third goal is to give external biotechs a better pulse on what’s going on. “The ultimate benefit is making a better decision and having a clinical program that is more likely to benefit patients at the end of the day.”
To build or to buy? That is the question.
It’s well known that building software requires time, deep resources, and most importantly, money. “There are some pharmaceutical companies, particularly the very large ones, that have chosen the path of [using their] own methodology…but it’s not necessarily that the bigger you are [as a company], the more likely you are to use internally [built resources].”
The question that Intelligencia is answering with risk assessing clinical trials is the core of drug development, making methodologies a necessity. “We are not suggesting that you take a room [of experts], throw it out the window, and use a piece of software. But instead, you continue to have that debate of experts recognizing you cannot capture everything in an algorithm.” By buying software like the ones Intelligencia has developed, “the machine learning algorithm [will] challenge the views in the room, give a different angle, provide systematic data, and, unbiased data so that everybody can hopefully arrive at a better conclusion.”
Celebrating wins and looking forward
Having raised $15 million in Series A funding, Intelligencia is moving out of its startup phase and into its growth phase with a full fledge leadership team and an end-of-year projection of 110 employees. However, the goal for the next five to ten years is a crucial thing that Vangelis has his sights set out on. “There’s a lot of things that can be done better, whether you’re talking about drug development, the commercial side, hospital operations…there’s no shortage of things that can be done more efficiently,” Vangelis says. And efficiency is key with software that streamlines productivity.
For Vangelis, the future will always be healthcare, whether that be at Intelligencia or helping consult for those who make the decisions in the pharmaceutical industry. As Vangelis puts it, “I think there will be two things that whatever I do will have in common. One is the intersection between healthcare and technology, and two, ultimately working on something that will make someone better.”
By identifying a problem through a passion for merging technology and healthcare, Vangelis and his co-founder Dimitros were able to create something special. “What we do is allow drug developers to make better decisions and allocate capital better. When it comes to what benefits the patient, we will see better drugs reaching patients faster.” At the end of the day, it’s about saving lives. Vangelis feels that Intelligencia is one of the pieces of the puzzle that will help others fit together for everyone’s benefit.
This is the ninth installment of ODAIA’s Making Impact Podcast series, where we interview other thought leaders who are using cutting-edge technology to innovate in the life sciences. Listen to our previous episode with Hassan Jaferi, Co-Director of the UTEST Accelerator, which operates under the Toronto Innovation Acceleration Partners, and CEO of Bitnobi Inc., where he discusses his experience working with startups in life sciences and starting his own company through an accelerator.