Episode Transcript
[00:00:00] Speaker A: Foreign.
Welcome to the Victory Show.
[00:00:16] Speaker B: Hey victors. Welcome to this episode of the Victory Show. If this is the first time you're joining us, I'm Rachel League with Bestseller By Design.
Our founder, Travis Cody is the best selling author of 16 books and we've had the privilege of helping hundreds of business consultants, founders and entrepreneurs write and publish their own best selling books as well.
Through that journey, we've discovered a fascinating pattern. Most businesses really struggle to break past the seven figure revenue mark. On this show, I sit down with some of the world's most successful CEOs, leaders and business owners to uncover the strategies they used to scale way past that mark so you can do the same.
So get ready for some deep insights and actionable takeaways that you can implement in your life and business. Starting now.
Today's guest is Ashwini Gogari, the head of AI and automation for Drug discovery at Merck, where she leads the development of AI driven platforms and automation ventures across life sciences and healthcare. She's also the co founder of BioFINIQ, a strategic AI consultancy focused on accelerating innovation at the intersection of biotech and finance.
Twenty has built and scaled multiple AI and gen AI initiatives from inception to commercialization, including Merck's Addison platform and the AIDD Automation lab. Her work integrates generative AI, robotics and intelligent platform design to transform R D workflows. She served on advisory boards for Boston University's Bioengineering Technology and Entrepreneurship center and the CDO Magazine and was recently named AI Leader of the Year in 2025.
She holds a PhD in oncology focused drug delivery systems and an MBA from the Wharton School at the University of Pennsylvania. And I'm excited to welcome Ashwini to the show. Thanks so much.
[00:02:02] Speaker A: Thanks, Rachel.
[00:02:05] Speaker B: So you've been called a pioneer in applying AI to drug discovery. What first drew you to this intersection of life sciences and artificial intelligence?
[00:02:16] Speaker A: So Rachel, I know we can edit this, right? Yes, sorry, we'll have to restart a bit. Just one correction. So a note and probably so when you say Merck, unfortunately you cannot say Merck because it's also going to be US based. So there are two different Mercs. So we have to say Merck KGA. Darmstadt, Germany.
If you want to say Merck.
[00:02:42] Speaker B: Mark KGA.
[00:02:45] Speaker A: Mark KGaA. I can type that for you if I'd not put that in the text.
[00:02:52] Speaker B: Okay.
[00:02:52] Speaker A: Let me do one thing.
[00:02:53] Speaker B: Kgaa. Okay.
[00:02:57] Speaker A: Darmstadt, Germany.
[00:03:02] Speaker B: Okay.
[00:03:07] Speaker A: And so I would rather that you just say it once and then after that just say she has done this and that and without saying the name because I know it is quite long and could get unwinding.
[00:03:21] Speaker B: Okay.
H E A A Darmstadt, Germany. Okay.
[00:03:26] Speaker A: Yeah.
Oops.
[00:03:50] Speaker B: All right, no problem. Let's take it from the top then.
Okay.
Hey Victors. Welcome to this episode of the Victory Show. If this is the first time you're joining us, I'm Rachel League with best seller By Design.
Our founder, Travis Cody is the best selling author of 16 books and we've had the privilege of helping hundreds of business consultants, founders and entrepreneurs write and publish their own best selling books as well.
Through that journey, we've discovered a fascinating pattern. Most businesses really struggle to break past the seven figure revenue mark.
On this show, I sit down with some of the world's most successful CEOs, leaders and business owners to uncover the strategies they used to scale way past that mark so you can do the same.
So get ready for some deep insights and actionable takeaways that you can implement in your life and business. Starting now.
Ashwini Ghagari is the Head of AI and Automation for Drug Discovery at Merck KGaA, Darmstadt, Germany where she leads the development of AI driven platforms and automation ventures across life sciences and healthcare.
She's also the co founder of biofiniq, a strategic AI consultancy focused on accelerating innovation at the intersection of biotech and finance.
Ashwini has built and scaled multiple AI and gen AI initiatives from inception to commercialization including the Addison platform and the AIDD Automation Lab.
Her work integrates generative AI, robotics and intelligent platform designed to transform R and D workflows.
She served on advisory boards for Boston University's Bioengineering Technology and Entrepreneurship center and the CDO Magazine and was recently named AI Leadership of the Year in 2025.
Ashwini holds a PhD in Oncology focused drug delivery systems and an MBA from the Wharton School at the University of Pennsylvania. Ashwini, welcome to the show.
[00:05:43] Speaker A: Thank you for having me, Rachel. It's nice to be here.
[00:05:46] Speaker B: Absolutely. So you've been called to pioneer in applying AI to drug discovery. What first drew you to this intersection of life sciences and artificial intelligence?
[00:05:58] Speaker A: Great question.
I think AI has the potential to impact all different sectors and specifically drug discovery, because patients cannot wait for medicines.
And this is where AI can really help in accelerating going from disease to generating new medicines and then bringing them to patients.
And Covid is a great example.
If you look classically at drug discovery, it would take 10 years, $2 billion with less than 4% success rate. But with COVID we were able to get from the disease to, to a vaccine in the shortest amount of time and then bring it to the patients.
So it's an incredible example and a motivator to see how new technologies like AI and automation can bring or help to bring medicines faster to our patients.
[00:06:59] Speaker B: Have you always been passionate about healthcare?
[00:07:04] Speaker A: Always, since I was a child.
My dad is also an entrepreneur and PhD chemist and he used to take us to his company and into the labs when we were really, really young. And I feel these programs where parents are allowed to take their kids to workplace was so impactful growing up. It inspired us to look at science, it inspired us to look at how medicines were really.
And that was the motivation to see that for myself to come into pharmaceutical business and to be an entrepreneur.
[00:07:46] Speaker B: And so you've worked both in corporate and done your own entrepreneurial ventures. Tell us a little bit about what inspired you to balance both.
[00:07:56] Speaker A: I've always been an entrepreneur at heart from the get go.
And as part of this large ecosystem, I had the privilege of leading to ventures internally. And that's why I call it as an versus an entrepreneur.
And the fun part of being an entrepreneur is you get the ecosystem of the larger corporation, but at the same time you have the freedom to raise capital, to build teams and to be extremely agile when you're building transformative technologies.
So that's, I feel amazing thing about being an entrepreneur in a large organization.
The motivation really is, I think when you're trying to build new technologies that are changing by the day, right? You're experiencing ChatGPT or any kind of new AI systems, they're changing quite fast. And so when you're in such a transformational area, you want to be agile, you want to be fast and you want to have a super talented team by your side. And that can only happen when you are in an entrepreneurial or an entrepreneurial I would say ecosystem as opposed to an enterprise. And so that's what motivated me to be an entrepreneur, to lead these ventures and entrepreneur while being in a larger ecosystem.
[00:09:16] Speaker B: And on the topic of speed, how are you balancing the need for scientific rigor with also the need to move fast on some of these innovations?
[00:09:27] Speaker A: That's a great question and it is tough.
There is no real magic bullet or answer to this. I think we, the way I look at this, there are two parts to it. There's pure scientific innovation, like building new models, building new scientific capabilities. And that's where we have to give our scientific crew freedom to operate and think beyond.
So for example, when we were building new AI models based on previous data or building truly new foundational models. We had to give some time there because science doesn't just happen. Right. It takes time.
The other part which is scaling some of these, whether it's a software solution, a software platform or it could be an automation system, that's where you can actually bring scale and speed. So adopting methodologies like agile methodologies, like scale frameworks and so on, that's where engineering and product can be scaled and made faster. And that's where you can gain speed much faster while your innovation is being incubated and coming to life.
[00:10:46] Speaker B: Interesting. Sort of cross pollinating the techniques from one department to another. And it sounds like you've been building and leading a lot of those cross functional teams. What have you learned about operating and leading in such different categories?
[00:11:04] Speaker A: Yeah, from my experience leading these cross ventures that have both AI but application in scientific domains, whether it's life science or pharma, the most valuable asset in this are the people.
And you need what we call as translators.
You need chemists who speak the data science world and the data scientists that are fluent in lab workflows.
These are the folks that really glue between the two different domains. They are the ones that help to break silos between data and to build insight from this data for scientific application.
And these bi and trilingual STEM experts, and this talent is super important to be successful when it comes to building scientific solution using any technology.
[00:12:08] Speaker B: And given the different backgrounds and mindsets and the need for like you say, this bilingual multilingual communication across the departments, how do you think about aligning the team against a specific financial ROI or one goal when everybody's speaking these different languages?
[00:12:31] Speaker A: Yeah.
Financial acumen in scientific teams I found to be extremely important.
I'll give you my example personally. As a scientist, we were always brought up to be to look at science first, which absolutely is important, no doubt.
But my personal transition going from there into business and entrepreneur or as commercial was one of the toughest transitions, I would say as personal leader, but also was extremely rewarding because it made me think about outward in perspective when it comes to building new technologies. What that means is looking at what customers are looking for, what patients are looking for, and then build your solution. That is, that answers that question. Right? You may build the best, I would say Ferrari, but if nobody's using it, it's just sits in a showroom. And in my opinion it's no good. And so that's to me that is the perspective we all need to train our scientists. Is having the financial acumen.
And when I say financial acumen, it's not really thinking about only cost, but it's rather thinking about value.
What value is the solution building when it comes to saving time? What value is it bringing or the impact is bringing when it comes to longevity of patients on the clinical outcomes that we think about? So the value based ROI to me is extremely important as opposed to any other roi. And instilling that in scientists, I feel like brings a unique perspective to bring these technologies to life.
[00:14:20] Speaker B: And as an entrepreneur, how are you thinking about and take us through, I suppose the process of scaling these projects, these business within a businesses, what's the impetus and what's your end goal?
[00:14:37] Speaker A: Probably if you figure that I try to think systematically thinking about this, I would probably categorize it into three different buckets based on my experience.
Delegation and leadership has served me well.
So rather than, you know, being doer, build a team of lieutenants who can take the vision to life is super important to empower them, to trust them, to lead. And being the person who can remove obstacles from their way, I see that as the goal of the leader and that served me well.
The second I would say is systems thinking and automation.
By that what I mean is standardizing and automating processes that could be done and could be redundant and leaving more freedom when it comes to innovation.
And that allows to scale businesses after you've kind of incubated it from the inception.
And last but not least, I would say building and we talked quite a bit about this, is building financial acumen in the scientific team and having a strong team that can break silos, that can be a good translator and be a huge multiplier for technology to commercialization has been a super asset. So for me these three things have been important when it comes from entrepreneurship. Going into scaling new businesses.
[00:16:20] Speaker B: You mentioned earlier infusing AI. How do you think about risk when introducing emerging technologies like AI, robotics, other things into critical healthcare workflows?
[00:16:35] Speaker A: Yeah, it's.
It's a double edged sword feel every new technology, if even if you look through history, has pros and cons to it. And it all depends on how it's applied.
If you look at all the AI applications that can be extremely useful in productivity gain, whether it's applying it in marketing content, in sales. Right.
Reach out, creating content, publishing it on LinkedIn, or when it comes to scientific domains, how do you optimize clinical trials so that you can shorten the timeline? How do you discover new drugs so there are so many good applications of AI when it comes to health care.
But of course the challenge is how do you ensure security and how do you ensure ethics when implementing, especially because you're dealing with patient data and patient outcomes. And so that's where strong foundation ethics and as well as data management are extremely important. Putting some of those frameworks in extremely important. And so all the organizations I've worked in, we have established ethics board as well as have rigorous security including ISO certifications and so on that ensure and that build that trust within the system has served as well. I think that's going to be important for any platform or any technology that's implemented in a healthcare ecosystem.
[00:18:10] Speaker B: Tell us about a time that you made a decision that felt somewhat risky, but it really positively changed the trajectory of your work or project that you were leading.
[00:18:25] Speaker A: Sorry, can you repeat the question again?
[00:18:27] Speaker B: Sure. I'm curious about a decision that you made that maybe felt a little bit risky at the time or uncertain, but it really positively changed the trajectory of your work or projects.
[00:18:41] Speaker A: Very interesting question.
Let me think about it. I think one of the way early on when we started building some of these platforms, bringing in new technology to scale is always a challenge because yes, these models are very much in proof of concept stage and when you try to scale them up, they break.
And if they, if somebody would tell me that systems don't break, I wouldn't. It'd be hard to believe.
And so when we started we made a decision to quickly sandbox create a sandbox environment to build these systems out.
We decided to have a small agile team that would work specifically on this, you know, this proof of concept and then took into production very, very quickly, which is a huge risk because when you take something quickly to production, it means it'll have multiple bugs in it.
But that was a really important decision to bring it to production and to bring it to a few of the beta users because as the Netflix CEO always said, the faster you bring the technology to the patients or to the customers, that going to give you feedback. And this early feedback is super crucial to guide you in the right direction.
Many a times new features have failed because a lot of teams work on perfection, trying to make it perfect. And perfect can be enemy of good.
That 8020 rule was important. Bringing those features early to the customers was important.
Sharing that, hey, we want you to be part of this journey. Tell us what we've done right, tell us where we could improve. And that helped us deprioritize some of the features that we thought were important.
And prioritize the ones that were important for drug discovery to our scientists. And that was a, again, a risk we took, but I think it was an important risk.
[00:20:51] Speaker B: What does victory look like to you today?
[00:20:55] Speaker A: Victory to me, always, whether it's today or in the future, is when you build something, it's embraced by your patients or your customers. To me, that's the victory. You may build the best Ferrari in the world, but like I said, if it sits in the showroom, it's no good.
[00:21:16] Speaker B: If you could give your younger self one piece of advice, what would you say?
[00:21:23] Speaker A: Oh, let me think.
I would say be bold, be courageous and learn as much as you can in multiple domains.
By that, what I mean is as scientists, we kind of become so expensive, expert in one domain, whether it is chemistry, biology. But keeping an eye on how we can use data, how we can embrace new technology to improve these specific scientific domains is extremely important.
And so I wish that time I would have been able to be able to embrace some more data science, become a better coder. And I always feel you could do better and more that would. That's always. I feel like as an entrepreneur, as a leader, keeps you hands on and gives you the ability to connect with.
[00:22:20] Speaker B: Your teams well, with a PhD and MBA and clear impact at your company and your own startup, it sounds like I think you're doing more than enough. But I get that. So thank you so much for joining us. It was a pleasure to have you on the show.
[00:22:37] Speaker A: Thanks, Rachel. It is great to be with another Wharton Allah. And congratulations on your graduation as well. Good to be on this podcast.
[00:22:46] Speaker B: Thank you.
[00:22:46] Speaker A: Thank you.
