74: Learn the Five Fingers Formula with Mel Engle

Mel Engle is the CEO & Chairman of the Board at Predictive Oncology, a knowledge-driven company focused on applying artificial intelligence to personalized medicine and drug discovery. We talk about the role of AI in the battle against cancer, the Five Fingers Formula, and the future of cancer care and research. 

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Learn the Five Fingers Formula with Mel Engle

Our guest is Mel Engle, the Chairman and CEO of Predictive Oncology, a company driving personalized medicine and drug discovery using artificial intelligence. Welcome to the show, Mel.

I’m glad to be here. Thank you.

It’s great to have you. So let’s start with your CEO journey. Mel, how did you become the chairman and CEO of this company? What’s been your journey?

Well, I kind of started out when I was younger. I was always working as a kid. Then I was working as an employee for others. And then I had people working for me and the same companies. And as a matter of, as you move up through the chain, you learn more and more about the business and more and more responsibility comes your way. And I made a decision to use my education, my background to expound into becoming a general management person, not simply a functional specialist. I was a financial person by trade.

So way back in when I was 32 years old, I decided that that would be a good thing to do. And since then I’ve moved from company to company as being either a general manager first and then moving to a CEO position and then a CEO position of a public company. And then from a public company to a company that was a CEO of a very large company, which is Merck, KGAA. And then from there, from the CEO of another company that’s on the NASDAQ. So one thing led to another, and I think that what ends up happening is that you learn from experience and people know who you are, and your reputation precedes you, and people want to enroll you in your company.

And if you wanna do the right things for your family and for yourself, you want to continue growing in the way that you manage and think. And so it’s just, it’s a blessing to have the well-rounded background of having the financial experience by being a financial person, having a degree in finance and then having the opportunity to actually roll that out into a general role as being a strategic thinking person that I am right now.

I totally get it. And in fact, I think this is something in common. I also started as a CPA and the financial background and move towards the strategy and management and strategy, which I found more exciting as I got into my career, I found people and the issues around people more exciting than just the numbers, but it’s great to have the numbers as a foundation. So talking about foundation and, you know, bridging onto the theme of this podcast, which is management blueprints, it’s conceptual frameworks that CEOs and entrepreneurs apply in building their businesses. In our pre-conversation, you talked about the five fingers formula, we call it, that you’ve developed. So can you tell our listeners a little bit about what that is and how it works?

I think that what I found in my travels is that when I meet different executives, I ask them what their business is all about. And those who are really on their game, pull up their hand just like this and say, there’s five things. Let me tell you, if we do these five things well, we’ll have a great year or we’ll have a great company. And they keep it simple. And the chief executive really comes down to, you know, this is too many. If you have too many different moving parts, there’s 10. Five is enough.

So if you can recite to whoever is asking you what your top goal is for the company, what your second one is, what your third one is, and by the time you get to the fifth one, you’ll be talking to perhaps not as a major point. But the number one goal is always the financial goal. The financial goal follows the strategy that’s really the cornerstone of the company. If you have the mission in place and the vision in place, those are not necessarily goals, but those follow.

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If you’re going to, as a CEO, you’re going to actually try to accomplish the mission and the vision, you’ve got to set out some goals for yourself to be able to make that happen. So if the team, if the team that surrounds you, the senior team actually has the same five goals in their goals, pardon my dog in the background, you will be successful. So the first goal is a financial goal. The second goal is generally associated with products, making sure that those products come to market as fast and as efficiently as possible.

The growth of the company is a very important ingredient of a CEO’s success. The other three are perhaps the specifics of the company of what state they’re in, if they happen to be in a retrenching goal or a manufacturing change or a different, they want to enter different markets or whatever it’s for the last three goals are perhaps not as important as the first two. Having the strategy in place that your management team knows where you’re going, if they can embrace that in their own goals as well, the odds are you’ll probably get there.

I love that. And yes, this makes it very simple. We have five fingers. We’re never gonna have a six. So as long as you find and articulate five robust goals, then we are in good stead to have a great year for a company. This is actually what I teach my clients as well. We set up to five goals each year and, okay, the company can have other goals, but these are the ones that we are going to focus on and make sure we drive every quarter and accomplish them. That’s awesome. And you said that these goals cascade from the mission and the vision of the company. So it’s kind of, OK, what is the vision? Where are you going long term? And then how do you bring it down to the five most important goals for the year? Is this how it works?

You have to start with a bigger picture. Simply achieving a goal, because it happens to be a short-term thing, is good, but it doesn’t move the needle for the company where it’s destined to go. The CEO has got to be looking over the horizon. Now, that’s the story of Christopher Columbus way back in the beginning when he had the orange in his hand. He was talking about what’s on the other side of the horizon. And I think that the CEO and his team or her team really need to determine, you know, what is the view of the future that we want to go accomplish? We can’t simply be inching along. We’ve got to make sizable gains. Otherwise we’re not earning our salary.

Yeah, no doubt. So switching gears here, let’s talk a little bit about your company, Predictive Oncology. So tell me about what is the mission for Predictive Oncology and why it’s so important.

Well, we simplified it to we want to eliminate cancer. It’s a pretty broad, bodacious goal, but it’s one that all the employees rally behind because that’s what they come to work for in the morning, be it virtually or in the different offices that we have around the United States. They know that their single purpose in life is to work towards their ultimate goal of eliminating cancer. And what we’re trying to do by doing, so what is our role in making that happen?

We start with the fact that we’ve been blessed with having 150,000 tumor samples, cancer tumor samples available to us, that’s our property. We nurture and make sure they stay there. And so, this 150,000 tumor samples are patient samples. These are not simply petri dish samples that might come from a mouse or from, you know, other places. These are human tumor samples. we actually analyze them and look at them from what kind of cancer it is. We have 137 different cancer types in our hands. And we have, I guess we have 32,000 ovarian cancer samples.

And so in total, we’ve got 150,000 samples to deal with. So what we do is we take that information and we use our artificial intelligence system that we’ve perfected with Carnegie Mellon. We call that our core system. And so that is, we take a look at the sample itself and put it together with the artificial intelligence technology we have and be able to look at the data to determine similarities of particularly whatever the cancer that the patient demonstrates or whatever the compound is coming back from a pharmaceutical company, we can actually marry together our information to whatever the cancer is that’s being analyzed. Historical information is important.

And if you can use the artificial intelligence to actually iteratively learn from the history of the sample base, we can actually make our predictions even better. But our ultimate goal is to be able to help pharmaceutical companies in their quest to be able to get cancer therapies to the market faster, more efficiently, and with less cost. And we believe that when we are faced with a challenge that would come from a pharmaceutical company, we can deploy our artificial intelligence to help them streamline that activity to get it to the market sooner. That saves them a lot of money. And if we can get that cancer therapy done on a patient by patient basis. That’s really going to help the planet.

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That is an unbelievable, unbelievably ambitious goal. And this is a goal. So obviously that I think everyone would want that to happen. So, tell me in layman terms, how does artificial intelligence help you sift through this hundred fifty thousand samples of cancers, and how is it actually deployed in in finding these new drugs that are going to kill, kill the cancer.

Well, it’s a system that we’ve been developing over the years and we call it discovery 21 the data that’s available. We have lots and lots of data on every patient that we have samples from. We know their background, that we know if they were a smoker, if they were a diabetic, or if they had alcohol in their family. So there’s a lot of objective data that is tied to the individual cancer type and to the patient. So there’s a lot of similarities that go along with that and it’s, it’s very hard for my from it’s just a human analytical standpoint of being able to have a spreadsheet and look at similarities to determine what the prediction of the future would be.

But if you can have a tool of an artificial intelligence machine if you will machine learning that analysis can be done very quickly. And so the artificial intelligence learns from the output from the prior run. So we go through all these, we go through all these, all these data points to be able to determine what are the similarities that we want to retain and what are the things that that are perhaps not as important than we discard. And so, so that retention becomes more and more important and we analyze it over and over again to be able to come down to what the root answer is. And I think that’s the that’s really what the efficiency is. We can’t possibly do this as a human thinkers, we really need the machine to be able to help us.

Okay, so the artificial intelligence it analyzes the different combinations of cancer cells. And it’s kind of an iterative process to get to a point where a good cross-section of these different combinations get eliminated by as narrow a drug as possible. And I’m trying to probably over here. You’re on it.

I think you just have to continue, you know, mincing through the data over and over again to be able to take the data that’s not important out and be able to focus on the points that are more important. From a technical standpoint, I’m not exactly sure what cancer we would be, or what patient problem we were trying to solve, but each patient has a different problem. So we would take the tumors from our history bank and be able to analyze it versus the tumors that are presented in front of us.

Either the tumors that would be coming towards us would be a compound that could vary from a pharmaceutical company or it could come from another patient who has a problem, who needs therapy to be able to help and get an answer as to what kind of drug therapy that should be applied that would be on the market right now. So there’s two ways to go. One is to help the pharmaceutical company get their products to the market sooner, and the other is to be able to help oncologists in evaluating the cancers that are out there and help them determine what kind of therapy, drug therapy, that would be the most efficient.

So basically, does it mean that you have two target markets? You have the oncologists who will use your product or your system, and then you have the drug companies as well, and kind of two completely different target markets you are positioning this in a different fashion?

It’s kind of a neat deal. We have been doing the latter for many years, but that has not been our focus now. We’re really, our biggest emphasis now is in the patient evaluation with pharmaceutical companies. So, it’s patient data that we’re working with, not just animal data, which is not too many companies have the database that we have, which is to our advantage.

That’s awesome. So, if there are 137 different cancer types and there are a magnitude more combinations of those, how do you even prioritize? How do you even pick which ones to work on first? Surely, you cannot work on all of these at the same time.

You’re right. I think it comes to a matter of the evolution of the company, you know, we figured that we would start someplace and that ovarian cancer was a very, it was a base that we had experience in with our company. And so, we’ve done a deep dive with ovarian cancer. Our longer-term goals is to be able to go after all the cancers and we have to now segment which ones we want to go after next. But we can’t do them all at the same time. So, we’re kind of looking, want to get through the ovarian cancer to be able to prove to the pharmaceutical companies that our artificial intelligence system works.

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So right now we are not marketing the product to pharmaceutical companies. We’ve had conversations with them and some of them have shown interest and have asked us to make sure that this could be validated, that we can prove that our system works over and over again. And that’s what we’re doing right now is to be able to validate that process. So they can talk to us, we’ll be able to say, okay, here’s our Discovery 21 system. You can test it if you want to against some compounds that you have, you’ll see that it works and then they can use it on a broader scale.

And so then we establish a working relationship with them and be able to handle other cancers that the pharmaceutical company might have. So it doesn’t necessarily have to be ovarian cancer specific. That’s where our validation is coming from. We believe that the tools that we have in the system we have can be applied to multiple cancer types. We have to make sure we do this one step at a time. And if we can validate to them that this ovarian cancer system works, and then we are able to have a broader conversation with other cancer types.

So you’re focusing all your energy on proving the business case for ovarian cancer and then you can roll it out to other cancers.

Right, exactly.

Okay, so what I also noticed that you are, you have different subsidiaries. So the business is not just one company, there are different subsidiaries doing different things. Can you just walk me through why you have these different subsidiaries and what are the things that they do?

Well, the overall goal is we want to eliminate cancer. And so that’s everybody has a sweatshirt that says POAI on it. I made sure that everybody got one delivered to them. So they all wear the same, no matter what subsidiary they’re in, they’re a POAI employee. And we really believe that we are one company. We happen to have different work groups that are working on different business issues, but it’s the same, they’re working towards the same goal of eliminating cancer.

So, one supports the other who supports the other. So, we interchangeably move information back and forth between the different divisions and work towards synergies where we can so we don’t have to have any overlap. But we’re a POAI, that’s who we are. We happen to have work groups who are located in different parts of the country and they have different names, but that doesn’t really necessarily mean that they’re different or in any way disparate, outgoing on their own. Everybody knows that POAI is the mother company.

So POAI, standing for Predictive Oncology AI. You got it. Artificial Intelligence. Got it. So what is the biggest challenge for you in growing this business? That you have to work on?

I think the challenges that we’re facing now is that we’ve got such a wonderful system that we’re developing. It’s a matter of making sure that it gets done the right way and having that endorsed internally to make sure that works and now be able to take it to the outside. We’re poised to be to have a much bigger year next year because of this, our discovery 21 being perfected. We’re very optimistic that that’s going to happen. Once we get that in place, we’ll be able to have meaningful conversations with a whole host of pharmaceutical companies, which we think will open the doors for us.

So we’re focused on perhaps the artificial intelligence piece right now, but we’re also looking at other businesses to be that are synergistic with our own. And so if cancer is to be eliminated, what else is there that we can do as adjacent markets? And so we’re looking from a collaboration standpoint and how we can do more with other companies as well, so business development is an important ingredient for us to supplement our internal research group.

Got it. Now one would think that cancer is one of the biggest topics in medicine and a lot of startups focusing on cancer and how to help doctors cure cancer. Is this a crowded marketplace or your solution is a unique thing?

No, I think this cancer has been around for a long time and will continue to be. It’s a terrible disease. I’m a cancer survivor. I had prostate cancer when I was about 10, 15 years ago. And I’ve been symptom-free, thank goodness. But I really am thankful for the cancer therapies that existed back then, which were the, it was a, I won’t go into the detail, but nevertheless, there’s, there are therapies that can be used not only for prostate cancer, but for ovarian cancer that are, that are not necessarily a surgical removal, but there’s also drug therapies to go along with it.

And so, when you can use both of those effectively, you know, pulling the, eliminating the cancer surgically and then treating it with the appropriate drugs seems to be the right one-two punch. And then if you’ve got, you know, other things that go along with it within a post-op basis that therapeutics are used are important as well. Cancer is a tough nut. And so we’re going to be living with it for a long time. We just have to work on it over and over again to get rid of it. It’s a terrible thing.

So, what is a predictive oncologist or POAIs like a 10-year goal or something not eradicating all the cancer is going to probably going to take a little bit longer, but what is it, what is your long-term vision of where you can take this company the next five to ten years?

We would continue adding to our database of where the 150,000 cancers, the tumors that we have, I mean, that’s important to be able to share that information internally in a machine and make sure that the artificial intelligence system we have is state of the art. And so that we can broaden the approach that we’re using instead of going to one or two pharmaceutical companies like we’re starting off, we want to be able to have this technology endorsed throughout the world. I mean, that’s the goal. So it’s a unique system, and that’s when we are making sure that nobody takes the trade secrets away from us, but we believe it has enormous application that can be used across the world.

Okay, that’s a very inspiring story. So if people would like to learn about predictive oncology, and maybe connected you personally, where can they reach you.

Well, Probably the best answer that is my personal email address which is M Engle, M-E_N_G_L_E at predictive hyphen oncology.com. And I look forward to receiving any correspondence anybody wants to send, I’ll be happy to return the note back to whoever the author is. We can also be found on www.predictive-oncology.com, which is our website. And there is a thing you can click on there that says contact. And so you’ll be able to get a response back by clicking on that as well.

Okay, well, that’s awesome. Thank you. Thank you for doing this work. This is very important work, and it’s very inspiring that you actually have a vision of how to achieve it, even if it’s not achieved yet, but you kind of know where you’re going and how you’re gonna tackle this problem. That’s very encouraging. And also, thank you for the five fingers scheme, the five goals. And number one is financial. Number two is the product. Where to take the product next. And then the three flexible goals is kind of a great framework to keep in mind. So so thank you for coming on the show. And to you, our dear listeners out there, please stay tuned. I’ll have another exciting entrepreneur CEO coming on the show next week. And in the meantime, if you enjoyed this episode, please don’t forget to rate and review us and subscribe on the Apple podcast and subscribe to our YouTube channel to allow us to spread the word to more listeners as well. So thank you and have a great day.


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