What if the best AI drug discovery company was just the best drug discovery company?
In this episode of CEO Series, we sit down with Viswa Colluru, Founder and CEO of Enveda, to unpack why the future of drug discovery may look less like engineering a target and more like reading the chemistry nature has spent billions of years refining.
For decades, the industry has worked target-first: nominate a protein, then spend enormous effort to inhibit or degrade it. But many of medicine's most important breakthroughs ran the other way. We made aspirin, and it taught us about inflammation. We understood how morphine worked, and it taught us about pain. Enveda is rebuilding discovery around that insight, pairing AI with the full complexity of living systems to find first-in-class medicines, and compressing the path from molecule to candidate into a 24-hour cycle that spans Boulder, Colorado and Hyderabad, India.
In this conversation, we cover:
- Why "molecules that make markets" is the bar for everything that enters the pipeline
- Why pouring AI over the existing paradigm won't move drug discovery's 90% failure rate
- How first-in-class mechanisms create a portfolio that is hard to copy, what Viswa calls "China-proof"
- What it takes to reach a candidate molecule in roughly 100 analogs, against an industry norm of 600 to 1,500
- The three-stage path to building a generational pharma company
Viswa also shares a candid perspective on why evolution's chemistry holds scaling laws that dwarf today's AI models, what it takes to build beyond the single-drug exit, and why patient, long-horizon capital changes how a pharma company gets built. Enveda recently raised a $150M Series D, led by Premji Invest, to advance its pipeline of first-in-class medicines into the clinic.
Enveda is a clinical-stage biotechnology company using AI to translate nature's chemistry into new medicines, discovering first-in-class drugs from molecules science has never explored.
Premji Invest is a $16B+ evergreen crossover fund partnering with founders from inception to IPO and beyond.
00:00:00:22 - 00:00:11:13
Viswa Colluru
You can't get the best drug discovery company, you should just be the best drug discovery company.
00:00:11:16 - 00:00:24:04
Akshay Rai
Hi everyone, I'm Akshay I lead healthcare investments at Premji Invest. Welcome to our CEO series. Here I have with me Viswa Colluru from Enveda, our long term portfolio company and something we are very excited about.
00:00:24:10 - 00:00:32:28
Viswa Colluru
Thank you so much for having me. Actually, I am so excited to tell you where we are on our quest to build one of the most consequential health care companies of the century.
00:00:33:03 - 00:00:42:05
Akshay Rai
Despite being one of the first AI native drug discovery companies, you kind of kept the AI piece out of your branding.
00:00:42:07 - 00:01:07:10
Viswa Colluru
You know, we have a very simple philosophy at the company, which is that the best AI drug discovery company should just be the best drug discovery company. My favorite analogy for AI, as much as it's the topic du jour today, is that it's like electricity. It's going to eventually permeate all aspects of our life, and it's going to make everything infinitely, almost unimaginably better.
00:01:07:12 - 00:01:21:08
Viswa Colluru
But this is not the first time we've been through such a paradigm shift. And at the end of the day, the only thing that matters is that you build an incredible business. And we think an incredible drug discovery business is just one that has drugs.
00:01:21:11 - 00:01:28:00
Akshay Rai
And when you think about building that pipeline, how would you did you go about selecting those drugs?
00:01:28:03 - 00:01:55:10
Viswa Colluru
You know, very simply, we think about molecules that invade as needing to pass just one bar. And it is molecules that make markets. And what does that mean specifically and how have you reduced it to practice? It's a three step formula. The first is where we think despite being a competitive and meaningful market there's headroom. So for example our lead asset is in atopic dermatitis.
00:01:55:12 - 00:02:25:07
Viswa Colluru
But most of the drugs fail to get a large fraction of the patients to an effective cure or a 90 plus percent reduction in their eczema. The second thing we look for is because we are a chemistry first company, that there should be a value premium for orals. In other words, if you can make a pill that should not just be the product of choice for the end customer base in pharma, but it should also be able to expand the market.
00:02:25:09 - 00:02:49:17
Viswa Colluru
So today, I think Dupixent serves sub 1 million atopic derm patients in America. They estimate it to be about 18% market penetration. The last leg of the proverbial stool, if you will, is that we need to be able to get clinical data with limited time and money because at the end of the day, the only race that every biotech company is against is that of time and capital.
00:02:49:24 - 00:02:56:00
Akshay Rai
Would you talk about your superpower on that side, or how you kind of get from a concept to a drug.
00:02:56:02 - 00:03:27:24
Viswa Colluru
That is such an interesting question, because while our core principle of being a drug company that has drugs and having those drugs be meaningful were a part of the story from the very beginning, we never sought to make scale or speed a part of our thesis. What we ended up making and finding along the way, in that order, was a company that could essentially prosecute hypotheses and test them in the clinic very quickly.
00:03:27:25 - 00:03:57:22
Viswa Colluru
We definitely want to choose indications that permit you to be able to generate high value clinical data with high facility, but you can also meaningfully change the time to that by essentially working harder than everyone else. And we have our version of that, which is a company work cycle that last 24 hours. Since we have teams that span both hemispheres, we discover new molecules here in Boulder, Colorado, and we turn them into medicines in Hyderabad, India.
00:03:57:22 - 00:04:25:28
Viswa Colluru
And we've chosen to fully integrate this prediction scale iteration loop such that we can turn nature's chemistry into the next blockbuster medicine as quickly as possible. So to put that in numbers for you, we go from a molecule to a essentially candidate medicine in about 100 analogs on average. And biotech companies usually do 600 to 700. Pharma companies can make, you know, 1500 or more.
00:04:26:00 - 00:04:33:08
Viswa Colluru
And this means that we can go from a hit to a candidate medicine in about a year, which is about four times faster.
00:04:33:10 - 00:04:48:11
Akshay Rai
There is a tendency in biotechs to go towards where it's comfortable, choose the biologically validated target. Where do you get that confidence from to kind of pursue a wide, diversified pipeline of new targets?
00:04:48:12 - 00:05:12:26
Viswa Colluru
Every interesting compound from nature that has made its way to becoming a medicine has written a new chapter in biology, for example, we didn't learn about inflammation and then make aspirin. We made aspirin and it taught us about inflammation. We didn’t learn about opioid biology and pain and then make morphine. We just understood how morphine worked and that taught us about pain.
00:05:12:26 - 00:05:40:10
Viswa Colluru
So we think we can take the same miracles from aspirin, morphine, metformin and so on and so forth, and continue building on that momentum. And to quote a very recent example, I think the beauty of daraxonrasib and revolution medicines, medicine also comes from, you know, a completely new mechanistic class that was enabled by the discovery of rapamycin on Easter Island, oh so long ago.
00:05:40:15 - 00:05:46:27
Akshay Rai
Do you see pharma companies of the future being very different from traditional biotechs or traditional pharma companies with.
00:05:46:27 - 00:06:15:06
Viswa Colluru
Respect to using AI and drug discovery? And Enveda we have a contrarian take, which is that if you take the existing paradigm and you pour jet fuel over it in the form of AI, you may ultimately move the economics of the number of hypotheses you try, but ultimately you won’t move the 90% failure rate and in fact you may make over time the economics worse because now everybody can zero shock the same biologic.
00:06:15:11 - 00:06:46:15
Viswa Colluru
We believe that AI will ultimately move the needle in drug discovery when you can fundamentally embrace, rather than shun, the complexity of living systems. For us, obviously, that involves revealing new chemical structures and understanding how they behave to reveal first in class drugs that are outside the one target inhibit, activate or degrade paradigm. This could take any number of forms and could take into account the dynamic states of biology.
00:06:46:19 - 00:07:14:19
Viswa Colluru
It could take into account the fact that there are aspects of biology that are perhaps irreducible. Using a neural network, or the fact that we are stochastic with time in ways that, you know, are very hard to understand in terms of how a cell behaves. And, can't wait to get more people to try what it means to embrace AI, to be fundamentally more intelligent rather than just accelerate what we came up with at the turn of the century.
00:07:14:22 - 00:07:25:25
Akshay Rai
So do you worry about the leads head start you have with your platform a novel biology being going away over time because people figure out how to do what you've done.
00:07:25:27 - 00:07:59:21
Viswa Colluru
I think the beauty of novel biology is that it frequently exists beyond how we've reduced a target first biology, first approach to practice, right? Very simply, the industry today, you know, does a tremendous amount of scientific work to nominate a particular protein. And the vast majority of the effort is to inhibit the protein or degrade the protein. And very small amount of effort is usually activating a particular protein.
00:07:59:21 - 00:08:32:00
Viswa Colluru
And that's both because that's harder to do. And we find less proteins that are contextually relevant to activation for a therapeutic effect. But if you look at the mechanisms that historically successful chemistry from living systems has taught us, that is those tiny inhibition activation, integrated degradation, paths are absolutely, I'd say the minority. And as far as nature is concerned, perhaps pretty inelegant.
00:08:32:02 - 00:09:03:17
Viswa Colluru
Another way of saying that the mechanisms we have discovered are akin to, for example, what rapamycin has done. So first in class biology in and of itself, I think is exciting. But what makes Enveda perhaps even more so exciting and defensible is the fact that our mechanisms are unprecedented in terms of what is done to a particular node of biology, and that has the unintended upside of being pretty hard to replicate.
00:09:03:19 - 00:09:34:04
Viswa Colluru
I think if you anointed a new target and, you know, a new particular kinase, and it had this perfect balance of efficacy and safety, but all you did was inhibit its ATP binding pocket with the small molecule, then you'd end up, you know, being extremely susceptible to everyone that can follow that paradigm. But if your molecules not just make markets but break paradigms, they're going to be extremely hard to copy, whether they're stateside or in China.
00:09:34:06 - 00:09:53:10
Viswa Colluru
So I like to think of our portfolio as a China proof, first in class portfolio. So if you're a pharma company or an investor and you're very interested in the mechanism that we just validated in our clinical trial, odds are that you won't be able to buy a stake in them anywhere else but Enveda.
00:09:53:17 - 00:10:00:26
Akshay Rai
What are the next steps here? How do you kind of think about the right partner and the right time to partner these assets?
00:10:00:26 - 00:10:27:25
Viswa Colluru
The end goal for us, as I may have slipped in earlier on, is to build a 21st century generational pharma company, and we think such a company will have multiple molecules that it owns and sells directly to the end buyers. Whether that is through the DTC revolution in obesity or, you know, the insured space, say, in atopic dermatitis and other TH2 inflammatory diseases.
00:10:27:27 - 00:10:54:03
Viswa Colluru
So we think of the path to getting there as a three stage process. Stage one is to produce mega blockbuster potential molecules with early clinical signal that first engender these partnership opportunities. Stage two is to be able to partner with companies that will give us a seat at the table for late stage development and show us what the complexities of phase two.
00:10:54:03 - 00:11:29:05
Viswa Colluru
Phase three studies, global regulatory submissions and commercial launches look like. And as we do that, choose our own key franchise molecules, perhaps 1 or 2 in a focused therapeutic area or indication space that we actually defer partnering on to reach stage three, which is, you know, our own launch at the global setting for one of these molecules. So we think that right from the beginning Enveda's been building towards this three stage process to become, you know, the Lilly competitor of the century.
00:11:29:07 - 00:11:36:00
Akshay Rai
How easy is it to ask investors to look beyond the one drug exit? How do you convince people to stay patient?
00:11:36:07 - 00:12:09:20
Viswa Colluru
The short version is if most investors were like you, it'd be very easy. Evergreen patient long term capital is rare, but it isn't absent. And I think one of the aspects of Enveda that I'm most proud of is being able to crowd our cap table with investors like you that think in that manner. But from a tactical perspective, you absolutely lay out a very important problem behavior with great incentives and structural familiarity, which is to build for the one drug exit and finance for the one drug exit.
00:12:09:24 - 00:12:38:05
Viswa Colluru
We've taken, you know, a few steps to make that harder to do when evaluating Enveda as a business and in the future, aEnveda as a publicly traded stock, the first one is to just make the second asset parallel in that in time, it's not displaced by quarters or years, which make it very easy for biotech investors to discount an asset because many biotechs cannot survive a single failure.
00:12:38:08 - 00:13:01:09
Viswa Colluru
The second one we've done is to make every asset be essentially related to a massive market. But it's not just that these are big markets that could have a meaningful effect on the business. They're markets that analysts cover because they cover large pharma caps. And they cover this space because it is extremely interesting to other single asset biotechs.
00:13:01:12 - 00:13:09:27
Akshay Rai
This has been a fascinating conversation. Thank you for the time. One last question. What gets you excited about Enveda as things stand today?
00:13:09:29 - 00:13:43:18
Viswa Colluru
You know, we've made more progress than I could have ever imagined. We've got multiple drugs into patients at a fraction of the time and the capital. But if I think about, you know, the excitement around AI, I want to frame the inherent scaling laws and the intelligence we're seeing emerge from it. And many of these models, if not all of them, have scaling laws that have, you know, trillions of parameters and at most, you know, 10 to the power of 12, 10
to the power of 14 parameters, and Enveda’s
00:13:43:18 - 00:14:04:23
Viswa Colluru
technology is a skeleton key to the intelligence of evolution. And the scaling laws of evolution, especially in chemistry, are ten to the power 60. And if I think about what might drop out of that for human and planetary health, it gives me chills. So thank you for allowing me to pursue that dream.
Recommended
CEO Series | Enveda: Building a 21st century generational pharma company.
CEO Series | Enveda: Building a 21st century generational pharma company.
CEO Series | DOSS: Turning operational complexity into competitive advantage
CEO Series | DOSS: Turning operational complexity into competitive advantage

Why I take founders on a 3-mile hike before writing a check

Why I take founders on a 3-mile hike before writing a check

Rearchitecting the Rigid ERP Core. Why we co-led Doss's $55M Series B
