Jul 30 , 2022

Inderpal Randhawa

 Dr. Inderpal Randhawa is the founder, CEO of Southern California Food Allergy Institute. He has revolutionized treatment through the Tolerance Induction Program™. By harnessing the power of AI and ML, the program has treated over 12,000 patients, allowing them to eat foods they were once allergic to, without fear of reaction.

One Line Life Lessons from Inderpal

Episode Highlights

  • (0:00:00) – Nitin Bajaj welcomes Dr. Inderpal Randhawa
  • (0:00:16) – Inderpal shares his unique story as a researcher and entrepreneur
  • (0:02:33) – Let’s play a little game about the underrated. And you’re restricted to one word responses
  • (0:04:13) – Dr. Randhawa founded Food Allergy Institute to help people with food allergies
  • (0:13:44) – As a pioneer, your work is breaking new ground in medicine
  • (0:16:24) – What is the biggest and most exciting opportunity you’re targeting
  • (0:19:21) – Talk about one instance where you blew your own expectations and then learned from it
  • (0:26:13) – Dr. Randhawa shares his one line life lessons

Show Transcript

Transcript - Full Episode

Nitin Bajaj: (0:00:00) – Hey, everyone, welcome to the industry show. I’m your host, Nitin Bajaj. And joining me today is Dr. Inderpal Randhawa. Doc, welcome on the show.

Inderpal Randhawa: (0:00:10) – Thanks, Nitin. Glad to be here and I really appreciate you inviting me.

Nitin Bajaj: (0:00:14) – Thanks. Pleasure is all ours. Let’s start with who is Inderpal?

Inderpal Randhawa: (0:00:21) – Well, I mean, I think my story has to start back with my parents. I’m a first generation american, but my parents are from Punjab, India. My dad came here about over 50 years ago with a very unique journey. He was able to come here on a visa based on his scientific capability. And he came from a village where his siblings were all illiterate. He was fortunate to have some good mentors. He was very self motivated, came to the US, tried to pursue research and science as a very good scientist, but also happened to be a veterinarian, a DBM. And so we moved around the whole us. I was born in Texas, my brother was born in Baltimore, and I have a sister as well who was born in India, but she actually has cerebral palsy, so she was born with a brain injury because at that time they didn’t know what to do. So I kind of grew up with this unique family slate. And come the late 1970s, economy was horrible, inflation was high, and the NIH froze funding. My dad had to settle down and basically open up an animal hospital. So I grew up watching a scientist practice a form of medicine. And I think that really informed how I grew up, constantly being asked questions. So as a classical indian kid who was expected to be a doctor, it wasn’t quite that story. We were kind of asked a lot of questions. We were kind of asked to be curious. And that kind of led my path down going into research science, eventually into entrepreneurship, and pursuing many different areas in healthcare, and has led me to where I am today, where basically I run a large nonprofit enterprise where we really focus on using applied math and technologies in healthcare.

Nitin Bajaj: (0:02:18) – It’s amazing what a curious mind can do. And I’m really looking forward to hear more and share with our audience your Unique journey as a researcher, as an entrepreneur. Nerve, and as someone who’s helping change lives for the good. But before we get into that, let’s play a little game. We call it the underrated. Overrated. And when you’re ready, I’ll shoot off a string of these themes that are impacting us as a community. And you’re restricted to a one word response.

Inderpal Randhawa: (0:02:48) – Yes, sir, I’m ready.

Nitin Bajaj: (0:02:50) – Let’s start with stock market prices, overrated.

Inderpal Randhawa: (0:02:57) – Inflation, underrated.

Nitin Bajaj: (0:03:01) – Real estate prices, underrated startup valuations.

Inderpal Randhawa: (0:03:11) – Highly overrated.

Nitin Bajaj: (0:03:15) – I’m going to love this one.

Inderpal Randhawa: (0:03:16) – Crypto, big time overrated.

Nitin Bajaj: (0:03:22) – Well, let’s continue this trend. Nfts overrated. The metawars?

Inderpal Randhawa: (0:03:31) – Overrated.

Nitin Bajaj: (0:03:33) – What about the great resignation?

Inderpal Randhawa: (0:03:38) – Underrated. Majorly underrated.

Nitin Bajaj: (0:03:43) – Diversity? Dei as a whole.

Inderpal Randhawa: (0:03:49) – Equity, inclusion.

Nitin Bajaj: (0:03:50) – Right.

Inderpal Randhawa: (0:03:54) – It’s underrated, in my opinion.

Nitin Bajaj: (0:03:57) – Well, thanks for playing along, and thanks for keeping it in the spirit of the one word. I know these are big themes. It’s hard to stick to a word, and that’s why it’s the game. Let’s talk about something that’s closer to you. And with that, let me ask you an open ended question, because you have so many facets, tell us, what do you do for a living?

Inderpal Randhawa: (0:04:24) – My goal in what I currently do is very simple. My job as a physician, scientist, entrepreneur is to advance health care so individuals have solutions for specific diseases. Today, not ten or 20 years from now, everything I can do to make that happen is my daily focus.

Nitin Bajaj: (0:04:47) – True. And you’re doing this as a nonprofit. You have a couple of institutions that are helping individuals with their allergies, the food allergies, which, as I have come to know and read, is an extremely difficult thing to tackle. You’ve come up with a unique solution for this. So tell us what that is, and tell us the size and scale and the impact you’ve been able to create so far.

Inderpal Randhawa: (0:05:19) – No, thank you. It’s interesting, and I do tell everyone this. I myself am not impacted by food anaphylaxis. My kids don’t have it. I’m a transplant immunologist by training. I’m a pulmonary immunology transplant. I spend my time in the ICu. I honestly had no interest in this field at all, in this disease, even up to about 2004, 2005. It just struck me that these patients would come in and they were so sick from a very small amount of exposure of a food that they would be in many ways sicker than some of my transplant patients. And that really bothered me that they just said, well, there’s nothing we could do about this. So I took my transplant background and I said, well, there must be some way to look at the way we are studying this food exposure differently. And so much like we do in the world of transplant, where we’re going to take a kidney, for example, and transplant it into somebody, we don’t just do that. We ask a lot of questions. We study many different markers of the immune system, on tissue, et cetera. So I spent many years studying that question across all different types of proteins that includes milk and eggs and peanuts and tree nuts and such. And as I started collecting that data, I found very clear patterns. There were patterns between these individual plant groups, as an example, between peanuts and walnuts and so forth. But there was also, more interestingly, an immune response that was predictable. There was patterns in this, but it was not a linear relationship. It was very complex co expression or very complex multivariate math that was the issue. And because I happened to be in that world, and as a scientist and somebody who works and lives in the laboratory, I tried to put it all together and essentially found a way to study an immune response to food. Anaphylaxis utilize proteins that are found in other food plants or animal proteins, and use those to actually turn off the allergic response. It’s very calculated, it’s extremely precise, and it’s one patient at a time. We’ve now done this for over 14,000 patients. We’re the biggest center of its kind in the world. This is really patients of all levels of complexity and severity, achieving a point of remission, so they actually can eat any amount of that food now, when previously a small amount could almost kill them. We have hundreds of employees, about 150,000 space. We have a diagnostics facility that’s top in the nation. We have our own r and D research facility, software, applied map, and a pharmaceutical grade manufacturing facility as well, in addition to clinical therapeutics. So very quickly built a very large institute, as the name is called.

Nitin Bajaj: (0:08:15) – Massive, massive impact. And congratulations to you, and a big thank you again, Touchwood. I don’t have any of these allergies, and no one around me does, but I can imagine, and I have seen the restrictions it puts people through, the challenges it puts people through when their loved one has one bite of something and it puts them into the ER and to give them back their freedom. It’s such a wonderful thing. And what I love about this is, of course, you are a curious person, and you took the applications in one practice, one industry brought it to another one, but you challenged the level of. I’m hurting for words here, but the medical practice as a whole is archaic. And you brought technology and artificial intelligence, but not just as a buzzword. You’ve taken your thorough research process and put this to its test, and you’re able to, almost to a level of certainty, show results. And what I love about this is there are other methods that expose you directly to those allergens. From what I know, that’s not how you’re doing it. You’re introducing proteins and other things that are surrounding it. And I’m obviously not using the right words, but I would love for you to tell us a little more about that.

Inderpal Randhawa: (0:09:56) – Yeah, no, it’s really well said. If you look at the data out there, and they’ve done large surveys on parents who have kids with food anaphylaxis, it’s devastating. It really changes their entire perspective on life. It’s isolating. They don’t have social experiences. I mean, food is at the center of everything. Certainly for the south asian population, food is a big part of everything. And you see those stories. They can’t go to the religious place of worship. They can’t go to proper schools and so forth. So this is extremely limiting. And despite those limitations, accidents happen. Grandparents will give something, and then it ends up in the emergency room. So the top three survey based data out there says that patients who have this disease, a, are unlikely to outgrow all of their allergies. They might grow one, but they’re going to be allergic for a long time, b, they have a high risk of reactions, high risk of anaphylaxis. So safety is a concern, and c, these patients are financially put in a bad spot. If you look at how they have to live on a day by day basis, they have to purchase an entirely different set of groceries, eat at different restaurants, not to mention medical visits and such. So it is actually a very big burden for them to carry. So when I was designing this program in its early stages, I was trying to understand what is the most effective method for doing this work. My goal was not to just find some level of minimum desensitization, because what we knew about the immune system is it can reject that state very quickly. That’s what transplant teaches us. If you do not find a very deep state of tolerance, to take a solid organ and say, it’s yours, those patients don’t do well long term. So we had to find a way to make sure that there was a same deep state of tolerance. And that’s why our program is called a tolerance induction program. We have to induce that process. So in order for that to occur, we would have to convince an immune system for many, many years that it could eat large exposures of food, protein, in a way that was really interrupted every seven days, 20 days, 30 days, like a non allergic person, and it would keep their immune system in a state of remission. That was the goal. So I first set the goal, and then I backed it up and said, okay, how do we achieve that type of goal? And what we were able to figure out is if you take something like peanut, it has not peanut or just one protein, it has 17 sequences of protein. We could identify those. We could then identify the binding of those proteins to people’s immune system markers, and we could take that data and take somebody who’s anaphylactic to peanut. Their numbers are 100, and we can say ten of those proteins if we expose them to, for example, hazelnut or, for example, sesame, and we can down regulate those approach towards those proteins of 17. Effectively, after nine or ten months, their peanut numbers have dropped 70%, 80%, depending on cross matching. So that when we expose them to the peanut, we can actually expose them aggressively to large amounts, and they can eat that freely, and they can do it on an interrupted basis. So that has been the model not only for peanut, but for literally everything from milk, eggs, fish, shellfish, anything that we have been able to study, we’ve done so successfully, and we’ve done it across thousands of patients.

Nitin Bajaj: (0:13:33) – I just love what you do and how you’re allowing people to get back and live their lives to the fullest. So kudos and thank you. Now, as exciting as your work is, I’m sure there is some hurdles, some challenges that you come across. What’s the one big challenge you’re facing?

Inderpal Randhawa: (0:13:57) – I think the biggest challenge is, as you mentioned, we’re dealing with an archaic system, and a lot of people don’t realize that medicine is really only about 110, 120 years old. It’s not a very old. Modern medicine is not very old. If you look at how we try to solve problems in healthcare, it is all based on old statistical methods. Just generally speaking, if I wanted to figure out if an antibiotic worked well, I take 200 people who have pneumonia and 200 people who have pneumonia, and I’ll give this group antibiotics and this people nothing. Placebo. Let’s see who gets better. So, for very simple diseases, the statistical methods were easy. You just pick big groups of people. But what we started learning, say, starting in the 1970s, once we kind of tackled major infections, heart disease, things like that, it’s as soon as you go into nuanced fields, whether it’s cancer or certain lung diseases, that all of a sudden, these kind of changes in statistics no longer worked. You would try to do something, and 90% of the time, it showed failure in statistical evaluation. Yet it is those statistics that the NIH still uses for its grants. It’s the same statistics that the FDA uses for approval. So we built a system that uses old mathematical models, and it’s functionally, even to this day, utilizing those to say something is good or bad. And the reality is that we have to be much more nuanced and detailed in that. And if we do that effectively, where we are really treating one patient at a time, utilizing much larger sets of markers, we can see great outcomes. Now, what I just said makes sense. Everyone tells me, oh, that makes sense. But it took literally until a year and a half ago for the FDA to have its very first department of machine learning and artificial intelligence open. So it’s taken a long time to get people to accept that something like this makes sense. I’m hopeful that this will start to be applied to other areas of medicine, but I do think we have a long way to go.

Nitin Bajaj: (0:16:07) – Well, clearly, as a pioneer, you’re breaking new ground. You’re defining the edge, not living it, just going and defining it. And obviously, if it’s someone else’s path, it’s easier, but then it’s not yours. So, on the flip side of this, what is the biggest and most exciting opportunity you’re targeting?

Inderpal Randhawa: (0:16:35) – Well, I think there’s many things that I’m very interested in, and if I may, I’ll step back one point.

Nitin Bajaj: (0:16:43) – Sure.

Inderpal Randhawa: (0:16:43) – And when I first built this nonprofit and really wanted to understand how to accomplish this, my very first question came around funding finance. Because I knew, as somebody who’s received grants from the government and NIH and such that the cost of these grants was significant and the use of the grants was swift. So the very first thing I did was built a nonprofit where I created shared overhead, whether that was laboratory diagnostics, therapeutics. And secondly, I tried to create really clean data workflows so that we can ask the same questions in the research lab, design the same answers in the diagnostic lab, and design the same answers in the clinical side. That’s a very unique model, because everywhere else, people are doing that in silos and in pieces at very high cost. So when I first built t PERc, which is the translational pulmonary immunology research center, my goal was to study basically a few lung diseases and a few immunological diseases. And my hope was when one of them takes off, it will essentially become the anchor and allow us to fund this idea into many different disease states. And that’s what has happened now so far. So overall, it’s important to recognize that, because that’s what gets me excited, because I do believe we can do this across many, many other conditions. But to answer your question, I’m most excited about defining disease as remission versus cure. If you talk to our patients who have food anaphylaxis, by the time they’re done, let’s say they’re anaphylactic. Most kids are anaphylactic to at least three to four foods. They can now eat these things just like anybody else. Peanut butter, jelly sandwiches, they can drink milk, they can eat all the desserts. Life is good. They don’t have to even do it on a daily basis. They’re doing it every two weeks, three weeks or four weeks. But when is the disease officially turned off? When we can officially remove their epipen, like take it away from them. And we are very close now to accomplishing that. It’s been many years. I mean, it’s taken us a long time to get to this point, but we are now going to study the key immune cells of the bone marrow of these patients and really show that these populations of cells have turned over completely, that they’re effectively cured of this disease. I’m very excited about that because remission is wonderful to them. It’s a cure mentally. But for me, as a scientist, to know that we’ve officially achieved that mark, it’d just be quite amazing.

Nitin Bajaj: (0:19:15) – That’s tremendous. I’m super excited. And of course, can’t wait to hear more about that. Now, as we look forward, let’s look back a little bit in the rear view mirror, if you will, and talk about one instance where you blew your own expectations and maybe allow yourself to brag a little bit, and then on the other side, something where things did not work out as you had planned and ended up becoming a lesson learned. Would love to hear both these perspectives from your past.

Inderpal Randhawa: (0:19:54) – Well, I’ll probably start with the latter first, and I will go back to my very early, earlier time in my career. I have to say I think I.

Nitin Bajaj: (0:20:05) – Was.

Inderpal Randhawa: (0:20:08) – Well, not even a bit significantly naive. When I finished medical school, I was always a bit different. I would ask questions and I think I annoyed people a little bit because I was very curious. And as I tell people, you choose to be bothered, and I was bothered a lot, if I saw something, I wondered why, if this didn’t work, I questioned how, and that was just how my brain worked. And I really believed that when I graduated medical school, I would find thousands of people who think like that. I went into my training seeing many different types of cases, and I believed that there would be solutions to these cases as every few months would go by. As you know, when you do training, you’re literally rotating into almost a new job every month or every two weeks, I would see a pretty regular fail rate in medicine where we weren’t getting things done. And I also saw that everyone in the system, whether physicians or nurses or scientists, they all felt pretty good about that. It was okay. There was an acceptable level of that. But I was bothered. I wanted to see things done differently. Why can’t we solve these problems? There was a sense of that urgency. And so when I going back to about 2005, I had essentially discovered a way to stop bleeding in the lungs, something that’s totally novel, no one else was thinking about it, did all the proper science behind it, built the models, published the work, et cetera. And I believe that this condition, which is a very serious condition when people are bleeding inside their lungs, would be received very positively. And there was a national organization at that time who said to me, who I was working with them in specific disease areas, and I went to their conference, presented my data, and I had no questions because it was so out of the box. I came back and I received some funding based on my work to get something established here at my main hospital. Well, that national foundation came down and said, oh, wait a second. You’re doing this as an outsider. You’re an outlier. And they saw me as a threat. I was no longer considered a friend. I was considered somebody who was competing with them. And I saw very quickly that how much of our efforts were in earnest was highly political, and it would become a significant problem. And I learned pretty early on at that time that if you don’t pay attention to the desires of these different organizations, I’m not saying they have ill will, but what is motivating them to get these things done, that it will significantly slow your ability to achieve impact. And that was an important thing for me to see early because it did change my approach right away. In fact, that’s what stimulated me to build this as a nonprofit, because I knew that in that sense, you were seen as unique, as nonthreatening, as collaborative, and most importantly, you’re very transparent. So that’s the first part of things that really woke me up. But to be frank, it was devastating to see that most of this system doesn’t feel that burden that you feel. And I don’t know that I’ve really ever got over that, to be honest with you. But as far as the positive side, I still remember the series of patients back in nine eight where I absolutely knew I was onto something, right. You see the patterns, you see the data, you see the science. And back then, I was working till 09:10 p.m. At night working these food allergy patients. We were in the ground floor of a hospital, and I remember the nursing staff I was with, and I basically stepped out with all of this data. I mean, back then computers were not quite as advanced as now, and I was yelling at them and saying, look at these, the peanut numbers dropped 90%. And to them they’re like, yeah, whatever, these patients are doing fine. But it blew my mind because I said, this is now fully reproducible, so we got to start taking it up a level. And I remember going home that night, talking to my wife and saying, this is big, and it’s big in a way that I got to find a way to actually expand this. And so this is not going to be a pill, this is going to be a system. And it was that day I actually sat down and started learning Javascript and started learning what was eventually python and some other languages because I knew that I had to build the software myself to make this go somewhere.

Nitin Bajaj: (0:24:45) – And this is such a testament. And I would love for more people to see and hear this and take this in, that as an entrepreneur and as someone who has to be successful, you have to go all in. You have multiple degrees across different practices, none of which are quick overnight. You spent the time years in each of these faculties, and then you go learn how to program. It’s amazing. It just hats off to you.

Inderpal Randhawa: (0:25:24) – Well, honestly, I don’t really think about it too much. Every once in a while I’ll step out and look at the scope of what’s been built in just really a decade and a half. But I always still wonder if I’ve done enough. It’s just a different kind of mindset, which, you know, again, I really think it’s the ultimate curiosity of the scientist, you know? I mean, we really do see things through a different aperture. You know, things are either very large in scale or extremely small in scale. But when you have the ability to open and close the aperture, it motivates you to stay active in learning and active in developing. And again, hopefully we all have a shot at trying to solve some problems.

Nitin Bajaj: (0:26:11) – Said it really wonderfully. Which brings me to my favorite part of the show where we do capture these one liners. We call it the one line life lessons and continuing the short and sweet model. Let’s talk about your one line life lessons.

Inderpal Randhawa: (0:26:32) – Oh, I will say my absolute one line life lesson is look for a problem and solve a problem. Doesn’t matter what scope or scale have the mindset to look, and that means not for a second, that doesn’t mean for a couple of minutes, and then it’s disconnected. But it’s right in front of you every day, whatever it may be. And it doesn’t have to be something of this scale. But what is it that you’re trying to address? Because we only progress as a species and as a planet. Frankly, if we at least have many people thinking that way, it’s collective learning that keeps us better. So you only learn if you identify the problem. And then the question around solving that problem is really your own impetus and your own inner will and strength to believe that you can do these things. And I have so many employees who are young, and they get labeled into a generation and limitations, and I don’t believe any of that stuff, because what I see in them is perhaps a different way that they learn. It’s a different way they perceive things, whether it’s through technology or whatnot. But they have the desire to try to see things be better. I think they have moved past a lot of those kind of steps of learning and education that many of us had to go through initially. But they do have this ultimate desire to make things better. And in fact, I’m relatively encouraged by that with this younger generation versus some of the older folks, where they just feel like that’s going to be kicked down the road for them. But yeah, look for a problem, solve a problem.

Nitin Bajaj: (0:28:17) – It’s extremely simple. And what I love about it is it gets you focused on that and stay there. It comes with a lot of persistence. And without overcomplicating things, just find your thing and go do it. I love that.

Inderpal Randhawa: (0:28:37) – And I’d say if I can add, it’s really an issue of having the desire to do so. I feel like in the current day and age, where everything is so overwhelming, there’s so much information thrown at everybody. Their ability to focus in on a single problem is sometimes very blurred. It’s very difficult. Even the way kids are educated, the way healthcare, I mean, look at Covid and look what that did. How difficult is to focus on one thing? And if individuals can get back to that, that is, to me, evolutionarily what humans did. Well, they were able to look at things and relatively quickly pick one problem, solve that problem, and then obviously share that information and move on. But that is a repetitive process that we have to get back to. And I think it’s extremely healthy. It’s really rewarding, builds confidence in learning. And for an individual, that has great benefits. But for the local community and society immense benefits.

Nitin Bajaj: (0:29:39) – Thank you so much for sharing your oneline life lesson and for our audience, we have an entire collection@onelinelifelessons.com. And wherever you guys socialize digitally. Well, Dr. Randhawa, thank you for making the time for being with us and sharing your amazing journey with us. Would love to bring you back on and see what more, more feathers you’ve added on to your cap. Thank you again for being with us.

Inderpal Randhawa: (0:30:06) – Thank you very much, Nitin. Really appreciate all the hard work that you do as well in bringing us all to the forefront, and I wish everyone well. Thanks.


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